Is Fault Detection and Diagnosis in Pneumatic Actuator A Topic of Concern?


  • Bhagya R Navada Department of Instrumentation and Control Engineering, Centre for Cyber-physical Systems, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India
  • Santhosh K. V Department of Instrumentation and Control Engineering, Centre for Cyber-physical Systems, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India



Fault detection, fault diagnosis, stiction, pneumatic actuator faults, review


The present civilization highly depends on industrial products and hence there is an increased demand for the same. Therefore, each industry is trying to increase its production output without hindering the quality. Maintenance of plant health is essential to improve the production rate without any loss. Industrial processes require monitoring of every element as their consistent behavior is a fundamental concern. Any deviation in the working of these components may alter the quality of the end product, causing a huge loss for the industry. Therefore, monitoring and finding the root cause for irregular behavior of industrial processes is a requisite for avoiding any future loss. In this paper, an attempt is made to present types of faults, types of pneumatic actuator faults, and different techniques used for the detection and isolation of faults.  Simulation work is carried out to generate stiction behavior in the control valve using the Choudhury stiction model. Valve stiction behavior for different values of stick band and jump values are discussed in this paper. A comparison of several techniques used for the detection of faults based on two performance indices namely true detection rate and false alarm rate has been given at the end of this paper. From these techniques, it is observed that these indices are interdependent, such that an increase in the detection rate increases the false detection rate and increases detection time.


BIMBA, MEAD. "Pneumatic Application & Reference Handbook." (2011).

Zhu, Jinlin, Zhiqiang Ge, and Zhihuan Song. "Robust supervised probabilistic principal component analysis model for soft sensing of key process variables." Chemical Engineering Science 122 (2015): 573-584.

Xie, Xiang-Peng, Dong Yue, and Ju H. Park. "Robust fault estimation design for discrete-time nonlinear systems via a modified fuzzy fault estimation observer." ISA transactions 73 (2018): 22-30.

Graves, Julio Cesar, Wallace Hessler Leal Turcio, and Takashi Yoneyama. "Degradation analysis of an aeronautical pneumatic actuator using hysteresis-based signatures." Journal of Control, Automation and Electrical Systems 29, no. 4 (2018): 451-459.

Lin, Bao, Bodil Recke, Jørgen KH Knudsen, and Sten Bay Jørgensen. "A systematic approach for soft sensor development." Computers & chemical engineering 31, no. 5-6 (2007): 419-425.

Heredia, G., A. Ollero, M. Bejar, and R. Mahtani. "Sensor and actuator fault detection in small autonomous helicopters." Mechatronics 18, no. 2 (2008): 90-99.

Abbaspour, Alireza, Payam Aboutalebi, Kang K. Yen, and Arman Sargolzaei. "Neural adaptive observer-based sensor and actuator fault detection in nonlinear systems: Application in UAV." ISA transactions 67 (2017): 317-329.

Naderi, Esmaeil, and Khashayar Khorasani. "A data-driven approach to actuator and sensor fault detection, isolation and estimation in discrete-time linear systems." Automatica 85 (2017): 165-178.

Miron, Mihaela, Lauren?iu Frangu, and Sergiu Caraman. "Actuator fault detection using extended Kalman filter for a wastewater treatment process." In 2017 21st International Conference on System Theory, Control and Computing (ICSTCC), pp. 583-588. IEEE, 2017.

Peng, Min-jun, Hang Wang, Xu Yang, Yong-kuo Liu, Liang-zhuang Guo, Wei Li, and Nan Jiang. "Real-time simulations to enhance distributed on-line monitoring and fault detection in Pressurized Water Reactors." Annals of Nuclear Energy 109 (2017): 557-573.

Li, Shuai, Xiaofeng Zhou, Fucheng Pan, Haibo Shi, Kaituo Li, and Zhongwei Wang. "Correlated and weakly correlated fault detection based on variable division and ICA." Computers & Industrial Engineering 112 (2017): 320-335.

Sheriff, M. Ziyan, Majdi Mansouri, M. Nazmul Karim, Hazem Nounou, and Mohamed Nounou. "Fault detection using multiscale PCA-based moving window GLRT." Journal of Process Control 54 (2017): 47-64.

