Traditional Demodulation Method Research Articles

High-sensitivity ocean temperature sensor usinga reflective optical microfiber coupler andmachine learning methods.

This paper proposes a novel seawater temperature sensor, to the best of our knowledge, that utilizes an optical microfiber coupler combined with a reflective silver mirror (OMCM). The sensor's sensitivity and durability are enhanced by encapsulating it in polydimethylsiloxane (PDMS). Additionally, a specially designed metal casing prevents the OMCM from responding to pressure, thus avoiding the challenge of multi-parameter demodulation and increasing its adaptability to harsh environments. The paper analyzes the advantages of the new sensor structure and evaluates its performance in terms of temperature sensitivity and compressive strength through experiments. Finally, the paper employs machine learning demodulation methods. Compared with traditional demodulation methods, the particle swarm optimization support vector regression (PSO-SVR) algorithm demonstrates a substantial reduction in the demodulation error. Specifically, the mean absolute percentage error (MAPE) relative to the full scale drops from 2.16% to 0.157%. This paper provides an effective solution for high-precision monitoring of the ocean environmental temperature.

Sub-surface thermal measurement in additive manufacturing via machine learning-enabled high-resolution fiber optic sensing

Microstructures of additively manufactured metal parts are crucial since they determine the mechanical properties. The evolution of the microstructures during layer-wise printing is complex due to continuous re-melting and reheating effects. The current approach to studying this phenomenon relies on time-consuming numerical models such as finite element analysis due to the lack of effective sub-surface temperature measurement techniques. Attributed to the miniature footprint, chirped-fiber Bragg grating, a unique type of fiber optical sensor, has great potential to achieve this goal. However, using the traditional demodulation methods, its spatial resolution is limited to the millimeter level. In addition, embedding it during laser additive manufacturing is challenging since the sensor is fragile. This paper implements a machine learning-assisted approach to demodulate the optical signal to thermal distribution and significantly improve spatial resolution to 28.8 µm from the original millimeter level. A sensor embedding technique is also developed to minimize damage to the sensor and part while ensuring close contact. The case study demonstrates the excellent performance of the proposed sensor in measuring sharp thermal gradients and fast cooling rates during the laser powder bed fusion. The developed sensor has a promising potential to study the fundamental physics of metal additive manufacturing processes.

Flexible Generalized Demodulation for Intelligent Bearing Fault Diagnosis Under Nonstationary Conditions

Rotating machinery fault diagnosis under nonstationary conditions still mainly relies on manual analysis of the frequency spectrums or the time-frequency representations of vibration signals. However, not only do the results of those methods depend on heavily the expert experience, but for some samples, the intricate interference frequency components caused by the complex modulation characteristics and the operation conditions also make it difficult to identify the frequency content. In this article, a novel intelligent fault diagnosis method for rolling bearings under nonstationary conditions is investigated. A new flexible generalized demodulation method is first proposed. Different from traditional demodulation methods, it can map the interest time-varying frequencies of extensive samples under different speed conditions to the defined base frequency as well as its multiples, and thus overcomes the effects of operation conditions on demodulation spectrums. Based on the demodulation method, a fault feature extraction method is further proposed to capture the useful fault information in the spectrums. Experiments validate that, for some samples, the health conditions cannot be manually identified by the demodulation spectrums due to the interference frequency components, but can be recognized by the proposed method automatically, and because of the definite physical meaning, the method is more adaptive to new operation conditions.

A dual-axis high-order harmonic and single-axis phase-insensitive demodulation atomic magnetometer for in situ NMR detection of Xe

Based on the parametric oscillation process, we demonstrate the dual-axis phase-sensitive demodulation (PSD) and single-axis phase-insensitive demodulation (PISD) for the atomic magnetometer in an in situ nuclear magnetic resonance (NMR) detection system, which can separate the precession signals of NMR from the oscillating magnetic fields. The two orthogonal magnetic fields can be detected simultaneously and independently by selecting the optimal demodulation phases with the traditional PSD method. The response signals of the parametric modulation magnetometer demodulated with high order harmonic signals are evaluated, which is a new exploration. The first order harmonic demodulation can present the best sensitivity about 250 fT/Hz1/2. The high order harmonic demodulation technology supplies a twofold 3 dB bandwidth. With the PISD method, a single-axis demodulation technique is proposed. The transverse nuclear spin precession magnetic fields can be extracted effectively with the demodulation R signal outputs by setting a specific longitudinal modulation magnetic field amplitude, which is a new demodulation strategy compared with the traditional demodulation method for the NMR system.

