Sewer pipe condition assessment by performing regular inspections is crucial for ensuring the systems’effective operation and maintenance.CCTV(closed-circuit television)is widely employed in North America to examine ...Sewer pipe condition assessment by performing regular inspections is crucial for ensuring the systems’effective operation and maintenance.CCTV(closed-circuit television)is widely employed in North America to examine the internal conditions of sewage pipes.Due to the extensive inventory of pipes and associated costs,it is not practical for municipalities to conduct inspections on each sanitary sewage pipe section.According to the ASCE(American Society of Civil Engineers)infrastructure report published in 2021,combined investment needs for water and wastewater systems are estimated to be$150 billion during 2016-2025.Therefore,new solutions are needed to fill the trillion-dollar investment gap to improve the existing water and wastewater infrastructure for the coming years.ML(machine learning)based prediction model development is an effective method for predicting the condition of sewer pipes.In this research,sewer pipe inspection data from several municipalities are collected,which include variables such as pipe material,age,diameter,length,soil type,slope of construction,and PACP(Pipeline Assessment Certification Program)score.These sewer pipe data exhibit a severe imbalance in pipes’PACP scores,which is considered the target variable in the development of models.Due to this imbalanced dataset,the performance of the sewer prediction model is poor.This paper,therefore,aims to employ oversampling and hyperparameter tuning techniques to treat the imbalanced data and improve the model’s performance significantly.Utility owners and municipal asset managers can utilize the developed models to make more informed decisions on future inspections of sewer pipelines.展开更多
The expected cost per unit of time for a sequential inspection policy is derived. It still has some difficulties to compute an optimal sequential policy numerically, which minimizes the expected cost of a system with ...The expected cost per unit of time for a sequential inspection policy is derived. It still has some difficulties to compute an optimal sequential policy numerically, which minimizes the expected cost of a system with finite number of inspections. This paper gives the algorithm for an optimal inspection schedule and specifies the computing procedure for a Weibull distribution. Using this algorithm, optimal inspection times are computed as a numerical result. Compared with the periodic point inspection, the policies in this paper reduce the cost successfully.展开更多
With the increasing number of vehicles,manual security inspections are becoming more laborious at road checkpoints.To address it,a specialized Road Checkpoints Robot(RCRo)system is proposed,incorporated with enhanced ...With the increasing number of vehicles,manual security inspections are becoming more laborious at road checkpoints.To address it,a specialized Road Checkpoints Robot(RCRo)system is proposed,incorporated with enhanced You Only Look Once(YOLO)and a 6-degree-of-freedom(DOF)manipulator,for autonomous identity verification and vehicle inspection.The modified YOLO is characterized by large objects’sensitivity and faster detection speed,named“LF-YOLO”.The better sensitivity of large objects and the faster detection speed are achieved by means of the Dense module-based backbone network connecting two-scale detecting network,for object detection tasks,along with optimized anchor boxes and improved loss function.During the manipulator motion,Octree-aided motion control scheme is adopted for collision-free motion through Robot Operating System(ROS).The proposed LF-YOLO which utilizes continuous optimization strategy and residual technique provides a promising detector design,which has been found to be more effective during actual object detection,in terms of decreased average detection time by 68.25%and 60.60%,and increased average Intersection over Union(Io U)by 20.74%and6.79%compared to YOLOv3 and YOLOv4 through experiments.The comprehensive functional tests of RCRo system demonstrate the feasibility and competency of the multiple unmanned inspections in practice.展开更多
This paper is a short introduction to the common type of damages in composite structures and different ways of their inspection. Due to the high increase of interest in composite materials in past decades and their us...This paper is a short introduction to the common type of damages in composite structures and different ways of their inspection. Due to the high increase of interest in composite materials in past decades and their usage in different structures, there is a need to discuss the damage types in them along with different ways of inspection. This paper provides a short review of these facts in order to fill out the gap that there is in the literature. Major emphasis is placed on the damage types and their mechanisms and inspection methods, mostly focused on wave propagation based structural health monitoring (SHM).展开更多
Periodical inspections and an age-based preventive replacement( APR) model were proposed based on a two-stage failure process for a single component system. Inspection activities were performed at regular intervals. O...Periodical inspections and an age-based preventive replacement( APR) model were proposed based on a two-stage failure process for a single component system. Inspection activities were performed at regular intervals. Once the system was identified to be at defective state by inspection,a maintenance decision needed to be made that whether to replace the defective system immediately or wait till the preset APR time. So a threshold was introduced into the model and called as inspection-based preventive replacement( IPR) threshold. If the distance from the defect identification point to the APR time was longer than the threshold, a preventive replacement( PR) action was made; otherwise PR action was to wait till the APR time. Two models were proposed and compared,and a numerical example was conducted to illustrate the applicability of the model.展开更多
