Single-cell biomechanics and electrophysiology measuring tools have transformed biological research over the last few decades,which enabling a comprehensive and nuanced understanding of cellular behavior and function....Single-cell biomechanics and electrophysiology measuring tools have transformed biological research over the last few decades,which enabling a comprehensive and nuanced understanding of cellular behavior and function.Despite their high-quality information content,these single-cell measuring techniques suffer from laborious manual processing by highly skilled workers and extremely low throughput(tens of cells per day).Recently,numerous researchers have automated the measurement of cell mechanical and electrical signals through robotic localization and control processes.While these efforts have demonstrated promising progress,critical challenges persist,including human dependency,learning complexity,in-situ measurement,and multidimensional signal acquisition.To identify key limitations and highlight emerging opportunities for innovation,in this review,we comprehensively summarize the key steps of robotic technologies in single-cell biomechanics and electrophysiology.We also discussed the prospects and challenges of robotics and automation in biological research.By bridging gaps between engineering,biology,and data science,this work aims to stimulate interdisciplinary research and accelerate the translation of robotic single-cell technologies into practical applications in the life sciences and medical fields.展开更多
A simple method for measuring grating groove density as well as its position and orientation is proposed based on the idea of ERT(Experimental Ray Tracing).Conventional methods only measure grating groove density with...A simple method for measuring grating groove density as well as its position and orientation is proposed based on the idea of ERT(Experimental Ray Tracing).Conventional methods only measure grating groove density with accuracy limited by its rotary stage and goniometer.The method proposed in the paper utilizes linear guides which could be calibrated to much higher accuracy.It is applicable to gratings of arbitrary surface profile or mosaic of a group of various gratings.Various measurement error sources are simulated by the Monte Carlo method and the results show high accuracy capability of grating parameters identification.A verification testing is performed.The accuracy dependency on main configuration parameters is evaluated.A method to expand measurement range by double wavelength is also discussed.展开更多
To fulfill the requirements of high-precision common baseline measurement for multiple parameters,such as surface profiling and the curvature radius of large-aperture optical elements on the same instrument,this paper...To fulfill the requirements of high-precision common baseline measurement for multiple parameters,such as surface profiling and the curvature radius of large-aperture optical elements on the same instrument,this paper proposes a research on a high-precision large-aperture laser differential confocal-interferometric measurement method.This method is based on the principle of laser differential confocal combined with interferometry.It utilizes a Galilean double-reflection collimation system to generate well large-aperture collimated beams and employs mechanical phase-shifting technology for large-aperture and heavy-load reference lenses to overcome the flaws of existing large-aperture wavelength-tuning phase shifting technology in theory,thus achieving highprecision and high-stable phase-shifting interference in large-aperture surface profiling measurements.By utilizing the laser differential confocal method with anti-scattering and anti-interference properties,high-precision common baseline measurements are achieved for the multiple-parameter of optical elements such as ultra-long focal lengths and ultra-large curvature radii.The measurements of large-aperture surface profiles,the mean PV was 46.0 nm.For the ultra-long focal length,the relative standard deviation was 0.019%,whereas for the ultra-large curvature radius,the relative standard deviation was 0.0036%.This method enables high-precision,high-stable,and high-efficient common baseline measurements for the multiple parameters of optical elements with large,medium,and small apertures thereby providing an effective technical approach for improving the detection and machining precision of optical elements.展开更多
Selecting the optimal machining parameters for impeller surface is a challenging task in the automatic manufacturing industry, due to its free-form surface and deep-crooked flow channel.Existing experimental methods r...Selecting the optimal machining parameters for impeller surface is a challenging task in the automatic manufacturing industry, due to its free-form surface and deep-crooked flow channel.Existing experimental methods require lots of machining experiments and off-line tests, which may lead to high machining cost and low efficiency. This paper proposes a novel method of machining parameters optimization for an impeller based on the on-machine measuring technique. The absolute average error and standard deviation of the measured points are used to define the grey relational grade for reconstructing the objective function, and the complex problem of multi-objective optimization is simplified into a problem of single-objective optimization. Then, by comparing the values of the defined grey relational grade in a designed orthogonal experiment, the optimal combination of the machining parameters is obtained. The experiment-solving process of the objective function corresponds to the minimization of the used errors, which is advantageous to reducing the machining error. The proposed method is efficient and low-cost, since it does not require re-clamping the workpiece for off-line tests. Its effectiveness is verified by an on-machine inspection experiment of the impeller blade.展开更多
Robustness against measurement uncertainties is crucial for gas turbine engine diagnosis.While current research focuses mainly on measurement noise,measurement bias remains challenging.This study proposes a novel perf...Robustness against measurement uncertainties is crucial for gas turbine engine diagnosis.While current research focuses mainly on measurement noise,measurement bias remains challenging.This study proposes a novel performance-based fault detection and identification(FDI)strategy for twin-shaft turbofan gas turbine engines and addresses these uncertainties through a first-order Takagi-Sugeno-Kang fuzzy inference system.To handle ambient condition changes,we use parameter correction to preprocess the raw measurement data,which reduces the FDI’s system complexity.Additionally,the power-level angle is set as a scheduling parameter to reduce the number of rules in the TSK-based FDI system.The data for designing,training,and testing the proposed FDI strategy are generated using a component-level turbofan engine model.The antecedent and consequent parameters of the TSK-based FDI system are optimized using the particle swarm optimization algorithm and ridge regression.A robust structure combining a specialized fuzzy inference system with the TSK-based FDI system is proposed to handle measurement biases.The performance of the first-order TSK-based FDI system and robust FDI structure are evaluated through comprehensive simulation studies.Comparative studies confirm the superior accuracy of the first-order TSK-based FDI system in fault detection,isolation,and identification.The robust structure demonstrates a 2%-8%improvement in the success rate index under relatively large measurement bias conditions,thereby indicating excellent robustness.Accuracy against significant bias values and computation time are also evaluated,suggesting that the proposed robust structure has desirable online performance.This study proposes a novel FDI strategy that effectively addresses measurement uncertainties.展开更多
