Locating Faulty Planet Gears Using External Vibration Measurements

2019 ◽  
Vol 9 (1) ◽  
pp. 14-17
Author(s):  
D Peng ◽  
W A Smith ◽  
R B Randall
Keyword(s):  
Vibration Signal ◽  
Processing Technique ◽  
Operating Conditions ◽  
Internal Vibration ◽  
Signal Processing Technique ◽  
Vibration Measurements ◽  
External Vibration ◽  
Gear Mesh ◽  
Mesh Phasing ◽  
Planet Carrier

In this study, a mesh phasing-based approach is developed to locate the positions of faulty planet gears using external vibration measurements. Previous studies have illustrated how this can be achieved using internal vibration measurements recorded from a sensor placed on the planet carrier. It was shown in these studies that the timing of identifiable fault symptoms in the vibration signal relative to the phase of the gear-mesh component depends on which of the planet gears carries a fault. A signal processing technique is then developed to locate the position of a spalled gear using internal vibration measurements. However, internally mounted sensors are not commonly used in planetary gearboxes and it is much more convenient to mount sensors externally, for example on the gearbox casing. Therefore, this study extends the concept of using mesh phasing relationships to locate faulty planet gears, this time using external vibration measurements. The updated procedure is validated using experimental data collected from a test-rig running under a range of operating conditions. The results show that the updated procedure is able to identify the locations of faulty planet gears so long as an absolute phase reference (for example from a tachometer) of the planet carrier is available.

Feature Extraction Based on Teager-Kaiser Energy Operation and Envelope Spectra for Fault Detection of a Reciprocating Compressor

2020 ◽  
Author(s):  
Chin-Che Hou ◽  
Min-Chun Pan
Keyword(s):  
Fault Detection ◽  
Energy Operator ◽  
Vibration Signal ◽  
Experiment Design ◽  
Processing Technique ◽  
Operating Conditions ◽  
Reciprocating Compressor ◽  
Signal Processing Technique ◽  
Two Phase ◽  
Synthetic Signal

Abstract In this paper, signal analysis techniques based on Teager-Kaiser energy operation and envelope spectra for fault detection of the discharge valve of a reciprocating compressor is proposed. The method can accurately identify the existing fault of vibration signal features that it simulated by the synthetic signals. A two-phase study was designed to explore the signals simulation and the experimental validation. Signals simulation, which is based on the operation of a reciprocating compressor, and experiment design, which uses three conditions. The first stage is to simulate the operation of the reciprocating compressor, which is to simulate a synthetic signal for the cycle and impact. The synthetic signal is composed of a noise, square wave, and pulse wave. In this study, the synthetic signal is signal-processed by the Teager-Kaiser energy operator and the envelope spectrum that they can effectively extract feature signal and the noise almost is eliminated. The second stage is applied to the signal processing technique proposed in the first stage. Experimental verification of experiment design by the different operating conditions of reciprocating compressor valves. Through the above analysis technology, it is proved that the synthetic signal can be eliminated the background noise to obtain the feature signal. The feasibility of the proposed approach is verified by simulation results, the experiment is to validate with the measurement signals from a six-cylinder reciprocating compressor under different valve conditions. Simulations and experimental results support the proposed technology positively.

An Analytical and Numerical Investigation of Modulation Sidebands of a Planetary Gear Under Fluctuated External Torque

2018 ◽  
Author(s):  
Yunbo Yuan ◽  
Wei Liu ◽  
Yahui Chen ◽  
Donghua Wang
Keyword(s):  
Planetary Gear ◽  
Transmission Error ◽  
Operating Conditions ◽  
Radial Acceleration ◽  
External Torque ◽  
Gear Mesh ◽  
Planetary Gear Sets ◽  
Static Transmission Error ◽  
Frequency Modulations ◽  
Mesh Phasing

