Accurate quantification of exercise interventions and changes in muscle function is essential for personalized health management.Electrical impedance myography(EIM)technology offers an innovative,noninvasive,painless,...Accurate quantification of exercise interventions and changes in muscle function is essential for personalized health management.Electrical impedance myography(EIM)technology offers an innovative,noninvasive,painless,and easy-to-perform solution for muscle health monitoring.However,current EIM platforms face a number of limitations,including large device size,wired connections,and instability of the electrode-skin interface,which limit their applicability for monitoring mus-cle movement.In this study,a miniature wireless EIM platform with a user-friendly smartphone app is proposed and devel-oped.The miniature,wireless,multi-frequency(20 kHz-1 MHz)EIM platform is equipped with flexible microneedle array elec-trodes(MAE).The advantages of MAEs over conventional electrodes were demonstrated by physical field modeling simula-tions and skin-electrode contact impedance comparison tests.The smartphone APP was developed to wirelessly operate the EIM platform,and to transmit and process real-time muscle impedance data.To validate its effectiveness,a seven-day adaptive fatigue training study was conducted,which demonstrated that the EIM platform was able to detect muscle adaptations and serve as a reliable indicator of fatigue.This study presents an innovative approach to applying EIM technology to muscle health monitoring and exercise testing,thereby advancing the development of personalized health management and athletic performance assessment.展开更多
Marine risers play a key role in the deep and ultra-deep water oil and gas production. The vortex-induced vibration （VIV） of marine risers constitutes an important problem in deep water oil exploration and productio...Marine risers play a key role in the deep and ultra-deep water oil and gas production. The vortex-induced vibration （VIV） of marine risers constitutes an important problem in deep water oil exploration and production. VIV will result in high rates of structural failure of marine riser due to fatigue damage accumulation and diminishes the riser fatigue life. In-service monitoring or full scale testing is essential to improve our understanding of V1V response and enhance our ability to predict fatigue damage. One ma- rine riser fatigue acoustic telemetry scheme is proposed and an engineering prototype machine has been developed to monitor deep and ultra-deep water risers＇ fatigue and failure that can diminish the riser fatigue life and lead to economic losses and eco-catastrophe. Many breakthroughs and innovation have been achieved in the process of developing an engineering prototype machine. Sea trials were done on the 6th generation deep-water drilling platform HYSY-981 in the South China Sea. The inclination monitoring results show that the marine riser fatigue acoustic telemetry scheme is feasible and reliable and the engineering prototype machine meets the design criterion and can match the requirements of deep and ultra-deep water riser fatigue monitoring. The rich experience and field data gained in the sea trial which provide much technical support for optimization in the engineering prototype machine in the future.展开更多
Fatigue damage is a primary contributor to the failure of composite structures,underscoring the critical importance of monitoring its progression to ensure structural safety.This paper introduces an innovative approac...Fatigue damage is a primary contributor to the failure of composite structures,underscoring the critical importance of monitoring its progression to ensure structural safety.This paper introduces an innovative approach to fatigue damage monitoring in composite structures,leveraging a hybrid methodology that integrates the Whale Optimization Algorithm(WOA)-Backpropagation(BP)neural network with an ultrasonic guided wave feature selection algorithm.Initially,a network of piezoelectric ceramic sensors is employed to transmit and capture ultrasonic-guided waves,thereby establishing a signal space that correlates with the structural condition.Subsequently,the Relief-F algorithm is applied for signal feature extraction,culminating in the formation of a feature matrix.This matrix is then utilized to train the WOA-BP neural network,which optimizes the fatigue damage identification model globally.The proposed model’s efficacy in quantifying fatigue damage is tested against fatigue test datasets,with its performance benchmarked against the traditional BP neural network algorithm.The findings demonstrate that the WOA-BP neural network model not only surpasses the BP model in predictive accuracy but also exhibits enhanced global search capabilities.The effect of different sensor-receiver path signals on the model damage recognition results is also discussed.The results of the discussion found that the path directly through the damaged area is more accurate in modeling damage recognition compared to the path signals away from the damaged area.Consequently,the proposed monitoring method in the fatigue test dataset is adept at accurately tracking and recognizing the progression of fatigue damage.展开更多
