On-line monitoring and fault diagnosis of chemical process is extremely important for operation safety and product quality. Principal component analysis (PCA) has been widely used in multivariate statistical process m...On-line monitoring and fault diagnosis of chemical process is extremely important for operation safety and product quality. Principal component analysis (PCA) has been widely used in multivariate statistical process monitoring for its ability to reduce processes dimensions. PCA and other statistical techniques, however, have difficulties in differentiating faults correctly in complex chemical process. Support vector machine (SVM) is a novel approach based on statistical learning theory, which has emerged for feature identification and classification. In this paper, an integrated method is applied for process monitoring and fault diagnosis, which combines PCA for fault feature extraction and multiple SVMs for identification of different fault sources. This approach is verified and illustrated on the Tennessee Eastman benchmark process as a case study. Results show that the proposed PCA-SVMs method has good diagnosis capability and overall diagnosis correctness rate.展开更多
A new on-line batch process monitoring and diagnosing approach based on Fisher discriminant analysis （FDA） was proposed. This method does not need to predict the future observations of variables, so it is more sensi...A new on-line batch process monitoring and diagnosing approach based on Fisher discriminant analysis （FDA） was proposed. This method does not need to predict the future observations of variables, so it is more sensitive to fault detection and stronger implement for monitoring. In order to improve the monitoring performance, the variables trajectories of batch process are separated into several blocks. The key to the proposed approach for on-line monitoring is to calculate the distance of block data that project to low-dimension Fisher space between new batch and reference batch. Comparing the distance with the predefine threshold, it can be considered whether the batch process is normal or abnormal. Fault diagnosis is performed based on the weights in fault direction calculated by FDA. The proposed method was applied to the simulation model of fed-batch penicillin fermentation and the resuits were compared with those obtained using MPCA. The simulation results clearly show that the on-line monitoring method based on FDA is more efficient than the MPCA.展开更多
A statistic-based benchmark was proposed for performance assessment and monitoring of model predic- tive control; the benchmark was straightforward and achievable by recording a set of output data only when the contro...A statistic-based benchmark was proposed for performance assessment and monitoring of model predic- tive control; the benchmark was straightforward and achievable by recording a set of output data only when the control performance was good according to the user’s selection. Principal component model was built and an auto- regressive moving average filter was identified to monitor the performance; an improved T2 statistic was selected as the performance monitor index. When performance changes were detected, diagnosis was done by model validation using recursive analysis and generalized likelihood ratio (GLR) method. This distinguished the fact that the per- formance change was due to plant model mismatch or due to disturbance term. Simulation was done about a heavy oil fractionator system and good results were obtained. The diagnosis result was helpful for the operator to improve the system performance.展开更多
At present, the on-line monitoring is widely applied to the power line monitoring. In this paper, a new mechanical calculation model is established according to the on-line monitoring. And this model is based on the p...At present, the on-line monitoring is widely applied to the power line monitoring. In this paper, a new mechanical calculation model is established according to the on-line monitoring. And this model is based on the parameters that tension sensors and angle sensors on suspended points detect, and combines with the parameters of the wire itself, and also considers the deflection angel of wires due to wind. In this model, mechanics parameters of wires are turned into the new coordinate plane after deflection angel of wires due to wind, or windage yaw plane. A statics tension balance equation is built in the vertical direction of the new windage yaw plane. According to the theoretical analysis and algorithm, we verify the accuracy of this newly developed mechanical calculation model.展开更多
Fault diagnosis and monitoring are very important for complex chemical process. There are numerous methods that have been studied in this field, in which the effective visualization method is still challenging. In ord...Fault diagnosis and monitoring are very important for complex chemical process. There are numerous methods that have been studied in this field, in which the effective visualization method is still challenging. In order to get a better visualization effect, a novel fault diagnosis method which combines self-organizing map (SOM) with Fisher discriminant analysis (FDA) is proposed. FDA can reduce the dimension of the data in terms of maximizing the separability of the classes. After feature extraction by FDA, SOM can distinguish the different states on the output map clearly and it can also be employed to monitor abnormal states. Tennessee Eastman (TE) process is employed to illustrate the fault diagnosis and monitoring performance of the proposed method. The result shows that the SOM integrated with FDA method is efficient and capable for real-time monitoring and fault diagnosis in complex chemical process.展开更多
Multivariate statistical process control methods have been widely used in biochemical industries. Batch process is usually monitored by the method of multi-way principal component analysis (MPCA). In this article, a n...Multivariate statistical process control methods have been widely used in biochemical industries. Batch process is usually monitored by the method of multi-way principal component analysis (MPCA). In this article, a new batch process monitoring and fault diagnosis method based on feature extract in Fisher subspace is proposed.The feature vector and the feature direction are extracted by projecting the high-dimension process data onto the low-dimension Fisher space. The similarity of feature vector between the current and the reference batch is calculated for on-line process monitoring and the contribution plot of weights in feature direction is calculated for fault diagnosis. The approach overcomes the need for estimating or tilling in the unknown portion of the process variables trajectories from the current time to the end of the batch. Simulation results on the benchmark model of penicillin fermentation process can demonstrate that in comparison to the MPCA method, the proposed method is more accurate and efficient for process monitoring and fault diagnosis.展开更多
