Matches in SemOpenAlex for { <https://semopenalex.org/work/W2318442936> ?p ?o ?g. }
Showing items 1 to 96 of
96
with 100 items per page.
- W2318442936 abstract "In this paper, a fault diagnosis method for hoisting machinery based on multi-source information fusion and BPNN that has a fast training time and a high accuracy rate and can be converted to on-line monitoring system easily is provided. This method can be used to help people to real-time monitoring equipment and components and trace hazards. Compared with traditional methods currently used, the method has higher diagnostic accuracy and wider diagnostic range. Keywords-multi-source information fusion; back propagation neural network; fault diagnosis; hoisting machinery introduction With the advancement of China's modernization process, the hoisting machinery is widely used in infrastructure construction. The hoisting machinery plays an important role in today's society. Once the related accident occurs, it will cause great bodily injury and property damage. Therefore, it is necessary to research the fault diagnosis method for the hoisting machinery to reduce the occurrence of accidents (1). However, the hoisting machinery actually is a kind of special equipment with most danger factors and biggest accident probability. The machine itself, the environment and the operators are potential hazards that may cause huge personal and property risk. Due to the special structure and movement forms, single-sensor cannot guarantee data acquisition normal. Only when multi-sensor information fusion is used, the reliable assessment of the equipment status can be ensured (2). To solve the problem, a fault diagnosis method for the hoisting machinery based on multi-source information fusion is proposed to realize hazard identification and get the most objective and true security information. The specific algorithm uses the back propagation neural network as the basis algorithm and be realized using Matlab. The modeling method and algorithms are detailed in Section 2 and the implementation method is detailed in Section 3. I. METHODS" @default.
- W2318442936 created "2016-06-24" @default.
- W2318442936 creator A5050808302 @default.
- W2318442936 creator A5082314036 @default.
- W2318442936 date "2016-01-01" @default.
- W2318442936 modified "2023-09-26" @default.
- W2318442936 title "Research on the Fault Diagnosis Method for Hoisting Machinery Based on Multi-source Information Fusion and BPNN" @default.
- W2318442936 cites W1481376396 @default.
- W2318442936 cites W2023787363 @default.
- W2318442936 cites W2029963932 @default.
- W2318442936 cites W2048012762 @default.
- W2318442936 cites W2057689952 @default.
- W2318442936 cites W2220660951 @default.
- W2318442936 cites W2386659552 @default.
- W2318442936 doi "https://doi.org/10.2991/icaita-16.2016.70" @default.
- W2318442936 hasPublicationYear "2016" @default.
- W2318442936 type Work @default.
- W2318442936 sameAs 2318442936 @default.
- W2318442936 citedByCount "0" @default.
- W2318442936 crossrefType "proceedings-article" @default.
- W2318442936 hasAuthorship W2318442936A5050808302 @default.
- W2318442936 hasAuthorship W2318442936A5082314036 @default.
- W2318442936 hasBestOaLocation W23184429361 @default.
- W2318442936 hasConcept C111472728 @default.
- W2318442936 hasConcept C111919701 @default.
- W2318442936 hasConcept C112930515 @default.
- W2318442936 hasConcept C116834253 @default.
- W2318442936 hasConcept C127313418 @default.
- W2318442936 hasConcept C127413603 @default.
- W2318442936 hasConcept C138885662 @default.
- W2318442936 hasConcept C154945302 @default.
- W2318442936 hasConcept C165205528 @default.
- W2318442936 hasConcept C175551986 @default.
- W2318442936 hasConcept C178790620 @default.
- W2318442936 hasConcept C185592680 @default.
- W2318442936 hasConcept C189950617 @default.
- W2318442936 hasConcept C200601418 @default.
- W2318442936 hasConcept C2982962833 @default.
- W2318442936 hasConcept C33954974 @default.
- W2318442936 hasConcept C41008148 @default.
- W2318442936 hasConcept C49261128 @default.
- W2318442936 hasConcept C59822182 @default.
- W2318442936 hasConcept C71924100 @default.
- W2318442936 hasConcept C79403827 @default.
- W2318442936 hasConcept C86803240 @default.
- W2318442936 hasConcept C98045186 @default.
- W2318442936 hasConceptScore W2318442936C111472728 @default.
- W2318442936 hasConceptScore W2318442936C111919701 @default.
- W2318442936 hasConceptScore W2318442936C112930515 @default.
- W2318442936 hasConceptScore W2318442936C116834253 @default.
- W2318442936 hasConceptScore W2318442936C127313418 @default.
- W2318442936 hasConceptScore W2318442936C127413603 @default.
- W2318442936 hasConceptScore W2318442936C138885662 @default.
- W2318442936 hasConceptScore W2318442936C154945302 @default.
- W2318442936 hasConceptScore W2318442936C165205528 @default.
- W2318442936 hasConceptScore W2318442936C175551986 @default.
- W2318442936 hasConceptScore W2318442936C178790620 @default.
- W2318442936 hasConceptScore W2318442936C185592680 @default.
- W2318442936 hasConceptScore W2318442936C189950617 @default.
- W2318442936 hasConceptScore W2318442936C200601418 @default.
- W2318442936 hasConceptScore W2318442936C2982962833 @default.
- W2318442936 hasConceptScore W2318442936C33954974 @default.
- W2318442936 hasConceptScore W2318442936C41008148 @default.
- W2318442936 hasConceptScore W2318442936C49261128 @default.
- W2318442936 hasConceptScore W2318442936C59822182 @default.
- W2318442936 hasConceptScore W2318442936C71924100 @default.
- W2318442936 hasConceptScore W2318442936C79403827 @default.
- W2318442936 hasConceptScore W2318442936C86803240 @default.
- W2318442936 hasConceptScore W2318442936C98045186 @default.
- W2318442936 hasLocation W23184429361 @default.
- W2318442936 hasOpenAccess W2318442936 @default.
- W2318442936 hasPrimaryLocation W23184429361 @default.
- W2318442936 hasRelatedWork W132957786 @default.
- W2318442936 hasRelatedWork W2062186694 @default.
- W2318442936 hasRelatedWork W2063447049 @default.
- W2318442936 hasRelatedWork W2102605237 @default.
- W2318442936 hasRelatedWork W2133426695 @default.
- W2318442936 hasRelatedWork W2133775348 @default.
- W2318442936 hasRelatedWork W2348067631 @default.
- W2318442936 hasRelatedWork W2353591200 @default.
- W2318442936 hasRelatedWork W2375662494 @default.
- W2318442936 hasRelatedWork W2392573273 @default.
- W2318442936 hasRelatedWork W2392670279 @default.
- W2318442936 hasRelatedWork W2460850363 @default.
- W2318442936 hasRelatedWork W2917014261 @default.
- W2318442936 hasRelatedWork W2946493557 @default.
- W2318442936 hasRelatedWork W2948027642 @default.
- W2318442936 hasRelatedWork W2970235046 @default.
- W2318442936 hasRelatedWork W3026005887 @default.
- W2318442936 hasRelatedWork W3186191971 @default.
- W2318442936 hasRelatedWork W2855359650 @default.
- W2318442936 hasRelatedWork W2959538898 @default.
- W2318442936 isParatext "false" @default.
- W2318442936 isRetracted "false" @default.
- W2318442936 magId "2318442936" @default.
- W2318442936 workType "article" @default.