Yongzhi Qu

A Fiber Bragg Grating Sensing Based Triaxial Vibration Sensor.

A fiber Bragg grating (FBG) sensing based triaxial vibration sensor has been presented in this paper. The optical fiber is directly employed as elastomer, and the triaxial vibration of a measured body can be obtained by two pairs of FBGs. A model of a triaxial vibration sensor as well as decoupling principles of triaxial vibration and experimental analyses are proposed. Experimental results show that: sensitivities of 86.9 pm/g, 971.8 pm/g and 154.7 pm/g for each orthogonal sensitive direction with linearity are separately 3.64%, 1.50% and 3.01%. The flat frequency ranges reside in 20–200 Hz, 3–20 Hz and 4–50 Hz, respectively; in addition, the resonant frequencies are separately 700 Hz, 40 Hz and 110 Hz in the x/y/z direction. When the sensor is excited in a single direction vibration, the outputs of sensor in the other two directions are consistent with the outputs in the non-working state. Therefore, it is effectively demonstrated that it can be used for three-dimensional vibration measurement.

A New Signal Processing and Feature Extraction Approach for Bearing Fault Diagnosis using AE Sensors

Abstract In this paper, a new signal processing and feature extraction approach for bearing fault diagnosis using acoustic emission (AE) sensors is presented. The presented approach uses time-frequency manifold analysis to extract time-frequency manifold features from AE signals. It reconstructs a manifold by embedding AE signals into a high-dimensional phase space. The tangent direction of the neighborhood for each point is then used to approximate its local geometry. The variation of the manifolds representing different condition states of the bearing can be revealed by performing multiway principal component analysis. AE signals acquired from a bearing test rig are used to validate the presented approach. The test results have shown that the presented approach can interpret different bearing conditions and is effective for bearing fault diagnosis.

A novel fault diagnostic technique for gearboxes under speed fluctuations without angular speed measurement

In practice, fluctuations around the nominal operating speed often result in vibration spectra of gearboxes to appear smeared. Order tracking technique can be employed to remove the spectral smearing of such signals. However, this technique requires simultaneous measurements of vibration and rotational speed, which is often unavailable in industrial settings. Thus, a new diagnostic algorithm without a tachometer is proposed in this paper for monitoring of gear faults. This new tacho-less method uses fast dynamic time warping (FDTW) algorithm to remove the spectral smearing, is based on the introduction of an estimated reference signal having the same frequency as the nominal shaft rotational frequency. The effectiveness of this method is validated using both simulated signals from a fixed axis gear pair and experimental signals from a planetary gearbox test rig. The results demonstrate the ability of the proposed approach in extracting fault information from gearbox vibration signals under fluctuating speed conditions.

Vibration Based Diagnosis for Planetary Gearboxes Using an Analytical Model

The application of conventional vibration based diagnostic techniques to planetary gearboxes is a challenge because of the complexity of frequency components in the measured spectrum, which is the result of relative motions between the rotary planets and the fixed accelerometer. In practice, since the fault signatures are usually contaminated by noises and vibrations from other mechanical components of gearboxes, the diagnostic efficacy may further deteriorate. Thus, it is essential to develop a novel vibration based scheme to diagnose gear failures for planetary gearboxes. Following a brief literature review, the paper begins with the introduction of an analytical model of planetary gear-sets developed by the authors in previous works, which can predict the distinct behaviors of fault introduced sidebands. This analytical model is easy to implement because the only prerequisite information is the basic geometry of the planetary gear-set. Afterwards, an automated diagnostic scheme is proposed to cope with the challenges associated with the characteristic configuration of planetary gearboxes. The proposed vibration based scheme integrates the analytical model, a denoising algorithm, and frequency domain indicators into one synergistic system for the detection and identification of damaged gear teeth in planetary gearboxes. Its performance is validated with the dynamic simulations and the experimental data from a planetary gearbox test rig.

