Tacholess Envelope Order Analysis and Its Application to Fault Detection of Rolling Element Bearings with Varying Speeds

Abstract

Vibration analysis is an effective tool for the condition monitoring and fault diagnosis of rolling element bearings. Conventional diagnostic methods are based on the stationary assumption, thus they are not applicable to the diagnosis of bearings working under varying speed. This constraint limits the bearing diagnosis to the industrial application significantly. In order to extend the conventional diagnostic methods to speed variation cases, a tacholess envelope order analysis technique is proposed in this paper. In the proposed technique, a tacholess order tracking (TLOT) method is first introduced to extract the tachometer information from the vibration signal itself. On this basis, an envelope order spectrum (EOS) is utilized to recover the bearing characteristic frequencies in the order domain. By combining the advantages of TLOT and EOS, the proposed technique is capable of detecting bearing faults under varying speeds, even without the use of a tachometer. The effectiveness of the proposed method is demonstrated by both simulated signals and real vibration signals collected from locomotive roller bearings with faults on inner race, outer race and rollers, respectively. Analyzed results show that the proposed method could identify different bearing faults effectively and accurately under speed varying conditions.

Incipient Fault Feature Extraction of Rolling Bearings Using Autocorrelation Function Impulse Harmonic to Noise Ratio Index Based SVD and Teager Energy Operator

“…When a defect occurs on a rolling bearing surface, the impulses are created in vibration signals [5,6]. As a result, the detection of faults in rolling element bearings is mainly achieved by identifying the frequency of the impulses from the signals [7,8]. For complicated mechanical systems, the rolling bearing often works in complicated environments, and the vibration signals are easily contaminated by environmental noise and other working parts such as the gearbox (misalignment, unbalance, crack on the rotating shaft, looseness, and distortions).…”

A new fault feature for rolling bearing fault diagnosis under varying speed conditions

“…However, in practice, it is much more complex, almost no machine can work under stationary condition. 4,6 Under varying operation conditions, the vibration signals collected from rolling bearing systems usually carry heavy background noise and the fault characteristic frequency is not only modulated as a series of harmonics but also is smeared on the frequency spectrum. 7,8 Therefore, existing techniques based on the assumption of working in stationary or approximate stationary condition such as FFT cannot work well in extracting the overwhelmed remarkable information for fault diagnosis.…”

Adjacent Order Separation for Variable Speed Bearing with Peak Detection and Fixed-point ICA

“…It not only increases the measurement cost, but also brings inconvenience in installation. To overcome the weakness, some tacholess order tracking techniques have been developed [9]. The tacholess order tracking directly extracts the shaft speed information from vibration signal by through of some signal processing techniques, such as short-time Fourier transform (STFT).…”

“…The spectrum of the segment with STFT is as following. (9) Where N is the length of signal, n, k are the discrete time and frequency in STFT spectrum.…”