Understanding the mechanical properties of the lithologies is crucial to accurately determine the horizontal stress magnitude.To investigate the correlation between the rock mass properties and maximum horizontal stre...Understanding the mechanical properties of the lithologies is crucial to accurately determine the horizontal stress magnitude.To investigate the correlation between the rock mass properties and maximum horizontal stress,the three-dimensional(3D)stress tensors at 89 measuring points determined using an improved overcoring technique in nine mines in China were adopted,a newly defined characteristic parameter C_(ERP)was proposed as an indicator for evaluating the structural properties of rock masses,and a fuzzy relation matrix was established using the information distribution method.The results indicate that both the vertical stress and horizontal stress exhibit a good linear growth relationship with depth.There is no remarkable correlation between the elastic modulus,Poisson's ratio and depth,and the distribution of data points is scattered and messy.Moreover,there is no obvious relationship between the rock quality designation(RQD)and depth.The maximum horizontal stress σ_(H) is a function of rock properties,showing a certain linear relationship with the C_(ERP)at the same depth.In addition,the overall change trend of σ_(H) determined by the established fuzzy identification method is to increase with the increase of C_(ERP).The fuzzy identification method also demonstrates a relatively detailed local relationship betweenσ_H and C_(ERP),and the predicted curve rises in a fluctuating way,which is in accord well with the measured stress data.展开更多
The centroid coordinate serves as a critical control parameter in motion systems,including aircraft,missiles,rockets,and drones,directly influencing their motion dynamics and control performance.Traditional methods fo...The centroid coordinate serves as a critical control parameter in motion systems,including aircraft,missiles,rockets,and drones,directly influencing their motion dynamics and control performance.Traditional methods for centroid measurement often necessitate custom equipment and specialized positioning devices,leading to high costs and limited accuracy.Here,we present a centroid measurement method that integrates 3D scanning technology,enabling accurate measurement of centroid across various types of objects without the need for specialized positioning fixtures.A theoretical framework for centroid measurement was established,which combined the principle of the multi-point weighing method with 3D scanning technology.The measurement accuracy was evaluated using a designed standard component.Experimental results demonstrate that the discrepancies between the theoretical and the measured centroid of a standard component with various materials and complex shapes in the X,Y,and Z directions are 0.003 mm,0.009 mm,and 0.105 mm,respectively,yielding a spatial deviation of 0.106 mm.Qualitative verification was conducted through experimental validation of three distinct types.They confirmed the reliability of the proposed method,which allowed for accurate centroid measurements of various products without requiring positioning fixtures.This advancement significantly broadened the applicability and scope of centroid measurement devices,offering new theoretical insights and methodologies for the measurement of complex parts and systems.展开更多
In this article,the multi-parameters Mittag-Leffler function is studied in detail.As a consequence,a series of novel results such as the integral representation,series representation and Mellin transform to the above ...In this article,the multi-parameters Mittag-Leffler function is studied in detail.As a consequence,a series of novel results such as the integral representation,series representation and Mellin transform to the above function,are obtained.Especially,we associate the multi-parameters Mittag-Leffler function with two special functions which are the generalized Wright hypergeometric and the Fox’s-H functions.Meanwhile,some interesting integral operators and derivative operators of this function,are also discussed.展开更多
Multi-parameter quantum estimation has attracted considerable attention due to its broad applications.Due to the complexity of quantum dynamics,existing research places significant emphasis on estimating parameters in...Multi-parameter quantum estimation has attracted considerable attention due to its broad applications.Due to the complexity of quantum dynamics,existing research places significant emphasis on estimating parameters in time-independent Hamiltonians.Here,our work makes an effort to explore multi-parameter estimation with time-dependent Hamiltonians.In particular,we focus on the discrimination of two close frequencies of a magnetic field by using a single qubit.We optimize the quantum controls by employing both traditional optimization methods and reinforcement learning to improve the precision for estimating the frequencies of the two magnetic fields.In addition to the estimation precision,we also evaluate the robustness of the optimization schemes against the shift of the control parameters.The results demonstrate that the hybrid reinforcement learning approach achieves the highest estimation precision,and exhibits superior robustness.Moreover,a fundamental challenge in multi-parameter quantum estimation stems from the incompatibility of the optimal control strategies for different parameters.We demonstrate that the hybrid control strategies derived through numerical optimization remain effective in enhancing the precision of multi-parameter estimation in spite of the incompatibilities,thereby mitigating incompatibilities between control strategies on the estimation precision.Finally,we investigate the trade-offs in estimation precision among different parameters for different scenarios,revealing the inherent challenges in balancing the optimization of multiple parameters simultaneously and providing insights into the fundamental distinction between quantum single-parameter estimation and multi-parameter estimation.展开更多
Battery safety has emerged as a critical challenge for achieving carbon neutrality,driven by the increasing frequency of thermal runaway incidents in electric vehicles(EVs)and stationary energy storage systems(ESSs).C...Battery safety has emerged as a critical challenge for achieving carbon neutrality,driven by the increasing frequency of thermal runaway incidents in electric vehicles(EVs)and stationary energy storage systems(ESSs).Conventional battery monitoring technologies struggle to track multiple physicochemical parameters in real time,hindering early hazard detection.Embedded optical fiber sensors have gained prominence as a transformative solution for next-generation smart battery sensing,owing to their micrometer size,multiplexing capability,and electromagnetic immunity.However,comprehensive reviews focusing on their advancements in operando multi-parameter monitoring remain scarce,despite their critical importance for ensuring battery safety.To address this gap,this review first introduces a classification and the fundamental principles of advanced battery-oriented optical fiber sensors.Subsequently,it summarizes recent developments in single-parameter battery monitoring using optical fiber sensors.Building on this foundation,this review presents the first comprehensive analysis of multifunctional optical fiber sensing platforms capable of simultaneously tracking temperature,strain,pressure,refractive index,and monitoring battery aging.Targeted strategies are proposed to facilitate the practical development of this technology,including optimization of sensor integration techniques,minimizing sensor invasiveness,resolving the cross-sensitivity of fiber Bragg grating(FBG)through structural innovation,enhancing techno-economics,and combining with artificial intelligence(AI).By aligning academic research with industry requirements,this review provides a methodological roadmap for developing robust optical sensing systems to ensure battery safety in decarbonization-driven applications.展开更多
