工具機主軸製程管制系統與損壞辨識系統開發

Development of Manufacture Execution System & Fault Diagnosis System

林威延(Wei-Yen Lin)

指導教授 ： 楊宏智

國立臺灣大學/工學院/機械工程學研究所/博士(2010年)

https://doi.org/10.6342/NTU.2010.10770

摘要

為了提升全球競爭力，提昇產品品質、降低生產成本、縮短製造及維修時間為目前工具機產業必須採取的競爭策略，機械在運作時會產生震動與噪音，並且可以透過監測此數值達到非破壞檢測與監控。但往往受限於成本或無適當量測工具，只能採取試誤法為檢測的方式，不僅浪費時間、材料及人力成本，更降低生產力。本研究透過人工製作以及退修主軸蒐集等兩種方式，建立主軸常見的損壞模型，除了傳統的傅立葉轉換之外，使用了經驗模態分解法和多尺度熵等三種訊號處理方法，開發特徵擷取以及比對演算法，建立主軸損壞辨識系統。由於機械震動通常為非穩態且非線性的訊號，傳統傅立葉轉換有其限制，本研究利用經驗模態分解法將原始訊號拆解成各個內部模態函數，並透過過零點速度以及能量分佈來表示各種模型的訊號特徵，對於大部分的模型分析有顯著效果，且研究中發現，若是為合格主軸，會產生四個目標內部模態函數；若是為組裝瑕疵主軸，例如不對心、潤滑油過多過少、預壓過大過小，會產生五個目標內部模態函數；若是是結構損壞主軸，會產生六個目標內部模態函數；多尺度熵則是計算訊號在各尺度下的亂度值，此方法亦在此研究中驗證針對某些特徵模型有非常佳的辨識效果。
本研究於最後提出快速軟體開發方法，並且利用此方式開發製程管制系統 (Manufacturing Execution System, MES)，製程管制系統是指生產現場電子化與製程之控管，系統以即時的方式，收集生產製程中各種資訊，供生產與管理者等參考，除了幫助生產管理者，管控生產製程外，更重要的是透過統計分析，找出每一種主軸最佳的精度參數，搭配本研究開發的損壞辨識系統，於台中工具機廠商驗證，提升其主軸品質。

關鍵字

經驗模態分解法 ； 內部模態函數 ； 過零點速度 ； 多尺度熵 ； 主軸 ； 損壞辨識

並列摘要

Aiming at reducing cost and time of repair, condition-based shaft faults diagnosis is considered an efficient strategy for machine tool community. While the shaft with faults is operating, its vibration signals normally indicate nonlinear and non-stationary characteristics with its Fourier-based approaches shown limitations for handling this kind of signals. The methodology proposed in this research is to extract the features from shaft faults related vibration signals, from which the corresponding fault condition is then effectively identified. Besides Fourier Transform, two new algorithms are used to extract the feature of signals, empirical mode decomposition (EMD) and multi-scale entropy (MSE). With an incorporation of EMD method, the model applied in this research embraces some characteristics, like zero-crossing rate and energy, of intrinsic mode functions (IMFs) to represent the feature of the shaft condition. The other method called MSE is used to calculate the entropy of multi-scale of the signal. The curve of MSE can be used to identify some defect model of shafts clearly. Fourier-based, EMD-based and MSE-based methods were implemented to develop a diagnosis system in this research. In the buildup stage a knowledgeware is created from the database compiled from the existing defect models. Finally, the Manufacturing Execution System (MES), conventionally called in the production field, is developed with diagnosis system. The system will collect various kinds of information during production process in real-time, and provide them to supervisors and the management in production line for their references. MES and fault diagnosis system are both implemented in a machine tool manufacturing company to validate its capacity.

並列關鍵字

EMD ； IMF ； Zero-Crossing Rate ； MSE ； MES ； Shaft ； Diagnosis

參考文獻

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