Zhang, Shirong, Qian Tang, Yu Lin, and Yuling Tang. "Fault detection of feed water treatment process using PCA-WD with parameter optimization." ISA transactions 68 (2017): 313-326.

Ji, Hongquan, Xiao He, Jun Shang, and Donghua Zhou. "Incipient fault detection with smoothing techniques in statistical process monitoring." Control Engineering Practice 62 (2017): 11-21.

Turner, W. J. N., A. Staino, and B. Basu. "Residential HVAC fault detection using a system identification approach." Energy and Buildings 151 (2017): 1-17.

Sharifi, Siavash, Ali Tivay, S. Mehdi Rezaei, Mohammad Zareinejad, and Bijan Mollaei-Dariani. "Leakage fault detection in Electro-Hydraulic Servo Systems using a nonlinear representation learning approach." ISA transactions 73 (2018): 154-164.

Nozari, Hasan Abbasi, Sina Nazeri, Hamed Dehghan Banadaki, and Paolo Castaldi. "Model-free fault detection and isolation of a benchmark process control system based on multiple classifiers techniques—A comparative study." Control Engineering Practice 73 (2018): 134-148.

Jun-Jie, Huang, and Jiang Zhen. "A method on fault detection and isolation of the actuator mechanism." Journal of Applied Sciences 13 (2013): 1100-1105.

Madrigal-Espinosa, G., G-L. Osorio-Gordillo, C-M. Astorga-Zaragoza, M. Vázquez-Román, and M. Adam-Medina. "Fault detection and isolation system for boiler-turbine unit of a thermal power plant." Electric Power Systems Research 148 (2017): 237-244.

Avram, Remus C., Xiaodong Zhang, and Jonathan Muse. "Quadrotor actuator fault diagnosis and accommodation using nonlinear adaptive estimators." IEEE Transactions on Control Systems Technology 25, no. 6 (2017): 2219-2226.

Mehennaoui, L., N. Debbache, and M. L. Benloucif. "Neuro-Fuzzy Methods for Fault Diagnosis of Nonlinear Systems." Journal of Applied Sciences 6, no. 9 (2006): 2020-2030.

Ramdani, Messaoud, and Noureddine Doghmane. "Fault Diagnosis of Technical Processes Based on the Multi-Model Approach." Asian Journal of Information Technology 5 (2006): 1166-1171.

Zhang, Qinghua. "Actuator fault diagnosis with robustness to sensor distortion." Journal of Control Science and Engineering 2008 (2008): 5.

Lin, Paul P., Dapeng Ye, Zhiqiang Gao, and Qing Zheng. "Intelligent process fault diagnosis for nonlinear systems with uncertain plant model via extended state observer and soft computing." Intelligent Control and Automation 3, no. 04 (2012): 346.

Mrugalski, Marcin, and Marcin Witczak. "State-space GMDH neural networks for actuator robust fault diagnosis." Advances in Electrical and Computer Engineering 12, no. 3 (2012): 65-72.

Zhang, Yingzhi, Liming Mu, Guixiang Shen, Yang Yu, and Chenyu Han. "Fault diagnosis strategy of CNC machine tools based on cascading failure." Journal of Intelligent Manufacturing 30, no. 5 (2019): 2193-2202.

Fernando, Heshan, and Brian Surgenor. "An unsupervised artificial neural network versus a rule-based approach for fault detection and identification in an automated assembly machine." Robotics and Computer-Integrated Manufacturing 43 (2017): 79-88.

Caliskan, Fikret, Youmin Zhang, N. Eva Wu, and Jong-Yeob Shin. "Actuator fault diagnosis in a Boeing 747 model via adaptive modified two-stage Kalman filter." International Journal of Aerospace Engineering 2014 (2014).

Li, P. and Jin, F. “Adaptive Fuzzy Backstepping Control against Actuator Faults.” Information Technology Journal, 10(12), (2011):2458-2463.

Yang, Inseok, and Dongik Lee. "Networked fault-tolerant control allocation for multiple actuator failures." Mathematical Problems in Engineering 2015 (2015).

López-Zapata, B., M. Adam-Medina, R. F. Escobar, P. E. Álvarez-Gutiérrez, J. F. Gómez-Aguilar, and L. G. Vela-Valdés. "Sensors and actuator fault tolerant control applied in a double pipe heat exchanger." Measurement 93 (2016): 215-223.