The accurate characterization of thermoelectric properties at low temperatures is crucial for the development of high-performance thermoelectric cooling devices. While measurement errors of thermoelectric properties a...The accurate characterization of thermoelectric properties at low temperatures is crucial for the development of high-performance thermoelectric cooling devices. While measurement errors of thermoelectric properties at temperatures above room temperature have been extensively discussed, there is a lack of standard measurement protocols and error analyses for low-temperature transport properties. In this study, we present a measurement system capable of characterizing all three key thermoelectric parameters, i.e., Seebeck coefficient, electrical conductivity, and thermal conductivity, for a single sample across a temperature range of 10 K to 300 K. We investigated six representative commercial Bi_(2)Te_(3)-based samples(three N-type and three P-type). Using an error propagation model, we systematically analyzed the measurement uncertainties of the three intrinsic parameters and the resulting thermoelectric figure of merit. Our findings reveal that measurement uncertainties for both N-type and P-type Bi_(2)Te_(3)-based materials can be effectively maintained below 5% in the temperature range of 40 K to 300 K. However, the uncertainties increase to over 10% at lower temperatures, primarily due to the relatively smaller values of electrical resistivity and Seebeck coefficients in this regime. This work establishes foundational data for Bi_(2)Te_(3)-based thermoelectric materials and provides a framework for broader investigations of advanced low-temperature thermoelectrics.展开更多
The concept of emissivity has been with the scientific and engineering world since Planck formulated his blackbody radiation law more than a century ago.Nevertheless,emissivity is an elusive concept even for ex⁃perts....The concept of emissivity has been with the scientific and engineering world since Planck formulated his blackbody radiation law more than a century ago.Nevertheless,emissivity is an elusive concept even for ex⁃perts.It is a vague and fuzzy concept for the wider community of engineers.The importance of remote sensing of temperature by measuring IR radiation has been recognized in a wide range of industrial,medical,and environ⁃mental uses.One of the major sources of errors in IR radiometry is the emissivity of the surface being measured.In real experiments,emissivity may be influenced by many factors:surface texture,spectral properties,oxida⁃tion,and aging of surfaces.While commercial blackbodies are prevalent,the much-needed grey bodies with a known emissivity,are unavailable.This study describes how to achieve a calibrated and stable emissivity with a blackbody,a perforated screen,and a reliable and linear novel IR thermal sensor,18 dubbed TMOS.The Digital TMOS is now a low-cost commercial product,it requires low power,and it has a small form factor.The method⁃ology is based on two-color measurements,with two different optical filters,with selected wavelengths conform⁃ing to the grey body definition of the use case under study.With a photochemically etched perforated screen,the effective emissivity of the screen is simply the hole density area of the surface area that emits according to the blackbody temperature radiation.The concept is illustrated with ray tracing simulations,which demonstrate the approach.Measured results are reported.展开更多
In modern industrial design trends featuring with integration,miniaturization,and versatility,there is a growing demand on the utilization of microstructural array devices.The measurement of such microstructural array...In modern industrial design trends featuring with integration,miniaturization,and versatility,there is a growing demand on the utilization of microstructural array devices.The measurement of such microstructural array components often encounters challenges due to the reduced scale and complex structures,either by contact or noncontact optical approaches.Among these microstructural arrays,there are still no optical measurement methods for micro corner-cube reflector arrays.To solve this problem,this study introduces a method for effectively eliminating coherent noise and achieving surface profile reconstruction in interference measurements of microstructural arrays.The proposed denoising method allows the calibration and inverse solving of system errors in the frequency domain by employing standard components with known surface types.This enables the effective compensation of the complex amplitude of non-sample coherent light within the interferometer optical path.The proposed surface reconstruction method enables the profile calculation within the situation that there is complex multi-reflection during the propagation of rays in microstructural arrays.Based on the measurement results,two novel metrics are defined to estimate diffraction errors at array junctions and comprehensive errors across multiple array elements,offering insights into other types of microstructure devices.This research not only addresses challenges of the coherent noise and multi-reflection,but also makes a breakthrough for quantitively optical interference measurement of microstructural array devices.展开更多
Real-time and accurate drogue pose measurement during docking is basic and critical for Autonomous Aerial Refueling(AAR).Vision measurement is the best practicable technique,but its measurement accuracy and robustness...Real-time and accurate drogue pose measurement during docking is basic and critical for Autonomous Aerial Refueling(AAR).Vision measurement is the best practicable technique,but its measurement accuracy and robustness are easily affected by limited computing power of airborne equipment,complex aerial scenes and partial occlusion.To address the above challenges,we propose a novel drogue keypoint detection and pose measurement algorithm based on monocular vision,and realize real-time processing on airborne embedded devices.Firstly,a lightweight network is designed with structural re-parameterization to reduce computational cost and improve inference speed.And a sub-pixel level keypoints prediction head and loss functions are adopted to improve keypoint detection accuracy.Secondly,a closed-form solution of drogue pose is computed based on double spatial circles,followed by a nonlinear refinement based on Levenberg-Marquardt optimization.Both virtual simulation and physical simulation experiments have been used to test the proposed method.In the virtual simulation,the mean pixel error of the proposed method is 0.787 pixels,which is significantly superior to that of other methods.In the physical simulation,the mean relative measurement error is 0.788%,and the mean processing time is 13.65 ms on embedded devices.展开更多
