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Due to the complex functional structure and harsh working environment of wind turbines, their degradation states are characterized by diversity, and the failure forms are often the result of the coupling of multiple faults, so it is not comprehensive to adopt the performance degradation process of one variable alone as a model for assessing the life and reliability of wind turbines. In order to more accurately reflect the correlation between internal and external performance indicators of the system, a failure physics-based multi-fault reliability modeling method for wind turbines was proposed. Firstly, the operating environment and fault characteristics of wind turbine under multi-stress coupling were analyzed, and the life distribution function was obtained by the failure physics-based reliability simulation analysis method and used as the marginal distribution function. Secondly, the two-stage estimation method was introduced to estimate the parameters of the model of Copula function when considering the failure mode correlation. The optimal Copula function was determined by comparing the rank correlation coefficient and squared euclidean distance of different types of Copula functions. Finally, a simplified wind turbine reliability model under multi-failure mode coupling is established by using Skla's theorem and the idea of stepwise analysis. The results show that the reliability results obtained when considering the correlation of reliability indexes are more reasonable, while the method avoids the conservative estimation of wind turbine life prediction and reliability assessment, and has better practicality and operability. [ABSTRACT FROM AUTHOR]

Regarding the impacts of failures among elevator components, a combination model based on decision-making trial and evaluation laboratory (DEMATEL) and interpretation structural model (ISM) was proposed to establish the hierarchical model for elevator component failure. The method of determining the direct impact matrix was enhanced. Firstly, the evaluation of the elevator-component fault correlation was obtained from various aspects. Secondly, the entropy weight method (EWM) was used to determine the weight of the evaluation and calculate the direct impact matrix. Finally, the elevator-component failure correlation model was utilized to derive the elevator-component failure causality and failure transmission rules. The results show that the motor, brake and speed limiter are strong-cause components, while the traction rope, car and guidance system components are strong-effect components. The elevator-component failure correlation rules manifest as either same-level or cross-level transmission. Through an analysis of component failure mechanisms, the fault transfer rules obtained through the proposed method align with the actual operation of the elevator system. [ABSTRACT FROM AUTHOR]

The maintenance cost of offshore wind farms accounts for a high proportion of the total cost of power generation. In order to reduce the operational and maintenance costs of offshore wind farms, based on a reliability threshold, a maintenance strategy is proposed in the paper that considers the fault-relatedness among subsystems and the subsystem fault risk levels of wind turbine units. This strategy includes fault risk levels, dual reliability thresholds, and a maintenance matrix. Firstly, a fault chain model is used to describe the fault relationships among subsystems of wind turbine units, and reliability models for each subsystem are established. Secondly, the concept of multi-level maintenance is introduced, and the optimization model of wind farm opportunity maintenance strategy considering the fault risk level is proposed. The risk factor of subsystem opportunity maintenance is optimized using particle swarm algorithm, and then the maintenance strategy of a single unit is determined. Thirdly, an offshore wind farm maintenance strategy optimization model based on the maintenance matrix is proposed by considering factors such as offshore accessibility and spare parts inventory. The model takes the minimum total maintenance cost per unit time as the objective function and dynamically adjusts the maintenance strategy according to the subsystem's spare parts inventory and failure risk level. Finally, a single wind turbine in an offshore wind farm is used as an example to analyse the impact of factors such as accessibility and multilevel maintenance on the wind farm opportunity maintenance strategy. The results show that the opportunity maintenance strategy considering the failure risk level can reduce the cost by 27.34% compared with the traditional opportunity maintenance strategy, which verifies the effectiveness of the proposed opportunity maintenance strategy in reducing maintenance costs.

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This paper presents an analysis of the fault correlation between CNC machine tool subsystems using decision laboratory analysis and the House of Reliability (HoR) methodology. Initially, the maintenance information of the machine tool and other hazard indicators is comprehensively analyzed based on the cognitive best worst method (CBWM) to assign weights of hazard indicators. The HoR method is then employed to perform fault correlation fusion, which results in comprehensive hazard analysis results of the machine tool subsystems considering the fault correlation. Finally, the results obtained from the fusion fault correlation and the traditional hazard analysis are compared. The results indicate that the proposed method can highlight the relatively important subsystems and the most vulnerable parts of the machine tools. Overall, the hazard analysis results of this paper contribute to the safe and reliable operational and maintenance optimization of CNC machine tools. [ABSTRACT FROM AUTHOR]

In recent years, with the development of new energy technology and the country’s strong support for electric vehicles, there is a lack of effective electric vehicle charging fault analysis and diagnosis methods at this stage. A comprehensive analysis of the working principle of the charging process of electric vehicles, based on the clarification of the failure mechanism of the power battery and charging equipment, analyzes the fault-related factors affecting the power battery and charging equipment from multiple angles, and summarizes the relationship between the power battery and charging equipment. The feature parameters related to equipment failure are discretized by the k-means clustering algorithm. Using the optimized FP-Growth algorithm based on weights, the association rules between the power battery and charging equipment failures and the characteristic parameters of the failure factors are mined, and the correlation of the failures is analyzed based on the association rules, and the correlation between the failure factors and the failures is obtained relevant level.

Considering the characteristics of mutual support system in which unit fault leads to the failure rate mutation, through the analysis of practical problems, using the theory of stochastic process, the paper gives the procedure and method of consumption forecast model of spare parts to establish the relay board mutual support system of a communication device. The applicability of the model is illustrated by examples. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Harbin Institute of Technology. Social Sciences Edition / Haerbin Gongye Daxue Xuebao. Shehui Kexue Ban is the property of Harbin Institute of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)