仪表与量测PPT课件-Chapter 6 Tools and Methods of Signal Analysis.pptVIP

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仪表与量测PPT课件-Chapter 6 Tools and Methods of Signal Analysis.ppt

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仪表与量测PPT课件-Chapter 6 Tools and Methods of Signal Analysis

Chapter 6Tools and Methods of Signal Analysis I. Kollar Introduction Measurement - to extract the maximum amount of informtion efficiently and effectively. Signal analysis need be done during the whole measurement time. Intelligent microprocessor provides sophisticated signal processing capability. Profound understanding of the measured results is vital for whom intend to use them. This chapter is to provide the basics of signal analysis for those who use complex instruments. The most important signal processing techniquesa The building blocks and main features of the instruments. The errors on random signal and since waves are discussed. Basic Signal Processing Methods There are many DSP techniques. We will focus on the ones that are already customarily built into instruments. The purpose is the analysis and design of DSP procedures and instrument settings. Study the relation among record length, signal bandwidth, and variance reduction. Signal of interests: stochastic signals with continuous spectrum, sinusoidal signals with fixed or random phases, transient signals Measure iterations to adapt model to reduce errors. Approximation is necessary to analyze errors, e.g. equivalent bandlimited white noise (Bendat 1971) Signal Processing - Equivalent Bandlimited White Noise DSP - Time/Frequency Domain Frequency Domain Advantages: Time domain convolution = frequency domain multiplication Signal and noise can be decomposed into different bands for very high noise rejection. Period waves are discrete in time domain. Attainable dynamic range (80-100dB) is much larger. Slight nonlinearities can be easily detected (harmonics). FFT is a very powerful tool, hence, correlation is much faster via frequency domain then directly in time domain. Time Domain Advantages: It’s a natural to view time domain signal. Recursive methods provide on-line calculation. Time varying systems can be modeled easily. Time domain methods are not sensitive to signal types while F domain has lea