本研究將透過實驗探討氧化效應對鋼放射率的影響，分別比較在真空環境和大氣環境下六種不同鋼材(AISI 420、AISI 630、AISI A2、AISI A6、AISI H2、AISI H10)在加熱溫度700 K、800 K與900 K時的放射率行為，並應用多光譜輻射測溫法搭配六種放射率模型預測表面溫度，以了解氧化效應對溫度預測的影響，並且找出最佳的放射率模型。
放射率的分析上：(1) 無論試件有無氧化，放射率大致上隨波長的增加而遞減；(2) 無氧化試件之放射率大致都隨溫度提升而增加，而有氧化試件之放射率則無此趨勢；(3) 無論試件有無氧化，鋼材的鉻金屬元素含量越高在高溫時有較低的放射率值。(4) 無氧化試件之放射率不隨加熱時間的增加而有太大改變；有氧化試件之放射率則因為氧化層隨著加熱時間增長而變動。
對推測溫度而言，(1) 無論試件有無氧化，對於使用MRT時放射率模型的選擇上，WLT與IWS皆很理想，平均溫度誤差百分比在5 %以內，表示MRT用於鋼材上有不錯的預測溫度效果。(2) 使用MRT推測溫度，增加波長數並無改善溫度誤差，故使用最小波長數即可，並且可以減少計算的時間。(3)當推測的放射率越接近真實的放射率，其預測溫度勢必越準確。

In this study, experiments were conducted to examine the effect of surface oxidation on emissivity behavior. The spectral emissivity were measured under a high-vacuum heater system for six different steel (AISI 420、AISI 630、AISI A2、AISI A6、AISI H2、AISI H10) at three temperatures (700 K、800 K、900 K) and compared with the data under an open air heater system. Six emissivity models were used to examine the MRT for steel in order to understand the effect of surface oxidation on temperature determination and find the best MRT emissivity model.
For steel emissivity behaviors, (1) Emissivity decreases with increasing wavelength whether steel is oxidized or not. (2) Emissivity increases with increasing temperature for oxidized samples, but emissivity doesn’t have the same behavior for unoxidized samples. (3) Steel with high chromium has low emissivity at high temperature. (4) Emissivity of unoxidized sample doesn’t change obviously with time. However, emissivity of oxidized sample changes due to the growing oxide layer with time.
For the examination of MRT emissivity models on steel, (1) WLT and IWS emissivity models show the best overall stability and accuracy whether steel is oxidized or not, and the percentage of average inferred temperature error is under 5%. Therefore, MRT is suitable and applicable for steel temperature determination. (2) Increasing number of wavelengths doesn’t improve inferred accuracy while applying MRT. Therefore, it is sufficient to employ the required minimum number of wavelengths to reduce the time on computation. (3)The closer the inferred emissivity value ane real one, the more the accurate inferred temperature.

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