Gearbox Vibration Signal Amplitude and Frequency Modulation

Abstract-Condition monitoring (CM) of gearbox is a crucial activity due to its importance in power transmission for many industrial applications. Monitoring temperature is an effective mean to collect useful information about the healthy conditions of the gearbox. This study investigates the use of a novel wireless temperature node to monitor and diagnose different faults on a gearbox transmission system under different conditions. The wireless temperature node was fabricated with a novel feature that it is supplied by a thermoelectric generator module mounted on the gearbox house to be monitored so that the measurement system avoids the shortage of using a wired power sources or the requirement for recharging or changing batteries. Moreover, the temperatures from lubricating oils and housing are modelled empirically to implement a model based detection. The results show that this monitoring approach allows a number of common faults: tooth breakage, oil shortage, and shaft misalignment to be separated under different loads, which demonstrates the outstanding performance of the proposed system and thus suitable for online and automated condition monitoring.

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“…The design was built by using a commercially available TE module CP85438 [24]. The TEG is sandwiched between two pieces of aluminium.…”

Section: B Thermal Energy Harvesting Generator Designmentioning

confidence: 99%

Monitoring gearbox using a wireless temperature node powered by thermal energy harvesting module

Elforjani

Brethee

et al. 2017

2017 23rd International Conference on Automation and Computing (ICAC)

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“…Though the time-frequency resolution is less severely affected for this technology, it is widely used in the mechanical fault diagnosis [6,14].…”

Section: Optimum Imfs Selection Basedmentioning

confidence: 99%

“…Though the WVD usually suffers from the disturbance of cross terms, the pseudo Wigner-Ville distribution (PWVD) offers an alternative selection. A plenty of examples show that the PWVD has good time-frequency centralization and is widely used in mechanical fault diagnosis [6].…”

Section: Introductionmentioning

confidence: 99%

Optimum IMFs Selection Based Envelope Analysis of Bearing Fault Diagnosis in Plunger Pump

Wang

Gong

et al. 2016

Shock and Vibration

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As the plunger pump always works in a complicated environment and the hydraulic cycle has an intrinsic fluid-structure interaction character, the fault information is submerged in the noise and the disturbance impact signals. For the fault diagnosis of the bearings in plunger pump, an optimum intrinsic mode functions (IMFs) selection based envelope analysis was proposed. Firstly, the WignerVille distribution was calculated for the acquired vibration signals, and the resonance frequency brought on by fault was obtained. Secondly, the empirical mode decomposition (EMD) was employed for the vibration signal, and the optimum IMFs and the filter bandwidth were selected according to the Wigner-Ville distribution. Finally, the envelope analysis was utilized for the selected IMFs filtered by the band pass filter, and the fault type was recognized by compared with the bearing character frequencies. For the two modes, inner race fault and compound fault in the inner race and roller of rolling element bearing in plunger pump, the experiments show that a promising result is achieved.

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“…2, 3 (Zimroz et al 2011;Chaari et al 2012). Main spectral components, related to meshing phenomena or shaft rotation are frequency modulated with respect to engine output shaft speed variation and amplitude modulated according to engine torque variation.…”

Section: Real Data Descriptionmentioning

confidence: 99%

Periodic Autoregressive Modeling of Vibration Time Series From Planetary Gearbox Used in Bucket Wheel Excavator

Wyłomańska

Obuchowski

Zimroz

et al. 2014

Lecture Notes in Mechanical Engineering

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Vibration signals acquired from machines operating under non-stationary operations are difficult to process due to their time varying spectral content, statistical properties, signal to noise ratio etc. In case of damaged machine vibration analysis, the classical damage detection approach might be defined as informative and non-informative contents separation. It can be done in many ways, including model based approaches. One of the most known solutions for constant load/speed operations exploits autoregressive (AR) modeling of the deterministic high energy components that often mask the weak impulsive and stochastic part of the signal. After establishing the model, the residual signal is extracted and further analyzed. In the case presented here, AR modeling is considered inappropriate because of the variation of speed/load conditions. To illustrate importance of the problem and novelty of our approach, a planetary gearbox vibration will be analyzed. The gearbox operates in a bucket wheel excavator (heavy duty mining machine) subjected to cyclic load/speed variation due to the digging/excavating process. Due to periodicity of the excavation process, it seems appropriate to assume a periodic autoregressive (PAR) model for the deterministic high energy components. In the chapter several topics will be discussed: real data inspired motivation for PAR modeling, estimation A. Wyłomańska (B)

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Gearbox Vibration Signal Amplitude and Frequency Modulation

Cited by 79 publications

References 14 publications

Monitoring gearbox using a wireless temperature node powered by thermal energy harvesting module

Monitoring gearbox using a wireless temperature node powered by thermal energy harvesting module

Optimum IMFs Selection Based Envelope Analysis of Bearing Fault Diagnosis in Plunger Pump

Periodic Autoregressive Modeling of Vibration Time Series From Planetary Gearbox Used in Bucket Wheel Excavator

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