An approach to performance assessment and fault diagnosis for rotating machinery equipment

Tao, Xiaochuang; Lu, Chen; Chuan, Lu; Wang, Zili

doi:10.1186/1687-6180-2013-5

Cited by 20 publications

(15 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For example, the Euclidean distance in [12,13] can determine the diagnosability by the distance between the state variables. In addition, the Mahalanobis distance used in [14,15,16,17] and the improved support vector machine method proposed in [18,19] can be used to evaluate the diagnosability by introducing state-to-state distances.…”

Section: Permissible Area Of Measurement Errors For Evaluation Of mentioning

confidence: 99%

Permissible Area Analyses of Measurement Errors with Required Fault Diagnosability Performance

Jiang

2019

Sensors

View full text Add to dashboard Cite

Fault diagnosability is the basis of fault diagnosis. Fault diagnosability evaluation refers to whether there is enough measurable information in the system to support the rapid and reliable detection of a fault. However, due to unavoidable measurement errors in a system, a quantitative evaluation index of system fault diagnosability is inadequate. In order to overcome the adverse effects of measurement errors, improve the accuracy of the quantitative evaluation of fault diagnosability, and improve the safety level of the system, a method for a permissible area analysis of measurement errors for a quantitative evaluation of fault diagnosability is proposed in this paper. Firstly, in order for the residuals obey normal distribution, a design method of the permissible area of measurement errors based on the Kullback–Leibler divergence (KLD) is given. Secondly, two key problems in calculating the KLD are solved by sparse kernel density estimation and the Monte Carlo method. Finally, the feasibility and validity of the method are analyzed through a case study.

show abstract

Section: Permissible Area Of Measurement Errors For Evaluation Of mentioning

confidence: 99%

Permissible Area Analyses of Measurement Errors with Required Fault Diagnosability Performance

Jiang

2019

Sensors

View full text Add to dashboard Cite

show abstract

“…When the standard is reached, the lower limit 95%V corresponded to a score of 60 and the upper limit 110%V corresponded to a score of 100. The three groups of test result corresponding to different periods during stable operation were averaged as the primary test result, and the score was calculated according to S = / − 95% 15% × 40 + 60 (5) where S is the item score, is the test displacement, and is the nominal displacement. The item score of the no-load test of the tested pump was 76.1.…”

Section: Analyses Of Comprehensive Evaluation For Working Performancementioning

confidence: 99%

“…Selvakumar J. et al determined the key parts of centrifugal pump and analyzed the reliability by mathematical modeling and FEM analyses [4]. Xiaochuang Tao et al introduced a method to evaluate the performance and diagnose the fault of rotating equipment based on the Fisher discriminant analysis and Mahalanobis distance [5]. By using proposing assessment methods, Ding et al collected and processed the vibration signal of hydraulic pumps to monitor their working condition in real time and diagnose the faults of the pumps [6,7].…”

Section: Introductionmentioning

confidence: 99%

The Research on Comprehensive Performance Evaluation of Axial Piston Pump Based on AHP

Wan

Zeng

et al. 2018

Mathematical Problems in Engineering

View full text Add to dashboard Cite

The axial piston pump is an important industrial power element, and its performance directly affects the operation of the system. However, owing to its complex structure and harsh operational environment, the actual operational performance of the axial piston pump is difficult to be assessed accurately, which makes ensuring the normal operation of the hydraulic system difficult. To improve the evaluation method for an axial piston pump, a comprehensive performance evaluation system was proposed based on analytic hierarchy process (AHP), which could assess the performance of an axial piston pump on the basis of theoretical analysis, test, operator interaction, and application. Considering a model of load-sensitive axial piston pump with good operability as an example, the model development and simulation of the pump were carried out based on AMESim and the pump was tested using a developed performance test bed for axial piston pump. The weights of factors in the evaluation system were determined on the basis of the simulation results, analyses, and calculation. The above results were used to comprehensively analyze the tested pump and design a set of comprehensive performance evaluation software. The evaluation result was nearly identical to the actual usage, which verified the feasibility of the designed evaluation system.

show abstract

“…This manner yields the fault information loss. Similar to [15], feature selection is an inevitable topic in [27]. Frequency spectrum analysis is a visual inspection method which is applied to select decomposition scale so that the work in [27] is not suitable for diagnosing fault automatically.…”

Section: Case Studymentioning

confidence: 99%

“…Similar to [15], feature selection is an inevitable topic in [27]. Frequency spectrum analysis is a visual inspection method which is applied to select decomposition scale so that the work in [27] is not suitable for diagnosing fault automatically. In this paper, different from the published works, SVD is applied to divide the original space into state space and residual space rather than to decompose modes.…”

Section: Case Studymentioning

confidence: 99%

Fault diagnosis of rolling bearing using CVA based detector

Wang¹,

Hong-xia²,

Yang³

2016

J. vibroeng.

View full text Add to dashboard Cite

There are two key problems in bearing fault diagnosis that need to be addressed, one is feature selection, the other is faulty dataset problem. On the one hand, signal decomposition methods are popular ways to decompose signal into a number of modes of interest, while the most interesting modes need to be selected to represent original signal. This procedure may easily lead to loss of important information. On the other hand, most of works adopt the faulty data to train fault diagnosis classifier, while the faulty data sets are difficult to collect in real life. Hence many existing methods are unsuitable for practical application. Moreover, a high number of researchers introduce various hybrid methods to improve the ability of original methods, which increases the complexity of fault diagnosis. To solve these problems, firstly, a canonical variate analysis (CVA) detector based on visual inspection is proposed to classify operating states. Healthy dataset obtained under normal condition is applied for building a reference model and generating a threshold. CVA transforms the unknown variable into state space and residual space, then and metrics are used to capture the variation in the two spaces, respectively. The metrics of variable compared with reference model will determine the state of rolling bearing. Considering that the threshold of proposed detector is likely to be exceeded, and visual inspection fails to identify bearing fault automatically. Then the means of and metrics are presented to enlarge the distance between normal and abnormal conditions to avoid those drawbacks. At last, experiment and comparison are conducted to verify the capability of the proposed work. The results demonstrate that the proposed work is simple and effective in bearing fault diagnosis.

show abstract

An approach to performance assessment and fault diagnosis for rotating machinery equipment

Cited by 20 publications

References 32 publications

Permissible Area Analyses of Measurement Errors with Required Fault Diagnosability Performance

Permissible Area Analyses of Measurement Errors with Required Fault Diagnosability Performance

The Research on Comprehensive Performance Evaluation of Axial Piston Pump Based on AHP

Fault diagnosis of rolling bearing using CVA based detector

Contact Info

Product

Resources

About