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Fault diagnosis method for main bearing of manufacturing equipment based on digital twinborn body

A fault diagnosis and main bearing technology, applied in mechanical bearing testing, measuring devices, character and pattern recognition, etc., can solve problems such as signal filtering expert experience dependence, achieve high practical significance, high autonomy, improve accuracy and effectiveness sexual effect

Pending Publication Date: 2022-02-01
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

In addition, the model only relies on the real-time acquisition signal itself for diagnosis without additional auxiliary means, so it solves the problem that the existing fault diagnosis model relies too much on signal filtering and expert experience

Method used

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  • Fault diagnosis method for main bearing of manufacturing equipment based on digital twinborn body
  • Fault diagnosis method for main bearing of manufacturing equipment based on digital twinborn body
  • Fault diagnosis method for main bearing of manufacturing equipment based on digital twinborn body

Examples

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Effect test

Embodiment 1

[0072] Example 1: Bearing outer ring failure.

[0073] See attached figure 1 As shown, the embodiment of the present application discloses a fault diagnosis method for the main bearing of manufacturing equipment based on digital twins, including:

[0074] S1, based on the data acquisition device to obtain the real-time vibration signal of the bearing, as shown in Figure 2(a) is the fault signal of the outer ring of the bearing, because the fault impact is more obvious, so it can be detected from the envelope spectrum shown in Figure 2(b) to the fault characteristic frequency of the outer ring of the bearing. In order to verify the outstanding advantages of this application, Gaussian white noise interference is added to the collected signal. The time domain and frequency domain of the signal after the noise are added are shown in Figure 2(c) and Figure 2(d), respectively. It can be seen from the figure that the original The signal has been completely covered by noise, and the...

Embodiment 2

[0109] Example 2: Bearing inner ring failure.

[0110] See attached figure 1 As shown, the embodiment of the present application discloses a fault diagnosis method for the main bearing of manufacturing equipment based on digital twins, including:

[0111] S1, based on the data acquisition device to obtain the real-time vibration signal of the bearing, as shown in Figure 4(a) is the fault signal of the inner ring of the bearing, because the fault impact is more obvious, so it can be detected from the envelope spectrum shown in Figure 4(b) to the fault characteristic frequency of the inner ring of the bearing. In order to verify the outstanding advantages of this application, Gaussian white noise interference is added to the collected signal. The time domain and frequency domain of the signal after adding noise are shown in Figure 4(c) and Figure 4(d), respectively. It can be seen from the figure that the original The signal has been completely covered by noise, and the charac...

Embodiment 3

[0129] Example 3: Bearing rolling element failure.

[0130] See attached figure 1 As shown, the embodiment of the present application discloses a fault diagnosis method for the main bearing of manufacturing equipment based on digital twins, including:

[0131] S1, based on the data acquisition device to obtain the real-time vibration signal of the bearing, as shown in Figure 6(a) is the fault signal of the bearing rolling body, because the fault impact is more obvious, so it can be detected from the envelope spectrum shown in Figure 6(b) to the characteristic frequency of bearing rolling element faults. In order to verify the outstanding advantages of this application, Gaussian white noise interference is added to the collected signal. The time domain and frequency domain of the signal after adding noise are shown in Figure 6(c) and Figure 6(d), respectively. It can be seen from the figure that the original The signal has been completely covered by noise, and the characteris...

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Abstract

The invention discloses a fault diagnosis method and system for a main bearing of manufacturing equipment based on a digital twinborn body. The system comprises a physical entity module and a digital twinborn body module. In the physical entity module, bearing vibration signals are acquired in real time based on a data acquisition device, the acquired vibration signals are input into an entity diagnosis model to obtain bearing early-stage fault characteristic frequency, and the bearing early-stage fault occurrence position is determined by comparing the bearing early-stage fault characteristic frequency with the theoretical fault characteristic frequency calculated in the digital twinborn body module. In addition, working condition parameters of the bearing under the real-time working condition are obtained based on the data acquisition device, and an analog simulation model of the working state of the bearing under the synchronous working condition is constructed in combination with bearing material performance parameters. The fault occurrence position is verified in an auxiliary mode through the analog simulation result, and meanwhile the analog simulation model is optimized and adjusted based on the diagnosis result of the entity diagnosis model. The auxiliary verification of the diagnosis result of the entity diagnosis model is realized by introducing the digital twinborn body, so that the rapid capture and accurate positioning of the early fault of the bearing are realized.

Description

technical field [0001] This application belongs to the field of intelligent operation and maintenance and health management of intelligent manufacturing equipment, and specifically relates to a fault diagnosis method for main bearings of manufacturing equipment based on digital twins. Background technique [0002] With the continuous development of industrial technology, mechanical equipment tends to be large-scale and intelligent. As an indispensable key component in industrial rotating equipment, rolling bearings play an important role in rotating machinery. Due to the harsh working environment and heavy workload, bearings are inevitably damaged after long hours of work. If the bearing failure is not found in time, it may cause a series of mechanical damage and even lead to catastrophic production accidents. On the contrary, if the bearing failure can be diagnosed at the early stage, the accident can be avoided through timely maintenance, which is of great significance a...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G01M13/04G01M13/045
CPCG01M13/04G01M13/045G06F2218/08G06F2218/12
Inventor 杨文安绳远远
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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