Demodulation method based on a component synthesis and gradient projection for phase-shifting interferometry.

In order to reduce the vibration error of phase-shifting interferometry (PSI) and improve the demodulation accuracy of the wavefront phase, a demodulation method based on a component synthesis and gradient projection for PSI is proposed. For two sequences of interference images with a phase shift of 0, π/2, the method first corrects the vibration error by the pre-processing mechanism and multi-component synthesis. At the same time, two frames of interference images with a phase shift of 0, π/2 are synthesized. Then the gradient projection algorithm is used to filter the background light of the synthesized image, and the wavefront phase is demodulated based on the arctangent operation. The experimental results show that the percentage of pixels demodulated effectively at the truncated interface is more than 90%. Compared with the traditional demodulation method, the number of pixels demodulated effectively (demodulation accuracy) is improved.

Study on phase demodulation algorithm of fiber optic pressure sensor based on nonlinear differential equation

Fiber optic Fabry–Pérot sensors have been widely developed with unique advantages, such as ease of reuse, resistance to electromagnetic interference, light weight, and their ability to work in extreme environments. There are many demodulation methods that can be applied to fiber optic Fabry–Pérot sensors, including the intensity demodulation method, spectral demodulation, and the phase carrier method, but these demodulation methods cannot meet the requirements that take into account range, speed, and dynamic and static demodulation capabilities. In view of these problems, this paper uses nonlinear differential equations to solve the problem of simultaneous measurement of a large number of ranges and dynamic and static parameters. The measuring interferometer in the demodulation module was built using a polarizing interferometer, which avoids the difficulty in optical wedge processing when using a Fizeau interferometer. Regarding the problems of high and low signal-to-noise ratios of the generated signal, for the problem that the introduction of dispersion in the crystal causes the demodulation result of the traditional demodulation method to be wrong, a nonlinear differential equation is proposed to achieve the correct demodulation of the fiber optic sensor: the slow demodulation speed problem. This paper designs the acquisition, transmission, and processing system based on digital signal processing and a field-programmable gate array, which provide a hardware platform for real-time demodulation. Finally, experiments to test the resolution, linearity, stability, and repeatability of the interferometer were carried out on the designed demodulation system.

A High Resolution Synchronous Demodulation Method Based on Gated Integrator for Precision Sensors

This article proposes a synchronous demodulation method based on gated integrator for precision sensors, which shows significant improvement in signal-to-noise ratio (SNR) and resolution. Several traditional demodulation methods are introduced, especially the lock-in amplifier in detail for comparison. Through a comprehensive analysis of the gated integrator, it is proven that the proposed method shows a larger useful signal output with similar noise suppression capability compared with the lock-in amplifier so a better SNR could be obtained. Circuits of the two demodulation methods are manufactured and tested, and the results show that the output characteristic of the proposed method is consistent with the theoretical analysis. A precision eddy current displacement sensor prototype with the two demodulation methods is designed and tested as an example. It is found that the resolution of the sensor is improved with the proposed method by about 0.4 bits. Furthermore, this method is expected to function efficiently for any precision sensor requiring synchronous demodulation.

Research on MSK Demodulation Method for M-Sequence in IFF System

M-Sequence, short for Maximum Linear Feedback Shift Register Sequence, is widely used in identification friend or foe (IFF) system because of its good equalization and autocorrelation characteristics, and Minimum Shift Keying (MSK) signal has been paid more attention in military communication field because of its excellent signal characteristics. A new demodulation method for MSK modulation signal of M-Sequence is studied. The MSK signal is sampled by A/D converter, and an integration circuit is designed in the FPGA. The same M-Sequence is generated by the same M-Sequence source polynomial as the integrator coefficient. The peak value of the integrated signal is judged to determine the M-Sequence. When the symbol rate is 1 Mbps and the carrier rate is 1 Mbps and M-Sequence is 5 bits, the recognition time of the new method is less than 1 us, which is less than one fifth of the recognition time of the traditional demodulation method. This method simplifies the demodulation process and is easy to implement. It improves the recognition speed of M-Sequence in MSK modulation signal and provides some reference value for the development of IFF system.