This study investigates a consistent fusion algorithm for distributed multi-rate multi-sensor systems operating in feedback-memory configurations, where each sensor's sampling period is uniform and an integer mult...This study investigates a consistent fusion algorithm for distributed multi-rate multi-sensor systems operating in feedback-memory configurations, where each sensor's sampling period is uniform and an integer multiple of the state update period. The focus is on scenarios where the correlations among Measurement Noises(MNs) from different sensors are unknown. Firstly, a non-augmented local estimator that applies to sampling cases is designed to provide unbiased Local Estimates(LEs) at the fusion points. Subsequently, a measurement-equivalent approach is then developed to parameterize the correlation structure between LEs and reformulate LEs into a unified form, thereby constraining the correlations arising from MNs to an admissible range. Simultaneously, a family of upper bounds on the joint error covariance matrix of LEs is derived based on the constrained correlations, avoiding the need to calculate the exact error cross-covariance matrix of LEs. Finally, a sequential fusion estimator is proposed in the sense of Weighted Minimum Mean Square Error(WMMSE), and it is proven to be unbiased, consistent, and more accurate than the well-known covariance intersection method. Simulation results illustrate the effectiveness of the proposed algorithm by highlighting improvements in consistency and accuracy.展开更多
Based on waveform fitting,full waveform inversion(FWI)is an important inversion method with the ability to reconstruct multi-parameter models in high precision.However,the strong nonlinear equation used in FWI present...Based on waveform fitting,full waveform inversion(FWI)is an important inversion method with the ability to reconstruct multi-parameter models in high precision.However,the strong nonlinear equation used in FWI presents the following challenges,such as low convergence efficiency,high dependence on the initial model,and the energy imbalance in deep region of the inverted model.To solve these inherent problems,we develop a timedomain elastic FWI method based on gradient preconditioning with the following details:(1)the limited memory Broyden Fletcher Goldfarb Shanno method with faster convergence is adopted to im-prove the inversion stability;(2)a multi-scaled inversion strategy is used to alleviate the nonlinear inversion instead of falling into the local minimum;(3)in addition,the pseudo-Hessian preconditioned illumination operator is involved for preconditioning the parameter gradients to improve the illumination equilibrium degree of deep structures.Based on the programming implementation of the new method,a deep depression model with five diffractors is used for testing.Compared with the conventional elastic FWI method,the technique proposed by this study has better effectiveness and accuracy on the inversion effect and con-vergence,respectively.展开更多
Under sensorless control, the position estimation error in interior permanent magnet(PM) synchronous machines will lead to parameter identification errors and a rank-deficiency issue. This paper proposes a parameter i...Under sensorless control, the position estimation error in interior permanent magnet(PM) synchronous machines will lead to parameter identification errors and a rank-deficiency issue. This paper proposes a parameter identification model that is independent of position error by combining the dq-axis voltage equations. Then, a novel dual signal alternate injection method is proposed to address the rank-deficiency issue, i.e., during one injection period, a zero, positive, and negative d-axis current injection together with a rotor position offset injection, to simultaneously identify the multi-parameters, including stator resistance, dq-axis inductances, and PM flux linkage. The proposed method is verified by experiments at different dq-axis current conditions.展开更多
The estimation of quantum phase differences plays an important role in quantum simulation and quantum computation,yet existing quantum phase estimation algorithms face critical limitations in noisy intermediate-scale ...The estimation of quantum phase differences plays an important role in quantum simulation and quantum computation,yet existing quantum phase estimation algorithms face critical limitations in noisy intermediate-scale quantum(NISQ)devices due to their excessive depth and circuit complexity.We demonstrate a high-precision phase difference estimation protocol based on the Bayesian phase difference estimation algorithm and single-photon projective measurement.The iterative framework of the algorithm,combined with the independence from controlled unitary operations,inherently mitigates circuit depth and complexity limitations.Through an experimental realization on the photonic system,we demonstrate high-precision estimation of diverse phase differences,showing root-mean-square errors(RMSE)below the standard quantum limit𝒪(1/√N)and reaching the Heisenberg scaling𝒪(1/N)after a certain number of iterations.Our scheme provides a critical advantage in quantum resource-constrained scenarios,and advances practical implementations of quantum information tasks under realistic hardware constraints.展开更多
The phasor data concentrator placement(PDCP)in wide area measurement systems(WAMS)is an optimization problem in the communication network planning for power grid.Instead of using the traditional integer linear program...The phasor data concentrator placement(PDCP)in wide area measurement systems(WAMS)is an optimization problem in the communication network planning for power grid.Instead of using the traditional integer linear programming(ILP)based modeling and solution schemes that ignore the graph-related features of WAMS,in this work,the PDCP problem is solved through a heuristic graphbased two-phase procedure(TPP):topology partitioning,and phasor data concentrator(PDC)provisioning.Based on the existing minimum k-section algorithms in graph theory,the k-base topology partitioning algorithm is proposed.To improve the performance,the“center-node-last”pre-partitioning algorithm is proposed to give an initial partition before the k-base partitioning algorithm is applied.Then,the PDC provisioning algorithm is proposed to locate PDCs into the decomposed sub-graphs.The proposed TPP was evaluated on five different IEEE benchmark test power systems and the achieved overall communication performance compared to the ILP based schemes show the validity and efficiency of the proposed method.展开更多
Two-dimensional(2D)materials are promising for next-generation electronic devices and systems due to their unique physical properties.The interfacial adhesion plays a vital role not only in the synthesis,transfer and ...Two-dimensional(2D)materials are promising for next-generation electronic devices and systems due to their unique physical properties.The interfacial adhesion plays a vital role not only in the synthesis,transfer and manipulation of 2D materials but also in the manufacture,integration and performance of the functional devices.However,the atomic thickness and limited lateral dimensions of 2D materials make the accurate measurement and modulation of their interfacial adhesion energy challenging.In this review,the recent advances in the measurement and modulation of the interfacial adhesion properties of 2D materials are systematically combed.Experimental methods and relative theoretical models for the adhesion measurement of 2D materials are summarized,with their scope of application and limitations discussed.The measured adhesion energies between 2D materials and various substrates are described in categories,where the typical adhesion modulation strategies of 2D materials are also introduced.Finally,the remaining challenges and opportunities for the interfacial adhesion measurement and modulation of 2D materials are presented.This paper provides guidance for addressing the adhesion issues in devices and systems involving 2D materials.展开更多
基金the National Natural Science Foundation of China[62525301,62127811,62433019]the New Cornerstone Science Foundation through the XPLORER PRIZEthe financial support by the China Postdoctoral Science Foundation[GZB20240797].
