Applied Mechanics and Materials Vols. 333-335

Abstract: With the development of social and economy, and the large demand for geospatial information, GIS and GPS technology have deeply penetrated into the areas of land resources, logistics and urban management. Therefore, the research on the position drift of GPS single point and improving the accuracy of positioning data by relatively low cost GPS module, to make the low cost products acquiring position information in high precision has a high practical value for meeting the demands of Low-precision navigation and agricultural survey.

Abstract: For the failure diagnose of onsite mechanical equipment, which based on vibration noise in section, both characteristic signal and noise influence were contained in vibration signal, which all accepted by the machine. The problem arise when the characteristic signal was weak compare with the useless noise, the useful signal becomes hard to obtain, hence result in lower accuracy of the equipment. In this thesis, a new method based on the delayed autocorrelation demodulation method was analyzed and will be used on demodulation noise reduction: Based on the noise reduction feature of autocorrelation function, the related analysis was taken on vibration signal, then the autocorrelation function for the signal was obtained. Then with proper delay on autocorrelation function to avoid noise effect and envelop demodulation, we could achieve the demodulation result. The theoretical analysis and simulation experiments has proven the delayed autocorrelation demodulation method achieve better anti-noise performance than direct demodulation method, meanwhile, the delayed autocorrelation demodulation method could also highlights the characteristic information.

Abstract: The noises with high level from the different positions of the train lead to the difficulty for extraction of the acoustic signal from the train bearings. Thus the de-noising should be carried out to eliminate the influence of the noises. A new de-noising method has been proposed based on the Doppler Shift. With the crazy climber detection algorithm, all the instantaneous frequencies could be extracted. According to the acoustic theory of Morse, the information of the position of these acoustic sources is revealed. Finally, the variable digital filtering was employed to remove the noises from the other positions of the train. A simulation on the signal containing with ten frequency components demonstrated the validity of this method proposed and the useful components of the signal were enhanced.

Abstract: The phenomenon of Doppler Shift leads to the difficulty for fault diagnosis of train bearings with a high moving speed. So the elimination of the Doppler shift should be implemented firstly. A Doppler Shift elimination method for the wayside acoustic signal is proposed. The instantaneous frequency estimation based on STFT was applied to attain the IF vector. According to the acoustic theory of Morse, the data fitting was then carried out to achieve the fitting IFs, with which the re-sampling sequence could be established to eliminate Doppler Shift. To demonstrate the validity of this method, an experiment with the synthetic signal containing several frequency components had been carried out. The results show that the re-sampled signal was revised without Doppler Shift.

Abstract: There are a great number of high-frequency and low-frequency noises in the airborne gravity data, so the filtering technology is needed to pick up the weak gravity anomaly. Based on the current filtering methods in airborne gravity data processing: butterworth infinite impulse response(IIR) filtering, window function finite impulse response(FIR) filtering and Kalman smoothing, several methods were compared and studied for the measured airborne gravity data, and the accuracies of extracted gravity anomalies were presented. Results show that the accuracy of Kalman smoothing is better than that of the combined filtering with butterworth IIR and window function FIR.

Abstract: Extended, continuous measuring and analysis for underwater ambient noise can find the objects like ships and submarine. It is important for passive detection of underwater object. A real-time processing method of one-third octave spectrum is presented. It is shown by tests that the method is steady and satisfy the real-time processing.

Abstract: The difficulty of the signal processing is not the acquisition of the signals, but how to get the reasonble interpretations from the signals. Since the 1960s, Wavelet Transform, Fast Fourier method and other theoryies have done some works by some innovative processing methods to achieve a breakthrough. But for their limitions, these methods can not achieve a complete separation if the there are two or more signals in one time domain or frequency domain. In this article, a new engineering signal processing method-pattern filter method has is introduced, by which the signal extraction, sepration and noise reduction can be achieved successfully. Experiments show that this method can not only make a reasonable separation of the various vibration signals, but also give the typical signal extractions and model building ways.

Abstract: The traditional digital modulation recognition methods have high requirements for the SNR. This paper presented a good identification method. The quadratic stochastic resonance for signal processing cascade was proposed, then the signal characteristics of high order cumulants were extracted and the support vector machine was used for classifier, simulation results showed that the correct identification rate was up to 88% or more when the SNR was low as-8dB. The bistable stochastic resonance treatment can effectively improve the SNR.

Abstract: Lock-in amplifier is particularly important in the fNIRS-based system, because the lock-in amplifier can recover the low-level signals buried in significant amounts of noise. But the price of lock-in amplifier is very expensive. This paper presented a software method for designing digital lock-in amplifier. Compared with analogue lock-in amplifier, results show that software lock-in amplifier is feasible for experimental research and can replace the expensive analogue lock-in amplifier.

Abstract: The paper introduces a novel algorithm to determine the optimal decomposition level in wavelet de-noising. The algorithm selects the optimal decomposition level by comparing the sparsity of wavelet coefficients at adjacent levels. The level whose wavelet coefficient has the maximum sparsity can be confirmed as the optimal decomposition level. We demonstrate experimentally that wavelet de-noising performs better using optimal decomposition level determined by our proposed algorithm than White Noise Test (WNT) method and Maximum Energy (ME) method.