【正文】 *2和40*2行等的模塊。第6腳：E端為使能端，當(dāng)E端由高電平跳變成低電平時，液晶模塊執(zhí)行命令。指令4：顯示開關(guān)控制。指令11：讀數(shù)據(jù)。AD0809是8位逐次逼近型A/D轉(zhuǎn)換器，它是由一個8路的模擬開關(guān)，一個地址鎖存譯碼器，一個A/D轉(zhuǎn)換器和一個三態(tài)輸出鎖存器組成。綜合上述幾種A/D轉(zhuǎn)換芯片的特點，為了滿足本次設(shè)計需求，本次設(shè)計選用ADC0809芯片。 　 f、工作溫度范圍為40～＋85攝氏度。 　表37 ADDA、ADDB、ADDC真值表ADDCADDBADDA輸入通道000IN0001IN1010IN2011IN3100IN4101IN5110IN6111IN7 ALE：地址鎖存允許信號，輸入，高電平有效。 　　 Vcc：電源，單一＋5V。圖38 ADC0809引腳圖第四章 接口電路 顯示電路根據(jù)設(shè)計要求，測量結(jié)果需要顯示如vol：，設(shè)計中采用LCD1602液晶屏來顯示電壓值。9腳為A/D轉(zhuǎn)換數(shù)據(jù)輸出允許控制，當(dāng)OE腳為高電平，A/D轉(zhuǎn)換數(shù)據(jù)從該端口輸出。10引腳為ADC0809的時鐘信號輸入端CLOCK。A/D轉(zhuǎn)換子程序每隔一定時間調(diào)用一次，即隔一段時間對輸入電壓采樣一次。)。測試對比表如表101所列，表中標(biāo)準(zhǔn)電壓值采用VICTOR VC890C+數(shù)字萬用表測得?？? 結(jié)本次設(shè)計總體還是比較成功的，首先，通過對簡易數(shù)字電壓表的兩種方案進(jìn)行論證與比較，確定出了用單片機與芯片構(gòu)建數(shù)字電壓表系統(tǒng)，該系統(tǒng)由單片機、A/D轉(zhuǎn)換芯片、顯示器件、電壓四大部分構(gòu)成，通過對幾種熟知的單片機、A/D轉(zhuǎn)換芯片、顯示器件的優(yōu)劣勢比較以確定出最適系統(tǒng)組成部件，然后又對總體電路進(jìn)行了設(shè)計，用Proteus畫出了電路圖，并對各接口電路進(jìn)行了詳細(xì)的分析與論證，并焊接了電路板，最后軟件部分在keil環(huán)境下進(jìn)行了調(diào)試與測量。無論是在硬件連接方面還是在軟件編程方面。從開始選題到論文的順利完成，都離不開老師、同學(xué)、朋友給以的幫助，在這里請接受我的謝意!首選，邵霞老師在本次畢業(yè)設(shè)計過程中，從選題、構(gòu)思、資料收集到最后定稿的各個環(huán)節(jié)給予細(xì)心指引與教導(dǎo)，使我對課程的多方面的知識有了深刻的認(rèn)識，使我得以最終完成畢業(yè)設(shè)計，在此表示衷心感謝。 Lowfrequency electrical metrology1. IntroductionIt is fundamental to take into account measurement errors when applying sampling techniques to highaccuracy digital measurements [1–3]. Reconstruction ofdeterministic,nonbandlimited, real signals from sampled values also benefit from a careful study of measurement errors [4–11].In this paper, we apply qualitative and quantitative analysis of some of error sources in sampling theory to asynchronous digital sampling measurements. We verify the significance of each error source in simulations and in laboratory measurements, and also the efficiency of errorreduction strategies. Although there are many papers that address sampling error analysis, our objective here is to study the most significant of those errors sources for electrical highaccuracy measurements.It is a mathematical idealization to assume that a signal function has limited bandwidth with finite energy and infinite duration. In practice, the signal to be sampled by an analogtodigital converter (ADC) is of limited time duration and often possesses a much wider frequency bandwidth than that of the converter. These limitations are responsible for aliasing error, one of the most significant error sources in digital sampling. Integration is another significant error source, for most ADCs average the input signal during a time interval. In addition to aliasing and integration, we also consider here two other error sources: quantization and jitter. This paper is organized as follows: in the following section, we present an introduction to sampling analysis and aliasing error. In the third section, we present an analysis of integration error in sampling systems and study a known method to pensate for it. These calculations are then applied to asynchronous data acquisition of periodical signals. In Section 4 we describe quantization and jitter errors. In Section 5 we present the conclusions.2. Sampling analysis and aliasing errorThe sampling theorem [1] states that a signal function, , defined over the field of real numbers R and square integrable over that field, with bandwidth limited to an interval radians per second, can be pletely reconstructed from its sampled values f（n），naswhere=Ts seconds is the sampling period and .Finiteduration signals do not have limited bandwidth,as stated by the uncertainty principle [12]. Therefore the signal function f(t) takes the formR[f(t)] is the aliasing error, whose norm is limited by [1] where is the Fourier transform of ，which shall be in the space of continuous real absolutely integrable functions， [1]: (5)2. 1 Aliasing error: theoretical calculationsFor signals with high harmonic distortion, the harmonic ponents’ energy can be significant even if the operational bandwidth is much larger than the fundamental frequency, Vo Hz, causing considerable aliasing error. For many reasons, evaluation of (3) is of great importance in error analysis for high accuracy measurements. However,as we will be able to verify in the examples that will follow,for some important signals (3) is a very loose upper bound. Signal 1: rectified sinusoidal waveformAs a first example, we discuss below the solution of (3) for the rectified sinusoidal waveform with period seconds. For this signal, all conditions for the signal function,f(t), are satisfied and (3) applies directly.Let denote the rectified sinusoidal waveform, , which can be rewritten, using its Fourier series expansion, asThe Fourier transform of is where radians per second.For a bandwidth of we have [13]where denotes the smaller integer not less than x and denotes the larger integer not greater than x. For M = 25, the upper bound for the aliasing error can becalculated as which indicates that even for a bandwidth 25 times larger than the fundamental frequency, , aliasing error contaminates harmonic measurement for most practical purposes. However, increasing the sampling rate even further may not be a viable solution: High sampling rates may cause high quantization errors due to internal limitations of the ADC. On the other hand, small sampling rates may cause very high aliasing error, eventually requiring the use of antialiasing filters, which may distort the original signal. Signal 2: sawtooth waveformFor a second example, we discuss the solution of (3) for the sawtooth waveform,which can be rewritten, using its Fourier series expansion,as （12）The Fourier transform of is （13）The sawtooth is also a wellknow waveform. However, unlike the rectified sinusoidal waveform, for this particular signal, (3) cannot be applied directly because and. The function is not continuous in time and its Fourier transform is not absolutely integrable.However, far from being an obstacle, the sawtooth w