文摘Single-cell biomechanics and electrophysiology measuring tools have transformed biological research over the last few decades,which enabling a comprehensive and nuanced understanding of cellular behavior and function.Despite their high-quality information content,these single-cell measuring techniques suffer from laborious manual processing by highly skilled workers and extremely low throughput(tens of cells per day).Recently,numerous researchers have automated the measurement of cell mechanical and electrical signals through robotic localization and control processes.While these efforts have demonstrated promising progress,critical challenges persist,including human dependency,learning complexity,in-situ measurement,and multidimensional signal acquisition.To identify key limitations and highlight emerging opportunities for innovation,in this review,we comprehensively summarize the key steps of robotic technologies in single-cell biomechanics and electrophysiology.We also discussed the prospects and challenges of robotics and automation in biological research.By bridging gaps between engineering,biology,and data science,this work aims to stimulate interdisciplinary research and accelerate the translation of robotic single-cell technologies into practical applications in the life sciences and medical fields.
基金the National Natural Science Foundation of China(Grant Nos.11927804 and 11873013)。
文摘A simple method for measuring grating groove density as well as its position and orientation is proposed based on the idea of ERT(Experimental Ray Tracing).Conventional methods only measure grating groove density with accuracy limited by its rotary stage and goniometer.The method proposed in the paper utilizes linear guides which could be calibrated to much higher accuracy.It is applicable to gratings of arbitrary surface profile or mosaic of a group of various gratings.Various measurement error sources are simulated by the Monte Carlo method and the results show high accuracy capability of grating parameters identification.A verification testing is performed.The accuracy dependency on main configuration parameters is evaluated.A method to expand measurement range by double wavelength is also discussed.
基金supported by National Natural Science Foundation Joint Fund Integrated Project(No.U22A6006)National Key scientific research instrument Development Project of the National Natural Science Foundation of China(No.52327806).
文摘To fulfill the requirements of high-precision common baseline measurement for multiple parameters,such as surface profiling and the curvature radius of large-aperture optical elements on the same instrument,this paper proposes a research on a high-precision large-aperture laser differential confocal-interferometric measurement method.This method is based on the principle of laser differential confocal combined with interferometry.It utilizes a Galilean double-reflection collimation system to generate well large-aperture collimated beams and employs mechanical phase-shifting technology for large-aperture and heavy-load reference lenses to overcome the flaws of existing large-aperture wavelength-tuning phase shifting technology in theory,thus achieving highprecision and high-stable phase-shifting interference in large-aperture surface profiling measurements.By utilizing the laser differential confocal method with anti-scattering and anti-interference properties,high-precision common baseline measurements are achieved for the multiple-parameter of optical elements such as ultra-long focal lengths and ultra-large curvature radii.The measurements of large-aperture surface profiles,the mean PV was 46.0 nm.For the ultra-long focal length,the relative standard deviation was 0.019%,whereas for the ultra-large curvature radius,the relative standard deviation was 0.0036%.This method enables high-precision,high-stable,and high-efficient common baseline measurements for the multiple parameters of optical elements with large,medium,and small apertures thereby providing an effective technical approach for improving the detection and machining precision of optical elements.
基金co-supported by the National Basic Research Program of China(No.2015CB057304)the National Natural Science Foundation of China(Nos.51535004 and91648111)
文摘Selecting the optimal machining parameters for impeller surface is a challenging task in the automatic manufacturing industry, due to its free-form surface and deep-crooked flow channel.Existing experimental methods require lots of machining experiments and off-line tests, which may lead to high machining cost and low efficiency. This paper proposes a novel method of machining parameters optimization for an impeller based on the on-machine measuring technique. The absolute average error and standard deviation of the measured points are used to define the grey relational grade for reconstructing the objective function, and the complex problem of multi-objective optimization is simplified into a problem of single-objective optimization. Then, by comparing the values of the defined grey relational grade in a designed orthogonal experiment, the optimal combination of the machining parameters is obtained. The experiment-solving process of the objective function corresponds to the minimization of the used errors, which is advantageous to reducing the machining error. The proposed method is efficient and low-cost, since it does not require re-clamping the workpiece for off-line tests. Its effectiveness is verified by an on-machine inspection experiment of the impeller blade.
文摘Robustness against measurement uncertainties is crucial for gas turbine engine diagnosis.While current research focuses mainly on measurement noise,measurement bias remains challenging.This study proposes a novel performance-based fault detection and identification(FDI)strategy for twin-shaft turbofan gas turbine engines and addresses these uncertainties through a first-order Takagi-Sugeno-Kang fuzzy inference system.To handle ambient condition changes,we use parameter correction to preprocess the raw measurement data,which reduces the FDI’s system complexity.Additionally,the power-level angle is set as a scheduling parameter to reduce the number of rules in the TSK-based FDI system.The data for designing,training,and testing the proposed FDI strategy are generated using a component-level turbofan engine model.The antecedent and consequent parameters of the TSK-based FDI system are optimized using the particle swarm optimization algorithm and ridge regression.A robust structure combining a specialized fuzzy inference system with the TSK-based FDI system is proposed to handle measurement biases.The performance of the first-order TSK-based FDI system and robust FDI structure are evaluated through comprehensive simulation studies.Comparative studies confirm the superior accuracy of the first-order TSK-based FDI system in fault detection,isolation,and identification.The robust structure demonstrates a 2%-8%improvement in the success rate index under relatively large measurement bias conditions,thereby indicating excellent robustness.Accuracy against significant bias values and computation time are also evaluated,suggesting that the proposed robust structure has desirable online performance.This study proposes a novel FDI strategy that effectively addresses measurement uncertainties.
