Pub Date : 2023-05-17DOI: 10.1177/00202940231175086
B. Sui, Jianqiang Zhang, Zhong Liu
In order to identify ship collision risk for the security of maritime transportation in a close-quarters situation, a novel real-time ship collision risk awareness approach is proposed by developing a novel non-linear velocity obstacle set, QSD-NLVO. More specifically, the Quaternion Ship Domain model was introduced into the non-linear velocity obstacle algorithm, and the conflict position was reasonably defined. By replacing the conflict position with ship domain, the proposed method can more reasonably assess the safety radius of the conflict in different ship encounter scenarios. The presented model enhanced the accuracy of collision risk identification by replacing the collision position in non-linear velocity obstacle algorithm with quaternion ship domain. Finally, case studies were implemented to illustrate the effectiveness of the QSD-NLVO approach. The developed model may be utilized as a guide for investigating port traffic safety as well as a tool for maritime surveillance operators to monitor port traffic collision risks and increase traffic safety.
{"title":"A real-time ship encounter collision risk detection approach in close-quarters situation","authors":"B. Sui, Jianqiang Zhang, Zhong Liu","doi":"10.1177/00202940231175086","DOIUrl":"https://doi.org/10.1177/00202940231175086","url":null,"abstract":"In order to identify ship collision risk for the security of maritime transportation in a close-quarters situation, a novel real-time ship collision risk awareness approach is proposed by developing a novel non-linear velocity obstacle set, QSD-NLVO. More specifically, the Quaternion Ship Domain model was introduced into the non-linear velocity obstacle algorithm, and the conflict position was reasonably defined. By replacing the conflict position with ship domain, the proposed method can more reasonably assess the safety radius of the conflict in different ship encounter scenarios. The presented model enhanced the accuracy of collision risk identification by replacing the collision position in non-linear velocity obstacle algorithm with quaternion ship domain. Finally, case studies were implemented to illustrate the effectiveness of the QSD-NLVO approach. The developed model may be utilized as a guide for investigating port traffic safety as well as a tool for maritime surveillance operators to monitor port traffic collision risks and increase traffic safety.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82721911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the wind tunnel test, the full-bridge aeroelastic model needs to simulate both the shape and dynamic characteristics of the real bridge, and modal parameters are key dynamic parameters. Therefore, it is essential to identify the modal parameters of the model accurately. To get accurate modal parameters of the long-span bridge model in the wind tunnel test, the applications of the Hilbert-Huang transform for modal parameter identification were analyzed in this paper. Then a band-pass filter is designed to filter the original signal so that the intrinsic mode function obtained by empirical mode decomposition can satisfy the single-component signal requirement and eliminate the mode mixing effect effectively. Meanwhile, the endpoint data extension method based on SVM (Support Vector Machine) was presented to restrain the end effects of empirical mode decomposition. Finally, taking the Oujiang Bridge as the engineering background, the improved algorithm was applied to modal parameter identification of the bridge under ambient excitation. The modal parameters such as modal frequency and damping ratio were obtained. The reliability of the improved method was verified by comparing the identified modal parameters with the results of the finite element method, and it turns out that the improved method can reduce the frequency identification error of vertical bend, lateral bend, and torsion to 1.01%, 4.07%, and 1.68%. The results indicated that the improved method based on the Hilbert-Huang transform can accurately identify the main modal parameters of the structure and can be better applied to identify the modal parameters of long-span bridge structures.