Mu, Wenying, Junping Wang, and Weiwei Feng. "Fault detection and fault-tolerant control of actuators and sensors in distributed parameter systems." Journal of the Franklin Institute 354, no. 8 (2017): 3341-3363.

Zou, Tao, Sheng Wu, and Ridong Zhang. "Improved state space model predictive fault-tolerant control for injection molding batch processes with partial actuator faults using GA optimization." ISA transactions 73 (2018): 147-153.

Bataghva, Meysam, and Mahnaz Hashemi. "Adaptive sliding mode synchronisation for fractional-order non-linear systems in the presence of time-varying actuator faults." IET Control Theory & Applications 12, no. 3 (2017): 377-383.

Vargas-Martinez, Adriana, and L. E. Garza-Castañón. "Combining artificial intelligence and advanced techniques in fault-tolerant control." Journal of applied research and technology 9, no. 2 (2011): 202-226.

Silva, Guilherme Costa, Walmir Matos Caminhas, and Reinaldo Martinez Palhares. "Artificial immune systems applied to fault detection and isolation: A brief review of immune response-based approaches and a case study." Applied Soft Computing 57 (2017): 118-131., December 2018.

Fisher, L. "Control valve handbook." (2005).

Isermann, Rolf. "Supervision, fault-detection and fault-diagnosis methods—an introduction." Control engineering practice 5, no. 5 (1997): 639-652.

Barty?, Micha?, Ron Patton, Micha? Syfert, Salvador de las Heras, and Joseba Quevedo. "Introduction to the DAMADICS actuator FDI benchmark study." Control engineering practice 14, no. 6 (2006): 577-596.

Previdi, Fabio, and Thomas Parisini. "Model-free actuator fault detection using a spectral estimation approach: the case of the DAMADICS benchmark problem." Control Engineering Practice 14, no. 6 (2006): 635-644.

Ko?cielny, Jan M., Micha? Barty?, Pawe? Rzepiejewski, and Jose Sá da Costa. "Actuator fault distinguishability study for the DAMADICS benchmark problem." Control Engineering Practice 14, no. 6 (2006): 645-652.

Dü?tegör, Dilek, Erik Frisk, Vincent Cocquempot, Mattias Krysander, and Marcel Staroswiecki. "Structural analysis of fault isolability in the DAMADICS benchmark." Control Engineering Practice 14, no. 6 (2006): 597-608.

Puig, Vicenç, Alexandru Stancu, Teresa Escobet, Fatiha Nejjari, Joseba Quevedo, and Ron J. Patton. "Passive robust fault detection using interval observers: Application to the DAMADICS benchmark problem." Control engineering practice 14, no. 6 (2006): 621-633.

Uppal, Faisel J., Ron J. Patton, and Marcin Witczak. "A neuro-fuzzy multiple-model observer approach to robust fault diagnosis based on the DAMADICS benchmark problem." Control Engineering Practice 14, no. 6 (2006): 699-717.

Mendonça, Luís F., J. M. C. Sousa, and JMG Sá da Costa. "An architecture for fault detection and isolation based on fuzzy methods." Expert systems with applications 36, no. 2 (2009): 1092-1104.

Laurentys, C. A., Reinaldo M. Palhares, and Walmir M. Caminhas. "Design of an artificial immune system based on Danger Model for fault detection." Expert Systems with Applications 37, no. 7 (2010): 5145-5152.

Chopra, Tarun, and Jayashri Vajpai. "Classification of faults in damadics benchmark process control system using self-organizing maps." Int. J. Soft Comput. Eng 1, no. 3 (2011): 85-90.

Subrahmanya, Niranjan, and Yung C. Shin. "A data-based framework for fault detection and diagnostics of non-linear systems with partial state measurement." Engineering Applications of Artificial Intelligence 26, no. 1 (2013): 446-455.

Kowsalya, A., and B. Kannapiran. "Principal component analysis based approach for fault diagnosis in pneumatic valve using DAMADICS benchmark simulator.", special issue-07, IJRET: International Journal of Research in Engineering and Technology, (May 2014): 702-707.