Individual aircraft life monitoring is required to ensure safety and economy of aircraft structure, and fatigue damage evaluation based on collected operational data of aircraft is an integral part of it. To improve t...Individual aircraft life monitoring is required to ensure safety and economy of aircraft structure, and fatigue damage evaluation based on collected operational data of aircraft is an integral part of it. To improve the accuracy and facilitate the application, this paper proposes an engineering approach to evaluate fatigue damage and predict fatigue life for critical structures in fatigue monitoring. In this approach, traditional nominal stress method is applied to back calculate the S-N curve parameters of the realistic structure details based on full-scale fatigue test data. Then the S-N curve and Miner＇s rule are adopted in damage estimation and fatigue life analysis for critical locations under individual load spectra. The relationship between relative small crack length and fatigue life can also be predicted with this approach. Specimens of 7 B04-T74 aluminum alloy and TA15 M titanium alloy are fatigue tested under two types of load spectra, and there is a good agreement between the experimental results and analysis results. Furthermore, the issue concerning scatter factor in individual aircraft damage estimation is also discussed.展开更多
The prevention of fatigue damages is a crucial issue for NPPs （nuclear power plants）. The AFC （AR.EVA fatigue concept） provides for a multi-step and mnlti-disciplinary process against fatigue during the design and...The prevention of fatigue damages is a crucial issue for NPPs （nuclear power plants）. The AFC （AR.EVA fatigue concept） provides for a multi-step and mnlti-disciplinary process against fatigue during the design and operating phase of NPPs. The entire process of fatigne design is based on an installed FAMOS （fatigue monitoring system）. In this way, realistic load data are available to manage the component ageing and enable the optimization of operating modes. The measured temperatures are processed via a FFE （fast fatigue evaluation）. Thus, an online fatigue evaluation of the cumulative usage factor is performed after every operational cycle. This procedure gives a first fatigue status of the power plant. Furthermore, a DFC （detailed fatigue calculation） conforming to the code rules is carried out in order to determine the state of the plant at the highest loaded positions. These finite element analyses include determination of thermal transient and subsequent stresses and strains. Fatigue environmental factors are taken into account in these studies.展开更多
Nonlinear ultrasonic imaging techniques in pulse-echo configuration have recently shown their potential to allow the effective separation of nonlinear and linear features in a nonlinear image.In this study,two ultraso...Nonlinear ultrasonic imaging techniques in pulse-echo configuration have recently shown their potential to allow the effective separation of nonlinear and linear features in a nonlinear image.In this study,two ultrasonic phased arrays are implemented to produce an image of elastic nonlinearity through the parallel-sequential subtraction of the coherently scattered components in the through-transmission acoustic field at the transmission or subharmonic frequency.In parallel mode,a physical focus at each pixel is achieved by firing the transmitters with a predefined delay law.In sequential mode,each transmitter is fired in sequence and all the receivers are employed to capture the data simultaneously.This full matrix captured data can be post-processed and focused synthetically at the target area.The images of parallel focusing and sequential focusing are expected to be linearly identical and hence any differences remained on the subtracted image can be related to the nonlinearities arising from the defects.Therefore,the imaging metric here is defined as the difference between parallel and sequentially focused amplitudes obtained from forward coherently scattered fields at each target point.Additionally,the negative influences due to the instrumentation nonlinearities are investigated by studying the remaining relative phase and amplitude at undamaged pixels.A compensation method is implemented to suppress these noises,significantly enhancing the selectivity of nonlinear scattering features.The proposed techniques are then implemented to monitor fatigue crack growth in order to explore the capability of these methods as measures of elastic nonlinearity induced by different sizes of small closed cracks.The promising results suggest that nonlinear imaging can be used to monitor crack growth and improve the detectability at early stages.展开更多
文摘Accurate quantification of exercise interventions and changes in muscle function is essential for personalized health management.Electrical impedance myography(EIM)technology offers an innovative,noninvasive,painless,and easy-to-perform solution for muscle health monitoring.However,current EIM platforms face a number of limitations,including large device size,wired connections,and instability of the electrode-skin interface,which limit their applicability for monitoring mus-cle movement.In this study,a miniature wireless EIM platform with a user-friendly smartphone app is proposed and devel-oped.The miniature,wireless,multi-frequency(20 kHz-1 MHz)EIM platform is equipped with flexible microneedle array elec-trodes(MAE).The advantages of MAEs over conventional electrodes were demonstrated by physical field modeling simula-tions and skin-electrode contact impedance comparison tests.The smartphone APP was developed to wirelessly operate the EIM platform,and to transmit and process real-time muscle impedance data.To validate its effectiveness,a seven-day adaptive fatigue training study was conducted,which demonstrated that the EIM platform was able to detect muscle adaptations and serve as a reliable indicator of fatigue.This study presents an innovative approach to applying EIM technology to muscle health monitoring and exercise testing,thereby advancing the development of personalized health management and athletic performance assessment.
