Pub Date : 2022-08-24DOI: 10.1109/IAI55780.2022.9976782
Wenfeng Li, Jing Zhao, Zhongchao Liang, P. Wong, Z. Xie, Yongfu Wang
This paper proposes a robust driver assistance fuzzy control method for vehicle lane keeping systems based on the road frequency range. First of all, taking the varying velocity, uncertain mass and time delay into account, a Takagi-Sugeno fuzzy model is constructed to approximate the global driver-vehicle-road system. Then, considering that the road curvature frequency usually belongs to a certain range, a finite frequency specification is employed to concern the fuzzy control problem of lane-keeping assistance systems. Moreover, based on the Lyapunov stability theory and the finite frequency specification, a set of sufficient conditions in the form of linear matrix inequalities are presented for the computation of desired controllers. Finally, the effectiveness of the proposed method is illustrated by simulations.
{"title":"Driver Assistance Fuzzy Control for Vehicle Lane Keeping Systems Based on Road Frequency Range","authors":"Wenfeng Li, Jing Zhao, Zhongchao Liang, P. Wong, Z. Xie, Yongfu Wang","doi":"10.1109/IAI55780.2022.9976782","DOIUrl":"https://doi.org/10.1109/IAI55780.2022.9976782","url":null,"abstract":"This paper proposes a robust driver assistance fuzzy control method for vehicle lane keeping systems based on the road frequency range. First of all, taking the varying velocity, uncertain mass and time delay into account, a Takagi-Sugeno fuzzy model is constructed to approximate the global driver-vehicle-road system. Then, considering that the road curvature frequency usually belongs to a certain range, a finite frequency specification is employed to concern the fuzzy control problem of lane-keeping assistance systems. Moreover, based on the Lyapunov stability theory and the finite frequency specification, a set of sufficient conditions in the form of linear matrix inequalities are presented for the computation of desired controllers. Finally, the effectiveness of the proposed method is illustrated by simulations.","PeriodicalId":138951,"journal":{"name":"2022 4th International Conference on Industrial Artificial Intelligence (IAI)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115286891","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 : 2022-08-24DOI: 10.1109/IAI55780.2022.9976854
Wei Ding, Jin‐Xi Zhang
This paper is concerned with the problem of generating smooth reference trajectories by filtering, for backstepping control designs for nonlinear systems. To solve this problem, a prescribed performance filtering approach is proposed. Our filter is driven by an input signal which is generated recursively. In each design step, a barrier function is employed to confine the filtering error within the predefined bound. In this way, the filtered reference is not only smooth but also approximate the original reference with any high accuracy. The simulation results on the tracking control of a Van der Pol system illustrate the effectiveness and superiority of our approach.
本文研究了用滤波方法生成光滑参考轨迹的问题，用于非线性系统的反步控制设计。为了解决这一问题，提出了一种规定性能的滤波方法。我们的过滤器由递归生成的输入信号驱动。在每个设计步骤中，使用屏障函数将滤波误差限制在预定义的范围内。这样，滤波后的参考文献不仅平滑，而且能以较高的精度逼近原始参考文献。对Van der Pol系统跟踪控制的仿真结果表明了该方法的有效性和优越性。
{"title":"Prescribed Performance Filtering for Generation of Smooth Reference Trajectory","authors":"Wei Ding, Jin‐Xi Zhang","doi":"10.1109/IAI55780.2022.9976854","DOIUrl":"https://doi.org/10.1109/IAI55780.2022.9976854","url":null,"abstract":"This paper is concerned with the problem of generating smooth reference trajectories by filtering, for backstepping control designs for nonlinear systems. To solve this problem, a prescribed performance filtering approach is proposed. Our filter is driven by an input signal which is generated recursively. In each design step, a barrier function is employed to confine the filtering error within the predefined bound. In this way, the filtered reference is not only smooth but also approximate the original reference with any high accuracy. The simulation results on the tracking control of a Van der Pol system illustrate the effectiveness and superiority of our approach.","PeriodicalId":138951,"journal":{"name":"2022 4th International Conference on Industrial Artificial Intelligence (IAI)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115480881","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 : 2022-08-24DOI: 10.1109/IAI55780.2022.9976509
Qiang Wang, Chao Cheng, Aichen Sun, Hongtian Chen
With the help of the sensor networks, this paper mainly develops a model-based distributed fault detection method for dynamic systems. Specifically, each sensor node is equipped with a Luenberger observer and a post-filter for residual generation. It is worth mentioning that, the post-filter is designed to improve detection performance through the $H_{-}/H_{infty}$ indices. Moreover, the design parameters are dependent on the linear matrix inequality. Finally, a numerical example is introduced to verify the accuracy and effectiveness of the proposed distributed approach.