Subbaraj, P., and B. Kannapiran. "Artificial neural network approach for fault detection in pneumatic valve in cooler water spray system." International Journal of Computer Applications 9, no. 7 (2010): 43-52.

Subbaraj, P., and B. Kannapiran. "Fault detection and diagnosis of pneumatic valve using adaptive neuro-fuzzy inference system approach." Applied Soft Computing 19 (2014): 362-371.

Prabakaran, K., S. Kaushik, R. Moulceshuwarapprabu, and A. Jagadeesan. "Fault Detection and Isolation Scheme for Pneumatic Actuator Using Sugeno-Type Fuzzy Inference System." International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering 3, no. 8 (2014): 11358-11365.

Prabakaran, K., S. Kaushik, and R. Mouleeshuwarapprabu. "Radial Basis Neural Networks Based Fault Detection and Isolation Scheme for Pneumatic Actuator." Journal of Engineering Computers & Applied Sciences 3, no. 9 (2014): 50-55.

Prabakaran, K., S. Kaushik, R. Mouleeshuwarapprabu, and Ajith B. Singh. "Self-Organizing Map Based Fault Detection and Isolation Scheme for Pneumatic Actuator." International Journal of Innovation and Applied Studies 8, no. 3 (2014): 1361.

Ahmed, Hafaifa, Djeddi Ahmed Zohair, and Daoudi Attia. "Fault detection and isolation in industrial control valve based on artificial neural networks diagnosis." Journal of Control Engineering and Applied Informatics 15, no. 3 (2013): 61-69.

Lemos, Andre, Walmir Caminhas, and Fernando Gomide. "Adaptive fault detection and diagnosis using an evolving fuzzy classifier." Information Sciences 220 (2013): 64-85.

Chopra, Tarun, and Jayashri Vajpai. "Fault diagnosis in benchmark process control system using stochastic gradient boosted decision trees." Int. J. Soft Comput. Eng 1 (2011): 98-101.

Calado, J. M. F., JMG Sá da Costa, M. Bartys, and J. Korbicz. "FDI approach to the DAMADICS benchmark problem based on qualitative reasoning coupled with fuzzy neural networks." Control Engineering Practice 14, no. 6 (2006): 685-698.

Bocaniala, Cosmin Danut, and Jose Sa da Costa. "Application of a novel fuzzy classifier to fault detection and isolation of the DAMADICS benchmark problem." Control engineering practice 14, no. 6 (2006): 653-669.

Korbicz, Józef, and Marek Kowal. "Neuro-fuzzy networks and their application to fault detection of dynamical systems." Engineering Applications of Artificial Intelligence 20, no. 5 (2007): 609-617.

Przysta?ka, Piotr, and Wojciech Moczulski. "Methodology of neural modelling in fault detection with the use of chaos engineering." Engineering Applications of Artificial Intelligence 41 (2015): 25-40.

Karpenko, M., N. Sepehri, and D. Scuse. "Diagnosis of process valve actuator faults using a multilayer neural network." Control Engineering Practice 11, no. 11 (2003): 1289-1299.

Bouamama, B. Ould, K. Medjaher, M. Bayart, A. K. Samantaray, and B. Conrard. "Fault detection and isolation of smart actuators using bond graphs and external models." Control Engineering Practice 13, no. 2 (2005): 159-175.

Mrugalski, Marcin, Marcin Witczak, and Józef Korbicz. "Confidence estimation of the multi-layer perceptron and its application in fault detection systems." Engineering Applications of Artificial Intelligence 21, no. 6 (2008): 895-906.

Witczak, Marcin, Józef Korbicz, Marcin Mrugalski, and Ron J. Patton. "A GMDH neural network-based approach to robust fault diagnosis: Application to the DAMADICS benchmark problem." Control Engineering Practice 14, no. 6 (2006): 671-683.

Bezerra, Clauber Gomes, Bruno Sielly Jales Costa, Luiz Affonso Guedes, and Plamen Parvanov Angelov. "An evolving approach to unsupervised and Real-Time fault detection in industrial processes." Expert systems with applications 63 (2016): 134-144.

Wang, H., and S. Daley. "Actuator fault diagnosis: an adaptive observer-based technique." IEEE transactions on Automatic Control 41, no. 7 (1996): 1073-1078.

