An Improved Sensor Fault Diagnosis Scheme Based on TA-LSSVM and ECOC-SVM

Monitoring the operational state of sensors promptly and the accurate diagnosis of faults are essential. This paper proposes an improved fault diagnosis scheme for sensors, which includes both fault detection and fault identification. Firstly, trend analysis combined with least squares support vector machine (TA-LSSVM) method is proposed and implemented to detect faults. Secondly, an improved error correcting output coding-support vector machine (ECOC-SVM) based fault identification method is proposed to distinguish different sensor failure modes. To demonstrate the effectiveness of the proposed scheme, experiments are conducted with an MTi-series sensor, and some comparisons are made with other fault identification methods. The experimental results demonstrate that the proposed fault diagnosis scheme offers an essential improvement with detection real-time property and better identification accuracy.

[1]  Fang Deng,et al.  Sensor Multifault Diagnosis With Improved Support Vector Machines , 2017, IEEE Transactions on Automation Science and Engineering.

[2]  Hengjian Cui,et al.  Discriminant analysis based on statistical depth , 2010, J. Syst. Sci. Complex..

[3]  I. Jolliffe.  Principal Component Analysis , 2002 .

[4]  Dong Wang,et al.  Learning machines: Rationale and application in ground-level ozone prediction , 2014, Appl. Soft Comput..

[5]  Shida Katsunori.  Sensor Fault Diagnosis Based on Wavelet Packet and Support Vector Machines , 2008 .

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

[7]  Daniel Gillblad,et al.  Learning Machines , 2020, AAAI Spring Symposia.

[8]  Bernhard Schölkopf,et al.  Nonlinear Component Analysis as a Kernel Eigenvalue Problem , 1998, Neural Computation.

[9]  Yoram Singer,et al.  Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers , 2000, J. Mach. Learn. Res..

[10]  Martin Brown,et al.  Data Driven Fault Diagnosis and Fault Tolerant Control: Some Advances and Possible New Directions , 2009 .

[11]  Nedret Billor,et al.  Identifying Plant Part Composition of Forest Logging Residue Using Infrared Spectral Data and Linear Discriminant Analysis , 2016, Sensors.

[12]  Jianbin Qiu,et al.  State Estimation in Nonlinear System Using Sequential Evolutionary Filter , 2016, IEEE Transactions on Industrial Electronics.

[13]  Jianbin Qiu,et al.  Fault Detection for Nonlinear Process With Deterministic Disturbances: A Just-In-Time Learning Based Data Driven Method , 2017, IEEE Transactions on Cybernetics.

[14]  Corinna Cortes,et al.  Support-Vector Networks , 1995, Machine Learning.

[15]  Heng Tao Shen,et al.  Principal Component Analysis , 2009, Encyclopedia of Biometrics.

[16]  Jun Li,et al.  Parametric and non-parametric combination model to enhance overall performance on default prediction , 2014, J. Syst. Sci. Complex..

[17]  Raghunathan Rengaswamy,et al.  A framework for on-line trend extraction and fault diagnosis , 2010, Eng. Appl. Artif. Intell..

[18]  G. Baudat,et al.  Generalized Discriminant Analysis Using a Kernel Approach , 2000, Neural Computation.

[19]  Soo-Hyun Park,et al.  Colorimetric Sensor Array for White Wine Tasting , 2015, Sensors.

[20]  Enrico Zio,et al.  Failure and reliability prediction by support vector machines regression of time series data , 2011, Reliab. Eng. Syst. Saf..

[21]  Jing Wang,et al.  Research of temperature predictive control based on LSSVM optimized by improved PSO for thick steel plate Roller hearth Normalizing Furnace , 2010, 2010 8th World Congress on Intelligent Control and Automation.

[22]  Paolo Mercorelli.  Denoising and Harmonic Detection Using Nonorthogonal Wavelet Packets in Industrial Applications , 2007, J. Syst. Sci. Complex..

[23]  Fang Deng,et al.  Sensor fault identification based on Error-Correcting Output Codes method , 2015, 2015 IEEE 7th International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM).

[24]  Jianbin Qiu,et al.  Descriptor reduced-order sliding mode observers design for switched systems with sensor and actuator faults , 2017, Autom..

[25]  Chi-Man Vong,et al.  Engine ignition signal diagnosis with Wavelet Packet Transform and Multi-class Least Squares Support Vector Machines , 2011, Expert Syst. Appl..

[26]  Sergio Escalera,et al.  On the Decoding Process in Ternary Error-Correcting Output Codes , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.