Machine Learning for Signal Demodulation in Underwater Wireless Optical Communications

The underwater wireless optical communication(UWOC)system has gradually become essential to underwater wireless communication technology.Unlike other existing works on UWOC systems,this paper evaluates the proposed machine learningbased signal demodulation methods through the selfbuilt experimental platform.Based on such a platform,we first construct a real signal dataset with ten modulation methods.Then,we propose a deep belief network(DBN)-based demodulator for feature extraction and multi-class feature classification.We also design an adaptive boosting(Ada Boost)demodulator as an alternative scheme without feature filtering for multiple modulated signals.Finally,it is demonstrated by extensive experimental results that the Ada Boost demodulator significantly outperforms the other algorithms.It also reveals that the demodulator accuracy decreases as the modulation order increases for a fixed received optical power.A higher-order modulation may achieve a higher effective transmission rate when the signal-to-noise ratio(SNR)is higher.

An improved initial rotor position estimation method using high-frequency pulsating voltage injection for PMSM

High frequency pulsating voltage injection method is a good candidate for detecting the initial rotor position of permanent magnet synchronous motor.However,traditional methods require a large number of filters,which leads to the deterioration of system stability and dynamic performance.In order to solve these problems,a new signal demodulation method is proposed in this paper.The proposed new method can directly obtain the amplitude of high-frequency current,thus eliminating the use of filters,improving system stability and dynamic performance and saving the work of adjusting filter parameters.In addition,a new magnetic polarity detection method is proposed,which is robust to current measurement noise.Finally,experiments verify the effectiveness of the method.

Lensless complex amplitude demodulation based on deep learning in holographic data storage

To increase the storage capacity in holographic data storage(HDS),the information to be stored is encoded into a complex amplitude.Fast and accurate retrieval of amplitude and phase from the reconstructed beam is necessary during data readout in HDS.In this study,we proposed a complex amplitude demodulation method based on deep learning from a single-shot diffraction intensity image and verified it by a non-interferometric lensless experiment demodulating four-level amplitude and four-level phase.By analyzing the correlation between the diffraction intensity features and the amplitude and phase encoding data pages,the inverse problem was decomposed into two backward operators denoted by two convolutional neural networks(CNNs)to demodulate amplitude and phase respectively.The experimental system is simple,stable,and robust,and it only needs a single diffraction image to realize the direct demodulation of both amplitude and phase.To our investigation,this is the first time in HDS that multilevel complex amplitude demodulation is achieved experimentally from one diffraction intensity image without iterations.

A Fault Feature Extraction Model in Synchronous Generator under Stator Inter-Turn Short Circuit Based on ACMD and DEO3S

This paper proposed a new diagnosis model for the stator inter-turn short circuit fault in synchronous generators.Different from the past methods focused on the current or voltage signals to diagnose the electrical fault,the sta-tor vibration signal analysis based on ACMD(adaptive chirp mode decomposition)and DEO3S(demodulation energy operator of symmetrical differencing)was adopted to extract the fault feature.Firstly,FT(Fourier trans-form)is applied to the vibration signal to obtain the instantaneous frequency,and PE(permutation entropy)is calculated to select the proper weighting coefficients.Then,the signal is decomposed by ACMD,with the instan-taneous frequency and weighting coefficient acquired in the former step to obtain the optimal mode.Finally,DEO3S is operated to get the envelope spectrum which is able to strengthen the characteristic frequencies of the stator inter-turn short circuit fault.The study on the simulating signal and the real experiment data indicates the effectiveness of the proposed method for the stator inter-turn short circuit fault in synchronous generators.In addition,the comparison with other methods shows the superiority of the proposed model.

