Advanced Engineering Forum Vols. 2-3

Abstract: Ocular artifacts are the most important form of interferences in EEG signals. Before analyzed, EEG signals should be pretreated by removal of ocular artifacts. CICA is an excellent approach to separate the desired source signals. But, the choice of reference signals is crucial. In this paper, we adopted CICA to separate ocular artifact from EEG, using a different method from Lu to build the reference signals, which can avoid the subjectivity during the operation. It was proved to be effective.

Abstract: Based on the demand of engineering, the motion characteristics and time-frequency properties of rotor system with rub-impact at fixed limiter are studied by experiment. Three typical cases at different rotating speeds are chosen from the experiment. On the basis of traditional amplitude spectrum and shaft center orbit methods, Hilbert-Huang transformation is applied to the fault signals analysis. Fault features are characterized completely and accurately by Hilbert spectrum. It is show that the vibration of the system is with typical characteristic of periodic motions and corresponding time-frequency (instantaneous frequency) -amplitude /energy representations in the rotor system with rub-impact at fixed limiter.

Abstract: Wavelet analysis with its unique features is very suitable for analyzing non-stationary signal, and it can also be used as an ideal tool for signal processing in fault diagnosis. The characteristics of the faults and the necessary information on the diagnosis can be constructed and extracted respectively by wavelet analysis. Though wavelet analysis is specialized in characteristics extraction, it can not determine the fault type. So this paper has proposed an energy analysis method based on wavelet transform. Experiment results show the method is very effective for sensor fault diagnosis, because it can not only detect the sensor faults, but also determine the fault type.

Abstract: In this paper, we proposed a peripheral sound visualization method based on improved ripple mode for the deaf. In proposed mode, we designed the processes of transforming sound intensity and exterminating the locations of sound sources. We used power spectrum function to determine the sound intensity. ARTI neural network was subtly applied to identify which kind of the real-time input sound signals and to display the locations of the sound sources. We present the software that aids the development of peripheral displays and four sample peripheral displays are used to demonstrate our toolkit’s capabilities. The results show that the proposed ripple mode correctly showed the information of combination of the sound intensity and location of the sound source and ART1 neural network made accurate identifications for input audio signals. Moreover, we found that participants in the research were more likely to achieve more information of locations of sound sources.

Abstract: Wavelet Neural Network (WNN) Is a Time-frequency Analysis Method, which Detects the Subtle Small Changes in the Signal Frequency Domain. Adaptive Filter Provides a Kind of Simple and Applied Method for Processing Signals in Noise. in this Paper, we Proposed a New Speech Enhancement Technique which Is Based on Wavelet Neural Network Using Adaptive Matched Filter Adjusting Weight. we Choose the Signal with Noise Pollution as the Input Signal and then Put it to the Trained Wavelet Neural Network. Wavelet Decomposition and Wavelet Neural Network Weights Processing Adopt Signal Sub-band Adaptive Matched Filter, the Output Signal of Wavelet Neural Network Is an Approximation Form of Original Signal. the Results Show that the WNN Is a Quite Effective Method for the Speech Enhancement and Improving the Ration of Signal to Noise.

Abstract: Sensor networks, which can immediately detect events and situations and automatically control actuators, are expected to proliferate in the future, even though their visualization of sensor networks has not been emphasized. Identifying broken nodes in real environments remains difficult using a traditional visualization tool that plots the virtual diagram on which sensor nodes are put. In this paper, we propose and implement a control system of sensor network devices with AR technology. Our proposed system displays sensor data and network information such as the link status, the packet data, and the traffic in the sensor network on an AR interface. In addition, we control the sensor devices through the AR interface. Our proposed system allows users to intuitively acquire the status of sensor networks. We can also control the devices through the AR interface.

Abstract: Speech endpoint detection is one of the key problems in the practical application of speech recognition system. In this paper, speech signal contained chirp is decomposed into several intrinsic mode function (IMF) with the method of ensemble empirical mode decomposition (EEMD). At the same time, it eliminates the modal mix superposition phenomenon which usually comes out in processing speech signal with the algorithm of empirical mode decomposition (EMD). After that, selects IMFs contained major noise through the adaptive algorithm. Finally, the IMFs and speech signal contained chirp are input into the independent component analysis (ICA) and pure voice signal is separated out. The accuracy of speech endpoint detection can be improved in this way. The result shows that the new speech endpoint detection method proposed above is effective, and has strong anti-noises ability, especially suitable for the speech endpoint detection in low SNR.

Abstract: The resonance frequency of the cymbal transducer ranges from 2kHz to 40kHz and its effective electromechanical coupling factor is around 20%. Finite element analysis has been performed to ascertain how the transducer’s makeup affect the transducer’s performance parameters. Two-dimensional axisymmetric model of the cymbal transducer was founded by finite element software-ANSYS, the application of the element type was discussed and the FEM models were built up under the far field condition. Eight groups of cymbal transducers of resonance frequency around 3kHz with different structural dimensions were designed. It was better for choosing the cymbal transducer of the 8mm cavity coping diameter, 20.8mm cavity bottom diameter and 26.8mm piezoelectric ceramic wafer diameter than others for reducing distortion degree of the signal and improving communication turnover in the researched cymbal transducers. It was appropriate for choosing the cymbal transducer of the 8mm cavity coping diameter, 22.4mm cavity bottom diameter and 26.4mm piezoelectric ceramic wafer diameter in order to improve the free-field voltage sensitivity and transmission efficient.

Abstract: The performance of bandwidth and transmitting voltage response to the piezoelectric dual-excited underwater acoustic transducer are studied by FEM software ANSYS in the paper. At first, the mechanism of the dual-excited transducer is analyzed, once this is done, The FEM models with different axial dimension of the piezoelectric stack and the mid mass, Al and steel are specified for the material of mid mass respectively. the calculated curves are contrasted, the results were found that the appropriate proportion of the mid-mass to the stack will broaden the bandwidth and enhance the transmitting voltage response, the increase of the thickness of the mid-mass will reduce the transmitting voltage response, and the bandwidth can be expanded to 13kHz, the resonance frequency has shifted to a higher value, it ranges from 34kHz to 46kHz. The results show that one octave bandwidth could be achieved and provide support for the next production and experiment of the broadband underwater acoustic transducer.

Abstract: This research aims at investigating the response characteristics of fiber Bragg grating sensors (FBGs) to ultrasonic signals. The testing system was set up with a tunable laser source and the FBGs installed on the surface of an aluminum plate. Then the response characteristics of FBGs were compared, in condition of putting the ultrasonic driving source in the different longitudinal, lateral and angular separation. Measurements were taken by changing the distance between the sensor and the transducer from 60 mm to 200 mm with a step of 20 mm. Then keeping the distance at 100 mm and 200 mm respectively, do the angular experiment with the angle from 0° to 90° by the step of 10°. Experiment results show that FBG can get better signals when the transducer is along its axial direction. When the location of the transducer is changed linearly, no obvious linear change of the signal strength has been found.