Certain operating conditions such as fluctuation of the external torque to planetary gear sets can cause additional sidebands. In this paper, a mathematical model is proposed to investigate the modulation mechanisms due to a fluctuated external torque (FET), and the combined influence of such an external torque and manufacturing errors (ME) on modulation sidebands. Gear mesh interface excitations, namely gear static transmission error excitations and time-varying gear mesh stiffness, are defined in Fourier series forms. Amplitude and frequency modulations are demonstrated separately. The predicted dynamic gear mesh force spectra and radial acceleration spectra at a fixed position on ring gear are both shown to exhibit well-defined modulation sidebands. Comparing with sidebands caused by ME, more complex sidebands appear when taking both FET and ME into account. An obvious intermodulation is found around the fundamental gear mesh frequency between the FET and ME in the form of frequency modulations, however, no intermodulation in the form of amplitude modulations. Additionally, the results indicate that some of the sidebands are cancelled out in radial acceleration spectra mainly due to the effect of planet mesh phasing, especially when only amplitude modulations are present.

Evaluation of acoustic emission burst detection methods in a gearbox under different operating conditions

2018 ◽  
Vol 25 (4) ◽  
pp. 895-906 ◽  
Author(s):  
F. Leaman ◽  
C. Niedringhaus ◽  
S. Hinderer ◽  
K. Nienhaus
Keyword(s):  
Acoustic Emission ◽  
Processing Technique ◽  
Operating Conditions ◽  
Detection Methods ◽  
Threshold Values ◽  
Burst Detection ◽  
Signal Processing Technique ◽  
Planetary Gearbox ◽  
Machine Condition Monitoring ◽  
Definition Of

In account of its abilities to follow the damage progression, also at early stages, the acoustic emission (AE) analysis has become an attractive technique for machine condition monitoring. An AE analysis involves the detection of transients within the signals, which are called AE bursts. Traditional methods for AE burst detection are based on the definition of threshold values. When the machine under analysis works under variable operating conditions, threshold-based methods could lead to poor results due to the influence of these conditions on the AE generation. The present work compares the ability of three AE burst detection methods in a planetary gearbox working under different rotational speeds and loads. The results showed that performance could be significantly improved by using factors of the root mean square value as threshold values instead of fixed values. Among the evaluated methods, the method that includes demodulation and differentiation as a signal processing technique had the best performance overall.

scholarly journals Vibration Signal Analysis of Journal Bearing Supported Rotor System by Cyclostationarity

2014 ◽  
Vol 2014 ◽  
pp. 1-16 ◽  
Author(s):  
Chang Peng ◽  
Lin Bo
Keyword(s):  
Journal Bearing ◽  
Wigner Distribution ◽  
Mechanical Vibration ◽  
Vibration Signal ◽  
Processing Technique ◽  
Rotor System ◽  
Signal Processing Technique ◽  
Spectral Correlation ◽  
Useful Signal ◽  
Vibration Signal Analysis

Cyclostationarity has been widely used as a useful signal processing technique to extract the hidden periodicity of the energy flow of the mechanical vibration signature. However, the conventional cyclostationarity is restricted to analyzing the real-valued signal, which is incapable of processing the constructed complex-valued signal obtained from the journal bearing supported rotor system operating with oil film instability. In this work, the directional cyclostationary parameters, such as directional cyclic mean, directional cyclic autocorrelation, and directional spectral correlation density, are defined based on the principle of directional Wigner distribution. Practical experiment has demonstrated the effectiveness and superiority of the proposed method in the investigation of the instantaneous planar motion of the journal bearing supported rotor system.