Accurate Phase Detection for ZigBee Using Artificial Neural Network

The IEEE802.15.4 standard has been widely used in modern industry due to its several benefits for stability,scalability,and enhancement of wireless mesh networking.This standard uses a physical layer of binary phase-shift keying(BPSK)modulation and can be operated with two frequency bands,868 and 915 MHz.The frequency noise could interfere with the BPSK signal,which causes distortion to the signal before its arrival at receiver.Therefore,filtering the BPSK signal from noise is essential to ensure carrying the signal from the sen-der to the receiver with less error.Therefore,removing signal noise in the BPSK signal is necessary to mitigate its negative sequences and increase its capability in industrial wireless sensor networks.Moreover,researchers have reported a posi-tive impact of utilizing the Kalmen filter in detecting the modulated signal at the receiver side in different communication systems,including ZigBee.Mean-while,artificial neural network(ANN)and machine learning(ML)models outper-formed results for predicting signals for detection and classification purposes.This paper develops a neural network predictive detection method to enhance the performance of BPSK modulation.First,a simulation-based model is used to generate the modulated signal of BPSK in the IEEE802.15.4 wireless personal area network(WPAN)standard.Then,Gaussian noise was injected into the BPSK simulation model.To reduce the noise of BPSK phase signals,a recurrent neural networks(RNN)model is implemented and integrated at the receiver side to esti-mate the BPSK’s phase signal.We evaluated our predictive-detection RNN model using mean square error(MSE),correlation coefficient,recall,and F1-score metrics.The result shows that our predictive-detection method is superior to the existing model due to the low MSE and correlation coefficient(R-value)metric for different signal-to-noise(SNR)values.In addition,our RNN-based model scored 98.71%and 96.34%based on recall and F1-score,respectively.

A Novel Digital Transceiver for CT0 Standard

This paper introduces a novel digital transceiver for the cordless telephone zero （CT0） standard,which uses a digital modulation and demodulation technique to handle the signal instead of the traditional analog meth-od. In the transmitter,a fractional-N phase locked loop （PLL） is utilized to realize the continuous phase frequency shift key （CPFSK） modulation,and a 2 Ts raised cosine （2RC） shaping technique is used to reduce the occupied bandwidth. In the receiver,a novel digital method is proposed to demodulate the 2RC CPFSK signal. This chip is fabricated using an SMIC 0.35μm mixed signal CMOS process with a die size of 2mm × 2mm. With an external low noise amplifier （LNA）,the sensitivity of the chip is better than -103dBm.

A Novel Low Power ASK Receiver with AGC Loop

We report a low power ASK IF receiver for short-range wireless systems,which includes an AGC loop that compensates the channel attenuation and an ASK detector. A novel current-limited transconductor and feed-forward differential peak detector have been designed to maintain a high compression ratio and fast response for the AGC with lower power consumption. A storage unit with a zero and a feed-forward structure have been introduced into the peak detector to control the damping characteristic of the AGC loop. A rectifier and low-pass filter included in the ASK detector have been integrated into a more compact structure to further lower the power consumption. The simulation results show the feasibility of the proposed technique.

HARDWARE DEMODULATION METHOD FOR &D EDGEDETEOTION AND ERROR OOMPENSATION

A hardwale demodulation method for 2-D edge detection is proposed. The filtering step and the differential step are implemented by using the hardware circuit. This demodulation circuit simplifies the edgefinder and reduces the measuring cycle. The calibration method of scale setting is also presented,and bymeasuring some calibrated objects,the demodulation errors and the error correction table is obtained.

VLSI Implementation of a Single-Chip DVB-C Demodulator

A single-chip DVB-C quadrature amplitude modulation（QAM） demodulator is proposed,which integrates a 3.3V 10bit 40MSPS analog-to-digital converter and a forward error correction decoder. The demodulator chip can support 4-256 QAM with variable bit rate up to 80Mbps. It features a wide carrier offset acquisition range,optimal demodulation algorithm,and small circuit area. The chip is implemented in SMIC 0.25μm 1P5M mixed-signal CMOS technology with a die size of 3.5mm×3. 5mm. The maximum power consumption is 447mW.

超小型气象卫星云图接收系统

超小型气象卫星云图接收系统于东海，孙敏松，齐宁华（东南大学毫米波国家重点实验室，南京２１００１８）卫星云图已广泛应用于天气预报、洪涝监测、海洋捕捞、森林防火、农业估产、植被覆盖观测等多种领域，但原有设备庞大复杂，造价高，操作过于专业，不利于普及使用，...

