Fault Detection for Nonlinear Process With Deterministic Disturbances: A Just-In-Time Learning Based Data Driven Method

Data-driven fault detection plays an important role in industrial systems due to its applicability in case of unknown physical models. In fault detection, disturbances must be taken into account as an inherent characteristic of processes. Nevertheless, fault detection for nonlinear processes with deterministic disturbances still receive little attention, especially in data-driven field. To solve this problem, a just-in-time learning-based data-driven (JITL-DD) fault detection method for nonlinear processes with deterministic disturbances is proposed in this paper. JITL-DD employs JITL scheme for process description with local model structures to cope with processes dynamics and nonlinearity. The proposed method provides a data-driven fault detection solution for nonlinear processes with deterministic disturbances, and owns inherent online adaptation and high accuracy of fault detection. Two nonlinear systems, i.e., a numerical example and a sewage treatment process benchmark, are employed to show the effectiveness of the proposed method.

[1]  Shen Yin,et al.  Performance Monitoring for Vehicle Suspension System via Fuzzy Positivistic C-Means Clustering Based on Accelerometer Measurements , 2015, IEEE/ASME Transactions on Mechatronics.

[2]  Spyridon V. Giannoutsos,et al.  A Data-Driven Process Controller for Energy-Efficient Variable-Speed Pump Operation in the Central Cooling Water System of Marine Vessels , 2015, IEEE Transactions on Industrial Electronics.

[3]  Kok-Meng Lee,et al.  Model-Based Fault Detection and Isolation Scheme for a Rudder Servo System , 2015, IEEE Transactions on Industrial Electronics.

[4]  Biao Huang,et al.  A unified recursive just-in-time approach with industrial near infrared spectroscopy application , 2014 .

[5]  Kai Zhang,et al.  A data-driven fault detection approach for static processes with deterministic disturbances , 2014, 2014 IEEE 23rd International Symposium on Industrial Electronics (ISIE).

[6]  Shusheng Li,et al.  ROBUST H∞ FAULT DETECTION FOR UNCERTAIN LDTV SYSTEMS USING KREIN SPACE APPROACH , 2013 .

[7]  Afshin Izadian,et al.  Adaptive Nonlinear Model-Based Fault Diagnosis of Li-Ion Batteries , 2015, IEEE Transactions on Industrial Electronics.

[8]  Steven X. Ding,et al.  Model-based Fault Diagnosis Techniques: Design Schemes, Algorithms, and Tools , 2008 .

[9]  Deyong You,et al.  WPD-PCA-Based Laser Welding Process Monitoring and Defects Diagnosis by Using FNN and SVM , 2015, IEEE Transactions on Industrial Electronics.

[10]  Okyay Kaynak,et al.  Improved PLS Focused on Key-Performance-Indicator-Related Fault Diagnosis , 2015, IEEE Transactions on Industrial Electronics.

[11]  Alberto Bellini,et al.  Evaluation of Combined Reference Frame Transformation for Interturn Fault Detection in Permanent-Magnet Multiphase Machines , 2015, IEEE Transactions on Industrial Electronics.

[12]  Hak-Keung Lam,et al.  Observer-Based Fuzzy Control for Nonlinear Networked Systems Under Unmeasurable Premise Variables , 2016, IEEE Transactions on Fuzzy Systems.

[13]  Lei Xie,et al.  Novel Just-In-Time Learning-Based Soft Sensor Utilizing Non-Gaussian Information , 2014, IEEE Transactions on Control Systems Technology.

[14]  Yi Liu,et al.  Modeling and Performance Evaluation of BPEL Processes: A Stochastic-Petri-Net-Based Approach , 2012, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[15]  Leopoldo García Franquelo,et al.  Model Based Adaptive Direct Power Control for Three-Level NPC Converters , 2013, IEEE Transactions on Industrial Informatics.

[16]  Ali Borji,et al.  What/Where to Look Next? Modeling Top-Down Visual Attention in Complex Interactive Environments , 2014, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[17]  Sheng Chen,et al.  Nonlinear Identification Using Orthogonal Forward Regression With Nested Optimal Regularization , 2015, IEEE Transactions on Cybernetics.

[18]  Shuzhi Sam Ge,et al.  Adaptive actuator fault tolerant control for uncertain nonlinear systems with multiple actuators , 2015, Autom..

[19]  James Lam,et al.  An Improved Incremental Learning Approach for KPI Prognosis of Dynamic Fuel Cell System , 2016, IEEE Transactions on Cybernetics.

[20]  Paul G. Plöger,et al.  Model-Based Fault Diagnosis Techniques for Mobile Robots , 2016 .

[21]  Sauro Longhi,et al.  Multi-apartment residential microgrid monitoring system based on kernel canonical variate analysis , 2015, Neurocomputing.

[22]  George Cybenko,et al.  Just-in-Time Learning and Estimation , 1996 .

[23]  Peng Shi,et al.  Reliable Mixed $H_\infty $ and Passivity-Based Control for Fuzzy Markovian Switching Systems With Probabilistic Time Delays and Actuator Failures , 2015, IEEE Transactions on Cybernetics.

[24]  Hubert Razik,et al.  Prognosis of Bearing Failures Using Hidden Markov Models and the Adaptive Neuro-Fuzzy Inference System , 2014, IEEE Transactions on Industrial Electronics.

[25]  Min-Sen Chiu,et al.  Nonlinear process monitoring using JITL-PCA , 2005 .

[26]  Raymond H. Kwong,et al.  Fault Diagnosis in Discrete-Event Systems with Incomplete Models: Learnability and Diagnosability , 2015, IEEE Transactions on Cybernetics.

[27]  Wei Sun,et al.  An Advanced PLS Approach for Key Performance Indicator-Related Prediction and Diagnosis in Case of Outliers , 2016, IEEE Transactions on Industrial Electronics.

[28]  X. Liu,et al.  Principal Component Analysis of Wide-Area Phasor Measurements for Islanding Detection—A Geometric View , 2015, IEEE Transactions on Power Delivery.

[29]  Simona Onori,et al.  Model-based Diagnosis of an Automotive Electric Power Generation and Storage System , 2014, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[30]  Xiaoping Liu,et al.  Robust Adaptive Neural Tracking Control for a Class of Stochastic Nonlinear Interconnected Systems , 2016, IEEE Transactions on Neural Networks and Learning Systems.

[31]  Shen Yin,et al.  Intelligent Particle Filter and Its Application to Fault Detection of Nonlinear System , 2015, IEEE Transactions on Industrial Electronics.