scholarly journals A Novel Quality Defects Diagnosis Method for the Manufacturing Process of Large Equipment Based on Product Gene Theory

Symmetry ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 685
Author(s):  
Wenxiang Xu ◽  
Chen Guo ◽  
Shunsheng Guo ◽  
Xixing Li
Keyword(s):  
Quality Control ◽  
Knowledge Base ◽  
Manufacturing Process ◽  
Comprehensive Evaluation ◽  
Fuzzy Comprehensive Evaluation ◽  
Gene Model ◽  
Information Granularity ◽  
Gene Theory ◽  
Diagnosis Method ◽  
Quality Diagnosis

Focusing on the problems of quality information management and quality defects diagnosis in the manufacturing process of large equipment, a novel quality defects diagnosis method based on product gene theory and knowledge base was developed. First, a product gene model and a sectional encoding method for the quality control of the manufacturing process of large equipment were proposed. In that model, the processing surface was the minimum information granularity to meet the production characteristics of large equipment and to improve the flexibility of the product gene model. Then, a similarity evaluation rule and an optimization method of the weights of elements based on particle swarm optimization (PSO) were addressed to filter the available knowledge of product gene from the product gene knowledge base. Aiming at the characteristic of many-to-many between quality defects and quality influence factors in some cases, a fuzzy comprehensive evaluation (FCE) method was developed for the further localization of diagnosis knowledge. Finally, an experiment of bearing spacer was applied to illustrate the proposed quality diagnosis approach. In the experiment, the data from the target gene and knowledge genes were described reasonably. On this basis, available knowledge genes could be accurately filtered with the proposed similarity rule and the method of filtration, where the PSO was proved to be effective. The diagnosis results of the experiment show that multiple factors lead to the defects that were verified. Therefore, the proposed quality defects diagnosis method is an effective way for quality control.

scholarly journals Design of intelligent diagnosis system for teaching quality based on wireless sensor network and data mining

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Yanping Zhang ◽  
Wanwei Huang
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Comprehensive Evaluation ◽  
Fuzzy Comprehensive Evaluation ◽  
Teaching Quality ◽  
Wireless Sensor ◽  
Diagnosis System ◽  
Intelligent Diagnosis ◽  
Transmission Structure ◽  
Quality Diagnosis

AbstractWith the popularization of computers and various mobile intelligent terminals, intelligent teaching systems based on learners are becoming more and more popular among learners. The above phenomenon has greatly affected and changed the current teaching quality diagnosis methods and models. However, the author found through investigation that the current intelligent teaching quality diagnosis still has different degrees of deficiencies in the design and implementation. In response to the above problems, this paper proposes a teaching quality intelligent diagnosis model based on the combination of wireless sensor networks and fuzzy comprehensive evaluation algorithms. First of all, this article is based on the wireless sensor network to link various levels of intelligent teaching systems, and constructs the information transmission structure of the teaching intelligent diagnosis system. Secondly, this article uses fuzzy comprehensive evaluation and convolutional neural network algorithms to evaluate and excavate intelligent teaching information. Finally, the model successfully passed the simulation test and simulation application, which can provide intelligent diagnosis of teaching quality for modern intelligent teaching system.

scholarly journals Design of Intelligent Diagnosis System for Teaching Quality Based on Wireless Sensor Network and Data Mining

2020 ◽  
Author(s):  
Yanping Zhang ◽  
Wanwei Huang
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Comprehensive Evaluation ◽  
Fuzzy Comprehensive Evaluation ◽  
Teaching Quality ◽  
Wireless Sensor ◽  
Diagnosis System ◽  
Intelligent Diagnosis ◽  
Transmission Structure ◽  
Quality Diagnosis

Abstract With the popularization of computers and various mobile intelligent terminals, intelligent teaching systems based on learners are becoming more and more popular among learners. The above phenomenon has greatly affected and changed the current teaching quality diagnosis methods and models. However, the author found through investigation that the current intelligent teaching quality diagnosis still has different degrees of deficiencies in the design and implementation. In response to the above problems, this paper proposes a teaching quality intelligent diagnosis model based on the combination of wireless sensor networks and fuzzy comprehensive evaluation algorithms. First of all, this article is based on the wireless sensor network to link various levels of intelligent teaching systems, and constructs the information transmission structure of the teaching intelligent diagnosis system. Secondly, this article uses fuzzy comprehensive evaluation and convolutional neural network algorithms to evaluate and excavate intelligent teaching information. Finally, the model successfully passed the simulation test and simulation application, which can provide intelligent diagnosis of teaching quality for modern intelligent teaching system.

