Abstract: This paper mainly studies the method of continuous wavelet transformation and improved envelope analysis of spectral kurtosis. It is effectively implemented in the detection of rolling bearing faults, and while its advantages and functions are exerted, the rolling bearing is guaranteed to run well. The core of the method is to analyze the frequency band of the resonance frequency brought about by the bearing defect, and construct a perfect envelope to implement the fault diagnosis. The vibration signal of the faulted bearing can be simulated and measured, and finally satisfactory results are obtained, guaranteeing All work is carried out effectively.
In the current actual monitoring of rolling bearing faults, the effective method is the envelope analysis method. Some scholars point out two envelope analysis processes by using an intuitive graphical form, which makes the envelope analysis more practical and effective. However, there are certain defects in practical application, that is, the selection of a certain parameter in operation is determined by the operator’s experience and historical data. Later, some scholars used the form of time-frequency analysis to carry out fault diagnosis of automatic bearings, and proposed the form of maximum envelope established by wavelet transform, but the basis for parameter selection is very complicated. In order to reduce people’s dependence on experience and historical data and ensure the implementation of the automatic idea of bearing fault inspection, this paper uses the form of improved envelope to carry out corresponding analysis, so as to ensure the effective development of bearing fault detection work, and then to ensure the detection results. accuracy.
1. Main theoretical basis analysis
1.1 Analysis of the key vibration mechanism of rolling bearings
For the actual failure forms of rolling bearings, including fatigue spalling, equipment wear, plastic deformation, corrosion and fractures. If there is a local defect on the working surface of the component of the bearing, the broadband impact formed by the frequency will be used to obtain the corresponding data through the vibration frequency, which is also called the fault frequency.
1.2 Filter bank analysis of Morlet complex wavelet
For wavelet transform, it is a relatively effective form of signal processing technology, which has been effectively implemented and used in the diagnosis of mechanical faults.
Among them, α is a factor of scale, and τ is a factor of translation, and the function x(t) with finite energy and the analytical wavelet ψ(t) transform can be expressed by the convolution of the two.
For each α and τ, the definition form is the division form that affects the CET time-frequency to present different phase planes. You can choose to use the translation parameter in the form of a period, that is, the time-frequency interval on the upper edge of the phase plane can show the sampling period of the signal, which provides great help for specific calculations. For the functions of each wavelet, different time-frequency structures are presented [1]. For the part that already has a wavelet function, the Morlet complex wavelet and the impact vibration formed by the faulty bearing will show similar components, so the Morlet complex wavelet will be used to carry out wavelet transformation for the original signal.
2. Effectively improve the construction steps of the envelope analysis method
For spectral kurtosis, it belongs to the form of time-frequency decomposition, including wavelet transform, after the signal passes through, and then shows the size index of the component kurtosis value of the original signal at some frequency points. In practice, the concept of spectral kurtosis is effectively used, and its definition lies in the signal and is based on continuous wavelet transform. It defines the signal as the spectral moment of the successive wavelet transform stages, and then its spectral kurtosis can show the kurtosis at each frequency. , the obtained coefficient obtains its absolute value, by making it clear that its time domain kurtosis value is the final value of spectral kurtosis [2].
For the case where the frequency of the center of the Morlet complex wavelet is relatively close to the frequency of the resonance caused by the bearing fault, the final result of the CWT, that is, the corresponding wavelet coefficient, will include the components of the impulse response caused by the resonance, and This can be useful diagnostic information for the desired activity.
According to the above analysis, the construction steps of the improved optimal envelope analysis are as follows: First, combined with several methods briefly described in the article, it is of great help to optimize and form the filter bank of Morlet complex wavelet . Secondly, for each scale, the original signal FFT and the complex conjugate of the rows and columns of the filter bank matrix will be multiplied, and then the result will be calculated using the IEFT method, so that the The coefficients of the signal wavelet at scale. The same operation is performed for several scales, and finally the matrix of wavelet coefficients can be obtained. Third, the absolute values in the wavelet coefficient matrix are obtained. Each row and column will correspond to the time domain envelope of the wavelet coefficients in the center frequency. Thirdly, when calculating the SK value in each row and column, the row with the maximum value is the most reasonable envelope of the wavelet coefficients. Finally, the optimal envelope comes from the FFT operation, so that the envelope spectrum can be obtained, thereby ensuring the effective development of fault diagnosis.
3. Main case studies of applying improved envelope in fault detection of rolling bearings
For the actual fault vibration signal of the rolling bearing, the simulated model is represented by the response sequence of the system pulse with a single degree of freedom, and the waveform of the simulated signal after adding noise in practice, the frequency of the fault characteristic is about 200Hz, The resonance frequency is also around 9kHz.
For the simulation signal, it generally goes through the rock-changing tunnel technology of Modet complex wavelet, the construction technology of the surface landslide tunnel, the ventilation technology of the tunnel processing process, and the reinforcement processing technology outside the tunnel. The key to improving the level of railway tunnel construction technology is to formulate a reasonable construction plan. The construction technology selected in the plan should be able to reflect the defense against geological disasters, conform to the local geological conditions, and have a good risk handling mechanism. When problems occur, the team can be guided to handle them accurately and improve construction safety.
Taking the application of ventilation technology in tunnel processing as an example, the use of drilling and blasting methods in engineering is often inevitable, and a large amount of smoke and harmful substances will appear during the construction process. The engineering team should hire engineering experts in air quality testing, and under the leadership of the chief engineer, make necessary application of tunnel ventilation technology in the construction and excavation of railway tunnels. The project management personnel and technical director should make a detailed division of the construction personnel, and teach the construction personnel the principles, application methods and precautions of ventilation technology. The construction of ventilation technology should be based on a reasonable, scientific and complete construction plan. After each construction, the superintendent should make detailed records and generate a report to provide reference materials for future railway tunnel excavation work.
4. Improve the operation level and safety awareness of construction workers
Successful railway tunnel construction not only requires technical reliability, but also needs to improve the operation level and safety awareness of construction personnel. At present, many construction teams have different levels of engineers, and there are many young people with inexperience. Lack of operation experience and tunnel excavation experience is fatal in the construction process. Tunnel construction is not a simple application of theoretical knowledge, which involves a lot of knowledge that can only be understood through practical operation. In the construction under complex geological conditions, the Internet of Things technology and sensor technology cannot predict all the dangers in advance, which requires the staff to pay more attention during construction and improve their own safety on the premise practical level of operation.
For example, engineering managers can formulate a system in which professionals lead new personnel. During the construction process, a top-down management system is adopted. Engineering personnel with low operating skills must obey the orders of old employees and strictly abide by the construction of railway tunnels. related systems and regulations. Enterprise executives can hold seminars on railway tunnel safety and practice within the enterprise, and tunnel excavation professionals will give speeches to improve the overall level and safety awareness of construction workers.
5. Conclusion
In summary, the analysis of railway tunnel construction technology under complex geological conditions is mainly carried out from three aspects, including strengthening the investigation of the geological conditions of the construction area, rationally formulating construction plans, and improving the operation level and safety awareness of construction personnel. Geological investigation is the premise of the implementation of tunnel construction technology, construction plan is the core work of tunnel construction, and improving the operation level of personnel is to improve the construction technology from the aspect of personnel quality. It is hoped that the analysis results of this paper can be helpful for the construction of railway tunnels under complex geological conditions.
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