用於環境監測之溫度感測模組設計

The Design of Temperature Sensory Modules for Environmental Surveillance

陳上永(Shang-Yong Chen)

指導教授 ： 黃有評

國立臺北科技大學/電資學院/電機工程系所/碩士(2010年)

https://doi.org/10.6841/NTUT.2010.00053

摘要

氣溫突然變化，常會對環境造成重大的影響，如何設計一套具備溫度感測功能之模組，以用於環境監測，乃是本論文之研究動機。本研究主要是使用Keil C u Vision2程式設計晶片89S51，利用89S51強大的運算功能和充分的記憶體，結合溫度晶片AD590製作一套電子溫度計記錄環境的溫度，並且在晶片中加入灰色模型，使溫度計不只是單純的記錄溫度，更能用於預測溫度的變化，以防範災害的發生。單晶片的接收溫度間隔時間，可由實驗算出與實際溫度誤差最小之預測值，找出最適合該地區之接收溫度間隔時間，而間隔時間越長單晶片的記憶體使用越久，使用者擷取溫度資料的頻率也越低，若間隔時間為半小時，單晶片紀錄時間可達到24天又6小時，當間隔時間為一小時，單晶片紀錄時間可達到48天又13小時。在實驗過程中，我們使用四點資料去建構灰色模型，我們利用電烙鐵模擬溫度產生異常狀況，晶片89S51可計算出第五點的預測溫度，當預測溫度超越我們所設立的門檻值，系統便可透過無線網路或GPRS發出警訊通知使用者做處理。本論文利用灰色預測結合晶片89S51監測環境中的溫度，有別於一般的監測系統，系統只有在預測溫度異常時，才將警訊傳送給使用者，藉此解決大量資料傳輸和數據分析的問題，最後本研究實際測量環境溫度，以觀察環境溫度變化與預測功能，以驗證所提系統之有效性。

關鍵字

藍芽 ； 灰色預測 ； 無線射頻辨識系統 ； 溫度感測模組

並列摘要

Sudden changes in temperature often cause a significant impact on the environment. How to design a set of functions with temperature sensory modules for using in the environmental monitoring is the motivation of this study. In this study, we use an IC design program called Keil C u Vision2 to design IC 89S51. We design an electronic thermometer which combines chip temperature AD590 with IC 89S51 feature powerful computing and large capacity memory to record the temperature. And this study designs the IC 89S51 with grey prediction model. Thermometer will not just simply record the temperatures but also can predict the possibility of changes of temperature and prevent possibility of disasters. The interval of monocrystal chip receiving temperature data could be calculated by experiments which calculate the minimum difference between real temperature and prediction value, and find the most appropriate interval time for monitoring one specific region. The longer the interval is set, the longer the usage of memory is done, and the frequency of receiving temperature data is getting lower. If the interval is 30 minutes, the recording time of monocrystal chip could reach 24 days and 6 hours, while the interval is 1 hour, the recording time of monocrystal chip could reach 48 days and 13 hours. In the experiments, we use four data to construct grey prediction model. We use an electric iron to simulate the occurrence of abnormal temperatures and to predict the future temperature calculated by the chip. The system can send alerts via a wireless network or GPRS to notify the user to deal with when the predicted temperature is beyond the threshold we set. This study uses IC 89S51 with grey prediction model to monitor the environmental temperature. Unlike other general monitoring systems, the system will send alerts to users only when the predicted temperature anomalies are detected so as to reduce huge data transfer and analysis issues. Finally, this study experiments on environmental temperatures to observe the variety of environmental temperatures and to verify the effectiveness of the proposed system.

並列關鍵字

Bluetooth ； grey prediction ； RFID ； temperature sensory modules

參考文獻

[7] 溫坤禮、張簡士琨、葉鎮愷、王建文、林慧珊，Matlab 在灰色系統理論的應用，全華科技股份有限公司，台北，台灣，2006。

[18] 鄭儒鴻，以RFID技術為基礎之書籍推薦系統，碩士論文，國立清華大學工業成與工業管理學系，新竹，2006。

[5] J. C. Wen, K. H. Huang and K. L. Wen, “The study of α in GM(1,1) model,” Journal of The Chinese Institute of Engineering, vol. 23, no. 5, 2000, pp.583-589.

[13] D. Seguine, “Just Add Sensor-Integrating Analog and Digital Signal Conditioning in a Programmable System on Chip,” IEEE Sensors, vol. 1, 2002, pp.665-668.

[14] J.-B. Eom, T.-J. Lee, R. Rietman and A. Yener, "A System for Supporting Group Activities With a Sensor-Embedded Board," IEEE Transactions on Systems, Man and Cybernetics-Part C: Applications and Reviews, vol. 12, no. 11, 2008, pp.693-700.