1 Introduction
Rolling bearings are widely used in various rotating machines. It is of great significance to monitor and diagnose the working conditions of rolling bearings. According to the characteristics of the vibration signal, the failure of the rolling bearing during operation can be divided into two categories: one is a damage-type failure, including pitting, cracking, spalling, and scratches on the surface of the bearing element; the other is wear. Failures include abrasive wear due to foreign objects falling in and abrasive wear caused by direct contact with the component surface due to poor lubrication. At present, the commonly used methods for bearing monitoring and fault diagnosis are on-line monitoring and off-line analysis. This requires on-site analysts to have some basic knowledge of fault diagnosis, and it is difficult to implement fault diagnosis for field workers. Is it possible to use a simpler method to achieve automatic diagnosis of rolling bearing faults? The author reviewed a large number of documents and found that the use of resonant demodulation technology can achieve automatic diagnosis of rolling bearing damage faults.
2 resonant demodulation method to diagnose the principle of damage to rolling bearings
For rolling bearings, irregular damage to the roller, inner ring, and outer ring of the bearing, such as peeling, pitting, and cracks, will inevitably cause shocks. Although the basic repetition frequency of the impact is the same as or similar to the repetition frequency of the vibration, the magnitude of the impact caused by the initial failure is often much smaller than the vibration value. This is due to the long-lasting process of vibration. The energy is sustained release, the cumulative value is large, and the shock is an abnormally short process. The amplitude energy may be great, but the cumulative energy is very small. The use of frequency analysis to study the causes of failures is easy for people to accept, but it is also a relatively well-developed method. However, because of the short duration of the impact, its energy diverges into a broad frequency range, and the components falling within the vibration frequency range of the rolling bearing are smaller and cannot be compared with the vibration components that have a large energy but are basically concentrated in the low frequency area. Therefore, spectrum analysis using a vibration signal that directly contains a faulty shock to diagnose a bearing damage fault sometimes results in a fault that is not visible from the spectrogram.
Resonance is a common physical phenomenon. It can use resonance characteristics to extract fault impact information buried in normal vibration information. Since the normal vibration does not contain high-frequency components, and bearing and other faults are involved in the shock, a high-frequency resonant system with normal vibration frequency can be set. Normal vibration and shock excitation can be eliminated to achieve impact information. The extraction.
Therefore, the resonant demodulation technique performs envelope detection and low-pass filtering, ie, demodulation, on a high-frequency (10 times as many times as the impact frequency) resonant waveform that is excited by low-frequency (typically within a few kHz) impulses. The resonant demodulation wave that is impacted by the low frequency and amplified and expanded; the amplitude and the frequency spectrum analysis of the resonant demodulation wave are used to determine the magnitude of the fault and the type of the fault. The basic principle of resonance demodulation method is shown in Figure 1.
Figure 1 Fundamental Principles of Resonance Demodulation
3 Precise diagnosis of resonant demodulation signals
The main means for implementing resonant demodulation precision diagnostics is the Fourier transform of the resonant demodulation signal. Due to the full use of the resonant response of the sensor to its natural frequency, the normal machine vibration signals that are not related to the fault and are very powerful are eliminated, which greatly improves the signal-to-noise ratio and enables precise diagnosis without resorting to more frequency domain analysis methods. Accurate diagnosis can be achieved effectively.
The resonance demodulation fault diagnosis is different from the general vibration diagnosis to determine the presence or absence of a fault, and the resonance demodulation law is based on the characteristics of the multi-order demodulation spectrum which is inevitably guaranteed by the theoretical rule of the demodulation waveform, that is, the multi-stage characteristic. Faults increase reliability. The power amplifier demodulation precision diagnosis "no fault no spectral line", "everything has a fault, there are multi-stage spectral lines" to provide a theoretical basis for other diagnostics software to simplify fault diagnosis and design automation.
Resonance solution to achieve the basic process of automatic fault diagnosis of rolling bearings shown in Figure 2.
Figure 2 The basic steps of resonance demodulation automatic diagnosis
3 Implementation of Automatic Diagnosis of Rolling Bearing Failure
When the rolling bearing damage occurs, it will produce low-frequency impact and vibration, resulting in high-frequency resonant waves. Using the high-frequency components generated by the low-frequency impact of the fault in the running bearing, the resonance of the high-frequency resonator (sensor) is stimulated, and the high-frequency resonance wave is demodulated to obtain a low-frequency vibration interference but is rich in failure. Resonance demodulated wave of information. By analyzing the amplitude and frequency spectrum of this resonant demodulation wave, a clear peak can be seen at the frequency of the fault feature and its frequency multiplication, and the signal without the fault impact will not be in the spectrum of the resonant demodulation wave. Spectral peaks appear in the map, so it is easy to identify where the fault occurred.
Because of the different types and types of rolling bearings, the characteristic frequencies of their typical failures are also different. It is also not possible to perform various failure tests to obtain characteristic frequencies for rolling bearings that perform well. Therefore, in the automatic diagnosis of rolling bearing faults, the active diagnostic method should be adopted, that is, using the theoretical formula as a guide to calculate the characteristic frequency of the fault and compare it with the spectral peaks obtained from the spectrum analysis to diagnose the fault.
The characteristic frequency of the rolling bearing fault is calculated as follows:
(1) Cage failure characteristic frequency According to the geometry of the bearing, it is easy to find the frequency of the fault feature of the cage.
In the formula, Rpmi and Rpmo are inner and outer ring speeds (r/min), respectively;
D is the pitch circle diameter;
d is the diameter of the rolling element;
a is the contact angle.
(2) The characteristic frequencies of the inner and outer ring faults assume that the outer ring is not moving, and the characteristic frequencies of the inner and outer races of the rolling bearing are
Where N is the number of rolling elements.
(3) Characteristic frequency of rolling element failure
The negative sign in the formula indicates that the rolling element rotates counterclockwise.
Considering that there is a difference between the frequency of the fault feature calculated from the shaft speed and bearing geometry and the frequency of the fault feature in the actual demodulation spectrum, a frequency error may be set in the actual diagnosis. f. Rolling Bearing Failure Resonance Demodulation The automated diagnostic implementation steps are:
1. Enter the type of rolling bearings and related parameters in the equipment;
2. The system automatically calculates the characteristic frequency of each rolling bearing fault and generates a fault frequency table.
3. Arrange the sensor and measure the signal;
4. The system performs spectrum analysis on the measured signals;
5. The system automatically compares the peaks in the frequency table of the fault and the spectrum diagram, determines the bearings that have failed, and outputs the diagnostic results.
4 Conclusion
Combining resonance demodulation technology with computer technology to realize automatic diagnosis of rolling bearing damage faults has the advantages of simple method and high reliability. The software system is simple to operate and relatively low cost and easy to maintain compared to large fault diagnosis expert systems. Promotion. In particular, it is difficult to use general vibration analysis methods for failures occurring at the same time when multiple parts randomly exist. The resonance demodulation method can accurately diagnose such complex faults. This method can be applied not only to the fault diagnosis of rolling bearings, but also to impact-type failures of gears and other equipment.
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