F. Castaño, R. Haber, Raúl M. del Toro, Gerardo Beruvides
{"title":"混合增量建模在微加工过程表面粗糙度预测中的应用","authors":"F. Castaño, R. Haber, Raúl M. del Toro, Gerardo Beruvides","doi":"10.1109/CIES.2014.7011831","DOIUrl":null,"url":null,"abstract":"This paper presents the application of a hybrid incremental modeling strategy (HIM) for real-time estimation of surface roughness in micromachining processes. This strategy essentially consists of two steps. First, a representative hybrid incremental model of micromachining process is obtained. The final result of this model describes output as a function of two inputs (feed per tooth quadratic and vibration mean quadratic (rms) in the Z axis) and output (surface roughness Ra). Second, the hybrid incremental model is evaluated in real time for predicting the surface roughness. The model is experimentally tested by embedding the computational procedure in a real-time monitoring system of surface roughness. The prototype evaluation shows a success rate in the estimate of surface roughness about 80%. These results are the basement for developing a new generation of embedded systems for monitoring surface roughness of micro components in real time and the further exploitation of the monitoring system at industrial level.","PeriodicalId":287779,"journal":{"name":"2014 IEEE Symposium on Computational Intelligence for Engineering Solutions (CIES)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Application of hybrid incremental modeling for predicting surface roughness in micromachining processes\",\"authors\":\"F. Castaño, R. Haber, Raúl M. del Toro, Gerardo Beruvides\",\"doi\":\"10.1109/CIES.2014.7011831\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents the application of a hybrid incremental modeling strategy (HIM) for real-time estimation of surface roughness in micromachining processes. This strategy essentially consists of two steps. First, a representative hybrid incremental model of micromachining process is obtained. The final result of this model describes output as a function of two inputs (feed per tooth quadratic and vibration mean quadratic (rms) in the Z axis) and output (surface roughness Ra). Second, the hybrid incremental model is evaluated in real time for predicting the surface roughness. The model is experimentally tested by embedding the computational procedure in a real-time monitoring system of surface roughness. The prototype evaluation shows a success rate in the estimate of surface roughness about 80%. These results are the basement for developing a new generation of embedded systems for monitoring surface roughness of micro components in real time and the further exploitation of the monitoring system at industrial level.\",\"PeriodicalId\":287779,\"journal\":{\"name\":\"2014 IEEE Symposium on Computational Intelligence for Engineering Solutions (CIES)\",\"volume\":\"61 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE Symposium on Computational Intelligence for Engineering Solutions (CIES)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIES.2014.7011831\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE Symposium on Computational Intelligence for Engineering Solutions (CIES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIES.2014.7011831","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Application of hybrid incremental modeling for predicting surface roughness in micromachining processes
This paper presents the application of a hybrid incremental modeling strategy (HIM) for real-time estimation of surface roughness in micromachining processes. This strategy essentially consists of two steps. First, a representative hybrid incremental model of micromachining process is obtained. The final result of this model describes output as a function of two inputs (feed per tooth quadratic and vibration mean quadratic (rms) in the Z axis) and output (surface roughness Ra). Second, the hybrid incremental model is evaluated in real time for predicting the surface roughness. The model is experimentally tested by embedding the computational procedure in a real-time monitoring system of surface roughness. The prototype evaluation shows a success rate in the estimate of surface roughness about 80%. These results are the basement for developing a new generation of embedded systems for monitoring surface roughness of micro components in real time and the further exploitation of the monitoring system at industrial level.