Abnormal analysis method, device, electronic equipment and storage medium of process
A technology of process and analysis method, which is applied in the field of production monitoring, can solve the problems of insufficient utilization of industrial process data and poor detection accuracy, so as to improve the accuracy of monitoring, improve full utilization, and solve the effect of consuming too much manpower and material resources
Active Publication Date: 2022-02-22
CHENGDU SHULIANYUNSUAN TECH CORP
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[0004] The present invention provides a process abnormality analysis method, device and computer-readable storage medium, the main purpose of which is to solve the technical problem of poor detection accuracy due to insufficient utilization of industrial process data in the prior art
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[0054] It is to be understood that the specific embodiments described herein are intended to explain the present invention and is not intended to limit the invention.
[0055] The present application embodiment provides a process process abnormality analysis method. The execution body of the process process abnormality analysis method includes, but is not limited to, at least one of the electronic devices that can be configured to perform the method of the method provided in the present application embodiment. In other words, the process process abnormal analysis method can be performed by software or hardware mounted on a terminal device or a server device, the software can be a block chain platform. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster, and the like.
[0056]Refer figure 1 As shown, a flow chart of process process abnormality analysis method according to an embodiment of the present invention is ...
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The present invention relates to the technical field of production monitoring, and discloses a process abnormality analysis method, device, electronic equipment, and storage medium, including: receiving a process training set and a label set, and classifying the execution features of the process training set to obtain multiple A set of process feature training sets, according to multiple sets of process feature training sets to construct corresponding multiple sets of isolated tree models, each set of process feature training sets are input to the corresponding isolated tree models in order to perform training, and use the The above label set selects the isolated tree model whose training result meets the preset requirements, and obtains one or more sets of high-quality tree models, and inputs the abnormal process data set to be judged into the high-quality tree model to perform abnormal analysis, and obtains abnormal analysis results . The invention also provides a process abnormality analysis device, electronic equipment and storage medium. The invention can solve the technical problem of poor detection accuracy caused by insufficient utilization of industrial process data in the prior art.
Description
Technical field [0001] The present invention relates to the field of production monitoring, and more particularly to a process process abnormal analysis method, apparatus, electronic device, and storage medium. Background technique [0002] With the development of science and technology, the intelligence of various industries is getting higher and higher, and it can effectively save human materials. In particular, in the process of process production, the industrial process data is judged throughout the process products in each process. The degree, which can effectively predict the good price of process products. [0003] In the prior art, it is mainly achieved by traditional machine learning algorithms, such as support vector machines, although the product productivity detection can be realized, but due to the lack of sufficient use of industrial process data, the detection accuracy is caused Phenomenon. Inventive content [0004] The present invention provides a process proces...
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IPC IPC(8): G06V10/774G06V10/764G06K9/62G06N20/20
CPCG06N20/20G06F18/214G06F18/24
Inventor 不公告发明人
Owner CHENGDU SHULIANYUNSUAN TECH CORP