Visual inspection of the key components of nuclear power plants(NPPs)is important for NPP operation and maintenance. However,the underwater environment and existing radiation will lead to image degradation,thus making...Visual inspection of the key components of nuclear power plants(NPPs)is important for NPP operation and maintenance. However,the underwater environment and existing radiation will lead to image degradation,thus making it difficult to identify surface defects. In this study,a method for improving the quality of underwater images is proposed.By analyzing the degradation characteristics of underwater detection image,the image enhancement technology is used to improve the color richness of the image,and then the improved dark channel prior(DCP)algorithm is used to restore it. By modifying the estimation formula of transmittance and background light,the correction of insufficient brightness in DCP restored image is realized. The proposed method is compared with other state-of-the-art methods. The results show that the proposed method can achieve higher scores and improve the image quality by correcting the color and restoring local details,thus effectively enhancing the reliability of visual inspection of NPPs.展开更多
This paper covers the safely requirements and inspection methods for insulating components used in electrical accessories by an analyzing the properties of the insulating components used in electrical accessories base...This paper covers the safely requirements and inspection methods for insulating components used in electrical accessories by an analyzing the properties of the insulating components used in electrical accessories based on the standard of IEC 60884.展开更多
The manual visual inspections of façade building defects are posing a high and increasing cost for building asset managers,particularly when inspections delay projects or require asset outages,visits to decommiss...The manual visual inspections of façade building defects are posing a high and increasing cost for building asset managers,particularly when inspections delay projects or require asset outages,visits to decommissioned sites or work within hazardous environments.This paper reports on the development,testing and delivery of a working mobile app prototype to facilitate the inspections and documentation of building facade condition monitoring.The work presented builds upon the development of an online platform for remote building inspection based on the integration of methodologies and tools,including VR(virtual reality),and digital photogrammetry to collect real-time data that support automated decision making.The mobile app:(i)allows the user to import 3D models and 2D building plans;(ii)provides the means of first-person exploration of models via a VR headset;and(iii)captures,records and catalogues images of façade defect types,and the date and time.An inspection case study was used to demonstrate and evaluate the mobile app prototype.The Building Inspector app allows building professionals to manage inspections and to track past and ongoing monitoring of the condition of building façades.展开更多
To develop China’s human rights cause with a people-centered approach,we should pay close attention to the concrete experiences of the general public regarding the protection of human rights.Deepening the research on...To develop China’s human rights cause with a people-centered approach,we should pay close attention to the concrete experiences of the general public regarding the protection of human rights.Deepening the research on the perception of respect for human rights can contribute to a more comprehensive understanding of the practical achievements of the hu man rights cause.Public environmental rights,as a new type of human rights,have become an important aspect of the development of the human rights cause in the new era.The central envi ronmental inspection,as an authoritative and interventionist vertical governance mechanism,promotes the implementation of environmental policies by local Party committees and govern ments and strengthens environmental information disclosure and public participation in environ mental matters.As a result,it contributes to the realization of public environmental rights and stimulates public perception of respect for human rights.Among them,the“look-back inspec tion is an important component of the central environmental inspection,and its implemen tation consolidates and enhances the previous inspection work.An empirical analysis based on the World Values Survey’s data for China indicates that residents in the provinces that have underg one“look-back inspections are more inclined to believe that human rights are adequately re spected compared to residents in the provinces that have not underwent such inspections.It suggests that the advancement and improvement of the central environmental inspection system promote improvements in ecological environment quality and contribute to enhancing the public percep tion of respect for human rights.展开更多
Assume that a target is hidden or lost in one of several possible locations and is to be found by the unmanned aerial vehicle (UAV). A target can be either a hostile object or missing personnel in remote areas. Prior ...Assume that a target is hidden or lost in one of several possible locations and is to be found by the unmanned aerial vehicle (UAV). A target can be either a hostile object or missing personnel in remote areas. Prior probabilities of target locations are known. Inspection operations done by the UAVs are imperfect, namely, probabilities of overlooking the hidden target and probabilities of false alarms exist for any possible location. The UAV has to sequentially inspect the locations so that to find the target with the minimum loss or damage incurred by the target before it is detected subject to a required level of confidence of target identification. A fast (polynomial-time) priority-based algorithm for finding an optimal search strategy is developed.展开更多
