Figure 1 The form of equipment management based on big data (1) Original hoop bending machine operation data. Massive log information of equipment operation, such as equipment repair records, equipment incident records, etc., can use the collection system to collect data and store it in the database, so as to maintain the system's operational integrity more safely.
(2) Equipment data preprocessing. There is a lot of noise information in the original data of the equipment. Data cleaning and packing are used to further improve the quality of the data. The data preprocessing can commonize the operation data of different bending machine equipment operations, so that the data can be reduced. The rare features of these, these features have little or no dedication to the audit model, and improve the accuracy of data mining.
(3) Analysis of data mining. After the imported data is preprocessed, it can use data mining skills to mine and analyze the data. Commonly used data mining skills include K-means algorithm, support vector machine, BP neural network, genetic algorithm and other skills, can analyze these device data , The form of gathering data to hide, forming a common sense of resolution plans.
(4) Common sense application of the resolution plan. The common sense of the resolution plan can guess the operation trend of the equipment. It is common to find whether the bending machine will have problems. If there is a problem, the bending machine can be repaired in time, so that the failure can be prevented; other things can also be found. Whether these devices are unqualified or have a hidden risk, they can be replaced with higher quality devices. Reprinted: http: //
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