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

Jing, Shuangxi; Luo, Zhipeng; Leng, Jinsong; Wang, Zhiyang

doi:10.21595/jve.2019.20098

Cited by 6 publications

(3 citation statements)

References 22 publications

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“…Therefore, we can accurately calculate the center frequency of the main lobe using several spectral lines with large internal power rate spectrum values of the main lobe 19 , 21 – 24 LetGi be the value of the i ’th spectral line of the power spectrum,Gk is the maximum value of the spectral line in the main lobe, and k is the corresponding spectral line number of the point with the maximum amplitude.…”

Section: Double Correction Methods Of Spectrum Signalmentioning

confidence: 99%

Beat frequency extraction method of high speed and high noise Doppler signal based on double correction

Sun

Wang

et al. 2023

Opt. Eng.

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When detecting ultrahigh speed micro targets, because the photon Doppler signal will be seriously interfered with by high-frequency noise, it is difficult to accurately extract the beat frequency information, resulting in serious speed demodulation error. Therefore, we propose a beat frequency extraction method for high-speed and high-noise Doppler signals based on double correction, which can accurately correct the beat frequency signals of high-frequency noise interference. First, the ratio correction method is used for the first spectrum correction to screen out the normalized spectrum of high-frequency noise interference; then, according to the degree of noise interference, the energy barycenter correction method or linear interpolation method is used for the second spectrum correction. Numerical simulation results show that this method can reduce the spectral error by 1.6% to 2.1%. We used this method to process the Doppler signal from the detonation small flyer experiment in Initiating explosive device testing.The results show that it can reduce the beat frequency error by 1.83 times at most under highfrequency noise interfered, equivalent to the instantaneous velocity error of 1955 m/s can be decreased after velocity demodulation. Therefore, the beat frequency extraction method based on double correction has good noise resistance and reliability. We corrected the different regions' frequency spectrums according to the noise interference intensity, which provides an idea for the beat frequency extraction of high-speed and high-noise Doppler signals.

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Section: Double Correction Methods Of Spectrum Signalmentioning

confidence: 99%

Beat frequency extraction method of high speed and high noise Doppler signal based on double correction

Sun

Wang

et al. 2023

Opt. Eng.

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“…Several studies have investigated the non-use of phase signal approaches in TSA techniques. In recent years, the idea of a "tacholess" method has emerged and has been successfully applied to gear systems [34][35][36][37][38][39] and rolling bearings [40][41][42][43][44][45][46]. However, many studies frequently concentrate on reconstructing phase information when rotational speeds remain constant.…”

Section: Introductionmentioning

confidence: 99%

Tacholess Time Synchronous Averaging for Gear Fault Diagnosis in Wind Turbine Gearboxes Using a Single Accelerometer

Nguyen,

Nguyen

et al. 2024

Machines

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Wind power is increasingly seen as a global, sustainable, and eco-friendly energy option. However, one significant obstacle to further wind energy investment is the high failure rate of wind turbines. The gearbox plays a pivotal role in turbine performance. In recent years, there has been a surge in the focus on gearbox fault diagnosis, reflecting its criticality and prevalence in the industry. Time synchronous averaging (TSA) is a primary technique to identify faults in wind turbine gearboxes using mechanical vibration signals. Generally, implementing TSA requires a device that is capable of recording the phase information of a rotary shaft. Nevertheless, there are situations in which the installation of such a device poses difficulties. For instance, gearboxes that are in use cannot be halted to allow for the installation of a device, and sealed gearboxes provide challenges while being inserted into the device. This research presents an innovative technical way to improve the TSA method without requiring a phase signal. The proposed method has the advantage of extracting the shaft rotation angle signal from the measured acceleration signal, even in non-stationary conditions where the rotational speed varies over time. The effectiveness of the proposed method is validated through measured datasets from wind turbine gearboxes with actual faults and a dataset from a gear system with variable rotational speeds.

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“…Wu et al [ 30 ] proposed an improved TLOT method based on nonlinear compensation demodulation transform for the appliance of fault diagnosis of mechanical extreme state monitoring. A TLOT-based method combined with time varying filtering and continuous WT was proposed by Jing [ 31 ], which could be applied under the condition of strong fluctuations in speed with strong noises. Wan et al [ 32 ] proposed a variational modal decomposition filtering- and synchronous extraction transformation-based TLOT method that achieved an improvement in IF estimation accuracy.…”

Section: Introductionmentioning

confidence: 99%

An Adaptive Parameterized Domain Mapping Method and Its Application in Wheel–Rail Coupled Fault Diagnosis for Rail Vehicles

Yang

Yao

et al. 2023

Sensors

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The rapid development of cities in recent years has increased the operational pressure of rail vehicles, and due to the characteristics of rail vehicles, including harsh operating environment, frequent starting and braking, resulting in rails and wheels being prone to rail corrugation, polygons, flat scars and other faults. These faults are coupled in actual operation, leading to the deterioration of the wheel–rail contact relationship and causing harm to driving safety. Hence, the accurate detection of wheel–rail coupled faults will improve the safety of rail vehicles’ operation. The dynamic modeling of rail vehicles is carried out to establish the character models of wheel–rail faults including rail corrugation, polygonization and flat scars to explore the coupling relationship and characteristics under variable speed conditions and to obtain the vertical acceleration of the axle box. An APDM time–frequency analysis method is proposed in this paper based on the PDMF adopting Rényi entropy as the evaluation index and employing a WOA to optimize the parameter set. The number of iterations of the WOA adopted in this paper is decreased by 26% and 23%, respectively, compared with PSO and SSA, which means that the WOA performs at faster convergence speed and with a more accurate Rényi entropy value. Additionally, TFR obtained using APDM realizes the localization and extraction of the coupled fault characteristics under rail vehicles’ variable speed working conditions with higher energy concentration and stronger noise resistance corresponding to prominent ability of fault diagnosis. Finally, the effectiveness of the proposed method is verified using simulation and experimental results that prove the engineering application value of the proposed method.

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

Cited by 6 publications

References 22 publications

Beat frequency extraction method of high speed and high noise Doppler signal based on double correction

Beat frequency extraction method of high speed and high noise Doppler signal based on double correction

Tacholess Time Synchronous Averaging for Gear Fault Diagnosis in Wind Turbine Gearboxes Using a Single Accelerometer

An Adaptive Parameterized Domain Mapping Method and Its Application in Wheel–Rail Coupled Fault Diagnosis for Rail Vehicles

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