{"title":"Distributed Fault Detection for Dynamic Systems Based on H̲/H∞Indices","authors":"Qiang Wang, Chao Cheng, Aichen Sun, Hongtian Chen","doi":"10.1109/IAI55780.2022.9976509","DOIUrl":"https://doi.org/10.1109/IAI55780.2022.9976509","url":null,"abstract":"With the help of the sensor networks, this paper mainly develops a model-based distributed fault detection method for dynamic systems. Specifically, each sensor node is equipped with a Luenberger observer and a post-filter for residual generation. It is worth mentioning that, the post-filter is designed to improve detection performance through the $H_{-}/H_{infty}$ indices. Moreover, the design parameters are dependent on the linear matrix inequality. Finally, a numerical example is introduced to verify the accuracy and effectiveness of the proposed distributed approach.","PeriodicalId":138951,"journal":{"name":"2022 4th International Conference on Industrial Artificial Intelligence (IAI)","volume":"135 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124444890","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 : 2022-08-24DOI: 10.1109/IAI55780.2022.9976844
Zhaocai Dong, Kun Liu, Dongyu Han, Yuan Cao, Yuanqing Xia
This paper considers anomaly detection for cyber-physical systems, in which the multivariate time series data collected from different sensors have complex temporal dependencies and inter-sensor correlations. We firstly propose an improved unsupervised anomaly detection framework which extracts the temporal and spatial patterns based on the autoencoder and the attention-based convolutional long-short term memory networks. In particular, the original data are fused into the input signature matrices to avoid information loss and an improved sample-based threshold setting approach is proposed to estimate the optimal threshold automatically. Finally, the experiments on two sensor datasets illustrate that our model achieves superior performance over state-of-the-art methods.
{"title":"Reconstruction-based Multi-Scale Anomaly Detection for Cyber-Physical Systems","authors":"Zhaocai Dong, Kun Liu, Dongyu Han, Yuan Cao, Yuanqing Xia","doi":"10.1109/IAI55780.2022.9976844","DOIUrl":"https://doi.org/10.1109/IAI55780.2022.9976844","url":null,"abstract":"This paper considers anomaly detection for cyber-physical systems, in which the multivariate time series data collected from different sensors have complex temporal dependencies and inter-sensor correlations. We firstly propose an improved unsupervised anomaly detection framework which extracts the temporal and spatial patterns based on the autoencoder and the attention-based convolutional long-short term memory networks. In particular, the original data are fused into the input signature matrices to avoid information loss and an improved sample-based threshold setting approach is proposed to estimate the optimal threshold automatically. Finally, the experiments on two sensor datasets illustrate that our model achieves superior performance over state-of-the-art methods.","PeriodicalId":138951,"journal":{"name":"2022 4th International Conference on Industrial Artificial Intelligence (IAI)","volume":"189 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115955721","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 : 2022-08-24DOI: 10.1109/IAI55780.2022.9976736
R. Tang, Biao Luo, Yuxin Liao
In view of the reentry glide phase guidance problem of hypersonic vehicles, this paper proposes a profile tracking control method based on input-constrained backstepping sliding mode controller (BSMC). First, the multiple path constraints of gliding phase are transformed into the reentry corridor in the drag acceleration-velocity (D-V) profile. A standard profile is designed in the form of a quadratic function, and the function coefficients are optimized by the intelligent algorithm. Based on the second-order differential model of drag acceleration and velocity, an input-constrained BSMC is designed by using the auxiliary system to obtain the control commands required for the longitudinal motion of vehicle. Finally, the tracking performance of the control scheme is verified by numerical simulation of reentry gliding phase.
