皮帶系統為常見的動力傳輸系統。在此論文中，我們探討量產車輛中的皮帶傳動系統的設計，設計的主要目標為決定皮帶輪與張力輪的位置，以確保皮帶在靜態與動態行為下的表現均合乎要求，並考慮老化及不確定因素，使得皮帶系統在整個生命週期內均有良好的表現。然而，在皮帶設計過程中，仍然有許多困難尚未被解決。皮帶的結構為非均勻的複合材料，其中包含橡膠、鋼芯線體等。老化與不確定因素會使得皮帶特性難以預測，現有之皮帶設計分析均未將此因素列入考慮。若要準確的得知老化與不確定因素的影響，需要全面且大量的量測資料，但是在現實生活中，因為成本及資源有限，無法取得全面且大量的資料，所以重點式的量測為必要之方法。但是利用少量的量測點推估老化及不確定因素的影響，可能產生極大的誤差。所以需要一個可利用連續量測資料且可提供下一個重點量測參數的設計模式幫助我們進行皮帶系統設計。本論文中採用貝氏推估法進行皮帶系統之設計。貝氏推估法中的二項式推估，被用於評估皮帶系統在定時間下的可靠度表現；卜松推估，則被用於一段時間內的皮帶系統的破壞速率評估。在此論文中提出的設計模式中，先評估現有的資料的信心程度，而後再經由取樣重點參數提升信心程度。重點參數的選擇，取決於對有效限制式的敏感度分析結果。進一步利用蒙地卡羅過濾器去除偏頗之取樣。在本論文中提出的設計模式中，在不推估真實的老化與不確定因素模型的前提下，設計點必須滿足信心程度與可靠度要求，得到最化設計結果。在以一個數學範例演示此設計過程，並應用於一個工程皮帶系統設計問題上，得到一個考量老化與不確定因素的最佳設計。

Belt-pulley mechanism is commonly used in machinery and power transmission devices. In this thesis we investigate the use of tensioners of the belt-pulley mechanism inside a commercial vehicle. Design objective is to allocate the locations of pulleys and tensioners such that the static and dynamic behaviors of the entire system perform as desired throughout the entire life-time of the product. Design of the belt-pulley system suffers from the several issues that have not been fully addressed in the current literature. Most power transmission belts are semi-elastic transverse isotropic layered materials with steel core enhancements. Variation and deterioration of materials lead to uncertainty in materials that have not been accounted for in the current belt-related design problems. To obtain the precise material properties, extensive testing on various material properties are necessary. However, in reality the required measurement size is too large to provide abundant data; selective measurements are necessary due to time and other resource constraints. Unfortunately uncertainty models and the aging process can not be inferred accurately under few measurements. A design method that integrate sequential measurement data and also provide suggestions on additional data, whenever necessary, is needed. In this thesis we extend the Bayesian inference concept in the design of a more reliable belt-pulley system. Beta-binomial inference is used to estimate the reliability of a performance function given existing samples at a fixed time instant, an important tool to ensure product reliability at the initial state. Poisson-gamma inference is used to estimate the failure rate of a performance function given existing samples over a period of time. With the proposed method, we can first calculate the confidence with the current samples at hand and sequentially improve the confidence by adding samples. Addition samples are taken at the critical parameter decided by constraint activity and sensitivity analysis. An MCMC sample filter is applied to eliminate biased samples. The proposed design method will satisfy the confidence and reliability targets without inferring the true uncertainty and the aging model with the fewest samples. A mathematical example is used to demonstrate this design method and the solution to the belt-pulley system design problem is then provided.

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