Diagnostics of Fatigue Crack in the Shaft Using Spectral Kurtosis

2019 ◽  
Author(s):  
Sagi Rathna Prasad ◽  
A. S. Sekhar
Keyword(s):  
Fatigue Crack ◽  
Crack Detection ◽  
Fatigue Cracks ◽  
Processing Technique ◽  
Rotating Machinery ◽  
Operating Conditions ◽  
Laser Vibrometer ◽  
Signal Processing Technique ◽  
Spectral Kurtosis ◽  
Vibration Data

Abstract Rotating machinery components like shafts subjected to continuous fluctuating loads are prone to fatigue cracks. Fatigue cracks are severe threat to the integrity of rotating machinery. Therefore it is indispensable for early diagnostics of fatigue cracks in shaft to avoid catastrophic failures. From the literature, it is evident that the spectral kurtosis (SK) and fast kurtogram were used to detect the faults in bearings and gears. The present study illustrates the use of SK and fast kurtogram for early fatigue crack detection in the shaft using vibration data. To perform this study, experiments are conducted on a rotor test rig which is designed and developed according to the function specification proposed by ASTM E468-11 standard. Fatigue crack is developed, on three shaft specimens, each seeded with the same circumferential V-Notch configuration, by continuous application of stochastic loads on the shaft using electrodynamic shaker in addition to the unbalance forces that arise in normal operating conditions. Vibration data is acquired from various locations of the rotor, using different sensors like miniature accelerometers, laser vibrometer and wireless telemetry strain gauge, till the shaft specimen develops fatigue crack. The analysis results show that the combination of SK and fast kurtogram is an effective signal processing technique for detecting the fatigue crack in the shaft.

Fault Detection and Diagnosis in Gears Using Wavelet Analysis Techniques and Comparison on their Diagnostic Capability

2015 ◽  
Vol 789-790 ◽  
pp. 587-591
Author(s):  
M. Lokesha ◽  
M.C. Majumder ◽  
K.P. Ramachandran
Keyword(s):  
Signal Processing ◽  
Wavelet Analysis ◽  
Condition Monitoring ◽  
Experimental Studies ◽  
Vibration Signal ◽  
Processing Technique ◽  
Fault Detection And Diagnosis ◽  
Signal Processing Technique ◽  
Base Function ◽  
Fault Characterization

The concept of vibration based condition monitoring technology has been developing at a rapid stage in the recent years suiting to the maintenance of sophisticated and complicated machines. Nowadays, wavelet analysis based signal processing technique is applied as effective tool for condition monitoring. The experimental studies were conducted on the gear testing apparatus to obtain the vibration signal from a healthy gear and an induced faulty gear. In this paper, two different techniques using Laplace wavelet as base function are used to characterize the fault in the gear signals, specifically wavelet enveloped power spectrum and wavelet kurtosis. The wavelet parameters are optimized using genetic algorithm to select most fault related features. A comparative study detailing features of fault characterization is also given in order to understand the effectiveness of both the wavelet based signal processing methods and their fault diagnosis capability.

scholarly journals Experimental investigation into techniques to predict leak shapes in water distribution systems using vibration measurements

2018 ◽  
Vol 20 (4) ◽  
pp. 815-828 ◽  
Author(s):  
Joseph D. Butterfield ◽  
Gregory Meyers ◽  
Viviana Meruane ◽  
Richard P. Collins ◽  
Stephen B. M. Beck
Keyword(s):  
Distribution Systems ◽  
Water Distribution ◽  
Vibration Signal ◽  
Processing Technique ◽  
Prediction Algorithm ◽  
Signal Processing Technique ◽  
Shape Prediction ◽  
Leak Location ◽  
Signal Features ◽  
Water Companies

Abstract Water loss from leaking pipes represents a substantial loss of revenue as well as environmental and public health concerns. Leak location is normally identified by placing sensors either side of the leak and recording and analysing the leak noise. The leak noise contains information about the leak's characteristics, including its shape. Whilst a tool which non-invasively provides information about a leak's shape from the leak noise would be useful for water industry practitioners, no tool currently exists. This study evaluates the effect of various leak shapes on the vibration signal and presents a unique methodology for predicting the leak shape from the vibration signal. An innovative signal processing technique which utilises the machine learning method random forest classifiers is used in combination with a number of signal features in order to develop a leak shape prediction algorithm. The results demonstrate a robust methodology for predicting leak shape at several leak flow rates within several backfill types, providing a useful tool for water companies to assess leak repair based on leak shape.

