Health state evaluation of an item: A general framework and graphical representation

2008 ◽  
Vol 93 (1) ◽  
pp. 89-99 ◽  
Author(s):  
R. Jiang ◽  
A.K.S. Jardine
Keyword(s):  
General Framework ◽  
Graphical Representation ◽  
Health State ◽  
State Evaluation

Health State Evaluation of Continuous Girder Bridge Based on Fuzzy Analytic Hierarchy Process

2012 ◽  
Vol 178-181 ◽  
pp. 2285-2289
Author(s):  
Hai Tao Li
Keyword(s):  
Analytic Hierarchy Process ◽  
Technical State ◽  
Fuzzy Analytic Hierarchy Process ◽  
Health Evaluation ◽  
Health State ◽  
Fuzzy Evaluation ◽  
Analytic Hierarchy ◽  
State Evaluation ◽  
Degree Of Membership ◽  
Hierarchy Process

Based on fuzzy analytic hierarchy process, The model of bridge health evaluation is established using the quantification relations between the bridge technical state evaluation grade and degree of membership function of bridge health evaluation, making use of the computed result of various index of degree of membership value and weight, obtains all levels of fuzzy evaluation collection. According to the maximum membership principles to evaluate the technical state grade of bridge structure the corresponding level, and with its result to instruct the decision-making of bridge maintenance and strengthening.

Health‐state evaluation for aerospace systems

2013 ◽  
Vol 85 (2) ◽  
pp. 115-125 ◽  
Author(s):  
Xiaodong Tan ◽  
Jing Qiu ◽  
Guanjun Liu ◽  
Kehong Lv
Keyword(s):  
Health State ◽  
State Evaluation ◽  
Aerospace Systems

Evaluation of Health State of Mining Equipment by Dynamic Weighted Fuzzy Grey Method

2014 ◽  
Vol 528 ◽  
pp. 222-231 ◽  
Author(s):  
Xu Qian ◽  
Jin Li ◽  
Wei Tao Liu ◽  
Tian Zi Wang ◽  
Xv Feng Fan
Keyword(s):  
Evaluation System ◽  
Weighting Function ◽  
Influence Factors ◽  
Indicator System ◽  
The State ◽  
Operating Conditions ◽  
Health State ◽  
Mining Equipment ◽  
Data Set ◽  
State Evaluation

The state evaluation of mining electromechanical equipment is important but complicated, for the complexity, nonlinearity and the ambiguity of the influence factors. In this paper, a novel indicator system to assess the state of mining equipment is constructed from three main aspects, namely the product quality of the equipment, their operating conditions and statistic data of historical states. The ambiguity-fuzzy method and grey-sum method are both employed to evaluate different influence factors, and are summed up together as the final evaluation result by dynamic weighting function, which is derived from a modified expert scoring mechanism we propose. We further implement the proposed evaluation system and verify the effectiveness of the evaluation system through real data set based experiments. The experimental results indicate that this system is of important guiding significance to the state evaluation of coal mine equipment and safe production in coal mines.

Evaluation Model of Bridges Health State Based on DHNN

2014 ◽  
Vol 1079-1080 ◽  
pp. 207-211
Author(s):  
Min He ◽  
Rui Guang Hu ◽  
Shi Le ◽  
Liang Chen
Keyword(s):  
Neural Networks ◽  
Associative Memory ◽  
Evaluation Model ◽  
Memory Capacity ◽  
Iterative Learning ◽  
Health Evaluation ◽  
Health State ◽  
Outer Product ◽  
State Evaluation ◽  
Product Method

Inthis paper, according to the more important ten evaluation indicators, the fourgrades ideal evaluation is established corresponding to the level of healthstate of bridges. Combined with associative memory capacity of discreteHopfield neural networks, a new health state evaluation of bridges ispresented. Five bridges is evaluated by the model, the network connectionweights is obtained by iterative learning using the outer product method. Thesimulation results shows that the health evaluation model can evaluate thehealth state of bridges fast, accurately and intuitively.

scholarly journals A Mission Reliability-Driven Manufacturing System Health State Evaluation Method Based on Fusion of Operational Data

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 442 ◽  
Author(s):  
Xiao Han ◽  
Zili Wang ◽  
Yihai He ◽  
Yixiao Zhao ◽  
Zhaoxiang Chen ◽  
...  
Keyword(s):  
Manufacturing Systems ◽  
Manufacturing System ◽  
Evaluation Method ◽  
Rapid Development ◽  
Evidence Theory ◽  
System Level ◽  
Health State ◽  
Theory Approach ◽  
State Evaluation ◽  
Operational Data

The rapid development of complexity and intelligence in manufacturing systems leads to an increase in potential operational risks and therefore requires a more comprehensive system-level health diagnostics approach. Based on the massive multi-source operational data collected by smart sensors, this paper proposes a mission reliability-driven manufacturing system health state evaluation method. Characteristic attributes affecting the mission reliability are monitored and analyzed based on different sensor groups, including the performance state of the manufacturing equipment, the execution state of the production task and the quality state of the manufactured product. The Dempster-Shafer (D-S) evidence theory approach is used to diagnose the health state of the manufacturing system. Results of a case study show that the proposed evaluation method can dynamically and effectively characterize the actual health state of manufacturing systems.

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