D'Angelo, Marcos FSV, Reinaldo M. Palhares, Ricardo HC Takahashi, and Rosangela H. Loschi. "Fuzzy/Bayesian change point detection approach to incipient fault detection." IET control theory & applications 5, no. 4 (2011): 539-551.

Ding, Steven X. Model-based fault diagnosis techniques: design schemes, algorithms, and tools. Springer Science & Business Media, 2008.

Horch, Alexander. "A simple method for detection of stiction in control valves." Control Engineering Practice 7, no. 10 (1999): 1221-1231.

Rossi, M., and Claudio Scali. "A comparison of techniques for automatic detection of stiction: simulation and application to industrial data." Journal of Process Control 15, no. 5 (2005): 505-514.

Daneshwar, M. A., and Norlaili Mohd Noh. "Detection of stiction in flow control loops based on fuzzy clustering." Control Engineering Practice 39 (2015): 23-34.

Ramos, Adrián Rodríguez, Carlos Domínguez Acosta, Pedro J. Rivera Torres, Eileen I. Serrano Mercado, Gerson Beauchamp Baez, Luis Anido Rifón, and Orestes Llanes-Santiago. "An approach to multiple fault diagnosis using fuzzy logic." Journal of Intelligent Manufacturing 30, no. 1 (2019): 429-439.

Zeghlache, Samir, Hemza Mekki, Abderrahmen Bouguerra, and Ali Djerioui. "Actuator fault tolerant control using adaptive RBFNN fuzzy sliding mode controller for coaxial octorotor UAV." ISA transactions 80 (2018): 267-278.

McGhee, Joseph, Ian A. Henderson, and Alistair Baird. "Neural networks applied for the identification and fault diagnosis of process valves and actuators." Measurement 20, no. 4 (1997): 267-275.

Precup, Radu-Emil, Plamen Angelov, Bruno Sielly Jales Costa, and Moamar Sayed-Mouchaweh. "An overview on fault diagnosis and nature-inspired optimal control of industrial process applications." Computers in Industry 74 (2015): 75-94.

Feng, Zhigang, Xuejuan Zhang, and He Yang. "Research of pneumatic actuator fault diagnosis method based on GA optimized BP neural network and fuzzy logic." In International Symposium on Neural Networks, pp. 578-585. Springer, Berlin, Heidelberg, 2013.

Cai, Baoping, Yubin Zhao, Hanlin Liu, and Min Xie. "A data-driven fault diagnosis methodology in three-phase inverters for PMSM drive systems." IEEE Transactions on Power Electronics 32, no. 7 (2016): 5590-5600.

Gholizadeh, Mehdi, Alireza Yazdizadeh, and Hamed Mohammad-Bagherpour. "Fault detection and identification using combination of ekf and neuro-fuzzy network applied to a chemical process (cstr)." Pattern Analysis and Applications 22, no. 2 (2019): 359-373.

Ali, Salah M., K. H. Hui, L. M. Hee, and M. Salman Leong. "Automated valve fault detection based on acoustic emission parameters and support vector machine." Alexandria engineering journal 57, no. 1 (2018): 491-498.

Abad, Mohammad Reza Asadi Asad, Ashkan Moosavian, and Meghdad Khazaee. "Wavelet transform and least square support vector machine for mechanical fault detection of an alternator using vibration signal." Journal of Low Frequency Noise, Vibration and Active Control 35, no. 1 (2016): 52-63.

Xu, Zhanyang, Charles Zhan, and Shunyi Zhang. "A new non-invasive method for valve stiction dection using wavelet technology." Journal of Electronics (China) 26, no. 5 (2009): 673.

Heydarzadeh, Mehrdad, and Mehrdad Nourani. "A two-stage fault detection and isolation platform for industrial systems using residual evaluation." IEEE Transactions on Instrumentation and Measurement 65, no. 10 (2016): 2424-2432.

Yu, Ming, and Juan Xu. "Sequential fault diagnosis for mechatronics system using diagnostic hybrid bond graph and composite harmony search." Advances in Mechanical Engineering 7, no. 12 (2015): 1687814015620321.