Multivariate statistical process control methods have been widely used in biochemical industries. Batch process is usually monitored by the method of multi-way principal component analysis (MPCA). In this article, a n...Multivariate statistical process control methods have been widely used in biochemical industries. Batch process is usually monitored by the method of multi-way principal component analysis (MPCA). In this article, a new batch process monitoring and fault diagnosis method based on feature extract in Fisher subspace is proposed. The feature vector and the feature direction are extracted by projecting the high-dimension process data onto the low-dimension Fisher space. The similarity of feature vector between the current and the reference batch is calcu- lated for on-line process monitoring and the contribution plot of weights in feature direction is calculated for fault diagnosis. The approach overcomes the need for estimating or filling in the unknown portion of the process vari- ables trajectories from the current time to the end of the batch. Simulation results on the benchmark model of peni- cillin fermentation process can demonstrate that in comparison to the MPCA method, the proposed method is more accurate and efficient for process monitoring and fault diagnosis.展开更多
This paper analyzes the reasons of the tension unbalance of the ropes in multi-rope fric-tion winder, introduces the method of an on-line monitoring rope tensions with a testing device de-veloped by authors, and propo...This paper analyzes the reasons of the tension unbalance of the ropes in multi-rope fric-tion winder, introduces the method of an on-line monitoring rope tensions with a testing device de-veloped by authors, and proposes the criteria of the fault diagnosis and the method of adjustment for the tension unbalance of the ropes, which is important to the theoretical study on the tension unbalance of the ropes and the maintenance of multi-rope winder.展开更多
Faults in rotating machine are difficult to detect and identify,especially when the system is complex and nonlinear.In order to solve this problem,a novel performance monitoring and fault diagnosis method based on ker...Faults in rotating machine are difficult to detect and identify,especially when the system is complex and nonlinear.In order to solve this problem,a novel performance monitoring and fault diagnosis method based on kernel generalized discriminant analysis(kernel GDA,KGDA)was proposed.Through KGDA,the data were mapped from the original space to the high-dimensional feature space.Then the statistic distance between normal data and test data was constructed to detect whether a fault was occurring.If a fault had occurred,similar analysis was used to identify the type of faults.The effectiveness of the proposed method was evaluated by simulation results of vibration signal fault dataset in the rotating machinery,which was scalable to different rotating machinery.展开更多
This paper puts forward the LPM fault diagnosis method in the view of the important purpose of on-line monitoring and fault diagnosis for hoister brake system. The feasibility of the two diagnosis methods are proved i...This paper puts forward the LPM fault diagnosis method in the view of the important purpose of on-line monitoring and fault diagnosis for hoister brake system. The feasibility of the two diagnosis methods are proved in theories; two methods are proved about feasibility and reliability through testing. Two methods are manifestoed that they can undertake the on-line monitoring and fault diagnosis for hoister brake system with satisfied effect.展开更多
In this paper an expert system for remote fault diagnosis in the ship lift was developed by analysis of the fault tree and combination with VPN. The fault tree was constructed based on the operation condition of the s...In this paper an expert system for remote fault diagnosis in the ship lift was developed by analysis of the fault tree and combination with VPN. The fault tree was constructed based on the operation condition of the ship lift. The diagnosis model was constructed by hierarchical classification of the fault tree structure, and the inference mechanism was given. Logical structure of the fault diagnosis in the ship lift was proposed. The implementation of the expert system for remote fault diagnosis in the ship lift was discussed, and the expert system developed was realized on the VPN virtual network. The system was applied to the Gaobaozhou ship lift project, and it ran successfully.展开更多
The bearings in the trunnion of convertor are characterized by low-speed, heavy-load and huge-dimension. In case they experience failure in operation, the output of the convertor and even that of the whole product lin...The bearings in the trunnion of convertor are characterized by low-speed, heavy-load and huge-dimension. In case they experience failure in operation, the output of the convertor and even that of the whole product line would be affected and the huge loss would be resulted in. Thus it is very important to master the working conditions of the bearings. Vibration and oil analysis are two main techniques to monitor the conditions of the rotary machine at present. But normal vibration analysis cannot be used here because of the limitation of their sensors in signal collecting for the rotary frequencies of the bearings are too low. In this paper, the wear condition of the bearing on the driving side of the No.5 convertor during/after the run-in period was monitored through oil analysis including atomic emissive spectrum and ferrography. It has been observed that its run-in period was as long as 19 months. This is mainly attributed to the relative short accumulated working time of the bearing.展开更多
文摘On-line monitoring and fault diagnosis of chemical process is extremely important for operation safety and product quality. Principal component analysis (PCA) has been widely used in multivariate statistical process monitoring for its ability to reduce processes dimensions. PCA and other statistical techniques, however, have difficulties in differentiating faults correctly in complex chemical process. Support vector machine (SVM) is a novel approach based on statistical learning theory, which has emerged for feature identification and classification. In this paper, an integrated method is applied for process monitoring and fault diagnosis, which combines PCA for fault feature extraction and multiple SVMs for identification of different fault sources. This approach is verified and illustrated on the Tennessee Eastman benchmark process as a case study. Results show that the proposed PCA-SVMs method has good diagnosis capability and overall diagnosis correctness rate.
