本文選題：真空冷噴涂粒子 + 測速��； 參考：《西安工程大學》2015年碩士論文

【摘要】：基于空氣動力學原理,真空冷噴涂是在室溫及真空條件下,通過高壓混合氣體加速超細固態(tài)陶瓷粉末顆粒以一定的速度撞擊基體,從而實現(xiàn)涂層制備。真空冷噴涂技術(shù)的特點是沉積效率高、沉積溫度低,涂層結(jié)構(gòu)致密,陶瓷顆粒不易產(chǎn)生氧化、相變、組織變化等問題,因而真空冷噴涂研究受到了廣泛關(guān)注。粒子飛行速度大小是真空冷噴涂技術(shù)中至關(guān)重要的性能參數(shù)之一,直接影響涂層制備效果和質(zhì)量,粒子飛行速度的研究具有重要意義。國內(nèi)某大學真空冷噴涂實驗室研究人員,在進行真空冷噴涂粒子飛行速度的測算研究中,通過自主研發(fā)的粒子參數(shù)采集系統(tǒng)平臺,采集粒子飛行時產(chǎn)生的電壓數(shù)據(jù),再通過示波器軟件存儲電壓數(shù)據(jù)和通用分析軟件來測算粒子的飛行速度。但其粒子測速實驗方案效率不高,無法將粒子數(shù)據(jù)的采集、顯示和分析一體化執(zhí)行。本文介紹如何在真空冷噴涂粒子測速研究基礎上,研發(fā)集真空冷噴涂粒子參數(shù)實時采集、顯示和分析為一體的真空冷噴涂粒子測速軟件,并且介紹了軟件研發(fā)中的相關(guān)技術(shù)和實施方案。測速軟件解決了真空冷噴涂粒子在數(shù)據(jù)實時采集存儲、顯示和計算分析上一體化執(zhí)行的問題,提高真空冷噴涂粒子測速實驗效率,滿足了真空冷噴涂技術(shù)研究的要求。本文主要任務如下:(1)設計真空冷噴涂粒子飛行速度檢測軟件,軟件通過內(nèi)存映射文件方式實時存儲粒子電壓信號,并通過Tee Chart控件將粒子電壓信號清晰顯示在測速軟件中。(2)對粒子信號進行時域和頻域分析,對比多鄰點平均濾波法、快速傅里葉變換(fast fourier transform,簡稱FFT)帶通濾波和FFT低通濾波法處理后的粒子信號的性能參數(shù)和特點,確定在測速軟件中使用FFT[0-1.22MHz]低通濾波零漂補償加16鄰點平均濾波的組合方法濾除信號中的噪聲。(3)對粒子噪聲信號進行FFT[0-1.22MHz]低通濾波零漂補償加16鄰點平均濾波處理,根據(jù)噪聲信號高斯分布特性確定有效粒子脈沖信號幅值大小,并通過矩形窗函數(shù)截取有效粒子脈沖信號。(4)對有效粒子脈沖信號數(shù)據(jù)進行最小二乘法線性擬合,計算出有效粒子脈沖信號擬合方程系數(shù),并通過系數(shù)得出最新粒子上升沿和下降沿擬合數(shù)據(jù)。(5)根據(jù)最新的擬合數(shù)據(jù),通過測速算法得出每屏粒子飛行速度值,以速度平均值為最終實驗結(jié)果并顯示在測速軟件中。
[Abstract]:Based on the principle of aerodynamics, vacuum cold spraying is used to accelerate the impact of superfine solid ceramic powder particles on the substrate at a certain speed through high pressure gas mixing under room temperature and vacuum conditions, so that the coating can be prepared. The vacuum cold spraying technology is characterized by high deposition efficiency, low deposition temperature, dense coating structure, difficult oxidation of ceramic particles, phase transformation, microstructure change and so on, so the research of vacuum cold spraying has been paid more and more attention. Particle flying velocity is one of the most important performance parameters in vacuum cold spraying technology, which directly affects the preparation effect and quality of coating, and the study of particle flying velocity is of great significance. In the course of measuring and studying the flying velocity of vacuum cold spraying particles, researchers in a vacuum cold spraying laboratory at a university in China collect the voltage data generated by particles flying through a self-developed particle parameter acquisition system platform. Then the velocity of particles is calculated by storing voltage data and general analysis software with oscilloscope software. However, the experimental scheme of particle velocimetry is not efficient, so it can not carry out the collection, display and analysis of particle data. This paper introduces how to develop the software of vacuum cold spray particle velocity measurement based on the research of vacuum cold spray particle velocity measurement, which can collect, display and analyze the parameters of vacuum cold spray particle in real time. And introduced the software research and development related technology and the implementation plan. The software solves the problem of real-time data collection and storage, display and calculation and analysis of vacuum cold spray particles, and improves the efficiency of the velocity measurement of vacuum cold spraying particles, and meets the requirements of the research of vacuum cold spraying technology. The main tasks of this paper are as follows: (1) designing a software for detecting the flying velocity of cold sprayed particles in vacuum. The software stores the voltage signals of particles in real time by memory mapping file. The particle voltage signal is clearly displayed in the velocimetry software by the Tee Chart control. The particle signal is analyzed in time domain and frequency domain, and the multi-neighbor point average filtering method is compared. The performance parameters and characteristics of particle signals processed by fast fourier transform bandpass filtering and FFT low-pass filtering. It is determined that FFT [0-1.22MHz] low-pass filter zero-drift compensation plus 16-neighbor average filtering method is used to filter the noise in the signal in the velocity measurement software. The particle noise signal is filtered by FFT [0-1.22MHz] low-pass filter zero-drift compensation plus 16-neighbor average filter. According to the distribution characteristics of noise signal Gao Si, the amplitude of effective particle pulse signal is determined, and the effective particle pulse signal is intercepted by rectangular window function. The fitting equation coefficient of effective particle pulse signal is calculated, and the fitting data of rising edge and descending edge of the latest particle are obtained by the coefficient. (5) according to the latest fitting data, the velocity value of particles per screen is obtained by the velocity measurement algorithm. The average velocity is taken as the final experimental result and displayed in the software of velocity measurement.
【學位授予單位】：西安工程大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TQ639;TQ174.7

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本文編號：1823579