Data mining service platform based on cloud computing

Abstract

The invention belongs to the field of data mining, and relates to a cloud computing technology, in particular to a data mining service platform based on cloud computing, which comprises a processor, and the processor is in communication connection with a data acquisition module, a data storage module, a product quality detection module, an equipment detection module, an environment detection module and a cloud platform. The cloud platform is in communication connection with a data classification module, the data acquisition module comprises a product data acquisition unit, an equipment data acquisition unit and an environment data acquisition unit, and the equipment data acquisition unit is used for acquiring a processing platform surface image of processing equipment; the product data can be deeply analyzed through the arranged data classification module, and after unqualified products are removed, the remaining qualified products are subjected to data classification, so that the data processing time is shortened, and the data classification efficiency is improved.

Description

technical field [0001] The invention belongs to the field of data mining, relates to cloud computing technology, in particular to a data mining service platform based on cloud computing. Background technique [0002] Data mining is usually related to computer science, and achieves the above goals through many methods such as statistics, online analysis processing, intelligence retrieval, machine learning, expert system and pattern recognition; data mining is a hot issue in the field of artificial intelligence and database research, the so-called data Mining refers to the non-trivial process of revealing implicit, previously unknown and potentially valuable information from a large amount of data in a database. [0003] The invention patent with the notification number CN109670695B discloses a parallel detection method for abnormalities in the processing procedures of mechanical products based on outlier data mining. In this way, a series of hidden problems such as equipment...

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Problems solved by technology

[0003] The invention patent with the notification number CN109670695B discloses a parallel detection method for abnormalities in the processing procedures of mechanical products based on outlier data mining. In this way, a series of hidden problems such as equipment performance degradation, lack of precision, wear of consumable parts, and instability of process parameters in the manufacturing system can be found. At the same time, the outlier data mining method involved effectively improves the efficiency and accuracy of outlier mining. However, the abnormal parallel detection method of mechanical product processing procedures based on outlier data mining cannot quickly detect the cause of hidden problems after detecting hidden problems in product processing. After the product, it takes a lot of time to check the processing equipment and processing environment, which reduces the production efficiency of the equipment

[0004] The invention patent with the notification number CN106649329A discloses a big data mining system for safe production. The big data mining system for safe production can reduce the amount of manual participation, and carry out multi-level and all-round mining processing of the data input in the accident hidden danger database. After further structural analysis of the mining results, classification, visualization and other processing are performed, which have the advantages of high efficiency, high accuracy, and high value; however, the safety production big data mining system does not analyze and rate the data before classifying the data, and Judging whether the product processing is qualified or not, resulting in a lot of invalid data processing unqualified products when classifying the data, which reduces the data processing speed and data classification efficiency

[0005] The invention patent with the announcement number CN110096532A discloses a method and system for big data analysis and mining of safety production. The focus of hidden danger investigation, the focus of law enforcement inspection and the law of accidents are to discover hidden dangers in advance and reduce the probability of accidents. "Prevention" transformation to achieve safe production of enterprises; however, the safety production big data analysis and mining method and system did not perform data classification and rating on previous accidents, and there were inaccuracies in predicting and analyzing accidents

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