Catastrophic Tool Failure Detection in Aeronautical Industrial Drilling Systems Based on Spindle Power Consumption Analysis

IF 1 Q3 ENGINEERING, MULTIDISCIPLINARY Advances in Science and Technology-Research Journal Pub Date : 2023-10-02 DOI:10.4028/p-d3tseu
Antonio Guerra-Sancho, Carlos Domínguez-Monferrer, María Henar Miguélez, José Luis Cantero
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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.
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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
航空业处于第四次工业革命的前沿,这意味着监控、数据分析和连接的指数级部署。根据这一新的范例,本研究工作提出了一种基于工业飞机机身钻孔过程中主轴功耗监测的灾难性工具故障(CTF)分析。在所研究的案例中,在钻孔过程中,机身部件被安排在碳纤维增强塑料(CFRP)和钛(Ti6Al4V)的混合堆叠中,这增加了高度可变的工业加工条件。这种固有的复杂性可能导致CTF,由于其相关的成本和时间,特别是在自动过程中,CTF是一个值得关注的问题。工业CTF检测系统基于电机功耗建立最大和最小功率限制,以检测刀具破损。然而,由于过程可变性和不可预见的事件,这些系统产生了许多假阳性和假阴性。因此,提出了一种探索性数据分析(EDA)的电力主轴消耗信号和其他加工相关的特征,以了解断裂的性质和开发更有效的检测系统。该分析旨在为从电主轴消耗监测中实时检测刀具巨灾故障奠定基础。为此,提出了一种先进的处理时域检测方法。
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来源期刊
Advances in Science and Technology-Research Journal
Advances in Science and Technology-Research Journal ENGINEERING, MULTIDISCIPLINARY-
CiteScore
1.60
自引率
27.30%
发文量
152
审稿时长
8 weeks
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