{"title":"Research on improved modal parameter identification method using Hilbert-Huang transform","authors":"Mingjin Zhang, Hongyu Chen, Tingyuan Yan, Hao Sun, Lianhuo Wu","doi":"10.1177/00202940231173752","DOIUrl":"https://doi.org/10.1177/00202940231173752","url":null,"abstract":"In the wind tunnel test, the full-bridge aeroelastic model needs to simulate both the shape and dynamic characteristics of the real bridge, and modal parameters are key dynamic parameters. Therefore, it is essential to identify the modal parameters of the model accurately. To get accurate modal parameters of the long-span bridge model in the wind tunnel test, the applications of the Hilbert-Huang transform for modal parameter identification were analyzed in this paper. Then a band-pass filter is designed to filter the original signal so that the intrinsic mode function obtained by empirical mode decomposition can satisfy the single-component signal requirement and eliminate the mode mixing effect effectively. Meanwhile, the endpoint data extension method based on SVM (Support Vector Machine) was presented to restrain the end effects of empirical mode decomposition. Finally, taking the Oujiang Bridge as the engineering background, the improved algorithm was applied to modal parameter identification of the bridge under ambient excitation. The modal parameters such as modal frequency and damping ratio were obtained. The reliability of the improved method was verified by comparing the identified modal parameters with the results of the finite element method, and it turns out that the improved method can reduce the frequency identification error of vertical bend, lateral bend, and torsion to 1.01%, 4.07%, and 1.68%. The results indicated that the improved method based on the Hilbert-Huang transform can accurately identify the main modal parameters of the structure and can be better applied to identify the modal parameters of long-span bridge structures.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75221895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rolling bearing is one of the core components in rotating machinery, and its running status directly affects the operation of the whole equipment. Faults of rolling bearings in the actual working process are often multiple faults. To effectively separate fault sources, the blind source separation method is used for the compound fault diagnosis of rolling bearings. Because of the impact of the number of artificially limited decompositions and quadratic penalty factor on VMD in the decomposition process, and the slow convergence and low accuracy in the objective function of traditional FastICA operation, the VMD algorithm based on the energy loss coefficient and the information entropy is proposed, which adaptively determines the number of modal components and the quadratic penalty factor; The Tukey M estimation is selected as the objective convergence function of the FastICA algorithm to improve its robustness. First, VMD is used to decompose the signal; Secondly, the original signal and the decomposed IMF component are reconstructed, the covariance matrix and the singular value decomposition are constructed, the number of fault sources is estimated by the proximity dominance method, and the decomposed IMF components are filtered through correlation analysis and kurtosis index to build a multi-channel feature set; Finally, the constructed multi-channel feature set is input to the FastICA algorithm based on the Tukey M estimation for the separation of fault source signals to achieve composite fault diagnosis. The compound fault experiment shows that the proposed method in this paper can effectively realize the blind source separation of rolling bearing fault features to realize the compound fault diagnosis in different positions.
{"title":"The Single-channel blind source separation based on VMD and Tukey M estimation for rolling bearing composite fault diagnosis","authors":"Yaping Wang, Qisong Zhang, Ruofan Cao, Shenmin Zhang, Shisong Li, Di Xu","doi":"10.1177/00202940231174405","DOIUrl":"https://doi.org/10.1177/00202940231174405","url":null,"abstract":"Rolling bearing is one of the core components in rotating machinery, and its running status directly affects the operation of the whole equipment. Faults of rolling bearings in the actual working process are often multiple faults. To effectively separate fault sources, the blind source separation method is used for the compound fault diagnosis of rolling bearings. Because of the impact of the number of artificially limited decompositions and quadratic penalty factor on VMD in the decomposition process, and the slow convergence and low accuracy in the objective function of traditional FastICA operation, the VMD algorithm based on the energy loss coefficient and the information entropy is proposed, which adaptively determines the number of modal components and the quadratic penalty factor; The Tukey M estimation is selected as the objective convergence function of the FastICA algorithm to improve its robustness. First, VMD is used to decompose the signal; Secondly, the original signal and the decomposed IMF component are reconstructed, the covariance matrix and the singular value decomposition are constructed, the number of fault sources is estimated by the proximity dominance method, and the decomposed IMF components are filtered through correlation analysis and kurtosis index to build a multi-channel feature set; Finally, the constructed multi-channel feature set is input to the FastICA algorithm based on the Tukey M estimation for the separation of fault source signals to achieve composite fault diagnosis. The compound fault experiment shows that the proposed method in this paper can effectively realize the blind source separation of rolling bearing fault features to realize the compound fault diagnosis in different positions.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"14 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79657338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-09DOI: 10.1177/00202940231173767
Wei Zhang, Dongsheng Zuo, Congjiao Wang, Bing Sun
As the mine hoist monitors video images with poor light, low brightness, heavy dust, and low contrast, the monitoring video images are not conducive to monitoring. They cannot meet the needs of applications. Based on actual video surveillance data, this paper proposes a dark channel prior (DCP) method integrated with a guided image filter video image enhancement algorithm. Firstly, we analyzed the characteristics of the mine hoist system’s video images. Then, the DCP technique was used to enhance the video images. A guided image filter algorithm was introduced to ensure that the video has more clarity and visual impact. Comparing the suggested method to the other four algorithms, it performed better both subjectively and objectively than the algorithms mentioned above. Experiments demonstrate that the proposed technique can successfully improve the entire clarity and contrast of video images while avoiding the over-enhancement of bright areas close to the light source, meeting the practical application requirements of video surveillance.
