LED Landscape Lighting Equipment Fault Diagnosis Research
Aiming at the fault diagnosis characteristics of LED landscape lighting equipment, a class of genetic algorithm improved particle swarm optimization optimized wavelet neural network model is constructed. This fusion algorithm introduces the idea of cross factors and inertia weights in the genetic al...
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| Veröffentlicht in: | Journal of physics. Conference series 2020-10, Vol.1650 (3), p.32142 |
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| container_issue | 3 |
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| container_title | Journal of physics. Conference series |
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| creator | Tian, Zhihong Zhao, Yuwei Zheng, Zicheng Meng, Xiangang |
| description | Aiming at the fault diagnosis characteristics of LED landscape lighting equipment, a class of genetic algorithm improved particle swarm optimization optimized wavelet neural network model is constructed. This fusion algorithm introduces the idea of cross factors and inertia weights in the genetic algorithm to the basic particle swarm optimization algorithm, and adjusts for the traits of the standard wavelet neural network that has a slow convergence rate and might fall into local extreme values. The simulation results prove that this fusion algorithm can be efficaciously applied to the fault diagnosis of LED landscape lighting equipment and meet the needs of real-time monitoring of equipment. |
| doi_str_mv | 10.1088/1742-6596/1650/3/032142 |
| format | Article |
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The simulation results prove that this fusion algorithm can be efficaciously applied to the fault diagnosis of LED landscape lighting equipment and meet the needs of real-time monitoring of equipment.</description><subject>Extreme values</subject><subject>Fault diagnosis</subject><subject>Genetic algorithms</subject><subject>Light emitting diodes</subject><subject>Lighting equipment</subject><subject>Neural networks</subject><subject>Particle swarm optimization</subject><subject>Physics</subject><issn>1742-6588</issn><issn>1742-6596</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>O3W</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNqFkFtLw0AQhRdRsFZ_gwHfhJq9ZLO7j1JbLwQUL8_LbLJpt7RJups8-O9NiFQEwXmZgTlnzvAhdEnwDcFSxkQkdJZylcYk5ThmMWaUJPQITQ6b48Ms5Sk6C2GDMetLTJDKFndRBlURcmhslLnVunXVKlrsO9fsbNVGS-i2bXTnYFXVwYXo1QYLPl-fo5MStsFefPcp-lgu3ucPs-z5_nF-m81yOmSqtDA2YVQITJSQUAiDjaGUSsoVkyB4boBASjnB1BIjQJqkfzTBtuRGAZuiq_Fu4-t9Z0OrN3Xnqz5SUy4IFlKotFeJUZX7OgRvS914twP_qQnWAyc9ENADDT1w0kyPnHonG52ubn5O_--6_sP19DJ_-y3UTVGyL22cdSE</recordid><startdate>20201001</startdate><enddate>20201001</enddate><creator>Tian, Zhihong</creator><creator>Zhao, Yuwei</creator><creator>Zheng, Zicheng</creator><creator>Meng, Xiangang</creator><general>IOP Publishing</general><scope>O3W</scope><scope>TSCCA</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>H8D</scope><scope>HCIFZ</scope><scope>L7M</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope></search><sort><creationdate>20201001</creationdate><title>LED Landscape Lighting Equipment Fault Diagnosis Research</title><author>Tian, Zhihong ; Zhao, Yuwei ; Zheng, Zicheng ; Meng, Xiangang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2742-96dbe4327701978ad7b0bb222825938a75cba1a625102e1b7a8b465840ef5b9a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Extreme values</topic><topic>Fault diagnosis</topic><topic>Genetic algorithms</topic><topic>Light emitting diodes</topic><topic>Lighting equipment</topic><topic>Neural networks</topic><topic>Particle swarm optimization</topic><topic>Physics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Tian, Zhihong</creatorcontrib><creatorcontrib>Zhao, Yuwei</creatorcontrib><creatorcontrib>Zheng, Zicheng</creatorcontrib><creatorcontrib>Meng, Xiangang</creatorcontrib><collection>Institute of Physics Open Access Journal Titles</collection><collection>IOPscience (Open Access)</collection><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Aerospace Database</collection><collection>SciTech Premium Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><jtitle>Journal of physics. 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| subjects | Extreme values Fault diagnosis Genetic algorithms Light emitting diodes Lighting equipment Neural networks Particle swarm optimization Physics |
| title | LED Landscape Lighting Equipment Fault Diagnosis Research |
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