{"title":"Profile Tracking Control of Reentry Vehicle With Input-constrained Backstepping Sliding Mode Controller","authors":"R. Tang, Biao Luo, Yuxin Liao","doi":"10.1109/IAI55780.2022.9976736","DOIUrl":"https://doi.org/10.1109/IAI55780.2022.9976736","url":null,"abstract":"In view of the reentry glide phase guidance problem of hypersonic vehicles, this paper proposes a profile tracking control method based on input-constrained backstepping sliding mode controller (BSMC). First, the multiple path constraints of gliding phase are transformed into the reentry corridor in the drag acceleration-velocity (D-V) profile. A standard profile is designed in the form of a quadratic function, and the function coefficients are optimized by the intelligent algorithm. Based on the second-order differential model of drag acceleration and velocity, an input-constrained BSMC is designed by using the auxiliary system to obtain the control commands required for the longitudinal motion of vehicle. Finally, the tracking performance of the control scheme is verified by numerical simulation of reentry gliding phase.","PeriodicalId":138951,"journal":{"name":"2022 4th International Conference on Industrial Artificial Intelligence (IAI)","volume":"49 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122875187","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 : 2022-08-24DOI: 10.1109/IAI55780.2022.9976818
Chujian Zeng, Bo Zhao, Derong Liu
This paper investigates the fault tolerant control (FTC) scheme against multiple failures (i.e., both actuator and sensor failures occur simultaneously) for nonlinear systems via adaptive dynamic programming (ADP). A descriptor observer is designed to estimate the system states and failures concurrently. Next, a critic neural network (NN) is used to solve the Hamilton-Jacobi-Bellman (HJB) equation for the nominal system, i.e., the failure-free system, and the approximate optimal control policy is obtained. The FTC law is achieved by combining the estimated system states and failures with the approximate optimal control policy. By using the Lyapunov's direct method, we conclude that the closed-loop system is uniformly ultimately bounded. An example is employed to illustrate the effectiveness of the present FTC method.
{"title":"Adaptive Dynamic Programming-Based Fault Tolerant Control for Nonlinear Systems with Multiple Failures","authors":"Chujian Zeng, Bo Zhao, Derong Liu","doi":"10.1109/IAI55780.2022.9976818","DOIUrl":"https://doi.org/10.1109/IAI55780.2022.9976818","url":null,"abstract":"This paper investigates the fault tolerant control (FTC) scheme against multiple failures (i.e., both actuator and sensor failures occur simultaneously) for nonlinear systems via adaptive dynamic programming (ADP). A descriptor observer is designed to estimate the system states and failures concurrently. Next, a critic neural network (NN) is used to solve the Hamilton-Jacobi-Bellman (HJB) equation for the nominal system, i.e., the failure-free system, and the approximate optimal control policy is obtained. The FTC law is achieved by combining the estimated system states and failures with the approximate optimal control policy. By using the Lyapunov's direct method, we conclude that the closed-loop system is uniformly ultimately bounded. An example is employed to illustrate the effectiveness of the present FTC method.","PeriodicalId":138951,"journal":{"name":"2022 4th International Conference on Industrial Artificial Intelligence (IAI)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123552103","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 : 2022-08-24DOI: 10.1109/IAI55780.2022.9976688
Haitao Guo, Jian Tang, Xia Heng, J. Qiao
In municipal solid waste incineration (MSWI) process, combustion line is one of the key controlled variables to characterize the combustion stability and operation safety. Realizing the quantification of combustion line can replace “manual fire monitoring”, which can improve the intelligent degree of MSWI process through real-time feedback. However, the quantification of combustion line needs the combustion flame image data set. Currently, there is no standard flame image data set containing multiple combustion line locations. This paper constructs a flame image set containing multiple combustion line locations. First, the flame image acquisition process is introduced. Then, the combustion line level is divided by combining with the location information of three-dimensional space inside the furnace. Finally, a calibration algorithm facing the position of the combustion line is proposed. Thus, combustion flame image dataset was constructed, which provided a reference for relevant researchers to utilize this dataset in the future study.