Xu, Feng, Junbo Tan, Xueqian Wang, Vicenç Puig, Bin Liang, and Bo Yuan. "Mixed active/passive robust fault detection and isolation using set-theoretic unknown input observers." IEEE Transactions on Automation Science and Engineering 15, no. 2 (2017): 863-871.

Zhou, Meng, Zhenhua Wang, Yi Shen, and Mouquan Shen. "$ H_ {-}/H_ {infty} $ H?/H? fault detection observer design in finite-frequency domain for Lipschitz non-linear systems." IET Control Theory & Applications 11, no. 14 (2017): 2361-2369.

Durand, Helen, Robert Parker, Anas Alanqar, and Panagiotis D. Christofides. "Elucidating and handling effects of valve-induced nonlinearities in industrial feedback control loops." Computers & Chemical Engineering 116 (2018): 156-175.

Jelali, Mohieddine, and Biao Huang, eds. Detection and diagnosis of stiction in control loops: state of the art and advanced methods. Springer Science & Business Media, 2009.

Choudhury, MAA Shoukat, Nina F. Thornhill, and Sirish L. Shah. "Modelling valve stiction." Control engineering practice 13, no. 5 (2005): 641-658.

Maruta, Hiroshi, Manabu Kano, Hidekazu Kugemoto, and Keiko Shimizu. "Modeling and Detection of Stiction in Pneumatic Control Valve." Transactions of the Society of Instrument and Control Engineers 40, no. 8 (2004): 825-833.

Xie, Lei, Yu Cong, and Alexander Horch. "An improved valve stiction simulation model based on ISA standard tests." Control Engineering Practice 21, no. 10 (2013): 1359-1368.

di Capaci, Riccardo Bacci, Claudio Scali, and Gabriele Pannocchia. "System identification applied to stiction quantification in industrial control loops: A comparative study." Journal of Process Control 46 (2016): 11-23.

Yamashita, Yoshiyuki. "An automatic method for detection of valve stiction in process control loops." Control Engineering Practice 14, no. 5 (2006): 503-510.

Zakharov, Alexey, Elena Zattoni, Lei Xie, Octavio Pozo Garcia, and Sirkka-Liisa Jämsä-Jounela. "An autonomous valve stiction detection system based on data characterization." Control Engineering Practice 21, no. 11 (2013): 1507-1518.

Ma, Lingling, Xiangshun Li, Cheng Lei, and Wenling Wang. "Process monitoring of the pneumatic control valve using canonical variate analysis." In 2017 Chinese Automation Congress (CAC), pp. 2784-2788. IEEE, 2017.

Jiang, Hailei, MAA Shoukat Choudhury, and Sirish L. Shah. "Detection and diagnosis of plant-wide oscillations from industrial data using the spectral envelope method." Journal of Process Control 17, no. 2 (2007): 143-155.

Schubert, Udo, Uwe Kruger, Günter Wozny, and Harvey Arellano?Garcia. "Input reconstruction for statistical?based fault detection and isolation." AIChE Journal 58, no. 5 (2012): 1513-1523.

Mansouri, M., M. Z. Sheriff, R. Baklouti, M. Nounou, H. Nounou, A. Ben Hamida, and N. Karim. "Statistical fault detection of chemical process-comparative studies." Journal of Chemical Engineering & Process Technology 7, no. 1 (2016): 282-291.

Bafroui, Hojat Heidari, and Abdolreza Ohadi. "Application of wavelet energy and Shannon entropy for feature extraction in gearbox fault detection under varying speed conditions." Neurocomputing 133 (2014): 437-445.

Ebrahimi, Bashir Mahdi, and Jawad Faiz. "Feature extraction for short-circuit fault detection in permanent-magnet synchronous motors using stator-current monitoring." IEEE Transactions on Power Electronics 25, no. 10 (2010): 2673-2682.

Tian, Jing, Carlos Morillo, Michael H. Azarian, and Michael Pecht. "Motor bearing fault detection using spectral kurtosis-based feature extraction coupled with K-nearest neighbor distance analysis." IEEE Transactions on Industrial Electronics 63, no. 3 (2015): 1793-1803.

Li, Guannan, and Yunpeng Hu. "An enhanced PCA-based chiller sensor fault detection method using ensemble empirical mode decomposition based denoising." Energy and Buildings 183 (2019): 311-324.