{"title":"Research on image enhancement algorithm for the monitoring system in coal mine hoist","authors":"Wei Zhang, Dongsheng Zuo, Congjiao Wang, Bing Sun","doi":"10.1177/00202940231173767","DOIUrl":"https://doi.org/10.1177/00202940231173767","url":null,"abstract":"As the mine hoist monitors video images with poor light, low brightness, heavy dust, and low contrast, the monitoring video images are not conducive to monitoring. They cannot meet the needs of applications. Based on actual video surveillance data, this paper proposes a dark channel prior (DCP) method integrated with a guided image filter video image enhancement algorithm. Firstly, we analyzed the characteristics of the mine hoist system’s video images. Then, the DCP technique was used to enhance the video images. A guided image filter algorithm was introduced to ensure that the video has more clarity and visual impact. Comparing the suggested method to the other four algorithms, it performed better both subjectively and objectively than the algorithms mentioned above. Experiments demonstrate that the proposed technique can successfully improve the entire clarity and contrast of video images while avoiding the over-enhancement of bright areas close to the light source, meeting the practical application requirements of video surveillance.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"169 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85078572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-28DOI: 10.1177/00202940221103563
Yan Zhang, Xiaoqiang Zhao, Yongyong Hui, Jie Cao
Batch process quality-related fault detection is necessary for keeping operation safety and quality consistency. However, the process variables have a weak ability to explain the quality variables makes the batch process quality-related fault detection a difficult task. In this work, a multi-way orthogonal signal correction enhanced total principal component regression (MOSC-ETPCR) is proposed to achieve the nonlinear quality-related fault detection of the batch process. First, after batch process data expansion, the orthogonal signal correction algorithm is used to filter out the quality-irrelevant information in process variables and avoid the influence of quality-irrelevant data on process modeling. Secondly, the nonlinear characteristics of the process are extracted by the maximum information coefficient matrix, and the quality-related nonlinear regression model is constructed to ensure the maximum correlation between the extracted features and quality variables. Thirdly, the statistics and corresponding control limits are established based on the obtained regression model. Finally, the effectiveness of the MOSC-ETPCR algorithm was verified by numerical simulation and the penicillin fermentation process.
{"title":"Quality-related batch process monitoring based on multi-way orthogonal signal correction enhanced total principal component regression","authors":"Yan Zhang, Xiaoqiang Zhao, Yongyong Hui, Jie Cao","doi":"10.1177/00202940221103563","DOIUrl":"https://doi.org/10.1177/00202940221103563","url":null,"abstract":"Batch process quality-related fault detection is necessary for keeping operation safety and quality consistency. However, the process variables have a weak ability to explain the quality variables makes the batch process quality-related fault detection a difficult task. In this work, a multi-way orthogonal signal correction enhanced total principal component regression (MOSC-ETPCR) is proposed to achieve the nonlinear quality-related fault detection of the batch process. First, after batch process data expansion, the orthogonal signal correction algorithm is used to filter out the quality-irrelevant information in process variables and avoid the influence of quality-irrelevant data on process modeling. Secondly, the nonlinear characteristics of the process are extracted by the maximum information coefficient matrix, and the quality-related nonlinear regression model is constructed to ensure the maximum correlation between the extracted features and quality variables. Thirdly, the statistics and corresponding control limits are established based on the obtained regression model. Finally, the effectiveness of the MOSC-ETPCR algorithm was verified by numerical simulation and the penicillin fermentation process.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"112 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76374407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The single axis linear displacement measurement system of CMM is composed of grating ruler, servo motor and linear motion mechanism. Although the measuring accuracy of grating ruler is high, the accuracy of servo motor and linear motion mechanism is low. Therefore, the complex structure limits the measurement accuracy of the linear displacement measurement system. This paper introduces a novel linear displacement measurement system named magnetic levitation ruler. According to the working principle of grating ruler and the characteristics of magnetic levitation technology, the magnetic circuit design and structural design of magnetic levitation ruler are completed in this paper. The mover core of the magnetic levitation ruler is in the stable working magnetic field provided by the stator yoke. The horizontal control coil wound on the mover core can obtain more stable ampere force to improve the control accuracy of the mover core displacement. Therefore, the mover core can be moved in step mode, and the length of each step is fixed. Each step is the minimum scale of the magnetic levitation ruler. Therefore, the mover core can implement displacement measurement while moving in a linear motion. This paper analyzes the working principle of levitation, horizontal motion, and displacement measurement of magnetic levitation ruler, and determines the structural materials and parameters of magnetic levitation ruler with the help of finite element analysis software. The simulation results show that the levitation force of the magnetic levitation ruler is proportional to the current passing through the levitation coils, and the thrust of the horizontal control coil is less disturbed by the magnetic field. Compared with the linear displacement measurement system with rotational servo motor or permanent magnet synchronous linear motor as the core, the magnetic levitation ruler has stable magnetic field, strong controllability, high integration, and is easier to achieve high-precision control.