基金supported in part by the National Science and Technology Major Project of China (2011ZX 05026-001-06)the National Natural Science Foundation of China (51249005 60972153)
文摘Marine risers play a key role in the deep and ultra-deep water oil and gas production. The vortex-induced vibration （VIV） of marine risers constitutes an important problem in deep water oil exploration and production. VIV will result in high rates of structural failure of marine riser due to fatigue damage accumulation and diminishes the riser fatigue life. In-service monitoring or full scale testing is essential to improve our understanding of V1V response and enhance our ability to predict fatigue damage. One ma- rine riser fatigue acoustic telemetry scheme is proposed and an engineering prototype machine has been developed to monitor deep and ultra-deep water risers＇ fatigue and failure that can diminish the riser fatigue life and lead to economic losses and eco-catastrophe. Many breakthroughs and innovation have been achieved in the process of developing an engineering prototype machine. Sea trials were done on the 6th generation deep-water drilling platform HYSY-981 in the South China Sea. The inclination monitoring results show that the marine riser fatigue acoustic telemetry scheme is feasible and reliable and the engineering prototype machine meets the design criterion and can match the requirements of deep and ultra-deep water riser fatigue monitoring. The rich experience and field data gained in the sea trial which provide much technical support for optimization in the engineering prototype machine in the future.
基金funded by the Key Program of the National Natural Science Foundation of China(U2341235)Youth Fund for Basic Research Program of Jiangnan University(JUSRP123003)+2 种基金Postgraduate Research&Practice Innovation Program of Jiangsu Province(SJCX23_1237)the National Key R&D Program of China(2018YFA0702800)Key Technologies R&D Program of CNBM(2023SJYL01).
文摘Fatigue damage is a primary contributor to the failure of composite structures,underscoring the critical importance of monitoring its progression to ensure structural safety.This paper introduces an innovative approach to fatigue damage monitoring in composite structures,leveraging a hybrid methodology that integrates the Whale Optimization Algorithm(WOA)-Backpropagation(BP)neural network with an ultrasonic guided wave feature selection algorithm.Initially,a network of piezoelectric ceramic sensors is employed to transmit and capture ultrasonic-guided waves,thereby establishing a signal space that correlates with the structural condition.Subsequently,the Relief-F algorithm is applied for signal feature extraction,culminating in the formation of a feature matrix.This matrix is then utilized to train the WOA-BP neural network,which optimizes the fatigue damage identification model globally.The proposed model’s efficacy in quantifying fatigue damage is tested against fatigue test datasets,with its performance benchmarked against the traditional BP neural network algorithm.The findings demonstrate that the WOA-BP neural network model not only surpasses the BP model in predictive accuracy but also exhibits enhanced global search capabilities.The effect of different sensor-receiver path signals on the model damage recognition results is also discussed.The results of the discussion found that the path directly through the damaged area is more accurate in modeling damage recognition compared to the path signals away from the damaged area.Consequently,the proposed monitoring method in the fatigue test dataset is adept at accurately tracking and recognizing the progression of fatigue damage.
