本文選題：浪涌檢測 + 電參數檢測��； 參考：《華南理工大學》2015年碩士論文

【摘要】：針對目前浪涌檢測采用檢測技術人員觀察和記錄EUT面板指示燈的方式,存在檢測工作量大、效率低和檢測結果判定依據少、主觀性強、不可溯源等問題,本論文以“浪涌檢測過程產品狀態(tài)自動記錄與分析系統(tǒng)”為題,研究浪涌檢測過程電參數檢測方法、基于k-NN的多狀態(tài)燈模式識別與分析方法以及系統(tǒng)集成、軟件實現,對促進EMC浪涌檢測自動化技術的發(fā)展具有重要的實際工程意義。研究工作得到中國電器科學研究院有限公司2014年青年科技基金項目(SQRV2014008)資助。論文分別設計浪涌檢測過程產品狀態(tài)自動記錄與分析系統(tǒng)框架、研究浪涌檢測過程電參數檢測技術、研究基于k-NN的多狀態(tài)燈模式識別與分析方法、設計浪涌檢測過程產品狀態(tài)自動記錄與分析軟件系統(tǒng),并通過實驗對該系統(tǒng)浪涌檢測效果和功能進行驗證。主要突出工作包括：(1)提出新型浪涌檢測過程產品狀態(tài)自動記錄與分析系統(tǒng)框架,該系統(tǒng)框架在傳統(tǒng)浪涌檢測系統(tǒng)的基礎上,新增浪涌電參數測試子系統(tǒng)、設備面板信號燈圖像識別子系統(tǒng)和關系-時態(tài)數據庫管理系統(tǒng)三個子系統(tǒng),同時分析浪涌檢測過程產品狀態(tài)自動記錄與分析系統(tǒng)關鍵技術實現方案。(2)研究浪涌電參數測試子系統(tǒng),提出并搭建基于示波器和功率分析儀器的電參數采集系統(tǒng),對產品浪涌可靠性檢測進行詳細分析、研究,并對浪涌檢測中示波器MDO3034、功率分析儀PA1000和檢測軟件的相關設置進行詳細分析。(3)提出基于HSI顏色空間的狀態(tài)燈樣本快速訓練方法,并在此基礎上,研究基于k-NN的狀態(tài)燈模式識別技術,重點研究圖像快速去噪技術、基于k-NN的狀態(tài)燈模式識別和狀態(tài)判斷分類方法。(4)設計并實現基于LabVIEW的浪涌自動化檢測軟件系統(tǒng),包括對本系統(tǒng)的數據庫表空間進行合理劃分,設計浪涌檢測電參數數據字典等數據字典,研究本系統(tǒng)時態(tài)數據庫的數據結構圖。最后,通過實驗對浪涌檢測過程產品狀態(tài)自動記錄與分析系統(tǒng)的功能進行驗證,結果表明,系統(tǒng)能有效檢測、顯示有效電壓Urms、有效電流Irms、有功功率Pr和浪涌瞬時電壓Upk四個電參數,能準確捕捉EUT狀態(tài)燈閃爍現象和識別EUT狀態(tài)燈的亮滅,并能正確判定浪涌檢測結果,同時實現檢測過程電參數和視頻回放等其他功能。
[Abstract]:In view of the current surge detection method, the detection technicians observe and record the EUT panel indicator lamp, there are many problems, such as large workload, low efficiency, little basis for judging the test results, strong subjectivity and non-traceability, etc. Under the title of "automatic recording and Analysis system of Product status in surge Detection process", this paper studies the detection method of electrical parameters in surge detection process, the method of multi-state lamp pattern recognition and analysis based on k-NN, the system integration, and the software implementation. It has important engineering significance to promote the development of EMC surge detection automation technology. The research was funded by the 2014 Youth Science and Technology Foundation project SQRV2014008 of China Electric Science Research Institute Ltd. In this paper, the automatic recording and analyzing system framework of product state in surge detection process is designed, the detection technology of electrical parameters in surge detection process is studied, and the multi-state lamp pattern recognition and analysis method based on k-NN is studied. A software system for automatic recording and analysis of product status during surge detection is designed, and the effect and function of surge detection are verified by experiments. The main work includes: (1) A new system framework for automatic recording and analysis of product status in surge detection process is proposed. Based on the traditional surge detection system, a new surge power parameter testing subsystem is added. Equipment panel signal lamp image recognition subsystem and relational temporal database management system three subsystems, At the same time, the paper analyzes the key technology of automatic recording and analyzing system of product state in surge detection process. (2) Research surge parameter testing subsystem, and put forward and build the electric parameter acquisition system based on oscilloscope and power analysis instrument. This paper makes a detailed analysis and research on the reliability detection of product surge, and puts forward a fast training method of state lamp samples based on HSI color space, including the related settings of oscilloscope MDO3034, power analyzer PA1000 and the testing software, in which the Oscilloscope MDO3034, the power analyzer PA1000 and the testing software are set up in detail. On this basis, the state light pattern recognition technology based on k-NN is studied, and the image fast de-noising technology is emphasized. The software system of automatic surge detection based on LabVIEW is designed and implemented, including the reasonable division of database table space of the system. Data dictionaries such as surge detection data dictionary are designed to study the data structure of the temporal database of the system. Finally, the function of the automatic recording and analyzing system of product status during surge detection is verified by experiments. The results show that the system can detect effectively. It shows four electrical parameters: effective voltage Urms, effective current Irms, active power pr and surge instantaneous voltage Upk, which can accurately capture the flicker phenomenon of EUT state lamp and identify the light of EUT state lamp, and can correctly judge the result of surge detection. At the same time, the detection process of electrical parameters and video playback and other functions.
【學位授予單位】：華南理工大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TM83

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