NN‐based IDF demodulator in band‐limited communication system

To meet the spectrum requirement in the future wireless communication system, the m-ary phase position shift keying as a type of the spectrally efficient modulation has been considered in this study. However, the inter-symbol interference (ISI), the waveform distortion and the non-white noise are introduced by the band-pass infinite impulse response filters, which is adopted to limit the signal bandwidth and eliminate the out-band interference. The traditional demodulation methods based on impacting filter or matched filter cannot work well in these scenarios. Therefore, a neural network (NN)-based demodulator is proposed to solve the problem of waveform distortion. Additionally, a novel NN-based iterative decision feedback (IDF) demodulator is also proposed to further reduce the ISI iteratively by using the previous estimated symbol information. Simulation results show that both the NN-based demodulator and the NN-based IDF demodulator can greatly outperform the traditional demodulation methods in the band-limited communication system, and the NN-based IDF demodulator achieves better performance than the normal NN-based demodulator.

GMSK iterative carrier recovery for AIS burst-mode

In this paper, an iterative carrier recovery algorithm of Gaussian filtered minimum shift keying (GMSK) in burst-mode was designed. The data utilization rate and precision of the traditional demodulation method for recovering carrier signal in burst data packet with limited-length is poor. In order to solve this problem, this paper proposed an iterative carrier recovery algorithm. This algorithm can improve the estimated precision of carrier recovery and data utilization rate of burst data packet in a large extent by performing multiple forward and backward iterations. And the algorithm can be implemented in Simulink environment. As the communication mode of automatic identification system (AIS) is abrupt, the algorithm is especially suitable for satellite-based AIS.

Cyclostationary Analysis of a Faulty Bearing in the Wind Turbine

Bearing faults occur frequently in wind turbines, thus resulting in an unplanned downtime and economic loss. Vibration signal collected from a failing bearing exhibits modulation phenomenon and “cyclostationarity.” In this paper, the cyclostationary analysis is utilized to the vibration signal from the drive-end of the wind turbine generator. Fault features of the inner and outer race become visible in the frequency–cyclic frequency plane. Such fault signatures can not be produced by the traditional demodulation methods. Analysis results demonstrate effectiveness of the cyclostatonary analysis. The disassembled faulty bearing visualizes the fault.

Demodulation for hydraulic pump fault signals based on local mean decomposition and improved adaptive multiscale morphology analysis

Scales of IAMMA are adaptively determined by morphological features of signal, thus fault features of a hydraulic pump fault signal presented in multi-scales can be adaptively demodulated. In some coefficient range, IAMMA outperforms AMMA in demodulation ability based on the same SE, and it is less susceptible to noises than AMMA. The best performance of IAMMA with triangle SE is stronger than that of IAMMA with plat and semi-circle SE when they demodulate the same fault signal of hydraulic pump. Compared with traditional demodulation methods of HT and TKEO, IAMMA is adaptive and has stronger demodulation ability. An evaluation method based on kurtosis, power and standard deviation is proposed, by which some PFs which are rich in fault features can be selected as data source.

Application of Resonance Demodulation in Rolling Bearing Fault Diagnosis Based on Electronic Resonant

The resonance demodulation is an important method in rolling bearing fault feature extraction and fault diagnosis. But in the traditional resonance demodulation method, the resonant frequency of the accelerometer sensing fault information is discrete to some degree due to processing, debugging and installing factors, and the parameters of the band-pass filter are in need for defining beforehand. Meanwhile, as the message generated by bearing early minor failure is often submerged in strong background noise, the SNR is low, the capacity to apply traditional resonance demodulation method to improve the SNR is limited, and the diagnosis effects are not obvious enough. This paper makes use of the equivalence between the electronic resonant system and the mechanical resonance system and conducts resonant gain for sensor output signal using electronic resonators, overcoming the shortcomings of the traditional methods, realizing a UNB high-resolution detection and improved fault feature signal SNR. Besides, the effectiveness of the proposed method has been validated by simulations and experiments, which possess important guiding significance for the engineering practice.

Study on Multipath Effect under the Environment of PCM/FM Telemetry Soft Demodulation

Because the reentry telemetry wireless channel multipath propagation effects and the effect, channel will introduce transmission time delay dispersion, caused between the PCM/FM telemetry signal crosstalk and signal to noise ratio is too low, significantly increase BER. While traditional demodulation method because the demodulator threshold higher no longer apply. Study the problem, a multiple Symbol Detection method based on sliding strategy (Multi - Symbol Detection, MSD), can effectively overcome the low SNR and inter symbol interference. The simulation and test results verify the effectiveness of the method.