数字移动通信中的均衡技术

数字移动通信中的均衡技术林福华曹基荣邢松（东南大学移动通信国家重点实验室，南京２１００１８）模拟蜂窝移动通信系统因其话音采用模拟制调频，通信质量及系统容量受到较大限制．而数字蜂窝通信系统因其频谱利用率高、质量性能优良、可支持多种业务等优点，正日益显示...

Advances in phase-sensitive optical time-domain reflectometry

Phase-sensitive optical time-domain reflectometry(Φ-OTDR)has attracted numerous attention due to its superior performance in detecting the weak perturbations along the fiber.Relying on the ultra-sensitivity of light phase to the tiny deformation of optical fiber,Φ-OTDR has been treated as a powerful technique with a wide range of applications.It is fundamental to extract the phase of scattering light wave accurately and the methods include coherent detection,I/Q demodulation,3 by 3 coupler,dual probe pulses,and so on.Meanwhile,researchers have also made great efforts to improve the performance ofΦ-OTDR.The frequency response range,the measurement accuracy,the sensing distance,the spatial resolution,and the accuracy of event discrimination,all have been enhanced by various techniques.Furthermore,lots of researches on the applications in various kinds of fields have been carried out,where certain modifications and techniques have been developed.Therefore,Φ-OTDR remains as a booming technique in both researches and applications.

Demodulation Based on Harmonic Wavelet and Its Application into Rotary Machinery Fault Diagnosis

The harmonic wavelet transform（HWT） and its fast realization based on fast Fourier transform（FFT） are introduced. Its ability to maintain the same amplitude-frequency feature is revealed. A new method to construct the time-frequency（TF） spectrum of HWT is proposed, which makes the HWT TF spectrum able to correctly reflect the time-frequency-amplitude distribution of the signal. A new way to calculate the HWT coefficients is proposed. By zero padding the data taken out, the non-decimated coefficients of HWT are obtained. Theoretical analysis shows that the modulus of the coefficients obtained by the new calculation way and living at a certain scale are the envelope of the component in the corresponding frequency band. By taking the cross section of the new TF spectrum, the demodulation for the component at a certain frequency band can be realized. A comparison with the Hilbert demodulation combined with band-pass filtering is done, which indicates for multi-components, the method proposed here is more suitable since it realizes ideal band-pass filtering and avoids pass band selecting. In the end, it is applied to bearing and gearbox fault diagnosis, and the results reflect that it can effectively extract the fault features in the signal.

Demodulation System for Fiber Bragg Grating Sensors Using Digital Filtering Technique

A discrimination measurement method and demodulation technique for fiber Bragg grating (FBG) sensors were presented using digital filtering technique. The system can control a tunable fiber Fabry-Perot filter with sawtooth wave voltage generated by digital clock to interrogate FBG sensors. Using the analogue digital converter (ADC), the reflected FBG signals were sampled with synchronous digital clock. With the aid of digital matched filtering technique, the sampled FBG signals were processed to obtain the maximum signal-to-noise ratio (SNR) and the Bragg wavelength shift from the FBG signals was recovered. The results demonstrate that this system has a scanning range of 1 520 nm-1 575 nm,and the wavelength detection accuracy is less than 2 pm with 1.5 Hz scanning frequency.

Improved adaptive filter and its application in acoustic emission signals

In order to de-noise and filter the acoustic emission(AE) signal, the adaptive filtering technology is applied to AE signal processing in view of the special attenuation characteristics of burst AE signal. According to the contradiction between the convergence speed and steady-state error of the traditional least mean square(LMS) adaptive filter, an improved LMS adaptive filtering algorithm with variable iteration step is proposed on the basis of the existing algorithms. Based on the Sigmoid function, an expression with three parameters is constructed by function translation and symmetric transformation.As for the error mutation, e(k) and e(k-1) are combined to control the change of the iteration step. The selection and adjustment process of each parameter is described in detail, and the MSE is used to evaluate the performance. The simulation results show that the proposed algorithm significantly increases the convergence speed, reduces the steady-state error, and improves the performance of the adaptive filter. The improved algorithm is applied to the AE signal processing, and the experimental signal is demodulated by an empirical mode decomposition(EMD) envelope to obtain the upper and lower envelopes. Then, the expected function related to the AE signal is established. Finally, the improved algorithm is substituted into the adaptive filter to filter the AE signal. A good result is achieved, which proves the feasibility of adaptive filtering technology in AE signal processing.