Bum-in has been proven effective in identifying and removing defective products before they are delivered to customers.Most existing bum-in models adopt a one-shot scheme,which may not be sufficient enough for identif...Bum-in has been proven effective in identifying and removing defective products before they are delivered to customers.Most existing bum-in models adopt a one-shot scheme,which may not be sufficient enough for identification.Borrowing the idea from sequential inspections for remaining useful life prediction and accelerated lifetime test,this study proposes a sequential degradation-based bum-in model with multiple periodic inspections.At each inspection epoch,the posterior probability that a product belongs to a normal one is updated with the inspected degradation level.Based on the degradation level and the updated posterior probability,a product can be disposed,put into field use,or kept in the test till the next inspection epoch.We cast the problem into a partially observed Markov decision process to minimize the expected total bum-in cost of a product,and derive some interesting structures of the optimal policy.Then,algorithms are provided to find the joint optimal inspection period and number of inspections in steps.A numerical study is also provided to illustrate the effectiveness of our proposed model.展开更多
HUBEI AND THE RISE OF CENTRAL CHINA Outlook Weekly 9 February Hubei’s recent development trajectory offers a vivid case study of how China’s central provinces are being repositioned as engines of national growth.Dur...HUBEI AND THE RISE OF CENTRAL CHINA Outlook Weekly 9 February Hubei’s recent development trajectory offers a vivid case study of how China’s central provinces are being repositioned as engines of national growth.During an inspection tour in November 2024.展开更多
Fabric defect detection plays a vital role in ensuring textile quality.However,traditional manual inspection methods are often inefficient and inaccurate.To overcome these limitations,we propose FD-YOLO,an enhanced li...Fabric defect detection plays a vital role in ensuring textile quality.However,traditional manual inspection methods are often inefficient and inaccurate.To overcome these limitations,we propose FD-YOLO,an enhanced lightweight detection model based on the YOLOv11n framework.The proposed model introduces the Bi-level Routing Attention(BRAttention)mechanism to enhance defect feature extraction,enabling more detailed feature representation.It proposes Deep Progressive Cross-Scale Fusion Neck(DPCSFNeck)to better capture smallscale defects and incorporates a Multi-Scale Dilated Residual(MSDR)module to strengthen multi-scale feature representation.Furthermore,a Shared Detail-Enhanced Lightweight Head(SDELHead)is employed to reduce the risk of gradient explosion during training.Experimental results demonstrate that FD-YOLO achieves superior detection accuracy and Lightweight performance compared to the baseline YOLOv11n.展开更多
The main cable is the primary load-bearing component of a suspension bridge,continuously exposed to harsh environmental conditions,such as wind and rain,throughout the year.These adverse conditions contribute to varyi...The main cable is the primary load-bearing component of a suspension bridge,continuously exposed to harsh environmental conditions,such as wind and rain,throughout the year.These adverse conditions contribute to varying degrees of degradation and damage to the main cable,necessitating regular inspections to prevent catastrophic failures.Traditional manual inspection methods not only suffer from low efficiency but also pose significant safety risks to personnel.To address these challenges and ensure the safe and effective inspection of suspension bridge main cables,this study introduces a novel cooperative climbing robot,designated as Main Cable Robot Version II(CCRobot-M-II),inspired by the locomotion of the inchworm.The robot employs an alternating opening and closing mechanism of four gripper sets,mimicking the inchworm's movement to achieve efficient crawling along the suspension bridge handrails.This paper provides a comprehensive analysis of the structural design,key components,and motion mechanisms of CCRobot-M-II.A detailed force analysis of the robot's crawling process is also presented,followed by the design of the control system and the development of an efficient motion control algorithm.Laboratory experiments demonstrate that the robot achieves a positional error of 00.64%during crawling,with a maximum average crawling speed of 7.6 m/min.Furthermore,the biomimetic design enables the robot to overcome obstacles up to 30 mm in height and possess the capability to handle suspension bridge cables with spans ranging from 740 to 1100 mm.Finally,CCRobot-M-II successfully conducted an inspection of the main cable on a suspension bridge,marking the world's first successful deployment of a climbing robot for main cable inspection on a suspension bridge.展开更多
The spatial offset of bridge has a significant impact on the safety,comfort,and durability of high-speed railway(HSR)operations,so it is crucial to rapidly and effectively detect the spatial offset of operational HSR ...The spatial offset of bridge has a significant impact on the safety,comfort,and durability of high-speed railway(HSR)operations,so it is crucial to rapidly and effectively detect the spatial offset of operational HSR bridges.Drive-by monitoring of bridge uneven settlement demonstrates significant potential due to its practicality,cost-effectiveness,and efficiency.However,existing drive-by methods for detecting bridge offset have limitations such as reliance on a single data source,low detection accuracy,and the inability to identify lateral deformations of bridges.This paper proposes a novel drive-by inspection method for spatial offset of HSR bridge based on multi-source data fusion of comprehensive inspection train.Firstly,dung beetle optimizer-variational mode decomposition was employed to achieve adaptive decomposition of non-stationary dynamic signals,and explore the hidden temporal relationships in the data.Subsequently,a long short-term memory neural network was developed to achieve feature fusion of multi-source signal and accurate prediction of spatial settlement of HSR bridge.A dataset of track irregularities and CRH380A high-speed train responses was generated using a 3D train-track-bridge interaction model,and the accuracy and effectiveness of the proposed hybrid deep learning model were numerically validated.Finally,the reliability of the proposed drive-by inspection method was further validated by analyzing the actual measurement data obtained from comprehensive inspection train.The research findings indicate that the proposed approach enables rapid and accurate detection of spatial offset in HSR bridge,ensuring the long-term operational safety of HSR bridges.展开更多
