以 M5Stack 感測器實作 PHM 精密量測機械手臂機台

Abstract

中文摘要 故障預測 及 健康管理（ Prognostic and Health Management, PHM 被廣泛 地 應 用在各種 專業 領域，像是軍事、航太等領域皆常出現，而在工業 上 常被應用 於 檢測設備 可能 故障 跡象並確 認 起 因、建立 設備老化模型並預測其使用 之壽命， 了解 其 健康狀況並 對 規劃 未來方向 。 本次 實驗 以 M5Stack C Plus 感測機械手臂機台之螺桿，量測其螺桿 於行進 中之穩定度，使用 WI FI 功能傳輸資料搭配 PuTTy 、 MATLAB 等軟體進行資料傳輸 及運算分析。本實驗對運行中的螺桿來回進行數次精密量測，收集數值並進行視 覺化分析，可以預測機器的健康狀況並加以改善，可運用 AI 技術進一步地進行 預測，可 提高系統的運行可靠性，減少系統的維修費用和提高維修準確性。

Abstract Failure prediction and health management (Prognostic and Health Management, PHM) is widely used in various professional fields, such as military, aerospace and other fields, and is often used in industry to detect possible signs of equipment failure and confirm Causes, establish equipment aging models and predict their service life, understand their health status and plan for future directions. In this experiment, the M5Stack C Plus is used to sense the screw of the robotic arm machine and measure the stability of the screw during travel. The WI-FI function is used to transmit data and PuTTy, MATLAB and other software are used for data transmission and calculation analysis. In this experiment, several precision measurements are made on the running screw back and forth, and the values are collected and analyzed visually, which can predict the health status of the machine and improve it. AI technology can be used to further predict and improve the operating reliability of the system. Reduce system maintenance costs and improve maintenance accuracy.