CN-121432933-B - Intelligent electromechanical comprehensive monitoring system based on industrial Internet

CN121432933BCN 121432933 BCN121432933 BCN 121432933BCN-121432933-B

Abstract

The invention relates to the technical field of industrial equipment predictive maintenance and health management, in particular to an intelligent electromechanical comprehensive monitoring system based on an industrial Internet, which comprises a data acquisition module, a control module and a control module, wherein the data acquisition module acquires equipment dynamic operation parameter sets, inherent physical attribute parameters and historical maintenance data of target electromechanical equipment, and invokes preset process topology data, economic loss data and maintenance cost data; the state evaluation module iteratively calculates an accumulated degradation index representing the health condition of the equipment; the invention realizes systematic risk cognition from the individual equipment to the global production line, gets rid of extensive management on the same vision of all the equipment, and ensures that the allocation of maintenance resources is more strategic and targeted.

Inventors

ZHAI CHUNYU
MOU LIANG
MAO HULIN
FU MING
LI ENLU
ZOU KUN
WANG BINGQUAN
YANG GUOKUAN
WU JINHONG
YANG HAO

Assignees

成都四为电子信息股份有限公司

Dates

Publication Date: 20260508
Application Date: 20251226

Claims (8)

1. An intelligent electromechanical integrated monitoring system based on the industrial internet is characterized by comprising: The system comprises a data acquisition module, a target electromechanical device and a target electromechanical device, wherein the data acquisition module is used for acquiring a device dynamic operation parameter set, inherent physical attribute parameters and historical maintenance data of the target electromechanical device, and calling preset process topology data, economic loss data and maintenance cost data; The state evaluation module is used for iteratively calculating the accumulated degradation index representing the health condition of the equipment based on the equipment dynamic operation parameter set, the inherent physical attribute parameter and the historical maintenance data which are acquired by the data acquisition module, wherein the historical maintenance data are used for recalibrating and optimizing the model parameters of the accumulated degradation index in the state evaluation module; The importance quantization module is used for calculating a process importance coefficient for representing the criticality of the equipment in the production line based on process topology data, wherein the process topology data represents the network position, redundancy configuration and the influence range of the equipment on the downstream process in a process flow map; The risk calculation module is used for determining the equipment failure probability according to the accumulated degradation index and generating a production risk degree for quantifying the influence of shutdown by combining the process importance coefficient and the economic loss data; The decision generation module is used for determining the decision priority of the maintenance task based on the production risk degree and the maintenance cost data and generating a dynamic maintenance decision instruction.
2. The intelligent electromechanical integrated monitoring system based on the industrial internet according to claim 1, wherein the state evaluation module is specifically configured to: Determining a reference degradation amount based on the inherent physical attribute parameter; determining the comprehensive disturbance quantity based on the equipment dynamic operation parameter set; And combining the reference degradation amount and the comprehensive disturbance amount to generate an accumulated degradation index.
3. The intelligent electromechanical integrated monitoring system based on the industrial internet of claim 1, wherein the risk calculation module is configured to determine a probability of failure of the device, and comprises: And inputting the accumulated degradation index into a preset logistic function model, and calculating the equipment failure probability.
4. The intelligent electromechanical integrated monitoring system based on the industrial internet according to claim 1, wherein the importance quantization module is specifically configured to: determining a bottleneck index based on the process topology data; Determining redundancy coefficients based on the process topology data; Determining a downstream impact factor based on the process topology data; and combining the bottleneck index, the redundancy coefficient and the downstream influence factor to generate a process importance coefficient.
5. The intelligent electromechanical integrated monitoring system based on the industrial internet according to claim 1, wherein the risk calculation module is configured to generate a production risk degree, and the intelligent electromechanical integrated monitoring system comprises: And determining the production risk degree according to the product of the equipment failure probability, the process importance coefficient and the economic loss data.
6. The intelligent electromechanical integrated monitoring system based on the industrial internet according to claim 1, wherein the decision generation module is specifically configured to: Determining a cumulative degradation index after maintenance based on a preset maintenance measure degradation improvement coefficient and the cumulative degradation index; Inputting the accumulated degradation index after maintenance into a logic substance function model, and determining the failure probability after maintenance; determining the residual production risk degree by combining the failure probability after maintenance, the process importance coefficient and the economic loss data; And generating a decision priority based on the production risk level, the residual production risk level and the maintenance cost data.
7. The intelligent electromechanical integrated monitoring system based on the industrial internet of claim 1, wherein the decision generation module is further configured to: setting a first response threshold and a second response threshold, wherein the second response threshold is larger than the first response threshold; Generating an emergency maintenance work order in response to the decision priority being greater than a second response threshold; Generating a planned maintenance recommendation in response to the decision priority being greater than the first response threshold and less than or equal to the second response threshold; responsive to the decision priority being less than or equal to a first response threshold, the maintenance task is included in a regular maintenance schedule.
8. The intelligent electromechanical integrated monitoring system based on the industrial internet of claim 1, further comprising: And the feedback closed loop module is used for recording the implementation condition of the maintenance activities and updating the historical maintenance data.

