磨耗性機械元件,例如滾珠螺桿或者是齒輪減速箱等,在長時間運作的過程當中,會因內部金屬摩擦而產生磨損,並使得使用這些機械元件 (如 CNC 加工機) 所加工的物件精度變差,而無法達到品質標準。因此若可於這些機械元件磨損達臨界值前,就及時進行維修替換,無論是以節省時間或者不良加工件成本等角度來看,都是比較好的策略。但是,這些機械元件的磨損通常外觀不顯著,或者磨損是在機械元件內部,無法直接用肉眼由外部觀察該機械元件是否已經達磨損的極限,或是決定是否要維修或者更換。因應這些需求,本研究進行磨耗性機械元件之無線感測系統的設計與實作,用來收集機械元件運作時產生的物理訊號。針對於在工廠環境中使用低功率無線通訊方式所可能會面臨通訊品質的問題,本研究於不同環境下進行完整通訊品質測試,並且在受限的硬體架構下仍可提供資料重送機制,因此可以保證最終所有感測節點上資料可以完整與正確的傳送到資料伺服器端。在可預見的未來,本系統所收集的資訊,可以用來建立機械元件的磨損模型,用來判斷特定機械元件是否達磨損標準,並提供是否應執行維修替換的依據。
Mechanical wear out part, like ball screw or gear reducer, need the check up frequently and replace before excessive wear out. As the cumulative friction of metal, regardless of due to long-time use or improper installation, may cause the mechanical parts worn out, and control the movement/rotation inaccurately. In addition, unnoticed wear out of mechanical parts might cause excessive backlashes, skid or lock up, as well cause deterioration of processing object’s quality that results in loss of money and time. Because the amount of being worn is invisible to the naked eye, we often rely on the judgments of experienced engineers based on unusual sound and vibration produced during the operation of the mechanical parts, or significant changes of processing target’s quality. We design a wireless sensor system for monitoring the mechanical wear out part in this study. In order to make this system can be used practically in industrial environment, the proposed system emphasizes on (1) low-power, low cost in hardware design, (2) logging the signals during operation of a mechanical wear out part in the local storage, (3) despite the hardware limitation, we guarantee all the logged data can wirelessly deliver to the data server without data loss or distortion, in contrast to the existed studies. We had design and implement this system, and evaluate the communication performance in real environments, therefore, ensured that our design is practical. We envision the miniature our design and embed it into mechanical parts, and use it for logging signals for monitoring and building its wear model for estimating the lifetime.