基金financially supported by the National Natural Science Foundation of China(No.52204084)the Open Research Fund of the State Key Laboratory of Coal Resources and safe Mining,CUMT,China(No.SKLCRSM 23KF004)+3 种基金the Interdisciplinary Research Project for Young Teachers of USTB(Fundamental Research Funds for the Central Universities),China(No.FRF-IDRY-GD22-002)the Fundamental Research Funds for the Central Universities and the Youth Teacher International Exchange and Growth Program,China(No.QNXM20220009)the National Key R&D Program of China(Nos.2022YFC2905600 and 2022 YFC3004601)the Science,Technology&Innovation Project of Xiongan New Area,China(No.2023XAGG0061)。
文摘Understanding the mechanical properties of the lithologies is crucial to accurately determine the horizontal stress magnitude.To investigate the correlation between the rock mass properties and maximum horizontal stress,the three-dimensional(3D)stress tensors at 89 measuring points determined using an improved overcoring technique in nine mines in China were adopted,a newly defined characteristic parameter C_(ERP)was proposed as an indicator for evaluating the structural properties of rock masses,and a fuzzy relation matrix was established using the information distribution method.The results indicate that both the vertical stress and horizontal stress exhibit a good linear growth relationship with depth.There is no remarkable correlation between the elastic modulus,Poisson's ratio and depth,and the distribution of data points is scattered and messy.Moreover,there is no obvious relationship between the rock quality designation(RQD)and depth.The maximum horizontal stress σ_(H) is a function of rock properties,showing a certain linear relationship with the C_(ERP)at the same depth.In addition,the overall change trend of σ_(H) determined by the established fuzzy identification method is to increase with the increase of C_(ERP).The fuzzy identification method also demonstrates a relatively detailed local relationship betweenσ_H and C_(ERP),and the predicted curve rises in a fluctuating way,which is in accord well with the measured stress data.
基金supported by National Natural Science Foundation of China(No.52176122).
文摘The centroid coordinate serves as a critical control parameter in motion systems,including aircraft,missiles,rockets,and drones,directly influencing their motion dynamics and control performance.Traditional methods for centroid measurement often necessitate custom equipment and specialized positioning devices,leading to high costs and limited accuracy.Here,we present a centroid measurement method that integrates 3D scanning technology,enabling accurate measurement of centroid across various types of objects without the need for specialized positioning fixtures.A theoretical framework for centroid measurement was established,which combined the principle of the multi-point weighing method with 3D scanning technology.The measurement accuracy was evaluated using a designed standard component.Experimental results demonstrate that the discrepancies between the theoretical and the measured centroid of a standard component with various materials and complex shapes in the X,Y,and Z directions are 0.003 mm,0.009 mm,and 0.105 mm,respectively,yielding a spatial deviation of 0.106 mm.Qualitative verification was conducted through experimental validation of three distinct types.They confirmed the reliability of the proposed method,which allowed for accurate centroid measurements of various products without requiring positioning fixtures.This advancement significantly broadened the applicability and scope of centroid measurement devices,offering new theoretical insights and methodologies for the measurement of complex parts and systems.
基金Supported by The National Undergraduate Innovation Training Program(Grant No.202310290069Z).
文摘In this article,the multi-parameters Mittag-Leffler function is studied in detail.As a consequence,a series of novel results such as the integral representation,series representation and Mellin transform to the above function,are obtained.Especially,we associate the multi-parameters Mittag-Leffler function with two special functions which are the generalized Wright hypergeometric and the Fox’s-H functions.Meanwhile,some interesting integral operators and derivative operators of this function,are also discussed.
基金supported by the National Natural Science Foundation of China(Grant No.12075323)the Innovation Program for Quantum Science and Technology(Grant No.2021ZD0300702).
文摘Multi-parameter quantum estimation has attracted considerable attention due to its broad applications.Due to the complexity of quantum dynamics,existing research places significant emphasis on estimating parameters in time-independent Hamiltonians.Here,our work makes an effort to explore multi-parameter estimation with time-dependent Hamiltonians.In particular,we focus on the discrimination of two close frequencies of a magnetic field by using a single qubit.We optimize the quantum controls by employing both traditional optimization methods and reinforcement learning to improve the precision for estimating the frequencies of the two magnetic fields.In addition to the estimation precision,we also evaluate the robustness of the optimization schemes against the shift of the control parameters.The results demonstrate that the hybrid reinforcement learning approach achieves the highest estimation precision,and exhibits superior robustness.Moreover,a fundamental challenge in multi-parameter quantum estimation stems from the incompatibility of the optimal control strategies for different parameters.We demonstrate that the hybrid control strategies derived through numerical optimization remain effective in enhancing the precision of multi-parameter estimation in spite of the incompatibilities,thereby mitigating incompatibilities between control strategies on the estimation precision.Finally,we investigate the trade-offs in estimation precision among different parameters for different scenarios,revealing the inherent challenges in balancing the optimization of multiple parameters simultaneously and providing insights into the fundamental distinction between quantum single-parameter estimation and multi-parameter estimation.
基金the financial supports of the National Natural Science Foundation of China(No.52372200)a project supported by the State Key Laboratory of Mechanics and Control for Aerospace Structures(No.MCAS-S-0324G01)。
文摘Battery safety has emerged as a critical challenge for achieving carbon neutrality,driven by the increasing frequency of thermal runaway incidents in electric vehicles(EVs)and stationary energy storage systems(ESSs).Conventional battery monitoring technologies struggle to track multiple physicochemical parameters in real time,hindering early hazard detection.Embedded optical fiber sensors have gained prominence as a transformative solution for next-generation smart battery sensing,owing to their micrometer size,multiplexing capability,and electromagnetic immunity.However,comprehensive reviews focusing on their advancements in operando multi-parameter monitoring remain scarce,despite their critical importance for ensuring battery safety.To address this gap,this review first introduces a classification and the fundamental principles of advanced battery-oriented optical fiber sensors.Subsequently,it summarizes recent developments in single-parameter battery monitoring using optical fiber sensors.Building on this foundation,this review presents the first comprehensive analysis of multifunctional optical fiber sensing platforms capable of simultaneously tracking temperature,strain,pressure,refractive index,and monitoring battery aging.Targeted strategies are proposed to facilitate the practical development of this technology,including optimization of sensor integration techniques,minimizing sensor invasiveness,resolving the cross-sensitivity of fiber Bragg grating(FBG)through structural innovation,enhancing techno-economics,and combining with artificial intelligence(AI).By aligning academic research with industry requirements,this review provides a methodological roadmap for developing robust optical sensing systems to ensure battery safety in decarbonization-driven applications.
