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An improved simplex-based adaptive evolutionary digital filter and its application for fault detection of rolling element bearings |
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| Affiliation: | 1. National Engineering Research Center of Flat Rolling Equipment, University of Science and Technology Beijing, Beijing 100083, PR China;2. State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400030, PR China;3. Department of Engineering, University of Glamorgan, Pontypridd CF37 1DL, UK;1. Politecnico di Torino, Dipartimento di Elettronica e Telecomunicazioni, Corso Duca degli Abruzzi, 24, 10129 Torino, Italy;2. Politecnico di Torino, Dipartimento Energia, Italy;3. Politecnico di Bari, Dipartimento di Ingegneria Elettrica e dell’Informazione, Italy;1. Automatic Test and Control Institute, School of Information and Electrical Engineering, Harbin Institute of Technology at WeiHai, WeiHai, China;2. Automatic Test and Control Institute, School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin, China;3. Guangxi Key Laboratory of Automatic Detecting Technology and Instruments, School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin, China;1. Instituto de Telecomunicações, DEEC, IST, UL, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal;2. Instituto de Telecomunicações, Universidade de Évora, Rua Romão Ramalho 59, 7000-671 Évora, Portugal |
| Abstract: | The de-noising performance and convergence behavior of the adaptive evolutionary digital filter (EDF) are restricted by the factors of constant evolutionary coefficients and taking the reciprocal of average energy of residual signal as the fitness function. In this paper, an improved adaptive evolutionary digital filter based on the simplex method (EDF-SM) is proposed to overcome the shortcomings of the original EDF. A new evolutionary rule was constructed by introducing the simplex-based mutating method and by then combining this with the original cloning and mating methods. The reciprocal of sample entropy was taken as the fitness function and variable evolutionary coefficients were employed. Numerical examples show that the proposed EDF-SM exhibits a higher convergence rate and a better de-noising behavior than the other EDFs. The effectiveness of the proposed method in discovering fault characteristics and detecting faults of rolling element bearings is supported using an experimental test. |
| Keywords: | Adaptive evolutionary filter Simplex method Fitness function Variable evolutionary coefficients Fault detection |
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