Gear Fault Diagnosis in Variable Speed Condition Based on Multiscale Chirplet Path Pursuit and Linear Canonical Transform

Xu, Shuiqing; Zhang, Ke; Chai, Yi; He, Yigang; Feng, Li

doi:10.1155/2018/3904598

Cited by 10 publications

(5 citation statements)

References 34 publications

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“…Similarly, a local mean decomposition technique was used for a low-speed helical gearbox resulting an instantaneous time-frequency spectrum for early detection of a local gear tooth fault [159]. A method based on multiscale chirplet path pursuit [93] and linear canonical transform was applied to diagnose gear faults in variable speed conditions [160]. For weak ridges in a time-frequency distribution, a dual-path optimization for ridge estimation was performed for the extracting gear fault, from vibration signals of a wind turbine planetary gearbox [161].…”

Section: Other Signal-processing Techniquesmentioning

confidence: 99%

A Review on Vibration-Based Fault Diagnosis Techniques for Wind Turbine Gearboxes Operating Under Nonstationary Conditions

Sharma

2021

J. Inst. Eng. India Ser. C

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Numerous studies on vibration-based techniques for fault diagnosis of wind turbine gearboxes operating under nonstationary conditions have been reported. In spite, a review on vibration-based condition monitoring and fault diagnosis techniques for gearboxes of wind turbines operating under nonstationary conditions is unavailable. Thus, the objective of this review is to discuss filtering, decomposition, entropy, and cyclostationary analysis techniques, as well as summarizing the remaining issues. This review will discuss various vibration-based diagnostic approaches developed for wind turbine gearboxes under nonstationary conditions, including both simulation and experimental approaches. Studies on dynamic models of gear systems and advanced signal-processing techniques developed for nonstationary conditions are reviewed. Additionally, the importance of multi-sensor and cointegration based approaches is discussed, and intelligent classification methods that have been used to distinguish healthy and faulty gear systems are also reviewed. Finally, the remaining research challenges are outlined.

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Section: Other Signal-processing Techniquesmentioning

confidence: 99%

A Review on Vibration-Based Fault Diagnosis Techniques for Wind Turbine Gearboxes Operating Under Nonstationary Conditions

Sharma

2021

J. Inst. Eng. India Ser. C

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“…The sampling frequency is 5120 Hz, and the acquisition time is 15 s. Characteristic orders are listed in Table 2, where , , denote the rotating order of motor, sungear, planet carrier, respectively, and denote the meshing order of planetary gearbox and fixed-shaft gearbox, respectively. The gear fault characteristic order is (1 ), and its corresponding meshing order is (36 ). The pulse signal of the motor shaft is measured by tachometer as shown in Fig.…”

Section: Application To the Gear Fault Detectionmentioning

confidence: 99%

“…Working under speed fluctuation, rotating machines are usually easier to reflect the inherent characteristics and fault characteristics of the system [1]. When the broken tooth fault of the gear meshes with other gear, the response exhibits impact characteristics [2].…”

Section: Introductionmentioning

confidence: 99%

Tacholess order tracking method for gearbox based on time-varying filter and energy centrobaric correction method

Jing¹,

Luo²,

Leng³

et al. 2019

J. vibroeng.

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Under the premise that the instantaneous speed can be accurately measured or precise estimated, order tracking is considered to be a classical and effective technique for non-stationary vibration analysis of rotating machinery. The meshing frequency components of the vibration signal measured from complex gearbox system interfere with each other mutually. The energy centrobaric correction method exhibits exact instantaneous frequency estimation (IFE) ability under the interference, but is susceptible to strong noise. Combining with time-varying filter and energy centrobaric correction method, a tacholess order tracking technique for gear fault diagnosis under the rotating frequency multi-linear fluctuation is proposed. The time-varying filter is designed to filter the strong noise signal, and then IFE could be accurately calculated from the filtered signal by energy centrobaric correction method. The instantaneous phase of reference shaft based on the Vold-Kalman filter (VKF) is used for angular resampling of the original vibration signal. The results show that the shaft rotating speed could be accurately identified from extracted gear meshing components. The order spectrum obtained by the proposed method with tacholess is substantially the same as the order spectrum obtained by a tachometer. Simulation analysis and experimental results verify the advantages of proposed tacholess order tracking technology for monitoring and fault diagnosis of gearbox vibration under the condition of strong noise and large speed variation.

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“…Pan et al [22] proposed an acoustic fault detection method, which was addressed for the gearbox based on the improved frequency-domain blind deconvolution flow. The signal-based approaches generally extract the major features of the output signals for fault diagnosis, but they pay less attention to system inputs [45].…”

Section: Literature Reviewmentioning

confidence: 99%

Interface Data Modeling to Detect and Diagnose Intersystem Faults for Designing and Integrating System of Systems

Seo

Park

2018

Complexity

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In system of systems engineering, system integrators are in charge of compatible and reliable interfaces between subsystems. This study explains a systematic solution to identify and diagnose interface faults during designing and integrating systems of systems. Because the systems targeted in this study are real underwater vessels, we first have anatomized 188 interface data transferred between 22 subsystems of them. Based on this, two interface data models are proposed, which include data sets regarding messages and inner fields and transition and decision functions for them. Specifically, a structure model at the message level evaluates how inner fields belong to a message, and a logic model at the field level assesses how each field is interpreted and if the interpreted value is understandable. The software that supports the modeling is implemented using the following concepts: (1) a model-view-viewmodel pattern for overall software design and (2) a computer network for representing sequential properties of field interpretations. The proposed modeling and software facilitate diagnostic decisions by checking the consistency between interface protocols and obtained real data. As a practical use, the proposed work was applied to an underwater shipbuilding project. Within 10 interfaces, 14 fault cases were identified and diagnosed. They were gradually resolved during the system design and integration phases, which formed the basis of successful submarine construction.

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Gear Fault Diagnosis in Variable Speed Condition Based on Multiscale Chirplet Path Pursuit and Linear Canonical Transform

Cited by 10 publications

References 34 publications

A Review on Vibration-Based Fault Diagnosis Techniques for Wind Turbine Gearboxes Operating Under Nonstationary Conditions

A Review on Vibration-Based Fault Diagnosis Techniques for Wind Turbine Gearboxes Operating Under Nonstationary Conditions

Tacholess order tracking method for gearbox based on time-varying filter and energy centrobaric correction method

Interface Data Modeling to Detect and Diagnose Intersystem Faults for Designing and Integrating System of Systems

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