基金support from National Natural Science Foundation of China (No. 11772027)National Key Research and Development Program of China (No. 2017YFB1104003)Aeronautical Science Foundation of China (No. 28163701002)
文摘Individual aircraft life monitoring is required to ensure safety and economy of aircraft structure, and fatigue damage evaluation based on collected operational data of aircraft is an integral part of it. To improve the accuracy and facilitate the application, this paper proposes an engineering approach to evaluate fatigue damage and predict fatigue life for critical structures in fatigue monitoring. In this approach, traditional nominal stress method is applied to back calculate the S-N curve parameters of the realistic structure details based on full-scale fatigue test data. Then the S-N curve and Miner＇s rule are adopted in damage estimation and fatigue life analysis for critical locations under individual load spectra. The relationship between relative small crack length and fatigue life can also be predicted with this approach. Specimens of 7 B04-T74 aluminum alloy and TA15 M titanium alloy are fatigue tested under two types of load spectra, and there is a good agreement between the experimental results and analysis results. Furthermore, the issue concerning scatter factor in individual aircraft damage estimation is also discussed.
文摘The prevention of fatigue damages is a crucial issue for NPPs （nuclear power plants）. The AFC （AR.EVA fatigue concept） provides for a multi-step and mnlti-disciplinary process against fatigue during the design and operating phase of NPPs. The entire process of fatigne design is based on an installed FAMOS （fatigue monitoring system）. In this way, realistic load data are available to manage the component ageing and enable the optimization of operating modes. The measured temperatures are processed via a FFE （fast fatigue evaluation）. Thus, an online fatigue evaluation of the cumulative usage factor is performed after every operational cycle. This procedure gives a first fatigue status of the power plant. Furthermore, a DFC （detailed fatigue calculation） conforming to the code rules is carried out in order to determine the state of the plant at the highest loaded positions. These finite element analyses include determination of thermal transient and subsequent stresses and strains. Fatigue environmental factors are taken into account in these studies.
基金the Young Talent Support Program of China Association for Science and Technology(Grant No.[2020]No.87)the Science and Technology Major Project of Anhui Province(Grant No.201903a05020010)+2 种基金the Key Research and Development Plan of Anhui Province(Grant No.202004a05020003)the Anhui Provincial Natural Science Foundation(Grant No.2008085J24)the Doctoral Science and Technology Foundation of Hefei General Machinery Research Institute(Grant No.2019010381)。
文摘Nonlinear ultrasonic imaging techniques in pulse-echo configuration have recently shown their potential to allow the effective separation of nonlinear and linear features in a nonlinear image.In this study,two ultrasonic phased arrays are implemented to produce an image of elastic nonlinearity through the parallel-sequential subtraction of the coherently scattered components in the through-transmission acoustic field at the transmission or subharmonic frequency.In parallel mode,a physical focus at each pixel is achieved by firing the transmitters with a predefined delay law.In sequential mode,each transmitter is fired in sequence and all the receivers are employed to capture the data simultaneously.This full matrix captured data can be post-processed and focused synthetically at the target area.The images of parallel focusing and sequential focusing are expected to be linearly identical and hence any differences remained on the subtracted image can be related to the nonlinearities arising from the defects.Therefore,the imaging metric here is defined as the difference between parallel and sequentially focused amplitudes obtained from forward coherently scattered fields at each target point.Additionally,the negative influences due to the instrumentation nonlinearities are investigated by studying the remaining relative phase and amplitude at undamaged pixels.A compensation method is implemented to suppress these noises,significantly enhancing the selectivity of nonlinear scattering features.The proposed techniques are then implemented to monitor fatigue crack growth in order to explore the capability of these methods as measures of elastic nonlinearity induced by different sizes of small closed cracks.The promising results suggest that nonlinear imaging can be used to monitor crack growth and improve the detectability at early stages.
