Fault Diagnosis of Hydraulic Pump Based on Multi-Sensor Data Fusion

Liu, Ying; Zuo, Dun Wen; Wang, Yao Hua; Han, Jun; Yang, Xiao Qiang

doi:10.4028/www.scientific.net/amm.33.539

Cited by 2 publications

(3 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…At the end of the 20th century, the concept of data mining was proposed and popularized. The current research on data mining is divided into the following categories: classification [20], clustering [21], association analysis [22], rule analysis, etc., mainly including neural network [23], Logistic regression [24], Apriori algorithm, FP-Growth algorithm [25] and other data mining methods. Literature established an automatic control model of input information based on data mining technology, which was used to control the pharmaceutical education resource library to automatically input information and improve work efficiency [26].…”

Section: Literature Reviewmentioning

confidence: 99%

Hidden Danger Association Mining for Water Conservancy Projects Based on Task Scenario-Driven

Tao

Zhang

et al. 2023

Water

View full text Add to dashboard Cite

With the rapid development of water conservancy engineering and infrastructure construction, there are many safety hazards in the construction process of water conservancy engineering, so it is of great significance to study the potential hazards in the construction process. In this context, this paper proposes a task scenario-based association mining method for hydraulic engineering hidden danger records. By analyzing transaction characteristics, the traditional Apriori algorithm is improved to optimize pruning results and generate hidden danger association rules. The research results of this paper have been successfully applied to the investigation and management of hidden dangers in the Xinmenghe dredging project. Based on the mapping of association rules driven by task scenarios, hidden dangers association rules in specific task scenarios are mined to assist construction safety managers in hidden dangers investigation, which reduces the complexity of the algorithm, reduces the running time of the algorithm and improves the efficiency of the algorithm.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Hidden Danger Association Mining for Water Conservancy Projects Based on Task Scenario-Driven

Tao

Zhang

et al. 2023

Water

View full text Add to dashboard Cite

show abstract

“…The use of multiple sensors becomes widespread. New challenges have arisen with regard to making a more reasonable inference based on Dempster-Shafer evidence theory (D-S theory) using multi-sensor data [1][2][3]. There are two main problems with fault diagnosis using multisensor data.…”

Section: Introductionmentioning

confidence: 99%

“…Ref. [2] presents a new combination technique based on the D-S theory which adapts to training data so that the overall mean square error is minimized. In [3] a comparison between Bayesian and Dempster-Shafer approaches is done.…”

Section: Introductionmentioning

confidence: 99%

Multisensor fault diagnosis based on data fusion using D-S theory

Quan

Peng

2014

Proceedings of the 33rd Chinese Control Conference

View full text Add to dashboard Cite

In multisensor fault diagnosis system, a relationship between the parameter space of feature and the type space for engine fault needs to be established. Also the problem that the diagnostic results from different sensors for the same engine may conflict needs to be addressed. The method of fault diagnosis based on D-S evidence theory using multisensor data fusion can solve the problems above to a large extent. The paper first discussed D-S theory in conjunction with fault diagnosis system; then an instance of fusion diagnosis using two sensors was given; finally we compared the simulation results in single sensor with fusion diagnosis. Analysis shows that the method based on D-S theory can solve the problem of evidence conflict in multisensor fault diagnosis effectively, as well as improve the accuracy of fault diagnosis decision to some extent.

show abstract

Fault Diagnosis of Hydraulic Pump Based on Multi-Sensor Data Fusion

Cited by 2 publications

References 0 publications

Hidden Danger Association Mining for Water Conservancy Projects Based on Task Scenario-Driven

Hidden Danger Association Mining for Water Conservancy Projects Based on Task Scenario-Driven

Multisensor fault diagnosis based on data fusion using D-S theory

Contact Info

Product

Resources

About