scholarly journals Health diagnosis of nuclear power plant

2019 ◽  
Vol 16 (5) ◽  
pp. 172988141988065 ◽  
Author(s):  
Wangyu Xue ◽  
Xiu Li ◽  
Biqing Huang
Keyword(s):  
Power Plant ◽  
Nuclear Power Plant ◽  
Failure Mode ◽  
Nuclear Power ◽  
Evaluation Method ◽  
Comprehensive Evaluation ◽  
Fuzzy Comprehensive Evaluation ◽  
Comprehensive Evaluation Method ◽  
Diagnosis Method ◽  
Health Diagnosis

At present, nuclear power plant is developing rapidly, and its application has been involved in many aspects including life, military, industry and many other important fields, bringing benefits to people’s life. However, the nuclear power plant has a relatively special structure. Once a safety accident occurs, the consequences will be unimaginable, and the cost of its operation and maintenance will be relatively high. Therefore, how to effectively diagnose the health status of the nuclear power plant is an urgent problem to be solved. On the above-mentioned research background, we need to study nuclear power plant health diagnosis method. Considering the characteristic of the nuclear power plant system and special failure mode, both the safety and economy, a health condition diagnosis method based on analytic hierarchy process and fuzzy comprehensive evaluation method is proposed for the structural characteristics and functional characteristics of nuclear power plants. According to the special failure mode and complex system structure of nuclear power plant, the evaluation index system based on failure mode is constructed by laying the system using the hierarchical analysis method, and the system is scored by fuzzy comprehensive evaluation method. The health status makes a coarse-grained diagnosis and provides a reference for the development of the operation and maintenance strategy.

Intelligent Method for Process Quality Diagnosis and Improvement

2013 ◽  
Vol 333-335 ◽  
pp. 1332-1337
Author(s):  
Wen Jie Xu ◽  
Jin Yao
Keyword(s):  
Manufacturing Process ◽  
Input Parameter ◽  
Threshold Value ◽  
Process Quality ◽  
Quality Performance ◽  
Integrated Method ◽  
Output Quality ◽  
Input Parameters ◽  
Diagnosis Method ◽  
Quality Diagnosis

An intelligent quality diagnosis method for process quality diagnosis and improvement was proposed to find out influencing input parameters for output quality and then provide suggestion for quality engineering to adjust them to acquire high quality performance. The diagnosis method extends the traditional quality control and diagnosis method that only for the output quality of manufacturing process. It can detect the input parameters of the manufacturing process and provide sensitivities of input parameter for adjustment. BN-MTY method was applied to explain the reason of quality failure in T2 control chart and the root output quality indicators that aroused the process quality anomaly was located. The integrated method of neural network and sensitivity analysis was applied to get the weight and threshold value of neural cell in the forecasting network. his integrated quality diagnosis method can diagnose the input parameters and provide accurate sensitivities for quality improvement.

Intelligent Lighting Control System in Large-Scale Sports Competition Venues

2018 ◽  
pp. 172-182 ◽  
Author(s):  
Shengmin CAO
Keyword(s):  
Control System ◽  
Large Scale ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Fuzzy Comprehensive Evaluation ◽  
Practical Significance ◽  
Lighting Control ◽  
Sports Events ◽  
Planning And Design ◽  
Comprehensive Evaluation Model

This paper mainly studies the application of intelligent lighting control system in different sports events in large sports competition venues. We take the Xiantao Stadium, a large­scale sports competition venue in Zaozhuang City, Shandong Province as an example, to study its intelligent lighting control system. In this paper, the PID (proportion – integral – derivative) incremental control model and the Karatsuba multiplication model are used, and the intelligent lighting control system is designed and implemented by multi­level fuzzy comprehensive evaluation model. Finally, the paper evaluates the actual effect of the intelligent lighting control system. The research shows that the intelligent lighting control system designed in this paper can accurately control the lighting of different sports in large stadiums. The research in this paper has important practical significance for the planning and design of large­scale sports competition venues.

Emerging Techniques for the Characterization of Nano-Mechanical Properties of Integrated Circuit Components

2008 ◽  
Author(s):  
Nicholas Randall ◽  
Rahul Premachandran Nair
Keyword(s):  
Mechanical Properties ◽  
Quality Control ◽  
Integrated Circuits ◽  
Integrated Circuit ◽  
Manufacturing Process ◽  
Solder Bumps ◽  
Initial Work ◽  
Circuit Components ◽  
Materials Used

Abstract With the growing complexity of integrated circuits (IC) comes the issue of quality control during the manufacturing process. In order to avoid late realization of design flaws which could be very expensive, the characterization of the mechanical properties of the IC components needs to be carried out in a more efficient and standardized manner. The effects of changes in the manufacturing process and materials used on the functioning and reliability of the final device also need to be addressed. Initial work on accurately determining several key mechanical properties of bonding pads, solder bumps and coatings using a combination of different methods and equipment has been summarized.

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