Big data system with fault diagnosis function applied to industrial production

Abstract

The invention discloses a big data system with a fault diagnosis function applied to industrial production and relates to the technical field of intelligent manufacturing. The working condition information of production equipment is collected by using Internet of Things equipment, big data equipment carries out modeling and forms a control strategy according to the working condition information, carries out fault diagnosis according to the established model and control strategy, then forms a control step and an early warning signal, and controls the production equipment through the control step. Meanwhile, temperature field data obtained by infrared temperature measurement equipment through monitoring is transmitted to the big data equipment, and the big data equipment sends out a corresponding temperature early warning signal according to the temperature measurement data. The early warning equipment performs early warning according to the early warning signal or the temperature earlywarning signal. The industrial production is modeled and controlled through the big data system, the production is conveniently monitored and maintained through the big data system which is applied tothe industrial production and has the fault diagnosis function, meanwhile, timely reminding can be achieved through fault diagnosis, further damage to equipment is reduced, and resource losses are reduced.

Description

technical field [0001] The invention belongs to the technical field of intelligent manufacturing, and in particular relates to a big data system with fault diagnosis function applied to industrial production. Background technique [0002] The dataset size of data is growing at an unimaginable rate, which brings great challenges to data processing. First, the development of information technology has made it easier to generate and consume data. For example, 72 hours of video are uploaded to Youtube servers every minute. This high-volume nature of big data makes it difficult to collect and integrate data from distributed locations in a scalable manner. Second, after data collection, how to store and manage these massive heterogeneous data with minimum hardware and software cost is a very challenging problem. Third, due to the characteristics of big data such as heterogeneity, scale, real-time, complexity, and privacy, big data analysis must efficiently mine data at differen...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a large data system with fault diagnosis function applied to industrial production, thereby overcoming the shortcomings of existing large data systems with fault diagnosis applied to industrial production

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