Condition monitoring and fault diagnosis of planetary gearboxes: A review

Vibration based condition monitoring and fault diagnosis of wind turbine planetary gearbox: A review

Due to significant industrial demands toward software systems with increasing complexity and challenging quality requirements, software architecture design has become an important development activity and the research domain is rapidly evolving. In the last decades, software architecture optimization methods, which aim to automate the search for an optimal architecture design with respect to a (set of) quality attribute(s), have proliferated. However, the reported results are fragmented over different research communities, multiple system domains, and multiple quality attributes. To integrate the existing research results, we have performed a systematic literature review and analyzed the results of 188 research papers from the different research communities. Based on this survey, a taxonomy has been created which is used to classify the existing research. Furthermore, the systematic analysis of the research literature provided in this review aims to help the research community in consolidating the existing research efforts and deriving a research agenda for future developments.

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Software Architecture Optimization Methods: A Systematic Literature Review

Software architecture optimization methods: A systematic literature review

A review of stochastic resonance in rotating machine fault detection

Joint amplitude and frequency demodulation analysis based on local mean decomposition for fault diagnosis of planetary gearboxes

This paper introduces a hybrid dimension reduction method that combines kernel feature selection and kernel Fisher discriminant analysis (KFDA). In the first stage, a kernel feature selection method is proposed to remove redundant and irrelevant features for two purposes: (1) reducing computation burden of the entire fault diagnosis system and (2) alleviating the impact of irrelevant features on KFDA. In the second stage, KFDA is used to establish a more compact feature subset by extracting a smaller number of features. We use Gaussian radial basis function as the kernel function for the two kernel stages in the proposed method. A parameter selection method for this kernel is proposed to select the optimal values for the proposed method. Experimental results on fault level diagnosis demonstrate that the proposed hybrid dimension reduction method has advantages over other approaches that use feature selection or KFDA separately.

Fault level diagnosis for planetary gearboxes using hybrid kernel feature selection and kernel Fisher discriminant analysis

When solving multi-objective optimization problems subject to constraints in reliability-based design, it is desirable for the decision maker to have a sufficient number of solutions available for selection. However, many existing approaches either combine multiple objectives into a single objective or treat the objectives as penalties. This results in fewer optimal solutions than would be provided by a multi-objective approach. For such cases, a niched Pareto Genetic Algorithm (GA) may be a viable alternative. Unfortunately, it is often difficult to set penalty parameters that are required in these algorithms. In this paper, a multi-objective optimization algorithm is proposed that combines a niched Pareto GA with a constraint handling method that does not need penalty parameters. The proposed algorithm is based on Pareto tournament and equivalence sharing, and involves the following components: search for feasible solutions, selection of non-dominated solutions and maintenance of diversified solutions. ...

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Genetic-algorithm-based optimal apportionment of reliability and redundancy under multiple objectives

Support vector machine based data processing algorithm for wear degree classification of slurry pump systems

The k-out-of-n:G system is widely used in reliability and maintenance engineering. We consider a general k-out-of-n:G system which has identical components with identical repair time and lifetime distributions. There are R identical repairmen in the system. The shut-off rules of suspended animation, continuous operation, and a mixture of these two are studied. Repair times and lifetimes are assumed to be statistically independent and exponentially distributed (within, and between). We derive new closed form solutions for important performance measures including steady state availability, mean time to system failure, and mean time to first system failure.

Jian Qu

Papers

Joint amplitude and frequency demodulation analysis based on local mean decomposition for fault diagnosis of planetary gearboxes

Fault level diagnosis for planetary gearboxes using hybrid kernel feature selection and kernel Fisher discriminant analysis

Genetic-algorithm-based optimal apportionment of reliability and redundancy under multiple objectives

Support vector machine based data processing algorithm for wear degree classification of slurry pump systems

Reliability and Availability Analysis of a Repairable $k$ -out-of- $n:G$ System With $R$ Repairmen Subject to Shut-Off Rules