Manual inspection of onba earing casting defects is not realistic and unreliable,particularly in the case of some micro-level anomalies which lead to major defects on a large scale.To address these challenges,we propo...Manual inspection of onba earing casting defects is not realistic and unreliable,particularly in the case of some micro-level anomalies which lead to major defects on a large scale.To address these challenges,we propose BearFusionNet,an attention-based deep learning architecture with multi-stream,which merges both DenseNet201 and MobileNetV2 for feature extraction with a classification head inspired by VGG19.This hybrid design,figuratively beaming from one layer to another,extracts the enormity of representations on different scales,backed by a prepreprocessing pipeline that brings defect saliency to the fore through contrast adjustment,denoising,and edge detection.The use of multi-head self-attention enhances feature fusion,enabling the model to capture both large and small spatial features.BearFusionNet achieves an accuracy of 99.66%and Cohen’s kappa score of 0.9929 in Kaggle’s Real-life Industrial Casting Defects dataset.Both McNemar’s and Wilcoxon signed-rank statistical tests,as well as fivefold cross-validation,are employed to assess the robustness of our proposed model.To interpret the model,we adopt Grad-Cam visualizations,which are the state of the art standard.Furthermore,we deploy BearFusionNet as a webbased system for near real-time inference(5-6 s per prediction),which enables the quickest yet accurate detection with visual explanations.Overall,BearFusionNet is an interpretable,accurate,and deployable solution that can automatically detect casting defects,leading to significant advances in the innovative industrial environment.展开更多
Purpose-Amidst an increasingly severe cybersecurity landscape,the widespread adoption of Xinchuang endpoints has become a strategic imperative.Governments and enterprises have established terminal localization as a cr...Purpose-Amidst an increasingly severe cybersecurity landscape,the widespread adoption of Xinchuang endpoints has become a strategic imperative.Governments and enterprises have established terminal localization as a critical objective,aiming for comprehensive indigenous replacement through rapid technological iteration.Consequently,Xinchuang systems and Windows platforms are expected to coexist over an extended period.This study seeks to establish an automated verification framework for multi-version operating systems and validate the efficacy of baseline hardening in mitigating security risks.Design/methodology/approach-Based on the Classified Protection 2.0 framework and relevant national standards for endpoint security,this study proposes an endpoint security baseline verification scheme applicable to multiple operating systems.The scheme addresses divergent security policies and implementation methodologies across heterogeneous environments.It automates the inspection of core baselines,including account password complexity,default shared service status and patch installation status.Furthermore,a comprehensive scoring model is established by incorporating differentiated weights for account security,patch management and log auditing,ultimately generating visualized risk reports to facilitate remediation prioritization.Findings-This study reveals that baseline configuration serves as the fundamental prerequisite in endpoint security practices.Through a scalable detection engine and quantitative scoring model,the system can promptly identify and remediate potential risks,thereby reducing the attack surface and mitigating intrusion risks.However,on certain domestic chip architectures,compatibility issues persist in detecting specific configuration items.Further improvement in hardware-software co-adaptation for domestic platforms is required to advance the development of localized security protection systems.Originality/value-Through in-depth research on security baseline configurations across multiple operating systems,this study implements an automated and visualized baseline verification methodology.This approach significantly strengthens the security posture of domestic operating systems and supports the establishment of a more robust,national-level cybersecurity defense framework.展开更多
Pipelines are extensively used in environments such as nuclear power plants,chemical factories,and medical devices to transport gases and liquids.These tubular environments often feature complex geometries,confined sp...Pipelines are extensively used in environments such as nuclear power plants,chemical factories,and medical devices to transport gases and liquids.These tubular environments often feature complex geometries,confined spaces,and millimeter-scale height restrictions,presenting significant challenges to conventional inspection methods.Here,we present an ultrasonic microrobot(weight,80 mg;dimensions,24 mm×7 mm;thickness,210μm)to realize agile and bidirectional navigation in narrow pipelines.The ultrathin structural design of the robot is achieved through a high-performance piezoelectric composite film microstructure based on MEMS technology.The robot exhibits various vibration modes when driven by ultrasonic frequency signals,its motion speed reaches81 cm s-1 at 54.8 k Hz,exceeding that of the fastest piezoelectric microrobots,and its forward and backward motion direction is controllable through frequency modulation,while the minimum driving voltage for initial movement can be as low as 3 VP-P.Additionally,the robot can effortlessly climb slopes up to 24.25°and carry loads more than 36 times its weight.The robot is capable of agile navigation through curved L-shaped pipes,pipes made of various materials(acrylic,stainless steel,and polyvinyl chloride),and even over water.To further demonstrate its inspection capabilities,a micro-endoscope camera is integrated into the robot,enabling real-time image capture inside glass pipes.展开更多