Generalized Demodulation Transform for Bearing Fault Diagnosis Under Nonstationary Conditions and Gear Noise Interferences

It is a challenging issue to detect bearing fault under nonstationary conditions and gear noise interferences. Meanwhile, the application of the traditional methods is limited by their deficiencies in the aspect of computational accuracy and e ciency, or dependence on the tachometer. Hence, a new fault diagnosis strategy is proposed to remove gear interferences and spectrum smearing phenomenon without the tachometer and angular resampling technique. In this method, the instantaneous dominant meshing multiple(IDMM) is firstly extracted from the time-frequency representation(TFR) of the raw signal, which can be used to calculate the phase functions(PF) and the frequency points(FP). Next, the resonance frequency band excited by the faulty bearing is obtained by the band-pass filter. Furthermore, based on the PFs, the generalized demodulation transform(GDT) is applied to the envelope of the filtered signal. Finally, the target bearing is diagnosed by matching the peaks in the spectra of demodulated signals with the theoretical FPs. The analysis results of simulated and experimental signal demonstrate that the proposed method is an e ective and reliable tool for bearing fault diagnosis without the tachometer and the angular resampling.

Design of Parallel Electrical Resistance Tomography System for Measuring Multiphase Flow

ERT(electrical resistance tomography) is effective method for visualization of multiphase flows,offering some advantages of rapid response and low cost,so as to explore the transient hydrodynamics.Aiming at this target,a fully programmable and reconfigurable FPGA(field programmable gate array)-based Compact PCI(peripheral component interconnect) bus linked sixteen-channel ERT system has been presented.The data acquisition system is carefully designed with function modules of signal generator module;Compact PCI transmission module and data processing module(including data sampling,filtering and demodulating).The processing module incorporates a powerful FPGA with Compact PCI bus for communication,and the measurement process management is conducted in FPGA.Image reconstruction algorithms with different speed and accuracy are also coded for this system.The system has been demonstrated in real time(1400 frames per second for 50 kHz excitation) with signal-noise-ratio above 62 dB and repeatability error below 0.7%.Static experiments have been conducted and the images manifested good resolution relative to the actual object distribution.The parallel ERT system has provided alternative experimental platform for the multiphase flow measurements by the dynamic experiments in terms of concentration and velocity.

Design of Demodulation System of Interferometric Sensor Based on Labview

For the modified demodulation arithmetic of 3×3 coupler, the processing software built on the basis of Labview is able to demodulate asymmetric 3×3 coupler signal and do further spectrum analysis. It shows that the measured frequency ranges from 10 Hz to 1 000 Hz and phase range is covered by -10 rad^10 rad. The phase sensitivity is 0.5 V/rad. This system is proved to show high resolution and wide dynamic range.

A new method of demodulating the digital frequency modulation signals

A new method of estimating the frequency-known signals from the strong background noise was presented first. Then the new method was used in the demodulation of the digital frequency modulation (FSK) signals. The new demodulation method can complete the demodulation of the FSK signals only with the carrier frequency and without any carrier phase information. The simulation results show that the performance of anti-noise of the new method is better than that of the incoherent demodulation method and the fluctuation of the carrier phase has little effect on the new method. So the new demodulation method has a fine prospect in the practical applications.

Research and test of the adaptive quadrature demodulation technology for silicon micro-machined gyroscope

A program of adaptive quadrature demodulation is proposed to supply the gaps in the traditional analog detection technology of a silicon micro-machined gyroscope (SMG). This program is suitable for digital phase locked loop (DPLL) drive technology that proposed in other papers. In addition the program adopts an adaptive filtering algorithm, which selects the in-phase and quadrature components that are outputs of the DPLL of the SMG's drive mode as reference signals to update the amplitude of the in-phase and quadrature components of the input signal by iteratively. An objective of the program is to minimize the mean square error of the accurate amplitudes and the estimated amplitudes of SMG's detection mode. The simulation and test results prove the feasibility of the program that lays the foundation for the further improvement of the SMG's system performance and the implementation of the SMG system's self-calibration and self-demarcation in future.