{"title":"A novel magnetic circuit and structure for magnetic levitation ruler","authors":"Jiyuan Sun, Pin Li, Yanbin Zheng, Chunlin Tian, Zhenxiong Zhou","doi":"10.1177/00202940231169528","DOIUrl":"https://doi.org/10.1177/00202940231169528","url":null,"abstract":"The single axis linear displacement measurement system of CMM is composed of grating ruler, servo motor and linear motion mechanism. Although the measuring accuracy of grating ruler is high, the accuracy of servo motor and linear motion mechanism is low. Therefore, the complex structure limits the measurement accuracy of the linear displacement measurement system. This paper introduces a novel linear displacement measurement system named magnetic levitation ruler. According to the working principle of grating ruler and the characteristics of magnetic levitation technology, the magnetic circuit design and structural design of magnetic levitation ruler are completed in this paper. The mover core of the magnetic levitation ruler is in the stable working magnetic field provided by the stator yoke. The horizontal control coil wound on the mover core can obtain more stable ampere force to improve the control accuracy of the mover core displacement. Therefore, the mover core can be moved in step mode, and the length of each step is fixed. Each step is the minimum scale of the magnetic levitation ruler. Therefore, the mover core can implement displacement measurement while moving in a linear motion. This paper analyzes the working principle of levitation, horizontal motion, and displacement measurement of magnetic levitation ruler, and determines the structural materials and parameters of magnetic levitation ruler with the help of finite element analysis software. The simulation results show that the levitation force of the magnetic levitation ruler is proportional to the current passing through the levitation coils, and the thrust of the horizontal control coil is less disturbed by the magnetic field. Compared with the linear displacement measurement system with rotational servo motor or permanent magnet synchronous linear motor as the core, the magnetic levitation ruler has stable magnetic field, strong controllability, high integration, and is easier to achieve high-precision control.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91116439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-12DOI: 10.1177/00202940231155496
Dariusz Maton, J. Economou, David Galvão Wall, David Ward, Simon Trythall
In this work, open-loop position tracking using low-cost inertial measurement units is aided by Takagi-Sugeno velocity classification using the subtractive clustering algorithm to help generate the fuzzy rule base. Using the grid search approach, a suitable window of classified velocity vectors was obtained and then integrated to generate trajectory segments. Using publicly available experimental data, the reconstruction accuracy of the method is compared against four competitive pedestrian tracking algorithms. The comparison on selected test data, has demonstrated more competitive relative and absolute trajectory error metrics. The proposed method in this paper is also verified on an independent experimental data set. Unlike the methods which use deep learning, the proposed method has shown to be transparent (fuzzy rule base). Lastly, a sensitivity analysis of the velocity classification models to perturbations from the training orientation at test time is investigated, to guide developers of such data-driven algorithms on the granularity required in an ensemble modeling approach. The accuracy and transparency of the approach may positively influence applications requiring low-cost inertial position tracking such as augmented reality headsets for emergency responders.