文摘Sewer pipe condition assessment by performing regular inspections is crucial for ensuring the systems’effective operation and maintenance.CCTV(closed-circuit television)is widely employed in North America to examine the internal conditions of sewage pipes.Due to the extensive inventory of pipes and associated costs,it is not practical for municipalities to conduct inspections on each sanitary sewage pipe section.According to the ASCE(American Society of Civil Engineers)infrastructure report published in 2021,combined investment needs for water and wastewater systems are estimated to be$150 billion during 2016-2025.Therefore,new solutions are needed to fill the trillion-dollar investment gap to improve the existing water and wastewater infrastructure for the coming years.ML(machine learning)based prediction model development is an effective method for predicting the condition of sewer pipes.In this research,sewer pipe inspection data from several municipalities are collected,which include variables such as pipe material,age,diameter,length,soil type,slope of construction,and PACP(Pipeline Assessment Certification Program)score.These sewer pipe data exhibit a severe imbalance in pipes’PACP scores,which is considered the target variable in the development of models.Due to this imbalanced dataset,the performance of the sewer prediction model is poor.This paper,therefore,aims to employ oversampling and hyperparameter tuning techniques to treat the imbalanced data and improve the model’s performance significantly.Utility owners and municipal asset managers can utilize the developed models to make more informed decisions on future inspections of sewer pipelines.
文摘The expected cost per unit of time for a sequential inspection policy is derived. It still has some difficulties to compute an optimal sequential policy numerically, which minimizes the expected cost of a system with finite number of inspections. This paper gives the algorithm for an optimal inspection schedule and specifies the computing procedure for a Weibull distribution. Using this algorithm, optimal inspection times are computed as a numerical result. Compared with the periodic point inspection, the policies in this paper reduce the cost successfully.
基金supported by the National Key Research and Development Program of China(grant number:2017YFC0806503)。
文摘With the increasing number of vehicles,manual security inspections are becoming more laborious at road checkpoints.To address it,a specialized Road Checkpoints Robot(RCRo)system is proposed,incorporated with enhanced You Only Look Once(YOLO)and a 6-degree-of-freedom(DOF)manipulator,for autonomous identity verification and vehicle inspection.The modified YOLO is characterized by large objects’sensitivity and faster detection speed,named“LF-YOLO”.The better sensitivity of large objects and the faster detection speed are achieved by means of the Dense module-based backbone network connecting two-scale detecting network,for object detection tasks,along with optimized anchor boxes and improved loss function.During the manipulator motion,Octree-aided motion control scheme is adopted for collision-free motion through Robot Operating System(ROS).The proposed LF-YOLO which utilizes continuous optimization strategy and residual technique provides a promising detector design,which has been found to be more effective during actual object detection,in terms of decreased average detection time by 68.25%and 60.60%,and increased average Intersection over Union(Io U)by 20.74%and6.79%compared to YOLOv3 and YOLOv4 through experiments.The comprehensive functional tests of RCRo system demonstrate the feasibility and competency of the multiple unmanned inspections in practice.
文摘This paper is a short introduction to the common type of damages in composite structures and different ways of their inspection. Due to the high increase of interest in composite materials in past decades and their usage in different structures, there is a need to discuss the damage types in them along with different ways of inspection. This paper provides a short review of these facts in order to fill out the gap that there is in the literature. Major emphasis is placed on the damage types and their mechanisms and inspection methods, mostly focused on wave propagation based structural health monitoring (SHM).
基金National Natural Science Foundation of China(NSFC)(No.71231001)China Postdoctoral Science Foundation Funded Project(No.2013M530531)+1 种基金the Fundamental Research Funds for the Central Universities of China(Nos.FRF-M P-13-009A,FRF-TP-13-026A)the MOE PhD Supervisor Fund,China(No.20120006110025)
文摘Periodical inspections and an age-based preventive replacement( APR) model were proposed based on a two-stage failure process for a single component system. Inspection activities were performed at regular intervals. Once the system was identified to be at defective state by inspection,a maintenance decision needed to be made that whether to replace the defective system immediately or wait till the preset APR time. So a threshold was introduced into the model and called as inspection-based preventive replacement( IPR) threshold. If the distance from the defect identification point to the APR time was longer than the threshold, a preventive replacement( PR) action was made; otherwise PR action was to wait till the APR time. Two models were proposed and compared,and a numerical example was conducted to illustrate the applicability of the model.