文摘A new on-line batch process monitoring and diagnosing approach based on Fisher discriminant analysis （FDA） was proposed. This method does not need to predict the future observations of variables, so it is more sensitive to fault detection and stronger implement for monitoring. In order to improve the monitoring performance, the variables trajectories of batch process are separated into several blocks. The key to the proposed approach for on-line monitoring is to calculate the distance of block data that project to low-dimension Fisher space between new batch and reference batch. Comparing the distance with the predefine threshold, it can be considered whether the batch process is normal or abnormal. Fault diagnosis is performed based on the weights in fault direction calculated by FDA. The proposed method was applied to the simulation model of fed-batch penicillin fermentation and the resuits were compared with those obtained using MPCA. The simulation results clearly show that the on-line monitoring method based on FDA is more efficient than the MPCA.
基金Supported by the National Natural Science Foundation of China (Nos.60474051, 60534020), the Key Technology and Devel-opment Program of Shanghai Science and Technology Department (No.04DZ11008), and the Program for New Century Ex-cellent Talents in the University of China (NCET).
文摘A statistic-based benchmark was proposed for performance assessment and monitoring of model predic- tive control; the benchmark was straightforward and achievable by recording a set of output data only when the control performance was good according to the user’s selection. Principal component model was built and an auto- regressive moving average filter was identified to monitor the performance; an improved T2 statistic was selected as the performance monitor index. When performance changes were detected, diagnosis was done by model validation using recursive analysis and generalized likelihood ratio (GLR) method. This distinguished the fact that the per- formance change was due to plant model mismatch or due to disturbance term. Simulation was done about a heavy oil fractionator system and good results were obtained. The diagnosis result was helpful for the operator to improve the system performance.
文摘At present, the on-line monitoring is widely applied to the power line monitoring. In this paper, a new mechanical calculation model is established according to the on-line monitoring. And this model is based on the parameters that tension sensors and angle sensors on suspended points detect, and combines with the parameters of the wire itself, and also considers the deflection angel of wires due to wind. In this model, mechanics parameters of wires are turned into the new coordinate plane after deflection angel of wires due to wind, or windage yaw plane. A statics tension balance equation is built in the vertical direction of the new windage yaw plane. According to the theoretical analysis and algorithm, we verify the accuracy of this newly developed mechanical calculation model.
基金Supported by the National Basic Research Program of China （2013CB733600）, the National Natural Science Foundation of China （21176073）, the Doctoral Fund of Ministry of Education of China （20090074110005）, the Program for New Century Excellent Talents in University （NCET-09-0346）, Shu Guang Project （09SG29） and the Fundamental Research Funds for the Central Universities.
文摘Fault diagnosis and monitoring are very important for complex chemical process. There are numerous methods that have been studied in this field, in which the effective visualization method is still challenging. In order to get a better visualization effect, a novel fault diagnosis method which combines self-organizing map (SOM) with Fisher discriminant analysis (FDA) is proposed. FDA can reduce the dimension of the data in terms of maximizing the separability of the classes. After feature extraction by FDA, SOM can distinguish the different states on the output map clearly and it can also be employed to monitor abnormal states. Tennessee Eastman (TE) process is employed to illustrate the fault diagnosis and monitoring performance of the proposed method. The result shows that the SOM integrated with FDA method is efficient and capable for real-time monitoring and fault diagnosis in complex chemical process.