Dynamic analysis of a helical gear reduction by experimental and numerical methods

2020 ◽  
Vol 68 (1) ◽  
pp. 48-58
Author(s):  
Chao Liu ◽  
Zongde Fang ◽  
Fang Guo ◽  
Long Xiang ◽  
Yabin Guan ◽  
...  
Keyword(s):  
Numerical Methods ◽  
Dynamic Analysis ◽  
Dynamic Behavior ◽  
Fourth Order ◽  
Numerical Models ◽  
Helical Gear ◽  
Operating Conditions ◽  
Dynamic Responses ◽  
Lumped Mass ◽  
Gear Mesh

Presented in this study is investigation of dynamic behavior of a helical gear reduction by experimental and numerical methods. A closed-loop test rig is designed to measure vibrations of the example system, and the basic principle as well as relevant signal processing method is introduced. A hybrid user-defined element model is established to predict relative vibration acceleration at the gear mesh in a direction normal to contact surfaces. The other two numerical models are also constructed by lumped mass method and contact FEM to compare with the previous model in terms of dynamic responses of the system. First, the experiment data demonstrate that the loaded transmission error calculated by LTCA method is generally acceptable and that the assumption ignoring the tooth backlash is valid under the conditions of large loads. Second, under the common operating conditions, the system vibrations obtained by the experimental and numerical methods primarily occur at the first fourth-order meshing frequencies and that the maximum vibration amplitude, for each method, appears on the fourth-order meshing frequency. Moreover, root-mean-square (RMS) value of the acceleration increases with the increasing loads. Finally, according to the comparison of the simulation results, the variation tendencies of the RMS value along with input rotational speed agree well and that the frequencies where the resonances occur keep coincident generally. With summaries of merit and demerit, application of each numerical method is suggested for dynamic analysis of cylindrical gear system, which aids designers for desirable dynamic behavior of the system and better solutions to engineering problems.

scholarly journals A Remote Sensor System Based on TDLAS Technique for Ammonia Leakage Monitoring

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2448
Author(s):  
Hongbin Lu ◽  
Chuantao Zheng ◽  
Lei Zhang ◽  
Zhiwei Liu ◽  
Fang Song ◽  
...  
Keyword(s):  
Signal Processing ◽  
Limit Of Detection ◽  
Processing Technique ◽  
Tunable Diode Laser ◽  
Sensor System ◽  
Signal Processing Technique ◽  
Suppression Effect ◽  
Output Wavelength ◽  
Deviation Analysis ◽  
Remote Sensor

The development of an efficient, portable, real-time, and high-precision ammonia (NH3) remote sensor system is of great significance for environmental protection and citizens’ health. We developed a NH3 remote sensor system based on tunable diode laser absorption spectroscopy (TDLAS) technique to measure the NH3 leakage. In order to eliminate the interference of water vapor on NH3 detection, the wavelength-locked wavelength modulation spectroscopy technique was adopted to stabilize the output wavelength of the laser at 6612.7 cm−1, which significantly increased the sampling frequency of the sensor system. To solve the problem in that the light intensity received by the detector keeps changing, the 2f/1f signal processing technique was adopted. The practical application results proved that the 2f/1f signal processing technique had a satisfactory suppression effect on the signal fluctuation caused by distance changing. Using Allan deviation analysis, we determined the stability and limit of detection (LoD). The system could reach a LoD of 16.6 ppm·m at an average time of 2.8 s, and a LoD of 0.5 ppm·m at an optimum averaging time of 778.4 s. Finally, the measurement result of simulated ammonia leakage verified that the ammonia remote sensor system could meet the need for ammonia leakage detection in the industrial production process.

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