基金supported by the National Natural Science Foundation of China (Grant No. 52172259)the National Key Research and Development Program of China (Grant Nos. 2021YFA0718700 and 2022YFB3803900)the Fundamental Research Funds for the Inner Mongolia Normal University (Grant No. 2022JBTD008)。
文摘The accurate characterization of thermoelectric properties at low temperatures is crucial for the development of high-performance thermoelectric cooling devices. While measurement errors of thermoelectric properties at temperatures above room temperature have been extensively discussed, there is a lack of standard measurement protocols and error analyses for low-temperature transport properties. In this study, we present a measurement system capable of characterizing all three key thermoelectric parameters, i.e., Seebeck coefficient, electrical conductivity, and thermal conductivity, for a single sample across a temperature range of 10 K to 300 K. We investigated six representative commercial Bi_(2)Te_(3)-based samples(three N-type and three P-type). Using an error propagation model, we systematically analyzed the measurement uncertainties of the three intrinsic parameters and the resulting thermoelectric figure of merit. Our findings reveal that measurement uncertainties for both N-type and P-type Bi_(2)Te_(3)-based materials can be effectively maintained below 5% in the temperature range of 40 K to 300 K. However, the uncertainties increase to over 10% at lower temperatures, primarily due to the relatively smaller values of electrical resistivity and Seebeck coefficients in this regime. This work establishes foundational data for Bi_(2)Te_(3)-based thermoelectric materials and provides a framework for broader investigations of advanced low-temperature thermoelectrics.
文摘The concept of emissivity has been with the scientific and engineering world since Planck formulated his blackbody radiation law more than a century ago.Nevertheless,emissivity is an elusive concept even for ex⁃perts.It is a vague and fuzzy concept for the wider community of engineers.The importance of remote sensing of temperature by measuring IR radiation has been recognized in a wide range of industrial,medical,and environ⁃mental uses.One of the major sources of errors in IR radiometry is the emissivity of the surface being measured.In real experiments,emissivity may be influenced by many factors:surface texture,spectral properties,oxida⁃tion,and aging of surfaces.While commercial blackbodies are prevalent,the much-needed grey bodies with a known emissivity,are unavailable.This study describes how to achieve a calibrated and stable emissivity with a blackbody,a perforated screen,and a reliable and linear novel IR thermal sensor,18 dubbed TMOS.The Digital TMOS is now a low-cost commercial product,it requires low power,and it has a small form factor.The method⁃ology is based on two-color measurements,with two different optical filters,with selected wavelengths conform⁃ing to the grey body definition of the use case under study.With a photochemically etched perforated screen,the effective emissivity of the screen is simply the hole density area of the surface area that emits according to the blackbody temperature radiation.The concept is illustrated with ray tracing simulations,which demonstrate the approach.Measured results are reported.
基金Supported by National Natural Science Foundation of China(Grant Nos.52375414,52075100)Shanghai Science and Technology Committee Innovation Grant of China(Grant No.23ZR1404200).
文摘In modern industrial design trends featuring with integration,miniaturization,and versatility,there is a growing demand on the utilization of microstructural array devices.The measurement of such microstructural array components often encounters challenges due to the reduced scale and complex structures,either by contact or noncontact optical approaches.Among these microstructural arrays,there are still no optical measurement methods for micro corner-cube reflector arrays.To solve this problem,this study introduces a method for effectively eliminating coherent noise and achieving surface profile reconstruction in interference measurements of microstructural arrays.The proposed denoising method allows the calibration and inverse solving of system errors in the frequency domain by employing standard components with known surface types.This enables the effective compensation of the complex amplitude of non-sample coherent light within the interferometer optical path.The proposed surface reconstruction method enables the profile calculation within the situation that there is complex multi-reflection during the propagation of rays in microstructural arrays.Based on the measurement results,two novel metrics are defined to estimate diffraction errors at array junctions and comprehensive errors across multiple array elements,offering insights into other types of microstructure devices.This research not only addresses challenges of the coherent noise and multi-reflection,but also makes a breakthrough for quantitively optical interference measurement of microstructural array devices.
基金supported by the National Science Fund for Distinguished Young Scholars,China(No.51625501)Aeronautical Science Foundation of China(No.20240046051002)National Natural Science Foundation of China(No.52005028).
文摘Real-time and accurate drogue pose measurement during docking is basic and critical for Autonomous Aerial Refueling(AAR).Vision measurement is the best practicable technique,but its measurement accuracy and robustness are easily affected by limited computing power of airborne equipment,complex aerial scenes and partial occlusion.To address the above challenges,we propose a novel drogue keypoint detection and pose measurement algorithm based on monocular vision,and realize real-time processing on airborne embedded devices.Firstly,a lightweight network is designed with structural re-parameterization to reduce computational cost and improve inference speed.And a sub-pixel level keypoints prediction head and loss functions are adopted to improve keypoint detection accuracy.Secondly,a closed-form solution of drogue pose is computed based on double spatial circles,followed by a nonlinear refinement based on Levenberg-Marquardt optimization.Both virtual simulation and physical simulation experiments have been used to test the proposed method.In the virtual simulation,the mean pixel error of the proposed method is 0.787 pixels,which is significantly superior to that of other methods.In the physical simulation,the mean relative measurement error is 0.788%,and the mean processing time is 13.65 ms on embedded devices.
基金supported by the National Natural Science Foundation of China (Nos. 62276204, 62203343)。
文摘This study investigates a consistent fusion algorithm for distributed multi-rate multi-sensor systems operating in feedback-memory configurations, where each sensor's sampling period is uniform and an integer multiple of the state update period. The focus is on scenarios where the correlations among Measurement Noises(MNs) from different sensors are unknown. Firstly, a non-augmented local estimator that applies to sampling cases is designed to provide unbiased Local Estimates(LEs) at the fusion points. Subsequently, a measurement-equivalent approach is then developed to parameterize the correlation structure between LEs and reformulate LEs into a unified form, thereby constraining the correlations arising from MNs to an admissible range. Simultaneously, a family of upper bounds on the joint error covariance matrix of LEs is derived based on the constrained correlations, avoiding the need to calculate the exact error cross-covariance matrix of LEs. Finally, a sequential fusion estimator is proposed in the sense of Weighted Minimum Mean Square Error(WMMSE), and it is proven to be unbiased, consistent, and more accurate than the well-known covariance intersection method. Simulation results illustrate the effectiveness of the proposed algorithm by highlighting improvements in consistency and accuracy.