基金Supported by the National Natural Science Foundation of China (No.60504033).
文摘Multivariate statistical process control methods have been widely used in biochemical industries. Batch process is usually monitored by the method of multi-way principal component analysis (MPCA). In this article, a new batch process monitoring and fault diagnosis method based on feature extract in Fisher subspace is proposed.The feature vector and the feature direction are extracted by projecting the high-dimension process data onto the low-dimension Fisher space. The similarity of feature vector between the current and the reference batch is calculated for on-line process monitoring and the contribution plot of weights in feature direction is calculated for fault diagnosis. The approach overcomes the need for estimating or tilling in the unknown portion of the process variables trajectories from the current time to the end of the batch. Simulation results on the benchmark model of penicillin fermentation process can demonstrate that in comparison to the MPCA method, the proposed method is more accurate and efficient for process monitoring and fault diagnosis.
基金the National Natural Science Foundation of China (No.60504033).
文摘Multivariate statistical process control methods have been widely used in biochemical industries. Batch process is usually monitored by the method of multi-way principal component analysis (MPCA). In this article, a new batch process monitoring and fault diagnosis method based on feature extract in Fisher subspace is proposed. The feature vector and the feature direction are extracted by projecting the high-dimension process data onto the low-dimension Fisher space. The similarity of feature vector between the current and the reference batch is calcu- lated for on-line process monitoring and the contribution plot of weights in feature direction is calculated for fault diagnosis. The approach overcomes the need for estimating or filling in the unknown portion of the process vari- ables trajectories from the current time to the end of the batch. Simulation results on the benchmark model of peni- cillin fermentation process can demonstrate that in comparison to the MPCA method, the proposed method is more accurate and efficient for process monitoring and fault diagnosis.
文摘This paper analyzes the reasons of the tension unbalance of the ropes in multi-rope fric-tion winder, introduces the method of an on-line monitoring rope tensions with a testing device de-veloped by authors, and proposes the criteria of the fault diagnosis and the method of adjustment for the tension unbalance of the ropes, which is important to the theoretical study on the tension unbalance of the ropes and the maintenance of multi-rope winder.
基金National Natural Science Foundation of China(No.60504033)
文摘Faults in rotating machine are difficult to detect and identify,especially when the system is complex and nonlinear.In order to solve this problem,a novel performance monitoring and fault diagnosis method based on kernel generalized discriminant analysis(kernel GDA,KGDA)was proposed.Through KGDA,the data were mapped from the original space to the high-dimensional feature space.Then the statistic distance between normal data and test data was constructed to detect whether a fault was occurring.If a fault had occurred,similar analysis was used to identify the type of faults.The effectiveness of the proposed method was evaluated by simulation results of vibration signal fault dataset in the rotating machinery,which was scalable to different rotating machinery.
文摘This paper puts forward the LPM fault diagnosis method in the view of the important purpose of on-line monitoring and fault diagnosis for hoister brake system. The feasibility of the two diagnosis methods are proved in theories; two methods are proved about feasibility and reliability through testing. Two methods are manifestoed that they can undertake the on-line monitoring and fault diagnosis for hoister brake system with satisfied effect.
文摘In this paper an expert system for remote fault diagnosis in the ship lift was developed by analysis of the fault tree and combination with VPN. The fault tree was constructed based on the operation condition of the ship lift. The diagnosis model was constructed by hierarchical classification of the fault tree structure, and the inference mechanism was given. Logical structure of the fault diagnosis in the ship lift was proposed. The implementation of the expert system for remote fault diagnosis in the ship lift was discussed, and the expert system developed was realized on the VPN virtual network. The system was applied to the Gaobaozhou ship lift project, and it ran successfully.
文摘The bearings in the trunnion of convertor are characterized by low-speed, heavy-load and huge-dimension. In case they experience failure in operation, the output of the convertor and even that of the whole product line would be affected and the huge loss would be resulted in. Thus it is very important to master the working conditions of the bearings. Vibration and oil analysis are two main techniques to monitor the conditions of the rotary machine at present. But normal vibration analysis cannot be used here because of the limitation of their sensors in signal collecting for the rotary frequencies of the bearings are too low. In this paper, the wear condition of the bearing on the driving side of the No.5 convertor during/after the run-in period was monitored through oil analysis including atomic emissive spectrum and ferrography. It has been observed that its run-in period was as long as 19 months. This is mainly attributed to the relative short accumulated working time of the bearing.
