Equipment spare part demand prediction system based on fault prediction and health management

Abstract

The invention relates to an equipment spare part demand prediction system based on fault prediction and health management, and the system comprises a data collection and edge calculation module whichcollects data through edge equipment, and extracts features needed by modeling through the analysis and calculation of the data; the data service module is used for carrying out unified management ondata assets of the field equipment and the system and providing data support for the intelligent analysis model; the intelligent analysis module is used for carrying out signal processing and featureprocessing on the acquired data and carrying out health assessment according to the processed signal data; and the visual application module is used for visually displaying fault prediction and healthassessment results. The method is easy to implement, spare part demand prediction can be more accurate on the premise that normal operation of the equipment is guaranteed, the spare part inventory isminimized, the equipment maintenance frequency is reduced, the overall maintenance cost of the equipment is reduced from spare part and labor cost, and the enterprise operation cost is reduced.

Description

technical field [0001] The application relates to an equipment spare parts demand prediction system based on failure prediction and health management, which is applicable to the technical field of equipment failure and health management. Background technique [0002] During the use of equipment, equipment spare parts are a necessary guarantee to ensure the normal operation of the equipment. However, the premature stocking of spare parts will lead to long-term occupation of the company's funds; the long delivery period of the spare parts will lead to the untimely delivery of spare parts, which will also cause the company's equipment to not be started in time and cause production losses. [0003] Equipment is the basis for ensuring the production efficiency and product quality of an enterprise, and the damage of key components of the equipment will directly affect the performance of the equipment, and even lead to equipment failure and downtime, affecting the smooth progress o...

AI Technical Summary

Problems solved by technology

If the above-mentioned feature selection and evaluation methods are used alone, they will be more or less disturbed by other factors, such as noise, feature mutation, etc., and it is difficult to select trending features that really meet the requirements.

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