Design Of Machinery System's Noise Failures Of Signal Acquisition System

Using sound information to diagnose fault is the method that had continuing to use in the past. But it is not got fast development because it has not combine with the modern signal processing and acquiring technology very well. But if the processing results of acoustic signal are used to stimulate characteristic of human audio system, then the performance may be even better and it is much easier to be accepted by operators. So fault diagnosis based on acoustic signals'acquisition and analysis is very important in real world.In fieldwork noise detection, because of complication of the real acoustic environment we often face with complex spatial acoustic field that covers large area, or is unsteady or has multi-sound source. Especially when the machine to be inspected is out of order, the fault signal, the steady normal working signal and background noise mix together. The signal detected in this condition is actually a mixture of multi sources and their reflections. When certain machine is out of order, the sound that represents characteristic of the fault may be canceled or covered totally by signals form other sources and accuracy and reliability of fault diagnosis are degraded drastically. This greatly limits the usage of audio fault diagnosis in real world. It is obvious that how to acquire real acoustic signal of the machines to be inspected is key to improve feasibility of audio sound diagnosis. Because of lacking in professional set of DAQ and effective method to acquire signals and denoise, nowadays there is no much progress in the study and application of noise fault diagnosis. So there needs an algorithm urgently which can acquire the fault sound source-signal and denoising to improve the realization of audio fault diagnosis.The main content of this paper is about the system development and its functions, including hardware system for data acquisition and software system for signal processing. And a system of sound intensity measurement including hardware and software was finished. A set of sound intensity probe and a suit of signal conditioning implement and a piece of USB DAQ card are composed of the part of hardware. After being compared with different products, the most appropriate instruments were selected. The data acquisition module, the data processing module are composed of the systerm's.Most instrument that use at present is belonging to traditional instrument category though they make the effective result, but still some insufficient exists, such as the restriction of the capacity of performance and memory, the power of a large amount of digital operation that deals with the signal is insufficient, The test performance of the small vibration signal is not good, but systematic function of expansion is limited.Now, the combination of technology oft he computer and instrument and meter technology produce the fictitious instrument-based on the technology of computer collection, est and analyses, the instrument enters virtual instrument era gradually. The convenient, high-efficient with their cheap characteristic of virtual instrument make more extensive application. It is necessary to improve precision of testing to meet modern world. This paper trtes to combine with virtual instrument (VI) technology, technology of dealing with digital signal and wavelet analyzing technology, utilizing software LabVIEW of graphics programming, Studied and developed the virtual wavelet analysis instrument based on virtual instrument technology.Comparing with the tradition instrument, this instrument panel is more friendly, it is more convenient to use. Can collect the data through the collecting card, and analyze and process the digital signal of collecting, improve the accuracy and stability of test result, and there is certain ability of trouble diagnosing, the capacity of expanding is good.The quickly development of Virtual Instrument makes the modular instrument, which is based on computer control, is accepted and applied widely. The new concept of Virtual Instruments(for short:VI) emerged from the deep intergradations of modern measurement technology with computer science. Different from the classic electronic instruments, functions of which are mainly defined by hardware, VI stake advantages of computer resources to realize the function of instruments by a set of software. With technology of VI, scientists can increase functions and flexibility of measurement system while decreasing the cost of system. This thesis introduces the typical architecture of VI's hardware and software. It analyses the construction of LabVIEW and computer language used in LabVIEW, because LabVIEW is one of development environment for VI in top class.We all know that fault signal of vehicle engine is time-variant. It often represents important information about fault of the engine. Traditional Fourier transform of the acoustic signal reflects its holistic feature. Fourier transform can not reflect the signal's frequency characteristics in local areas. Unfortunately, these local characteristics are no other than representation of fault. So we must adopt a signal processing method that compatible with characteristics of acoustic signal which is non-stationary in nature.Wavelet analysis is the newest progress of harmonic theory. Because of good time-frequency analytical ability, it is begin to be used in machine's dynamic signal analysis. Wavelet transform inherited and developed localization idea of Gabor transform. At the same time, it overcomes the shortage of Gabor transform such as the fact that the window can not change with frequency and the lack of orthogonal bases. Wavelet is not only an ideal tool to analyze local frequency spectrum, it also have good local characteristic in time domain. It provides a powerful analytical method for acoustic signal analysis.This paper realizes the basic theories of wavelet mainly, introduces the basic idea of disperse wavelet,series wavelet, research the noise reduction disposal of signal using disperse wavelet and the methods of decompounding signal using wavelet packet, than uses these methods to the disposal of the sound signal of vehicle engine. This course realizes noise reduction of sound signal of vehicle engine. The knowledge has laid a solid foundation for the research of the signal separating algorithm in the fault diagnosis of vehicle engine based on sound signal. This paper also analyses the characteristic of wavelet transform, indicates the advantage of wavelet transform comparing to other traditional analytical method of time frequency, using wavelet transform to carry on dynamic supervise and diagnosis of system fault has good results. This paper researches the noise reduction methods of signal using wavelet, chooses method based on layer threshold value and suitable soft threshold value to reduce noise. Through theory analysis and simulation example, wavelet has better frequency characteristic under different yardstick.