{"title":"Construction of Combustion Line Quantification Data Set for Municipal Solid Waste Incineration Process","authors":"Haitao Guo, Jian Tang, Xia Heng, J. Qiao","doi":"10.1109/IAI55780.2022.9976688","DOIUrl":"https://doi.org/10.1109/IAI55780.2022.9976688","url":null,"abstract":"In municipal solid waste incineration (MSWI) process, combustion line is one of the key controlled variables to characterize the combustion stability and operation safety. Realizing the quantification of combustion line can replace “manual fire monitoring”, which can improve the intelligent degree of MSWI process through real-time feedback. However, the quantification of combustion line needs the combustion flame image data set. Currently, there is no standard flame image data set containing multiple combustion line locations. This paper constructs a flame image set containing multiple combustion line locations. First, the flame image acquisition process is introduced. Then, the combustion line level is divided by combining with the location information of three-dimensional space inside the furnace. Finally, a calibration algorithm facing the position of the combustion line is proposed. Thus, combustion flame image dataset was constructed, which provided a reference for relevant researchers to utilize this dataset in the future study.","PeriodicalId":138951,"journal":{"name":"2022 4th International Conference on Industrial Artificial Intelligence (IAI)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122534530","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 : 2022-08-24DOI: 10.1109/IAI55780.2022.9976748
J. Leventides, E. Melas, C. Poulios
We apply the Koopman operator theory and Extended Dynamic Mode Decomposition in a pair of forward and reverse chemical reactions which occur simultaneously with comparable speeds. The system of ODES which governs the evolution of the concentration of the reactants constitutes a nonlinear dynamical system with an interesting feature: It possesses uncountable infinite equilibria which reside on an algebraic surface. Koopman operator captures the dynamics of a nonlinear system, however it is infinite dimensional. In this study, we approximate the chemical reaction dynamics with a data-driven finite dimensional linear system which is defined on some augmented state space. We approximate so, with given initial conditions, the trajectories of the system and obtain an alternative description of the system based on Koopman operator theory, Extended Dynamic Mode Decomposition, and Machine Learning.
{"title":"Koopman operators and Extended Dynamic Mode Decomposition for a pair of forward and reverse chemical reactions which occur simultaneously","authors":"J. Leventides, E. Melas, C. Poulios","doi":"10.1109/IAI55780.2022.9976748","DOIUrl":"https://doi.org/10.1109/IAI55780.2022.9976748","url":null,"abstract":"We apply the Koopman operator theory and Extended Dynamic Mode Decomposition in a pair of forward and reverse chemical reactions which occur simultaneously with comparable speeds. The system of ODES which governs the evolution of the concentration of the reactants constitutes a nonlinear dynamical system with an interesting feature: It possesses uncountable infinite equilibria which reside on an algebraic surface. Koopman operator captures the dynamics of a nonlinear system, however it is infinite dimensional. In this study, we approximate the chemical reaction dynamics with a data-driven finite dimensional linear system which is defined on some augmented state space. We approximate so, with given initial conditions, the trajectories of the system and obtain an alternative description of the system based on Koopman operator theory, Extended Dynamic Mode Decomposition, and Machine Learning.","PeriodicalId":138951,"journal":{"name":"2022 4th International Conference on Industrial Artificial Intelligence (IAI)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129755038","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 : 2022-08-24DOI: 10.1109/IAI55780.2022.9976810
Hui Yang, Kexuan Xu, Yating Fu
The study of heavy haul train (HHT) automatic and stable driving strategy has become the focus of many scholars due to the large load capacity, long body length, concentrated power, and complex line conditions. HHT is difficult to control, drivers are fatigued in manual driving, traction and braking force increase during operation, and the transmission time of braking waves is lengthened, resulting in serious longitudinal impulse, which leads to a series of serious accidents. In this paper, aiming at the safe and stable driving of HHT, the dynamic model of multi-particle model was established and designs the multi-objective curve optimization strategy of fuzzy adaptive genetic algorithm (FAGA). A fuzzy reasoner is mainly used for the adaptive selection of crossover and mutation probability. In terms of safety, energy-saving and punctuality designed train operation target curve combines the actual railway routes (speed limit, ramp, curve, etc.), and compares the optimization effect with standard genetic algorithm. Finally, an improved high-order model-free adaptive iterative learning control algorithm is adopted to track the optimized target curve with high precision, and compared the results of the standard iterative learning control algorithm. The simulation results show that the control method used in this paper can better track the ideal speed target curve and realize the optimal control of the HHT driving curve.
