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  • Open Access


    A Noise Reduction Method for Multiple Signals Combining Computed Order Tracking Based on Chirplet Path Pursuit and Distributed Compressed Sensing

    Guangfei Jia*, Fengwei Guo, Zhe Wu, Suxiao Cui, Jiajun Yang

    Structural Durability & Health Monitoring, Vol.17, No.5, pp. 383-405, 2023, DOI:10.32604/sdhm.2023.026885

    Abstract With the development of multi-signal monitoring technology, the research on multiple signal analysis and processing has become a hot subject. Mechanical equipment often works under variable working conditions, and the acquired vibration signals are often non-stationary and nonlinear, which are difficult to be processed by traditional analysis methods. In order to solve the noise reduction problem of multiple signals under variable speed, a COT-DCS method combining the Computed Order Tracking (COT) based on Chirplet Path Pursuit (CPP) and Distributed Compressed Sensing (DCS) is proposed. Firstly, the instantaneous frequency (IF) is extracted by CPP, and the speed is obtained by fitting.… More > Graphic Abstract

    A Noise Reduction Method for Multiple Signals Combining Computed Order Tracking Based on Chirplet Path Pursuit and Distributed Compressed Sensing

  • Open Access


    A New Diagnostic Method Applied to Gearbox Missing Gear Faults ——LOD-ICA

    Lida Liao1, Bo Xiao1,2,*, Kan Huang1,*, Bin Huang1,3, Kang Zhang1

    Energy Engineering, Vol.119, No.3, pp. 1219-1238, 2022, DOI:10.32604/ee.2022.017471

    Abstract With the increasingly stringent requirements for carbon emissions, countries have increased the scale of clean energy use in recent years. As an important new clean energy source, the ratio of wind power in energy utilization has been increasing. The horizontal axis wind turbine is the main form of wind power generation, which is subject to random wind loads during operation and is prone to various failures after a long period of operation, resulting in reduced power generation efficiency or even shutdown. In order to ensure stable external power transmission, it is necessary to perform fault diagnosis for wind turbines. However,… More >

  • Open Access


    Swarm-LSTM: Condition Monitoring of Gearbox Fault Diagnosis Based on Hybrid LSTM Deep Neural Network Optimized by Swarm Intelligence Algorithms

    Gopi Krishna Durbhaka1, Barani Selvaraj1, Mamta Mittal2, Tanzila Saba3,*, Amjad Rehman3, Lalit Mohan Goyal4

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 2041-2059, 2021, DOI:10.32604/cmc.2020.013131

    Abstract Nowadays, renewable energy has been emerging as the major source of energy and is driven by its aggressive expansion and falling costs. Most of the renewable energy sources involve turbines and their operation and maintenance are vital and a difficult task. Condition monitoring and fault diagnosis have seen remarkable and revolutionary up-gradation in approaches, practices and technology during the last decade. Turbines mostly do use a rotating type of machinery and analysis of those signals has been challenging to localize the defect. This paper proposes a new hybrid model wherein multiple swarm intelligence models have been evaluated to optimize the… More >

  • Open Access


    Comparisons of MFDFA, EMD and WT by Neural Network, Mahalanobis Distance and SVM in Fault Diagnosis of Gearboxes

    Jinshan Lina*, Chunhong Doub, Qianqian Wanga

    Sound & Vibration, Vol.52, No.2, pp. 11-15, 2018, DOI:10.32604/sv.2018.03653

    Abstract A method for gearbox fault diagnosis consists of feature extraction and fault identification. Many methods for feature extraction have been devised for exposing nature of vibration data of a defective gearbox. In addition, features extracted from gearbox vibration data are identified by various classifiers. However, existing literatures leave much to be desired in assessing performance of different combinatorial methods for gearbox fault diagnosis. To this end, this paper evaluated performance of several typical combinatorial methods for gearbox fault diagnosis by associating each of multifractal detrended fluctuation analysis (MFDFA), empirical mode decomposition (EMD) and wavelet transform (WT) with each of neural… More >

  • Open Access


    A Simplified Formulation to Estimate Influence of Gearbox Parameters on the Rattle Noise

    Jidong Zhang1,2,*, Wentao Sui2, Jaspreet Dhupia3

    Sound & Vibration, Vol.53, No.2, pp. 38-49, 2019, DOI:10.32604/sv.2019.04362

    Abstract Occurrence of gear rattle in transmission systems can result in severe vibration and noise, which in applications such as automobiles is an important source of user discomfort. As a result , the reduction of the rattling noise has attracted lot of concerns. The rattling noise level is affected by several gearbox parameters, an understanding of which is essential to prevent the expensive design modifications at later stages of product development. To develop such understanding at the gearbox design stage, this paper analytically evaluates the gear parameters’ effect on the root mean square of the wheel gear acceleration under idling condition,… More >

  • Open Access


    Combining Lumped Parameter Bond Graphs with Finite Element Shafts in a Gearbox Model

    J. Choi1, M.D. Bryant2

    CMES-Computer Modeling in Engineering & Sciences, Vol.3, No.4, pp. 431-446, 2002, DOI:10.3970/cmes.2002.003.431

    Abstract This paper presents an updated bond graph model of a gearbox, which now includes bending of shafts. The gearbox system has an input shaft, layshaft, output shaft, spur gears, bearings, and housing. The bond graph model integrates separate sub-models into a composite model. Sub-modules include tooth-to-tooth contact, rotor dynamics of shafts, global dynamics of the gearbox housing structure, and shaft bending modeled by finite element modeling. The tooth-to-tooth model includes tooth bending; shaft torsion; gear inertia; conversion of gear torque into tooth forces; tooth contact mechanics; and multiple tooth contact. To analyze shaft dynamics more precisely, elementary finite element theory… More >

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