【正文】 字符尺寸:(WH)mm2） 引腳功能說(shuō)明：1602LCD采用標(biāo)準(zhǔn)的14腳（無(wú)背光）或16腳（帶背光）接口，各引腳接說(shuō)明如表33所示:表33引腳接口說(shuō)明表編號(hào)符號(hào)引腳說(shuō)明編號(hào)符號(hào)引腳說(shuō)明1VSS電源地9D2數(shù)據(jù)2VDD電源正極10D3數(shù)據(jù)3V0液晶顯示偏壓11D4數(shù)據(jù)4RS數(shù)據(jù)/命令選擇12D5數(shù)據(jù)5R/W讀/寫(xiě)選擇13D6數(shù)據(jù)6E使能信號(hào)14D7數(shù)據(jù)7D0數(shù)據(jù)15A背光源正極8D1數(shù)據(jù)16K背光源負(fù)極第1腳：VSS為地電源。指令5：光標(biāo)或顯示移位 S/C：高電平時(shí)移動(dòng)顯示的文字，低電平時(shí)移動(dòng)光標(biāo)。些A/D轉(zhuǎn)換器是的特點(diǎn)是8位精度，屬于并行口，如果輸入的模擬量變化大快，必須在輸入之前增加采樣電路。 2）引腳功能　 ADC0809芯片有28條引腳，采用雙列直插式封裝，如圖38 所示。 　ADC0809的工作過(guò)程是：首先輸入3位地址，并使ALE=1，將地址存入地址鎖存器中。電路如圖42所示 圖42 ADC0809與STC89C52連接圖第五章 硬件電路系統(tǒng)模塊設(shè)計(jì) 總電路模塊簡(jiǎn)易數(shù)字電壓表應(yīng)用系統(tǒng)硬件電路由單片機(jī)、A/D轉(zhuǎn)換器、LCD顯示電路和電壓采集電路組成，它的硬件電路圖見(jiàn)附錄附錄IV（圖表）。主要流程圖如下：開(kāi)始啟動(dòng)A/D轉(zhuǎn)換 N A/D轉(zhuǎn)換結(jié)束？ Y取數(shù)據(jù)OE=1圖62 A/D轉(zhuǎn)化測(cè)量子函數(shù)流程圖 顯示子程序顯示程序?qū)Ξ?dāng)前選中的一路數(shù)據(jù)進(jìn)行顯示。 性能分析由于單片機(jī)為8位處理器，ADC0809輸出數(shù)據(jù)值為255（FFH），（5/255）。設(shè)計(jì)中還用到了模/數(shù)轉(zhuǎn)換芯片ADC0809，以前在學(xué)單片機(jī)課程時(shí)只是對(duì)其理論知識(shí)有了初步的理解。 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, ft, defined over the field of real numbers R and square integrable over that field, with bandwidth limited to an interval Ω，Ω radians per second, can be pletely reconstructed from its sampled values f（nπ/Ω），n∈Z， aswhere π/Ω=Ts seconds is the sampling period and sincx=sinxx .Finiteduration signals do not have limited bandwidth,as stated by the uncertainty principle [12]. Therefore the signal function f(t) takes the formRΩ[f(t)] is the aliasing error, whose norm is limited by [1] wherefω∈L1R is the Fourier transform of ft ，which shall be in the space of continuous real absolutely integrable functions，ft∈CR∩L1R [1]:ft=12π∞∞Ftejωtdω (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 12Vo seconds. For this signal, all conditions for the signal function,f(t), are satisfied and (3) applies directly.Let f1t denote the rectified sinusoidal waveform, f1t=sinω0t, which can be rewritten, using its Fourier series expansion, asThe Fourier transform of f1t is where ω0=2πV0 radians per second.For a bandwidth of Ω=2πMVo，M?N we have [13]where x denotes the smaller integer not less than x and xdenotes the larger integer not greater than x. For M = 25, the upper bound for the aliasing error can becalculated as RΩf1t≤，which indicates that even for a bandwidth 25 times larger than the fundamental frequency, Vo, 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,asf2t=2πk=1∞1k1sinω0ktk （12）The Fourier transform of f2t isF2ω=k=1∞21k1jkδωkω0δω+kω0 （13）The sawtooth is also a wellknow waveform. However, unlike the rectified sinusoidal waveform, for this particular signal, (3) cannot be applied directly becausef2t?CR∩L1R andF2ω?L1R. The function is not continuous in time and its Fourier transform is not absolutely integrable.However, far from being an obstacle, the sawtooth wav