基金supported by the Marine S&T Fund of Shandong Province for Pilot National Laboratory for Marine Science and Technology(Qingdao)(Grant No.2021QNLM020001)the National Key R&D Program of China(Grant No.2019YFC0605503C)+2 种基金the Major Scientific and Technological Projects of China National Petroleum Corporation(CNPC)(Grant No.ZD2019-183-003)the National Outstanding Youth Science Foundation(Grant No.41922028)the National Innovation Group Project(Grant No.41821002).
文摘Based on waveform fitting,full waveform inversion(FWI)is an important inversion method with the ability to reconstruct multi-parameter models in high precision.However,the strong nonlinear equation used in FWI presents the following challenges,such as low convergence efficiency,high dependence on the initial model,and the energy imbalance in deep region of the inverted model.To solve these inherent problems,we develop a timedomain elastic FWI method based on gradient preconditioning with the following details:(1)the limited memory Broyden Fletcher Goldfarb Shanno method with faster convergence is adopted to im-prove the inversion stability;(2)a multi-scaled inversion strategy is used to alleviate the nonlinear inversion instead of falling into the local minimum;(3)in addition,the pseudo-Hessian preconditioned illumination operator is involved for preconditioning the parameter gradients to improve the illumination equilibrium degree of deep structures.Based on the programming implementation of the new method,a deep depression model with five diffractors is used for testing.Compared with the conventional elastic FWI method,the technique proposed by this study has better effectiveness and accuracy on the inversion effect and con-vergence,respectively.
文摘Under sensorless control, the position estimation error in interior permanent magnet(PM) synchronous machines will lead to parameter identification errors and a rank-deficiency issue. This paper proposes a parameter identification model that is independent of position error by combining the dq-axis voltage equations. Then, a novel dual signal alternate injection method is proposed to address the rank-deficiency issue, i.e., during one injection period, a zero, positive, and negative d-axis current injection together with a rotor position offset injection, to simultaneously identify the multi-parameters, including stator resistance, dq-axis inductances, and PM flux linkage. The proposed method is verified by experiments at different dq-axis current conditions.
基金Project supported by the Natural Science Foundation of Jiangsu Province(Grant Nos.BK20233001 and BK20243060)the National Natural Science Foundation of China(Grant No.62288101)。
文摘The estimation of quantum phase differences plays an important role in quantum simulation and quantum computation,yet existing quantum phase estimation algorithms face critical limitations in noisy intermediate-scale quantum(NISQ)devices due to their excessive depth and circuit complexity.We demonstrate a high-precision phase difference estimation protocol based on the Bayesian phase difference estimation algorithm and single-photon projective measurement.The iterative framework of the algorithm,combined with the independence from controlled unitary operations,inherently mitigates circuit depth and complexity limitations.Through an experimental realization on the photonic system,we demonstrate high-precision estimation of diverse phase differences,showing root-mean-square errors(RMSE)below the standard quantum limit𝒪(1/√N)and reaching the Heisenberg scaling𝒪(1/N)after a certain number of iterations.Our scheme provides a critical advantage in quantum resource-constrained scenarios,and advances practical implementations of quantum information tasks under realistic hardware constraints.
基金supported by the National Key Research and Development Program of China(2023YFB 2906403).
文摘The phasor data concentrator placement(PDCP)in wide area measurement systems(WAMS)is an optimization problem in the communication network planning for power grid.Instead of using the traditional integer linear programming(ILP)based modeling and solution schemes that ignore the graph-related features of WAMS,in this work,the PDCP problem is solved through a heuristic graphbased two-phase procedure(TPP):topology partitioning,and phasor data concentrator(PDC)provisioning.Based on the existing minimum k-section algorithms in graph theory,the k-base topology partitioning algorithm is proposed.To improve the performance,the“center-node-last”pre-partitioning algorithm is proposed to give an initial partition before the k-base partitioning algorithm is applied.Then,the PDC provisioning algorithm is proposed to locate PDCs into the decomposed sub-graphs.The proposed TPP was evaluated on five different IEEE benchmark test power systems and the achieved overall communication performance compared to the ILP based schemes show the validity and efficiency of the proposed method.
基金supported by the National Natural Science Foundation of China(Grant Nos.12002133,12372109,and 11972171)the Natural Science Foundation of Jiangsu Province(Grant Nos.BK20200590 and BK20180031)+4 种基金the Fundamental Research Funds for the Central Universities(Grant No.JUSRP121040)the National Key R&D Program of China(Grant No.2023YFB4605101)the 111 project(Grant No.B18027)the Open Fund of Key Laboratory for Intelligent Nano Materials and Devices of the Ministry of Education(Grant No.NJ2020003)the Sixth Phase of Jiangsu Province“333 High Level Talent Training Project”Second Level Talents.
文摘Two-dimensional(2D)materials are promising for next-generation electronic devices and systems due to their unique physical properties.The interfacial adhesion plays a vital role not only in the synthesis,transfer and manipulation of 2D materials but also in the manufacture,integration and performance of the functional devices.However,the atomic thickness and limited lateral dimensions of 2D materials make the accurate measurement and modulation of their interfacial adhesion energy challenging.In this review,the recent advances in the measurement and modulation of the interfacial adhesion properties of 2D materials are systematically combed.Experimental methods and relative theoretical models for the adhesion measurement of 2D materials are summarized,with their scope of application and limitations discussed.The measured adhesion energies between 2D materials and various substrates are described in categories,where the typical adhesion modulation strategies of 2D materials are also introduced.Finally,the remaining challenges and opportunities for the interfacial adhesion measurement and modulation of 2D materials are presented.This paper provides guidance for addressing the adhesion issues in devices and systems involving 2D materials.