{"title":"Subtractive clustering Takagi-Sugeno position tracking for humans by low-cost inertial sensors and velocity classification","authors":"Dariusz Maton, J. Economou, David Galvão Wall, David Ward, Simon Trythall","doi":"10.1177/00202940231155496","DOIUrl":"https://doi.org/10.1177/00202940231155496","url":null,"abstract":"In this work, open-loop position tracking using low-cost inertial measurement units is aided by Takagi-Sugeno velocity classification using the subtractive clustering algorithm to help generate the fuzzy rule base. Using the grid search approach, a suitable window of classified velocity vectors was obtained and then integrated to generate trajectory segments. Using publicly available experimental data, the reconstruction accuracy of the method is compared against four competitive pedestrian tracking algorithms. The comparison on selected test data, has demonstrated more competitive relative and absolute trajectory error metrics. The proposed method in this paper is also verified on an independent experimental data set. Unlike the methods which use deep learning, the proposed method has shown to be transparent (fuzzy rule base). Lastly, a sensitivity analysis of the velocity classification models to perturbations from the training orientation at test time is investigated, to guide developers of such data-driven algorithms on the granularity required in an ensemble modeling approach. The accuracy and transparency of the approach may positively influence applications requiring low-cost inertial position tracking such as augmented reality headsets for emergency responders.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80594618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The operational cycle identification of the load-haul-dump (LHD) can help support the production process optimization in the underground mining industry and thus reduce mining costs. However, most of the existing research works use only the hydraulic bucket signal of LHD as the data source, and the stability and robustness of the identification method are poor. A few advanced research works use the variational Bayesian Gaussian mixture model to introduce other signals, but the accuracy of this recognition method is not perfect at present. In addition, the current identification methods are unable to simultaneously recognize the four working conditions of the LHD which include loading, hauling, dumping, and transiting. To solve these problems, a random forest feature selection (RFFS) and bidirectional long short-term memory (Bi-LSTM) based operation cycle recognition algorithm is proposed. Firstly, RFFS is used to remove redundant features based on the multi-sensor signals of the LHD. Then, Bi-LSTM is applied to fully exploit the temporal correlation between different operation regimes and accurately recognize the operation cycles. The effectiveness and superiority of the algorithm are verified by the experiment on the actual data of the LHD. The proposed algorithm can recognize four working conditions simultaneously, among which the recognition accuracy of loading conditions is the highest, up to 95.42%, and the weighted accuracy of this algorithm can reach 91.75% using the occupied time of each working condition as the weighting factor.
{"title":"The load-haul-dump operation cycle recognition based on multi-sensor feature selection and bidirectional long short-term memory network","authors":"Zhimin Qi, Qing Gu, Yu Meng, Guoxing Bai, Dawei Ding","doi":"10.1177/00202940231161569","DOIUrl":"https://doi.org/10.1177/00202940231161569","url":null,"abstract":"The operational cycle identification of the load-haul-dump (LHD) can help support the production process optimization in the underground mining industry and thus reduce mining costs. However, most of the existing research works use only the hydraulic bucket signal of LHD as the data source, and the stability and robustness of the identification method are poor. A few advanced research works use the variational Bayesian Gaussian mixture model to introduce other signals, but the accuracy of this recognition method is not perfect at present. In addition, the current identification methods are unable to simultaneously recognize the four working conditions of the LHD which include loading, hauling, dumping, and transiting. To solve these problems, a random forest feature selection (RFFS) and bidirectional long short-term memory (Bi-LSTM) based operation cycle recognition algorithm is proposed. Firstly, RFFS is used to remove redundant features based on the multi-sensor signals of the LHD. Then, Bi-LSTM is applied to fully exploit the temporal correlation between different operation regimes and accurately recognize the operation cycles. The effectiveness and superiority of the algorithm are verified by the experiment on the actual data of the LHD. The proposed algorithm can recognize four working conditions simultaneously, among which the recognition accuracy of loading conditions is the highest, up to 95.42%, and the weighted accuracy of this algorithm can reach 91.75% using the occupied time of each working condition as the weighting factor.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"44 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90306116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-31DOI: 10.1177/00202940231165262
Pengbo Zhu, Xin Liu, Ziqiang Yu, Lin Zhao, Xiaolong Li
Suspension chopper is a high-power electrical equipment which controls the suspension state of maglev train. Its performance directly determines the stability and safety of maglev train. However, the traditional suspension chopper has the problem of high voltage spikes of IGBT and load, which poses a threat to the safe operation of high-speed maglev train. In order to solve this problem, this paper designs a phase-shifted full-bridge suspension chopper, which only adds an auxiliary circuit and four parallel capacitors. The soft-switch is realized by using the phase-shifted control signals, so as to reduce the voltage spikes. Compared with other voltage spike suppression methods, the method has the advantages of good suppression of voltage spikes, simple circuit structure, less use of components, and insensitive to component parameters. The performance of the designed circuit is simulated by ANSYS Simplorer, and verified by experimental test platform. The simulation and experimental results show that the phase-shifted full-bridge suspension chopper can greatly reduce voltage spikes of the load and IGBT.
