{"title":"基于Labview的船舶仿真电路故障诊断程序","authors":"Pei Sheng, Heng Li, Liming Chen, Qingjiang Wang","doi":"10.1109/ICCEIC51584.2020.00057","DOIUrl":null,"url":null,"abstract":"There are a lot of adjustable components in the equipment of some ships of our army, which can make the key parameters meet the requirements of the indexes by means of artificial adjustment. To this end, a set of targeted fault feature extraction algorithm and fault classification method is designed, and Labview is used to complete the development of the program. The software USES virtual oscilloscope to complete signal acquisition, local characteristic scale decomposition and fractal box dimension algorithm to complete fault feature extraction, and probabilistic neural network to complete fault classification determination. Finally, taking the typical fault state of a circuit as an example, this software is used to judge the fault category. The results show that the software can effectively deal with fault state recognition in the case of multi-point continuous out-of-tolerance.","PeriodicalId":135840,"journal":{"name":"2020 International Conference on Computer Engineering and Intelligent Control (ICCEIC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fault diagnosis program of ship simulation circuit based on Labview\",\"authors\":\"Pei Sheng, Heng Li, Liming Chen, Qingjiang Wang\",\"doi\":\"10.1109/ICCEIC51584.2020.00057\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"There are a lot of adjustable components in the equipment of some ships of our army, which can make the key parameters meet the requirements of the indexes by means of artificial adjustment. To this end, a set of targeted fault feature extraction algorithm and fault classification method is designed, and Labview is used to complete the development of the program. The software USES virtual oscilloscope to complete signal acquisition, local characteristic scale decomposition and fractal box dimension algorithm to complete fault feature extraction, and probabilistic neural network to complete fault classification determination. Finally, taking the typical fault state of a circuit as an example, this software is used to judge the fault category. The results show that the software can effectively deal with fault state recognition in the case of multi-point continuous out-of-tolerance.\",\"PeriodicalId\":135840,\"journal\":{\"name\":\"2020 International Conference on Computer Engineering and Intelligent Control (ICCEIC)\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Conference on Computer Engineering and Intelligent Control (ICCEIC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCEIC51584.2020.00057\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on Computer Engineering and Intelligent Control (ICCEIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCEIC51584.2020.00057","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fault diagnosis program of ship simulation circuit based on Labview
There are a lot of adjustable components in the equipment of some ships of our army, which can make the key parameters meet the requirements of the indexes by means of artificial adjustment. To this end, a set of targeted fault feature extraction algorithm and fault classification method is designed, and Labview is used to complete the development of the program. The software USES virtual oscilloscope to complete signal acquisition, local characteristic scale decomposition and fractal box dimension algorithm to complete fault feature extraction, and probabilistic neural network to complete fault classification determination. Finally, taking the typical fault state of a circuit as an example, this software is used to judge the fault category. The results show that the software can effectively deal with fault state recognition in the case of multi-point continuous out-of-tolerance.