JPH0444932B2 - - Google Patents

Description

[Detailed description of the invention]

[Industrial Application Field] The present invention relates to a method for monitoring industrial equipment, ie, various production machines, machine tools, etc., for performance deterioration, possibility of failure, etc. [Prior art] Monitoring the status of equipment such as production and machine tools in factories, etc. not only helps prevent operational stoppages due to malfunctions, but also improves energy efficiency, improves economic efficiency by optimizing the timing of parts replacement, and more. It has become important in terms of preventing noise, vibration, etc. from the perspective of environmental conservation. However, conventionally, commercially available general-purpose signal processing equipment was generally used to analyze and process data collected from equipment to be monitored. were constrained by their abilities. Therefore, in the past, data analysis at the level of frequency analysis or correlation analysis of changes in vibration, pressure, or sound generated by the mechanical equipment to be monitored was not performed, and as a result, unexpected failures often occurred or Occasionally, situations such as production of defective products were expected. By the way, according to experiments conducted by the inventors of the present application,
If there is a performance drop or above occurrence in mechanical equipment, the frequency component, phase component, amplitude component, etc. of the physical signal generated by the mechanical equipment will be examined, such as the degree of performance decline, the type of abnormality, etc. It was found that it changes depending on [Object of the Invention] The present invention has been made in view of the above-mentioned problems and based on the above-mentioned knowledge of the inventors of the present invention, and has been made by conducting a more advanced analysis on multiple items than in the past. By doing so, the condition of machinery and equipment can be monitored with higher precision and accuracy, making it possible to predict in advance performance deterioration, failure occurrence, etc. that would have been overlooked or predicted in the past. The purpose is to propose monitoring methods. [Principle of the Invention] Next, the principle of the method of the present invention will be explained. If a physical (vibration, noise, etc.) signal f(t) representing the state of a certain mechanical equipment and its quantized data are f(k), then the finite discretized Fourier transform F(n/N) of the signal f(t) is is given by the following equation (1). F(n/N)=1/N _N-1 〓 ^k=0 f(k)e ^-j2 〓 ^nk/n …(1) where, N: number of data n: 0, 1, 2…, N/2 K: n/N j: √-1 Further, the inverse Fourier transform equation for the signal f(t) is the following equation (2). f(n)=a ₀ + _N-1 〓 ^k=1 a(k/N) cos(j2πkn/N) + _N-1 〓 ^k=1 b(b/N) sin(j2πkn/N) …(2 ) However, a(n/N)=1/N _N-1 〓 ^k=0 f(k)cos(-j2πkn/N) …(3) b(n/N)=1/N _N-1 〓 ^{k =0} f(k)sin(−j2πkn/N) …(4) From equations (3) and (4), the phase component φ(n/N) is as follows (5)
It can be found as a formula. φ(n/N)=tan ^-1 b(n/N)/a(n/N)...(5) Also, the amplitude component, average value, and effective value of signal f(t)
Urms, root mean square value Ur, maximum value U^, and fourth-order probability moment (flatness) β are given by the following equations (6) to (10), respectively. =1/T∫ ^T/0 |f(t)|dt …(6) Urms=[1/T∫ ^T/0 f ² (t)dt] ^1/2 …(7) Ur=[1/T∫ ^T/0 √(t)dt〕 ² …(8) U^=E{max｜f(t)} …(9) β=∫ ^∞ ／ _-∞ f ⁴ (t)・P(t)dt／ σ …(10) Where, T: Signal period P(t): Probability density function of f(t) σ: Standard deviation of f(t) From the above, the frequency component of signal f(t) can be calculated using equation (1). ,
The phase component is obtained using equation (5), and the amplitude component is obtained using equations (6) to (10). The criteria for determining the data of each component obtained in this way, in other words, the characteristics of the frequency component, phase component, amplitude component, etc. of mechanical signals generated by mechanical equipment with degraded performance are determined to be artificially degraded. This has already been clarified by the inventors of the present application through measurements on various mechanical equipment and verification of data collected from actual machines, and Table 1 shows the case of rotating machines as an example.

【table】

【table】

Claims (1)

[Claims] 1. Detecting a physical signal generated by the movement of the equipment to be monitored, and converting the physical signal into a quantum signal at a preset sampling period or a sampling period defined by the movement of the equipment to be monitored. quantized data, perform spectrum analysis on the quantized data to extract the frequency component, phase component, and amplitude component of the physical signal, and compare each of these components with predetermined criteria. An equipment status monitoring method characterized by determining the status of equipment to be monitored.