{"title":"Application of phase-shifted full-bridge soft-switch technology in suspension chopper","authors":"Pengbo Zhu, Xin Liu, Ziqiang Yu, Lin Zhao, Xiaolong Li","doi":"10.1177/00202940231165262","DOIUrl":"https://doi.org/10.1177/00202940231165262","url":null,"abstract":"Suspension chopper is a high-power electrical equipment which controls the suspension state of maglev train. Its performance directly determines the stability and safety of maglev train. However, the traditional suspension chopper has the problem of high voltage spikes of IGBT and load, which poses a threat to the safe operation of high-speed maglev train. In order to solve this problem, this paper designs a phase-shifted full-bridge suspension chopper, which only adds an auxiliary circuit and four parallel capacitors. The soft-switch is realized by using the phase-shifted control signals, so as to reduce the voltage spikes. Compared with other voltage spike suppression methods, the method has the advantages of good suppression of voltage spikes, simple circuit structure, less use of components, and insensitive to component parameters. The performance of the designed circuit is simulated by ANSYS Simplorer, and verified by experimental test platform. The simulation and experimental results show that the phase-shifted full-bridge suspension chopper can greatly reduce voltage spikes of the load and IGBT.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85026618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-31DOI: 10.1177/00202940231163935
Zheng-yu Xie, Xia Liu, Yazhuo Li, Hong Zhang, Qing Xiang
In an environment where completely automated lines are gaining popularity, station service employees are declining yearly while passenger volume increases. In many cities, the need for station video surveillance with “complete coverage without dead ends” has been high. The traditional layout scheme based on design experience estimates often results in large blind spots and low efficiency in monitoring. In order to solve this problem, based on BIM technology, this work develops a quantified camera layout optimization approach employing an improved genetic algorithm. The plan includes three modules: the data extraction, which extracts the spatial information of the functional area from the BIM model to generate a data image; the optimization module, which adopts the improved genetic algorithm and uses the pixel coordinates provided by the data image to realize the camera pre-deployment; the visualization module, which designs the simulation plug-in through BIM secondary development technology, simulates and verifies the pre-deployment, and provides the solutions. The approach’s effectiveness was confirmed by verifying the deployment optimization at the station platform level. The optimal solution’s camera coverage is 27.2% better than the experience-based camera layout.
{"title":"Camera placement optimization for CCTV in rail transit using BIM","authors":"Zheng-yu Xie, Xia Liu, Yazhuo Li, Hong Zhang, Qing Xiang","doi":"10.1177/00202940231163935","DOIUrl":"https://doi.org/10.1177/00202940231163935","url":null,"abstract":"In an environment where completely automated lines are gaining popularity, station service employees are declining yearly while passenger volume increases. In many cities, the need for station video surveillance with “complete coverage without dead ends” has been high. The traditional layout scheme based on design experience estimates often results in large blind spots and low efficiency in monitoring. In order to solve this problem, based on BIM technology, this work develops a quantified camera layout optimization approach employing an improved genetic algorithm. The plan includes three modules: the data extraction, which extracts the spatial information of the functional area from the BIM model to generate a data image; the optimization module, which adopts the improved genetic algorithm and uses the pixel coordinates provided by the data image to realize the camera pre-deployment; the visualization module, which designs the simulation plug-in through BIM secondary development technology, simulates and verifies the pre-deployment, and provides the solutions. The approach’s effectiveness was confirmed by verifying the deployment optimization at the station platform level. The optimal solution’s camera coverage is 27.2% better than the experience-based camera layout.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"64 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77926304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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