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Gear Fault Detection, Identification and Classification Using MLP Neural Network

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Recent Advances in Structural Health Monitoring and Engineering Structures

Part of the book series: Lecture Notes in Mechanical Engineering ((LNME))

Abstract

Gear fault detection, identification and classification are highly complicated tasks, as the faults which affect gearboxes tend to share similar frequency signatures. Therefore, load and speed changes in a rotating machinery inevitably provide inaccurate results. However, identifying the fault remains critical, as each individual gear fault influences overall mechanism operation in different manners. Therefore, defect identification and classification appear as the hardest challenge for a geared systems. An automatic method to detect, identify and classify different gear failures is presented in this paper. The intelligent approach consists of a combination of MODWPT, entropy and MLPNN. MODWPT was developed to decompose the signals with a uniform frequency bandwidth. Entropy is employed to build the feature matrix in the feature extraction phase. Then, MLP offers a very efficient classification tool for features classification stage. Based on data sets taken from a gearbox bench test with a good and five varied gear states under various loads and speeds, experimental results presented the efficiency of our technique.

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Author information

Authors and Affiliations

  1. Department of Mechanical Construction and Production Engineering, Houari Boumediene University of Science and Technology, Bab Ezzouar, Algeria

    Afia Adel

  2. Solid Mechanics and Systems Laboratory (LMSS), Department of Mechanical Engineering, University M’hamed Bougara, Boumerdès, Algeria

    Afia Adel, Ouelmokhtar Hand, Gougam Fawzi, Touzout Walid, Rahmoune Chemseddine & Benazzouz Djamel

Authors
  1. Afia Adel
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  2. Ouelmokhtar Hand
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  3. Gougam Fawzi
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  4. Touzout Walid
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  5. Rahmoune Chemseddine
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  6. Benazzouz Djamel
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Corresponding author

Correspondence to Afia Adel .

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Editors and Affiliations

  1. Department of Mechanical Engineering, Sardar Vallabhbhai National Institute of, Surat, India

    Ravipudi Venkata Rao

  2. Soete Laboratory, Faculty of Engineering and Architecture, Ghent University, Ghent, Belgium

    Samir Khatir

  3. Faculty of Civil Engineering, Ho Chi Minh City Open University, Ho Chi Minh City, Vietnam

    Thanh Cuong-Le

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Adel, A., Hand, O., Fawzi, G., Walid, T., Chemseddine, R., Djamel, B. (2023). Gear Fault Detection, Identification and Classification Using MLP Neural Network. In: Rao, R.V., Khatir, S., Cuong-Le, T. (eds) Recent Advances in Structural Health Monitoring and Engineering Structures. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-19-4835-0_18

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  • DOI: https://doi.org/10.1007/978-981-19-4835-0_18

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-4834-3

  • Online ISBN: 978-981-19-4835-0

  • eBook Packages: EngineeringEngineering (R0)

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