Study of Symbol Detection Performance of Two Kinds of Compensation Method

Pulse coding/frequency modulation (PCM/FM) system is a rocket system mainly adopts remote sensing system, and MSD (Multi - Symbol Detection) is to overcome the traditional demodulation methods threshold effect. For multiple symbol detection misjudgment rate is higher in the process of problem, put forward two compensation methods: under the premise of without changing the length of the observation, every time by changing the length of sliding between the ruling and ultimately achieve the purpose of reduce misjudgment. The simulation analysis and test results verified the effectiveness and applicability of two kinds of compensation algorithm.

An Improved Method of Demodulation for Air-Ground Data Link Communication System

The Aircraft Communication Addressing and Reporting System (ACARS) is playing an increasingly important role to guarantee the safety and the efficiency of aircraft, so more effective method of receiving is necessary. The modulation of the ACARS system is MSK, the aim of this paper is to find a better demodulation method for the signal of ACARS. The characteristic of mapping relationship between code-element and the signal of waveform is analyzed. A new demodulation method is proposed based on the characteristic. Compared to the traditional demodulation method, it has a more simple structure. A simulation is made to verify its performance in the background of Gaussian noise. The comparison with traditional methods is also be made. Finally the benefit and weakness of this method is discussed.

Research on Soft Demodulation of Anamorphic PCM/FM Signal under the Condition of Low SNR

Reentry telemetry channel is a special channel in the process of remote sensing, black barrier and multipath effect will cause the PCM/FM telemetry signal-to-noise ratio and frequency selective fading , even break through the traditional demodulation method of demodulation threshold, led to the bit error rate is greatly increased when aircraft fly through the reentry telemetry channel. Aiming at the problem, a sliding length of 1 more Symbol Detection (Multi - Symbol Detection, MSD) demodulation algorithm is studied: the continuous observations of N element signal and local signal for joint Detection, but each time the MSD sentences a MSD earlier with N - 1 element coincidence. In theory, the algorithm can increase the channel gain about 3 db, the simulation and test results verified the effectiveness of the proposed algorithm.

Research on Soft Demodulation of Telemetry Signal Based on the Orthogonal Complex Baseband Rotating MSD

For PCM/FM telemetry signal demodulation, compared to traditional demodulation method, multiple Symbol Detection technology (Multi - Symbol Detection, MSD) is an effective method for a lower demodulation threshold.[ For software MSD demodulation in the process of PCM/FM telemetry signal algorithm is too complex and cause a large computation takes longer problem, research based on baseband complex rotating orthogonal MSD soft PCM/FM signal demodulation method, this algorithm can greatly reduce the amount of calculation of MSD and performance with the ordinary MSD are basically identical. The simulation and test results verify the effectiveness of the proposed method.

Vibration signal demodulation and bearing fault detection: A clustering-based segmentation method

The resonance demodulation technique has been widely employed in vibration signal analysis. In order to construct a proper bandpass filter, the prior knowledge, i.e. the resonance frequency band of the mechanical system is required in the traditional demodulation method. However, as the collected vibration signal is often tainted by the background noise and interferences often with unknown frequency contents, it is difficult to identify the center frequency and the bandwidth of the filter. This paper introduces a clustering-based segmentation method to determine these parameters automatically. Envelope analysis is then applied to demodulating the vibration data. According to the simulated cases, the proposed approach is robust to Gaussian noise and interferences. Its effectiveness is further validated by applying it to detect rolling bearing faults based on experimental data.

Research of Single Component Shock Methods in Wind Turbine Fault Diagnosis

The structure of the wind turbine generator system is complex and it is difficult to identify the fault signals because of fault frequency aliasing on the vibration characteristics. The wind turbine fault diagnosis method is raised on single component shock to solve the vibration signal feature extraction during the wind turbines operating. Based on the principle of Hilbert envelope demodulation, this envelope demodulation method is presented for the single IMF component which contains shock fault characteristic frequency to solve the possible problem which fault Frequency is difficult to identify when the original signal is directly asked to envelope. This method has been applied and verified when a wind farm CSC-855W wind turbine vibration monitoring device was presented. The results show that compared with the traditional envelope demodulation method, by this method wind turbine fault characteristic can be more effectively and directly extracted and the accuracy of fault diagnosis can be improved. It is of great practical value.