基金supported by the National Natural Science Foundations of China (Nos. 51674031,51874022)。
文摘Visual inspection of the key components of nuclear power plants(NPPs)is important for NPP operation and maintenance. However,the underwater environment and existing radiation will lead to image degradation,thus making it difficult to identify surface defects. In this study,a method for improving the quality of underwater images is proposed.By analyzing the degradation characteristics of underwater detection image,the image enhancement technology is used to improve the color richness of the image,and then the improved dark channel prior(DCP)algorithm is used to restore it. By modifying the estimation formula of transmittance and background light,the correction of insufficient brightness in DCP restored image is realized. The proposed method is compared with other state-of-the-art methods. The results show that the proposed method can achieve higher scores and improve the image quality by correcting the color and restoring local details,thus effectively enhancing the reliability of visual inspection of NPPs.
文摘This paper covers the safely requirements and inspection methods for insulating components used in electrical accessories by an analyzing the properties of the insulating components used in electrical accessories based on the standard of IEC 60884.
文摘The manual visual inspections of façade building defects are posing a high and increasing cost for building asset managers,particularly when inspections delay projects or require asset outages,visits to decommissioned sites or work within hazardous environments.This paper reports on the development,testing and delivery of a working mobile app prototype to facilitate the inspections and documentation of building facade condition monitoring.The work presented builds upon the development of an online platform for remote building inspection based on the integration of methodologies and tools,including VR(virtual reality),and digital photogrammetry to collect real-time data that support automated decision making.The mobile app:(i)allows the user to import 3D models and 2D building plans;(ii)provides the means of first-person exploration of models via a VR headset;and(iii)captures,records and catalogues images of façade defect types,and the date and time.An inspection case study was used to demonstrate and evaluate the mobile app prototype.The Building Inspector app allows building professionals to manage inspections and to track past and ongoing monitoring of the condition of building façades.
基金a phased achievement of“Research on the Improvement of the Central Environmental Inspection System”(project No.21ZDA088)a key project on studying and interpreting the guiding principles of the Fifth Plenary Session of the 19th CPC Central Committeeunder the support of the National Social Science Fund of China。
文摘To develop China’s human rights cause with a people-centered approach,we should pay close attention to the concrete experiences of the general public regarding the protection of human rights.Deepening the research on the perception of respect for human rights can contribute to a more comprehensive understanding of the practical achievements of the hu man rights cause.Public environmental rights,as a new type of human rights,have become an important aspect of the development of the human rights cause in the new era.The central envi ronmental inspection,as an authoritative and interventionist vertical governance mechanism,promotes the implementation of environmental policies by local Party committees and govern ments and strengthens environmental information disclosure and public participation in environ mental matters.As a result,it contributes to the realization of public environmental rights and stimulates public perception of respect for human rights.Among them,the“look-back inspec tion is an important component of the central environmental inspection,and its implemen tation consolidates and enhances the previous inspection work.An empirical analysis based on the World Values Survey’s data for China indicates that residents in the provinces that have underg one“look-back inspections are more inclined to believe that human rights are adequately re spected compared to residents in the provinces that have not underwent such inspections.It suggests that the advancement and improvement of the central environmental inspection system promote improvements in ecological environment quality and contribute to enhancing the public percep tion of respect for human rights.
文摘Assume that a target is hidden or lost in one of several possible locations and is to be found by the unmanned aerial vehicle (UAV). A target can be either a hostile object or missing personnel in remote areas. Prior probabilities of target locations are known. Inspection operations done by the UAVs are imperfect, namely, probabilities of overlooking the hidden target and probabilities of false alarms exist for any possible location. The UAV has to sequentially inspect the locations so that to find the target with the minimum loss or damage incurred by the target before it is detected subject to a required level of confidence of target identification. A fast (polynomial-time) priority-based algorithm for finding an optimal search strategy is developed.
基金The research is supported by the National Natural Science Foundation of China(Grant Nos.7180116&72071138 and 72071071)the Young Talent Support Plan of Hebei Province.
文摘Bum-in has been proven effective in identifying and removing defective products before they are delivered to customers.Most existing bum-in models adopt a one-shot scheme,which may not be sufficient enough for identification.Borrowing the idea from sequential inspections for remaining useful life prediction and accelerated lifetime test,this study proposes a sequential degradation-based bum-in model with multiple periodic inspections.At each inspection epoch,the posterior probability that a product belongs to a normal one is updated with the inspected degradation level.Based on the degradation level and the updated posterior probability,a product can be disposed,put into field use,or kept in the test till the next inspection epoch.We cast the problem into a partially observed Markov decision process to minimize the expected total bum-in cost of a product,and derive some interesting structures of the optimal policy.Then,algorithms are provided to find the joint optimal inspection period and number of inspections in steps.A numerical study is also provided to illustrate the effectiveness of our proposed model.