Experimental study of dynamic strain for gear tooth using fiber Bragg gratings and piezoelectric strain sensors

It has always been a critical task to understand gear dynamics for gear design and condition monitoring. Many gear models have been proposed to simulate gear meshing dynamics. However, most of the theoretical models are based on simplified gear structure and may contain approximation errors. Direct measuring of gear strain is important for gear design validation, load analysis, reliability assessment, gear condition monitoring, etc. Most of the existing studies of tooth strain measurements are performed under static load condition. In this paper, we investigate new measuring techniques using fiber Bragg grating sensor and piezoelectric strain for gear dynamic strain measurement. We conduct gear dynamic strain measurement under both normal and pitted conditions to evaluate the strain transition process and pitting effect. The experiments are performed on an industrial gearbox with relatively small module gears. Multiple combinations of speed and load conditions are tested and the results are discussed and analyzed. We analyze multiple factors that affect the tooth root stress, including speed, load, extended tooth meshing, etc. It is found that under low operation speed range, the tooth root strain is mainly determined by the torque, while in the medium to high speed range, the tooth root strain is jointly affected by speed and torque. Extended tooth contact is shown in the measurement results with strong evidence. It conforms to earlier founding that the transmission error and dynamic load factor are overestimated for spur gear under heavy load. We also evaluate the change in dynamic strain caused by pitted tooth surface. It is shown that pitting faults lead to decreased bending strain on the tooth, especially in single-tooth contact zone, which represents a loss in torque and possibly reduced mesh stiffness. Numerical simulations are also provided to make comparisons and help to interpret the experimental results.

An Improved Feature Extraction Method for Rolling Bearing Fault Diagnosis Based on MEMD and PE

Abstract The health condition of rolling bearing can directly influence to the efficiency and lifecycle of rotating machinery, thus monitoring and diagnosing the faults of rolling bearing is of great importance. Unfortunately, vibration signals of rolling bearing are usually overwhelmed by external noise, so the fault frequencies of rolling bearing cannot be readily obtained. In this paper, an improved feature extraction method called IMFs_PE, which combines the multivariate empirical mode decomposition with the permutation entropy, is proposed to extract fault frequencies from the noisy bearing vibration signals. First, the raw bearing vibration signals are filtered by an optimal band-pass filter determined by SK to remove the irrelative noise which is not in the same frequency band of fault frequencies. Then the filtered signals are processed by the IMFs_PE to get rid of the relative noise which is in the same frequency band of fault frequencies. Finally, a frequency domain condition indicator FFR(Fault Frequency Ratio), which measures the magnitude of fault frequencies in frequency domain, is calculated to compare the effectiveness of the feature extraction methods. The feature extraction method proposed in this paper has advantages of removing both irrelative noise and relative noise over other feature extraction methods. The effectiveness of the proposed method is validated by simulated and experimental bearing signals. And the results are shown that the proposed method outperforms other state of the art algorithms with regards to fault feature extraction of rolling bearing.

A novel synergistic diagnostic scheme for planetary gearboxes based on an analytical vibration model of planetary gear-sets

The condition monitoring system of gearboxes usually employs accelerometers fixed on the gear housing to diagnose the gear damage. Such diagnostic system is essential in scheduling the maintenance of drive-trains. However, the successful application of vibration based diagnostic techniques for planetary gearboxes is still challenging because of the complexities of the sideband behaviors in the measured vibration signal, which is a result of the revolution of the planets around the sun gear. Moreover, the performance of diagnostic techniques may further deteriorate since the measured vibration signals are often contaminated by the noise. Therefore, it is essential to develop a diagnostic scheme for extracting the fault signatures in planetary gear-sets. This paper begins with the summary of an analytical model of the planetary gear-sets developed by the authors that describes the characteristic behaviors of the fault introduced sidebands of the vibration spectrum picked by the fixed vibration sensor. This analytical model, which predicts the frequency components of planetary gear-sets, is easy to implement because the only prerequisite information is the basic geometry of the planetary gearbox. Afterwards, a novel vibration based diagnostic scheme for planetary gear-sets is developed. Its performance is then validated using simulated vibration signals generated from a dynamic model of the planetary gearbox. The proposed diagnostic scheme integrates the analytical vibration model, a de-noising algorithm and a frequency-domain indicator into one synergistic system for the early detection of damaged gear teeth in planetary gear-sets.