Zhou, Funa, Ju H. Park, and Yajuan Liu. "Differential feature based hierarchical PCA fault detection method for dynamic fault." Neurocomputing 202 (2016): 27-35.

Bakdi, Azzeddine, Abdelmalek Kouadri, and Abderazak Bensmail. "Fault detection and diagnosis in a cement rotary kiln using PCA with EWMA-based adaptive threshold monitoring scheme." Control Engineering Practice 66 (2017): 64-75.

Yu, Dexin, Junqi Yu, Fukang Sun, Yu Deng, Qifan Wu, and Guangjie Cong. "Research on the PCA-based intelligent fault detection methodology for sewage source heat pump system." Procedia Engineering 205 (2017): 1064-1071.

Pozo, Francesc, and Yolanda Vidal. "Wind turbine fault detection through principal component analysis and statistical hypothesis testing." Energies 9, no. 1 (2016): 3.

Bakdi, Azzeddine, and Abdelmalek Kouadri. "A new adaptive PCA based thresholding scheme for fault detection in complex systems." Chemometrics and Intelligent Laboratory Systems 162 (2017): 83-93.

Daneshwar, M. A., and Norlaili Mohd Noh. "Identification of a process with control valve stiction using a fuzzy system: A data-driven approach." Journal of Process Control 24, no. 4 (2014): 249-260.

Michail, Konstantinos, Kyriakos M. Deliparaschos, Spyros G. Tzafestas, and Argyrios C. Zolotas. "AI-based actuator/sensor fault detection with low computational cost for industrial applications." IEEE Transactions on Control Systems Technology 24, no. 1 (2015): 293-301.

Cheng, Yao, Rixin Wang, and Minqiang Xu. "A combined model-based and intelligent method for small fault detection and isolation of actuators." IEEE Transactions on Industrial Electronics 63, no. 4 (2015): 2403-2413.

Amiruddin, Ahmad Azharuddin Azhari Mohd, Haslinda Zabiri, Sean Suraj Jeremiah, Weng Kean Teh, and Bashariah Kamaruddin. "Valve stiction detection through improved pattern recognition using neural networks." Control Engineering Practice 90 (2019): 63-84.

Jeremiah, Sean Suraj, Haslinda Zabiri, Marappagounder Ramasamy, Weng Kean Teh, Bashariah Kamaruddin, and Ahmad Azharuddin Azhari Mohd Amiruddin. "Generic framework for valve stiction detection and compensation with ANFIS-activated dual-mode MPC." Journal of Process Control 79 (2019): 85-97.

Nguyen, Ngoc Phi, Nguyen Xuan Mung, and Sung Kyung Hong. "Actuator Fault Detection and Fault-Tolerant Control for Hexacopter." Sensors 19, no. 21 (2019): 4721.

Lien, Yu-Hsuan, Chao-Chung Peng, and Yi-Hsuan Chen. "Adaptive Observer-Based Fault Detection and Fault-Tolerant Control of Quadrotors under Rotor Failure Conditions." Applied Sciences 10, no. 10 (2020): 3503.

Wang, Rijun, Changjun Zhao, Yue Bai, Wenhua Du, and Junyuan Wang. "An actuator fault detection and reconstruction scheme for hex-rotor unmanned aerial vehicle." IEEE Access 7 (2019): 93937-93951.

Tran, Hieu Manh, and Hieu Trinh. "Distributed functional observer based fault detection for interconnected time-delay systems." IEEE Systems Journal 13, no. 1 (2017): 940-951.

Hajiyev, Ch. "Tracy–Widom distribution based fault detection approach: Application to aircraft sensor/actuator fault detection." Isa Transactions 51, no. 1 (2012): 189-197.

di Capaci, Riccardo Bacci, Marco Vaccari, Gabriele Pannocchia, and Claudio Scali. "Identification and estimation of valve stiction by the use of a smoothed model." IFAC-PapersOnLine 51, no. 18 (2018): 684-689.




How to Cite

Navada, B. R., & K. V, S. (2020). Is Fault Detection and Diagnosis in Pneumatic Actuator A Topic of Concern?. Journal of Advanced Research in Fluid Mechanics and Thermal Sciences, 77(2), 102–129.