Edge detection is a fundamental issue in image analysis. This paper proposes multirate algorithms for efficient implementation of edge detector, and a design example is illustrated.The multirate (decimation and/or int...Edge detection is a fundamental issue in image analysis. This paper proposes multirate algorithms for efficient implementation of edge detector, and a design example is illustrated.The multirate (decimation and/or interpolation) signal processing algorithms can achieve considerable savings in computation and storage. The proposed algorithms result in mapping relations of their z-transfer functions between non-multirate and multirate mathematical expressions in terms of time-varying coefficient instead of traditional polyphase decomposition counterparts.The mapping properties can be readily utilized to efficiently analyze and synthesize multirate edge detection filters. The Very high-speed Hardware Description Language (VHDL) simulation results verify efficiency of the algorithms for real-time Field Programmable Gate-Array (FPGA)implementation.展开更多
Herein we report a highly sensitive filter-less fluorescence detection method using an APD （avalanche photodiode）. Experimental measurements using the proposed APD-based highly sensitive fluorescence detection metho...Herein we report a highly sensitive filter-less fluorescence detection method using an APD （avalanche photodiode）. Experimental measurements using the proposed APD-based highly sensitive fluorescence detection method exhibits the sensing capability to detect an excitation light and a fluorescence light without band pass filter or grating. The principle of this APD-based highly fluorescence detection method is used the varying multiplication ratio that is decided by wavelength. The wavelength controls running distance of photo-excited carrier by absorption coefficients, and this element decide multiplication ratio on fixed high electrical field. In fluorescence detection, they use two types of light： excitation light and fluorescence light. These lights have different wavelengths and make different multiplication ratio as well. Thus this method can separate two types of light easily by using multiplication ratios of APD without band pass filters/gratings. In this experiment, the excitation light is LED （light emitting diode） and fluorescence light occurs from FITC （fluorescein isothiocyanate） with ethanol. The FITC concentration changes from 0.1 μmol/L to 10 mmol/L. In this measurement circuit, we employ APD （S2385）, power supply voltage, and pico ampere current meter. As a result, these lights are correctly separated by using multiplication ratio with calculation at every concentration FITCs.展开更多
The local defect in rotating machine always gives rise to repetitive transients in the collected vibration signal. However, the transient signature is prone to be contaminated by strong background noises, thus it is a...The local defect in rotating machine always gives rise to repetitive transients in the collected vibration signal. However, the transient signature is prone to be contaminated by strong background noises, thus it is a challenging task to detect the weak transients for machine fault diagnosis. In this paper, a novel adaptive tunable Q-factor wavelet transform(TQWT) filter based feature extraction method is proposed to detect repetitive transients. The emerging TQWT possesses distinct advantages over the classical constant-Q wavelet transforms, whose Q-factor can be tuned to match the oscillatory behavior of different signals, but the parameter selection for TQWT heavily relies on prior knowledge. Within our adaptive TQWT filter algorithm, the automatic optimization techniques for three TQWT parameters are implemented to achieve an optimal TQWT basis that matches the transient components. Specifically, the decomposition level is selected according to a center frequency ratio based stopping criterion, and the Q-factor and redundancy are optimized based on the minimum energy-weighted normalized wavelet entropy.Then, the adaptive TQWT decomposition can be achieved in a sparse way and result in subband signals at various wavelet scales.Further, the optimum subband signal which carries transient feature information, is identified using a normalized energy to bandwidth ratio index. Finally, the single branch reconstruction signal from the optimum subband is obtained with transient signatures via inverse TQWT, and the frequency of repetitive transients is detected using Hilbert envelope demodulation. It has been verified via numerical simulation that the proposed adaptive TQWT filter based feature extraction method can adaptively select TQWT parameters and the optimum subband for repetitive transient detection without prior knowledge. The proposed method is also applied to faulty bearing vibration signals and its effectiveness is validated.展开更多
文摘Edge detection is a fundamental issue in image analysis. This paper proposes multirate algorithms for efficient implementation of edge detector, and a design example is illustrated.The multirate (decimation and/or interpolation) signal processing algorithms can achieve considerable savings in computation and storage. The proposed algorithms result in mapping relations of their z-transfer functions between non-multirate and multirate mathematical expressions in terms of time-varying coefficient instead of traditional polyphase decomposition counterparts.The mapping properties can be readily utilized to efficiently analyze and synthesize multirate edge detection filters. The Very high-speed Hardware Description Language (VHDL) simulation results verify efficiency of the algorithms for real-time Field Programmable Gate-Array (FPGA)implementation.
文摘Herein we report a highly sensitive filter-less fluorescence detection method using an APD （avalanche photodiode）. Experimental measurements using the proposed APD-based highly sensitive fluorescence detection method exhibits the sensing capability to detect an excitation light and a fluorescence light without band pass filter or grating. The principle of this APD-based highly fluorescence detection method is used the varying multiplication ratio that is decided by wavelength. The wavelength controls running distance of photo-excited carrier by absorption coefficients, and this element decide multiplication ratio on fixed high electrical field. In fluorescence detection, they use two types of light： excitation light and fluorescence light. These lights have different wavelengths and make different multiplication ratio as well. Thus this method can separate two types of light easily by using multiplication ratios of APD without band pass filters/gratings. In this experiment, the excitation light is LED （light emitting diode） and fluorescence light occurs from FITC （fluorescein isothiocyanate） with ethanol. The FITC concentration changes from 0.1 μmol/L to 10 mmol/L. In this measurement circuit, we employ APD （S2385）, power supply voltage, and pico ampere current meter. As a result, these lights are correctly separated by using multiplication ratio with calculation at every concentration FITCs.
基金supported by the National Natural Science Foundation of China (Grant Nos. 51335006 & 51605244)
文摘The local defect in rotating machine always gives rise to repetitive transients in the collected vibration signal. However, the transient signature is prone to be contaminated by strong background noises, thus it is a challenging task to detect the weak transients for machine fault diagnosis. In this paper, a novel adaptive tunable Q-factor wavelet transform(TQWT) filter based feature extraction method is proposed to detect repetitive transients. The emerging TQWT possesses distinct advantages over the classical constant-Q wavelet transforms, whose Q-factor can be tuned to match the oscillatory behavior of different signals, but the parameter selection for TQWT heavily relies on prior knowledge. Within our adaptive TQWT filter algorithm, the automatic optimization techniques for three TQWT parameters are implemented to achieve an optimal TQWT basis that matches the transient components. Specifically, the decomposition level is selected according to a center frequency ratio based stopping criterion, and the Q-factor and redundancy are optimized based on the minimum energy-weighted normalized wavelet entropy.Then, the adaptive TQWT decomposition can be achieved in a sparse way and result in subband signals at various wavelet scales.Further, the optimum subband signal which carries transient feature information, is identified using a normalized energy to bandwidth ratio index. Finally, the single branch reconstruction signal from the optimum subband is obtained with transient signatures via inverse TQWT, and the frequency of repetitive transients is detected using Hilbert envelope demodulation. It has been verified via numerical simulation that the proposed adaptive TQWT filter based feature extraction method can adaptively select TQWT parameters and the optimum subband for repetitive transient detection without prior knowledge. The proposed method is also applied to faulty bearing vibration signals and its effectiveness is validated.