文摘HUBEI AND THE RISE OF CENTRAL CHINA Outlook Weekly 9 February Hubei’s recent development trajectory offers a vivid case study of how China’s central provinces are being repositioned as engines of national growth.During an inspection tour in November 2024.
基金financially supported by the Fujian Provincial Department of Science and Technology,the Collaborative Innovation Platform Project for Key Technologies of Smart Warehousing and Logistics Systems in the Fuzhou-Xiamen-Quanzhou National Independent Innovation Demonstration Zone(No.2025E3024).
文摘Fabric defect detection plays a vital role in ensuring textile quality.However,traditional manual inspection methods are often inefficient and inaccurate.To overcome these limitations,we propose FD-YOLO,an enhanced lightweight detection model based on the YOLOv11n framework.The proposed model introduces the Bi-level Routing Attention(BRAttention)mechanism to enhance defect feature extraction,enabling more detailed feature representation.It proposes Deep Progressive Cross-Scale Fusion Neck(DPCSFNeck)to better capture smallscale defects and incorporates a Multi-Scale Dilated Residual(MSDR)module to strengthen multi-scale feature representation.Furthermore,a Shared Detail-Enhanced Lightweight Head(SDELHead)is employed to reduce the risk of gradient explosion during training.Experimental results demonstrate that FD-YOLO achieves superior detection accuracy and Lightweight performance compared to the baseline YOLOv11n.
基金Shenzhen Science and Technology Program(Grant No.20220817171811004)(Grant No.RCBS20231211090816033)+4 种基金the Major Key Project of PCL,China under Grant PCL2025A13Longgang District,Shenzhen's"Ten-Action Plan"for Supporting Innovation Projects(Grant No.LGKCSDPT2024002,LGKCSDPT2024003,LGKCSDPT2024004)the"Zhiguo"Action of Guangxi Science and Technology Program(Grant No.ZG2503980003)Guangdong S&T Program under(Grant No.2025B0909040003)Guangdong Provincial Leading Talent Program(Grant No.2024TX08Z319).
文摘The main cable is the primary load-bearing component of a suspension bridge,continuously exposed to harsh environmental conditions,such as wind and rain,throughout the year.These adverse conditions contribute to varying degrees of degradation and damage to the main cable,necessitating regular inspections to prevent catastrophic failures.Traditional manual inspection methods not only suffer from low efficiency but also pose significant safety risks to personnel.To address these challenges and ensure the safe and effective inspection of suspension bridge main cables,this study introduces a novel cooperative climbing robot,designated as Main Cable Robot Version II(CCRobot-M-II),inspired by the locomotion of the inchworm.The robot employs an alternating opening and closing mechanism of four gripper sets,mimicking the inchworm's movement to achieve efficient crawling along the suspension bridge handrails.This paper provides a comprehensive analysis of the structural design,key components,and motion mechanisms of CCRobot-M-II.A detailed force analysis of the robot's crawling process is also presented,followed by the design of the control system and the development of an efficient motion control algorithm.Laboratory experiments demonstrate that the robot achieves a positional error of 00.64%during crawling,with a maximum average crawling speed of 7.6 m/min.Furthermore,the biomimetic design enables the robot to overcome obstacles up to 30 mm in height and possess the capability to handle suspension bridge cables with spans ranging from 740 to 1100 mm.Finally,CCRobot-M-II successfully conducted an inspection of the main cable on a suspension bridge,marking the world's first successful deployment of a climbing robot for main cable inspection on a suspension bridge.
基金sponsored by the National Natural Science Foundation of China(Grant No.52178100).
文摘The spatial offset of bridge has a significant impact on the safety,comfort,and durability of high-speed railway(HSR)operations,so it is crucial to rapidly and effectively detect the spatial offset of operational HSR bridges.Drive-by monitoring of bridge uneven settlement demonstrates significant potential due to its practicality,cost-effectiveness,and efficiency.However,existing drive-by methods for detecting bridge offset have limitations such as reliance on a single data source,low detection accuracy,and the inability to identify lateral deformations of bridges.This paper proposes a novel drive-by inspection method for spatial offset of HSR bridge based on multi-source data fusion of comprehensive inspection train.Firstly,dung beetle optimizer-variational mode decomposition was employed to achieve adaptive decomposition of non-stationary dynamic signals,and explore the hidden temporal relationships in the data.Subsequently,a long short-term memory neural network was developed to achieve feature fusion of multi-source signal and accurate prediction of spatial settlement of HSR bridge.A dataset of track irregularities and CRH380A high-speed train responses was generated using a 3D train-track-bridge interaction model,and the accuracy and effectiveness of the proposed hybrid deep learning model were numerically validated.Finally,the reliability of the proposed drive-by inspection method was further validated by analyzing the actual measurement data obtained from comprehensive inspection train.The research findings indicate that the proposed approach enables rapid and accurate detection of spatial offset in HSR bridge,ensuring the long-term operational safety of HSR bridges.
