Antonio Guerra-Sancho, Carlos Domínguez-Monferrer, María Henar Miguélez, José Luis Cantero
{"title":"基于主轴功耗分析的航空工业钻孔系统刀具突变失效检测","authors":"Antonio Guerra-Sancho, Carlos Domínguez-Monferrer, María Henar Miguélez, José Luis Cantero","doi":"10.4028/p-d3tseu","DOIUrl":null,"url":null,"abstract":"The aeronautical industry is at the forefront of the fourth industrial revolution, which implies an exponential deployment of monitorization, Data Analytics, and connectivity. In alignment with this new paradigm, this research work presents a Catastrophic Tool Failure (CTF) analysis based on spindle power consumption monitoring in an industrial aircraft fuselage drilling process. In the case under study, the airframe components are arranged in hybrid stacks of Carbon Fiber Reinforced Plastic (CFRP) and titanium (Ti6Al4V) during drilling, which adds to the highly variable industrial machining conditions. This inherent complexity can lead to CTF, a significant concern due to its associated cost and time, especially in automatic processes. Industrial CTF detection systems based on motor power consumption establish maximum and minimum power limits to detect tool breakage. However, these systems generate many false positives and false negatives due to process variability and unforeseen events. Therefore, an Exploratory Data Analysis (EDA) of the power spindle consumption signals and other machining-related features is proposed to gain insights into the breakage nature and develop more effective detection systems. This analysis is oriented to set the basis for real-time Catastrophic Tool Failure detection from power spindle consumption monitoring. As a result, advanced processing time-domain detection methods are proposed.","PeriodicalId":46357,"journal":{"name":"Advances in Science and Technology-Research Journal","volume":null,"pages":null},"PeriodicalIF":1.0000,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Catastrophic Tool Failure Detection in Aeronautical Industrial Drilling Systems Based on Spindle Power Consumption Analysis\",\"authors\":\"Antonio Guerra-Sancho, Carlos Domínguez-Monferrer, María Henar Miguélez, José Luis Cantero\",\"doi\":\"10.4028/p-d3tseu\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The aeronautical industry is at the forefront of the fourth industrial revolution, which implies an exponential deployment of monitorization, Data Analytics, and connectivity. In alignment with this new paradigm, this research work presents a Catastrophic Tool Failure (CTF) analysis based on spindle power consumption monitoring in an industrial aircraft fuselage drilling process. In the case under study, the airframe components are arranged in hybrid stacks of Carbon Fiber Reinforced Plastic (CFRP) and titanium (Ti6Al4V) during drilling, which adds to the highly variable industrial machining conditions. This inherent complexity can lead to CTF, a significant concern due to its associated cost and time, especially in automatic processes. Industrial CTF detection systems based on motor power consumption establish maximum and minimum power limits to detect tool breakage. However, these systems generate many false positives and false negatives due to process variability and unforeseen events. Therefore, an Exploratory Data Analysis (EDA) of the power spindle consumption signals and other machining-related features is proposed to gain insights into the breakage nature and develop more effective detection systems. This analysis is oriented to set the basis for real-time Catastrophic Tool Failure detection from power spindle consumption monitoring. As a result, advanced processing time-domain detection methods are proposed.\",\"PeriodicalId\":46357,\"journal\":{\"name\":\"Advances in Science and Technology-Research Journal\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2023-10-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in Science and Technology-Research Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4028/p-d3tseu\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Science and Technology-Research Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4028/p-d3tseu","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
Catastrophic Tool Failure Detection in Aeronautical Industrial Drilling Systems Based on Spindle Power Consumption Analysis
The aeronautical industry is at the forefront of the fourth industrial revolution, which implies an exponential deployment of monitorization, Data Analytics, and connectivity. In alignment with this new paradigm, this research work presents a Catastrophic Tool Failure (CTF) analysis based on spindle power consumption monitoring in an industrial aircraft fuselage drilling process. In the case under study, the airframe components are arranged in hybrid stacks of Carbon Fiber Reinforced Plastic (CFRP) and titanium (Ti6Al4V) during drilling, which adds to the highly variable industrial machining conditions. This inherent complexity can lead to CTF, a significant concern due to its associated cost and time, especially in automatic processes. Industrial CTF detection systems based on motor power consumption establish maximum and minimum power limits to detect tool breakage. However, these systems generate many false positives and false negatives due to process variability and unforeseen events. Therefore, an Exploratory Data Analysis (EDA) of the power spindle consumption signals and other machining-related features is proposed to gain insights into the breakage nature and develop more effective detection systems. This analysis is oriented to set the basis for real-time Catastrophic Tool Failure detection from power spindle consumption monitoring. As a result, advanced processing time-domain detection methods are proposed.