Description

Intelligent electromechanical comprehensive monitoring system based on industrial Internet Technical Field The invention relates to the technical field of industrial equipment predictive maintenance and health management, in particular to an intelligent electromechanical comprehensive monitoring system based on an industrial Internet. Background In an industrial production environment, electromechanical equipment is a core for guaranteeing continuous operation of a production line, and in order to prevent equipment faults, the prior art generally obtains equipment operation data through a sensor and manages the equipment operation data in combination with a preset maintenance plan; The traditional maintenance strategy evaluates the physical state of a single device in a multi-isolation way, quantitatively evaluates the criticality of the device from the whole production line process topology structure, and dynamically associates the real-time health condition of the device with the economic loss possibly caused by the failure of the device, wherein the evaluation mode leads to insufficient basis of maintenance decision, and the priority of maintenance tasks is difficult to scientifically determine in a plurality of devices, so that the configuration of maintenance resources lacks optimized guidance, the risk of unplanned shutdown caused by the failure of the critical device exists, and the threat is formed to the continuity and economic benefit of production. Disclosure of Invention In order to solve the technical problems, the invention provides an intelligent electromechanical integrated monitoring system based on the industrial Internet, which concretely comprises the following technical scheme: an intelligent electromechanical integrated monitoring system based on the industrial internet, comprising: The data acquisition module is used for acquiring a device dynamic operation parameter set, inherent physical attribute parameters and historical maintenance data of the target electromechanical device, and calling preset process topology data, economic loss data and maintenance cost data; the state evaluation module is used for iteratively calculating an accumulated degradation index representing the health condition of the equipment based on the equipment dynamic operation parameter set, the inherent physical attribute parameters and the historical maintenance data acquired by the data acquisition module; the importance quantization module is used for calculating a process importance coefficient for representing the criticality of the equipment in the production line based on the process topology data; The risk calculation module is used for determining the equipment failure probability according to the accumulated degradation index and generating a production risk degree for quantifying the influence of shutdown by combining the process importance coefficient and the economic loss data; The decision generation module is used for determining the decision priority of the maintenance task based on the production risk degree and the maintenance cost data and generating a dynamic maintenance decision instruction. Preferably, the state evaluation module is specifically configured to: Determining a reference degradation amount based on the inherent physical attribute parameter; determining the comprehensive disturbance quantity based on the equipment dynamic operation parameter set; And combining the reference degradation amount and the comprehensive disturbance amount to generate an accumulated degradation index. Preferably, the risk calculation module is configured to determine a device failure probability, and includes: And inputting the accumulated degradation index into a preset logistic function model, and calculating the equipment failure probability. Preferably, the importance quantization module is specifically configured to: determining a bottleneck index based on the process topology data; Determining redundancy coefficients based on the process topology data; Determining a downstream impact factor based on the process topology data; and combining the bottleneck index, the redundancy coefficient and the downstream influence factor to generate a process importance coefficient. Preferably, the risk calculating module is configured to generate a production risk degree, including: And determining the production risk degree according to the product of the equipment failure probability, the process importance coefficient and the economic loss data. Preferably, the decision generation module is specifically configured to: Determining a cumulative degradation index after maintenance based on a preset maintenance measure degradation improvement coefficient and the cumulative degradation index; Inputting the accumulated degradation index after maintenance into a logic substance function model, and determining the failure probability after maintenance; determining the residual production risk degree by combinin