{"title":"Research on Multi-objective Optimal Control of Heavy Haul Train Based on Improved Genetic Algorithm","authors":"Hui Yang, Kexuan Xu, Yating Fu","doi":"10.1109/IAI55780.2022.9976810","DOIUrl":"https://doi.org/10.1109/IAI55780.2022.9976810","url":null,"abstract":"The study of heavy haul train (HHT) automatic and stable driving strategy has become the focus of many scholars due to the large load capacity, long body length, concentrated power, and complex line conditions. HHT is difficult to control, drivers are fatigued in manual driving, traction and braking force increase during operation, and the transmission time of braking waves is lengthened, resulting in serious longitudinal impulse, which leads to a series of serious accidents. In this paper, aiming at the safe and stable driving of HHT, the dynamic model of multi-particle model was established and designs the multi-objective curve optimization strategy of fuzzy adaptive genetic algorithm (FAGA). A fuzzy reasoner is mainly used for the adaptive selection of crossover and mutation probability. In terms of safety, energy-saving and punctuality designed train operation target curve combines the actual railway routes (speed limit, ramp, curve, etc.), and compares the optimization effect with standard genetic algorithm. Finally, an improved high-order model-free adaptive iterative learning control algorithm is adopted to track the optimized target curve with high precision, and compared the results of the standard iterative learning control algorithm. The simulation results show that the control method used in this paper can better track the ideal speed target curve and realize the optimal control of the HHT driving curve.","PeriodicalId":138951,"journal":{"name":"2022 4th International Conference on Industrial Artificial Intelligence (IAI)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133554948","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 electric drive system provides traction power for the entire high-speed train system, and its fault detection and diagnosis (FDD) has been widely studied. In this paper, a new method called just-in-time-learning multi-block dynamic independent comparative analysis (JITL-MBDICA) is proposed. The significant advantages of the FDD method based on JITL-MBDICA are: 1) It improves the matching ability of offline models with online data; 2) lt accurately detects faults through multiple modules; 3) It uses Support Vector Data Description (SVDD) to comprehensively analyze the detection results. The false alarms are reduced, The fault detection rate (FDR) is improved; 4) It is suitable for a non-Gaussian electric drive system. the effectiveness of JITL-MBDICA is verified on the high-speed train electric drive system.
{"title":"Just-In-Time-Learning Multi-Block Dynamic Independent Component Analysis for Electrical Drive Systems of High-Speed Trains","authors":"Xin Wang, Chao Cheng, Sheng Yang, Xiaoyue Yang, Hongtian Chen","doi":"10.1109/IAI55780.2022.9976655","DOIUrl":"https://doi.org/10.1109/IAI55780.2022.9976655","url":null,"abstract":"The electric drive system provides traction power for the entire high-speed train system, and its fault detection and diagnosis (FDD) has been widely studied. In this paper, a new method called just-in-time-learning multi-block dynamic independent comparative analysis (JITL-MBDICA) is proposed. The significant advantages of the FDD method based on JITL-MBDICA are: 1) It improves the matching ability of offline models with online data; 2) lt accurately detects faults through multiple modules; 3) It uses Support Vector Data Description (SVDD) to comprehensively analyze the detection results. The false alarms are reduced, The fault detection rate (FDR) is improved; 4) It is suitable for a non-Gaussian electric drive system. the effectiveness of JITL-MBDICA is verified on the high-speed train electric drive system.","PeriodicalId":138951,"journal":{"name":"2022 4th International Conference on Industrial Artificial Intelligence (IAI)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133919950","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：