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Component fatigue monitoring method for special machinery

A fatigue level, special machinery technology, applied in computer parts, neural learning methods, elevators, etc., can solve problems such as low efficiency and large labor input, and achieve high accuracy, improve accuracy, and enrich the effect of fault types.

Active Publication Date: 2022-04-26
杭州浅水数字技术有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The present invention solves the problems in the prior art that there are a large number of post-event audio and video manual analysis and supervision, huge manpower investment, but little effect, and provides a method for monitoring the fatigue degree of components of special machinery

Method used

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  • Component fatigue monitoring method for special machinery
  • Component fatigue monitoring method for special machinery

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0063] A component fatigue degree monitoring method for special machinery, especially for vertical elevators, (see attached figure 1 ), including the following steps:

[0064] Step 1, installing information data collection equipment for each component at the set position of the target equipment;

[0065] Step 2: For the target device, establish a baseline model and a fault model for the overall state of the target device on the cloud server, and perform training and iterative updates respectively;

[0066] Step 3, collecting the operating feature data of the target device and uploading it to the cloud server;

[0067] Step 4, constructing a mechanical state baseline through the baseline model on the operating characteristic data collected by the information data collection equipment on the cloud server;

[0068] Step 5: Use the established mechanical state baseline to compare and carry out fatigue warning, and use the operating characteristic data of the target equipment to ...

Embodiment 2

[0115] This embodiment is basically the same as Embodiment 1, the difference is:

[0116] The target device targeted by this embodiment is an escalator, and the target device monitored by the information data collection device includes a driving device, a step guide rail system, a handrail driving device and a safety protection device. The operation characteristic data of the collected target equipment includes the characteristic data of sound, vibration, current and temperature during the operation of the elevator, as well as the health data, sub-health data and fault data of the elevator, as well as the basic information data of the elevator and the actual operation data of the elevator. For the driving device, the information collected by the information data collection equipment includes data such as the sound, vibration, temperature, etc. of the driving host; the friction between the main drive chain and the driving wheel, and the running sound;

[0117] For the step guid...

Embodiment 3

[0121] This embodiment is basically the same as Embodiment 1, the difference is:

[0122] The target device targeted by this embodiment is a sliding amusement device, and the target device monitored by the information data collection device includes a power lifting device, a transmission device, a vehicle body, and a vehicle connection device. The operation characteristic data of the collected target equipment includes the sound and vibration data during the operation of the scooter, as well as the health data, sub-health data and fault data of the scooter, as well as basic information data and actual operation data. For the power lifting device, the information collected by the information data collection equipment includes the sound of the motor running, vibration information, and the sound of the friction of the reducer and the coupling;

[0123] For the transmission device, the information collected by the information data collection equipment includes the sound of tractio...

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Abstract

The present invention relates to a component fatigue degree monitoring method for special machinery. The present invention solves the problems of the prior art. The key point of the technical solution is that it includes the following steps: Step 1, at the set position of the target equipment, install Information data collection equipment; Step 2, for the target device, establish a baseline model and a fault model for the overall state of the target device on the cloud server, and perform training and iterative updates respectively; Step 3, collect the operating characteristic data of the target device and upload it to the cloud server ; Step 4: Construct a mechanical state baseline on the cloud server based on the operating characteristic data collected by the information data collection equipment through the baseline model; Step 5: Use the established mechanical state baseline to compare and perform fatigue warning, and use the operating characteristic data of the target equipment , through the calculation of the fault model to realize the early warning before the fault.

Description

technical field [0001] The invention belongs to a method for monitoring equipment, and relates to a method for monitoring the fatigue degree of components used in special machinery. Background technique [0002] Special equipment refers to boilers, pressure vessels, pressure pipes, elevators, hoisting machinery, passenger ropeways, large amusement facilities and special motor vehicles that involve life safety and are relatively dangerous. When special equipment breaks down, it is very easy to cause personal injury to uncertain personnel, and even serious fatal accidents. Therefore, it is necessary to ensure the safe and stable operation of special equipment. For this reason, the state has strict regulations on all kinds of special equipment from the three links of production, use, inspection and testing, and implements full-process supervision and mandatory maintenance. At present, the quality inspection of special equipment in the production stage is relatively complete. ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): B66B5/00B66B3/00B66B27/00B66B29/00G06K9/62G06N3/08
CPCB66B5/0037B66B5/0031B66B3/00B66B29/005B66B27/00G06N3/08G06F18/214
Inventor 李智彤郑传乾周栋武肖倩
Owner 杭州浅水数字技术有限公司
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