基金funded by Multimedia University,Cyberjaya,Selangor,Malaysia(Grant Number:PostDoc(MMUI/240029)).
文摘Manual inspection of onba earing casting defects is not realistic and unreliable,particularly in the case of some micro-level anomalies which lead to major defects on a large scale.To address these challenges,we propose BearFusionNet,an attention-based deep learning architecture with multi-stream,which merges both DenseNet201 and MobileNetV2 for feature extraction with a classification head inspired by VGG19.This hybrid design,figuratively beaming from one layer to another,extracts the enormity of representations on different scales,backed by a prepreprocessing pipeline that brings defect saliency to the fore through contrast adjustment,denoising,and edge detection.The use of multi-head self-attention enhances feature fusion,enabling the model to capture both large and small spatial features.BearFusionNet achieves an accuracy of 99.66%and Cohen’s kappa score of 0.9929 in Kaggle’s Real-life Industrial Casting Defects dataset.Both McNemar’s and Wilcoxon signed-rank statistical tests,as well as fivefold cross-validation,are employed to assess the robustness of our proposed model.To interpret the model,we adopt Grad-Cam visualizations,which are the state of the art standard.Furthermore,we deploy BearFusionNet as a webbased system for near real-time inference(5-6 s per prediction),which enables the quickest yet accurate detection with visual explanations.Overall,BearFusionNet is an interpretable,accurate,and deployable solution that can automatically detect casting defects,leading to significant advances in the innovative industrial environment.
基金supported by scientific research projects of China Academy of Railway Sciences Co.,Ltd.(grant no.2024YJ117).
文摘Purpose-Amidst an increasingly severe cybersecurity landscape,the widespread adoption of Xinchuang endpoints has become a strategic imperative.Governments and enterprises have established terminal localization as a critical objective,aiming for comprehensive indigenous replacement through rapid technological iteration.Consequently,Xinchuang systems and Windows platforms are expected to coexist over an extended period.This study seeks to establish an automated verification framework for multi-version operating systems and validate the efficacy of baseline hardening in mitigating security risks.Design/methodology/approach-Based on the Classified Protection 2.0 framework and relevant national standards for endpoint security,this study proposes an endpoint security baseline verification scheme applicable to multiple operating systems.The scheme addresses divergent security policies and implementation methodologies across heterogeneous environments.It automates the inspection of core baselines,including account password complexity,default shared service status and patch installation status.Furthermore,a comprehensive scoring model is established by incorporating differentiated weights for account security,patch management and log auditing,ultimately generating visualized risk reports to facilitate remediation prioritization.Findings-This study reveals that baseline configuration serves as the fundamental prerequisite in endpoint security practices.Through a scalable detection engine and quantitative scoring model,the system can promptly identify and remediate potential risks,thereby reducing the attack surface and mitigating intrusion risks.However,on certain domestic chip architectures,compatibility issues persist in detecting specific configuration items.Further improvement in hardware-software co-adaptation for domestic platforms is required to advance the development of localized security protection systems.Originality/value-Through in-depth research on security baseline configurations across multiple operating systems,this study implements an automated and visualized baseline verification methodology.This approach significantly strengthens the security posture of domestic operating systems and supports the establishment of a more robust,national-level cybersecurity defense framework.
基金supported by the National Key Research and Development Program of China(No.2024YFB3212901)National Natural Science Foundation of China(12072189)the Medicine and Engineering Interdisciplinary Research Fund of Shanghai Jiao Tong University(No.YG2025ZD05)。
文摘Pipelines are extensively used in environments such as nuclear power plants,chemical factories,and medical devices to transport gases and liquids.These tubular environments often feature complex geometries,confined spaces,and millimeter-scale height restrictions,presenting significant challenges to conventional inspection methods.Here,we present an ultrasonic microrobot(weight,80 mg;dimensions,24 mm×7 mm;thickness,210μm)to realize agile and bidirectional navigation in narrow pipelines.The ultrathin structural design of the robot is achieved through a high-performance piezoelectric composite film microstructure based on MEMS technology.The robot exhibits various vibration modes when driven by ultrasonic frequency signals,its motion speed reaches81 cm s-1 at 54.8 k Hz,exceeding that of the fastest piezoelectric microrobots,and its forward and backward motion direction is controllable through frequency modulation,while the minimum driving voltage for initial movement can be as low as 3 VP-P.Additionally,the robot can effortlessly climb slopes up to 24.25°and carry loads more than 36 times its weight.The robot is capable of agile navigation through curved L-shaped pipes,pipes made of various materials(acrylic,stainless steel,and polyvinyl chloride),and even over water.To further demonstrate its inspection capabilities,a micro-endoscope camera is integrated into the robot,enabling real-time image capture inside glass pipes.
