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Mechanical product quality analysis method based on subspace clustering

A technology for quality analysis and mechanical products, applied in computer parts, instruments, manufacturing computing systems, etc., can solve problems such as the inability to effectively handle massive multi-dimensional dynamic industrial big data, complex processing of industrial big data, etc.

Pending Publication Date: 2021-03-02
TAIYUAN UNIVERSITY OF SCIENCE AND TECHNOLOGY
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Problems solved by technology

In the process of digitizing the manufacturing industry, the processing of industrial big data is extremely complex. Changes in process parameters and production processes will lead to huge changes in the data structure. Obviously, traditional clustering analysis techniques cannot effectively deal with massive, multi-dimensional and dynamic industrial big data. data

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  • Mechanical product quality analysis method based on subspace clustering
  • Mechanical product quality analysis method based on subspace clustering
  • Mechanical product quality analysis method based on subspace clustering

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Embodiment Construction

[0054] The mechanical product quality analysis method based on subspace clustering provided by the present invention mainly includes: data preprocessing and quality detection and analysis based on subspace clustering.

[0055] Among them, data preprocessing mainly adopts technologies such as data conversion, data cleaning and data discretization. Among them, data cleaning includes blank value filling, noise data elimination and inconsistency processing. The main purpose of data discretization is to stabilize data characteristics and unify data types. The equal-width discretization method is used to convert non-categorical data into categorical data to meet the needs of clustering algorithm processing.

[0056] The specific steps of the data preprocessing are as follows: aiming at the massive, high-dimensional, and multi-type characteristics of industrial big data, in the Hadoop cluster, according to the change of the data volume, setting environmental parameters, such as the nu...

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Abstract

The invention discloses a mechanical product quality analysis method based on subspace clustering, and belongs to the technical field of mechanical product quality analysis. The technical problem to be solved is to provide a mechanical product quality analysis method based on subspace clustering. According to the technical scheme, the method comprises the following steps: in a Hadoop cluster, uploading processed process data to an HDFS (Hadoop Distributed File System) of Hadoop for storage according to the change of data volume; specifically, in a Hadoop cluster, executing three jobs in sequence: dividing similar process data into the same data block by adopting an LSH-based data division method, and projecting the similar process data to the same data node; identifying attribute subspacesof data on each data node; achieving a parallel subspace clustering process, generating a final clustering result from the sub-clusters obtained in the local clustering stage, and discovering a common recessive problem which influences the product quality and is hidden in a cluster set according to the clustering result. The method is applied to mechanical product quality analysis.

Description

technical field [0001] The invention discloses a mechanical product quality analysis method based on subspace clustering, which belongs to the technical field of mechanical product quality analysis. Background technique [0002] As an important basic industry of my country's national economy, the machinery manufacturing industry provides technical equipment and necessary guarantees for the entire national economy. With the development and improvement of product performance and product structure, the amount of information on production lines, production equipment and manufacturing processes has increased sharply. The support has transformed mechanical manufacturing from energy-driven to information-driven, thus opening the era of intelligent manufacturing. [0003] Product quality is the core of the development of manufacturing enterprises. Numerous links in the manufacturing process, complex process mechanisms, and dynamic changes in process parameters are all key factors ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06K9/62G06Q50/04
CPCG06Q10/06395G06Q50/04G06F18/23Y02P90/30
Inventor 庞宁张继福胡立华
Owner TAIYUAN UNIVERSITY OF SCIENCE AND TECHNOLOGY
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