Signal Distortion Research Articles

Formation of CBOC signals with a reduced level of out-of-band radiation

Formulation of the problem. The article considers the issues of choosing low-pass filters with finite and infinite pulse characteristics used to generate CBOC signals with phase manipulation with a reduced level of out-of-band radiation. Purpose. The influence of the filter frequency band on the distortion of CBOC signals in the frequency and time domain is estimated by mathematical modeling. Results. The following filter parameters, peak factor and ACPR (Adjacent Channel Power Ratio) were studied and calculated. Practical significance. The results obtained can be used by developers of local navigation systems.

Optoelectronic system for measuring and analyzing the parameters of an electrical signal in a radio receiver path

The relevance of monitoring the level of signal distortion in radio reception equipment is substantiated. A block diagram of a holographic optoelectronic system for measuring and analyzing the level of an electrical signal in a radio receiver path is presented. The measurement algorithm is described. The sensitivity of the holographic sensitive unit of the developed system was researched. Mathematical modeling made it possible to evaluate the influence of the parameters of the optical circuit of the holographic sensitive element in the developed optoelectronic system on its sensitivity was carried out.

FireSonic: Design and Implementation of an Ultrasound Sensing-Based Fire Type Identification System.

Accurate and prompt determination of fire types is essential for effective firefighting and reducing damage. However, traditional methods such as smoke detection, visual analysis, and wireless signals are not able to identify fire types. This paper introduces FireSonic, an acoustic sensing system that leverages commercial speakers and microphones to actively probe the fire using acoustic signals, effectively identifying fire types. By incorporating beamforming technology, FireSonic first enhances signal clarity and reliability, thus mitigating signal attenuation and distortion. To establish a reliable correlation between fire type and sound propagation, FireSonic quantifies the heat release rate (HRR) of flames by analyzing the relationship between fire-heated areas and sound wave propagation delays. Furthermore, the system extracts spatiotemporal features related to fire from channel measurements. The experimental results demonstrate that FireSonic attains an average fire type classification accuracy of 95.5% and a detection latency of less than 400 ms, satisfying the requirements for real-time monitoring. This system significantly enhances the formulation of targeted firefighting strategies, boosting fire response effectiveness and public safety.

Use of Neurophysiological Monitoring during MR Imaging–Guided Ablation Procedures at 1.5 T: Workflow and Safety Considerations

PurposeTo evaluate the feasibility of intraoperative neurophysiological monitoring (IONM) during magnetic resonance (MR) imaging–guided ablations and identify strategies to reduce IONM electrode radiofrequency (RF) heating during MR imaging. Materials and MethodsEx vivo experiments with a porcine tissue phantom simulating a typical high RF heating risk IONM setup during an MR imaging–guided ablation procedure on the shoulder were performed using a 1.5-T scanner. Mutual interference between MR imaging and IONM was evaluated. To assess RF heating risks, 4 pairs of IONM electrodes were inserted into the phantom at regions corresponding to the shoulders, midarm, and wrist. MR imaging of the “shoulder” was performed at 3 different specific absorption rates (SARs) with electrode wires positioned in various geometric configurations. Different combinations of electrode connections to the IONM system were investigated. Temperatures of each electrode were recorded using fiber-optic sensors. ResultsSimultaneous IONM readout and MR imaging resulted in distortion of the IONM signal, but interleaving MR imaging and IONM without moving electrodes was feasible. During MR imaging, temperature elevations greater than 60°C at the electrode insertion sites were observed. Temperature reductions were achieved by routing electrode wires along the scanner central axis, reducing the wire length within the scanner bore, or lowering the SAR of the imaging sequence. Altering the electrode connection with the IONM system did not result in consistent changes in RF heating. ConclusionsWith electrodes in the scanner bore, interleaving IONM and MR imaging is desired to avoid signal interference, and several strategies identified herein can reduce risk of electrode RF heating during MR imaging–guided ablation.

An instrumentation amplifier with series switch pseudo resistor DC-servo loop realizing 0.16-Hz high-pass corner

This paper presents an instrumentation amplifier for electrocardiogram (ECG) signal recording. A DC servo loop (DSL) based on a series-switch pseudo resistor (S2PR ) is utilized to suppress the effect of the unavoidable electrode DC offset effectively. The two-step pulse generation circuit realizes two sets of pulse signals with shallow duty cycles, and the pulse signals drive the path switches and virtual switches in the S2PR, respectively. Virtual switches reduce the channel charge injection effect, and finally, a great equivalent resistance with high linearity is realized. The continuous DSL realized based on S2PR can suppress the electrode DC offset of ±180 mV. At the same time, the active area of the DSL is significantly reduced. The proposed instrumentation amplifier is realized in a standard 0.18-μm CMOS process. Simulation results show the DSL designed with a 1.8-V supply introduces a 0.16-Hz high-pass corner. The power consumption of the S2PR-DSL is 92.7 μW. The gain of the instrumentation amplifier is 39.8 dB, and the input-referred noise at the TT corner is 1.78 μVrms over a bandwidth of 0.5 Hz to 150 Hz. The input impedance of the instrumentation amplifier is 772.2 MΩ, when the input signal frequency is 50 Hz, and the total harmonic distortion (THD) of a 10-mVpp input sinusoidal signal at 9.033 Hz is −61.6 dB.

Noise and sensitivity analysis of the dielectric modulated reconfigurable SiNW-SBT for biosensor applications

For the first time, we reported the noise and sensitivity analysis of the Dielectric Modulated Reconfigurable Silicon Nanowire-based Schottky Barrier Transistor (DMR SiNW-SBT) for biosensor applications. To validate the simulation, we present experimental calibration of the DMR SiNW-SBT biosensor. The biomolecules having different dielectric constants and charge densities are immobilized in the cavity region under the control gate. These biomolecules modulate the Schottky junction width at the source channel interface and enhance the drain current of the biosensor. The simulation results indicate that the proposed device ION and VTH sensitivity improved by 54.65 % and 85.71 %, respectively, with the state-of-the-art biosensors. Noise analysis shows that the NFmin decreased by 190.32 % and offers a low source impedance of 70Ω, which minimizes signal loss and distortion. Additionally, we investigate the linearity parameters that outperformed the FET-based biosensors. The gm3 experiences a reduction of 123.21 %, while the VIP3 sees an increase of 7.87 % and the IIP3 shows a rise of 7.21 %. Furthermore, we have conducted device optimization by varying the cavity length and thickness. We also outline potential fabrication steps for the DMR SiNW-SBT biosensor. Thus, results show that the proposed biosensor emerges as a promising candidate for advanced biosensing applications with high sensitivity, enhanced linearity, and robust noise resilience.

Deep Learning-Assisted High-Pass-Filter-Based Fixed-Threshold Decision for Free-Space Optical Communications

This paper proposes a deep learning (DL)-assisted high-pass-filter (HPF)-based fixed-threshold decision (FTD) for free-space optical (FSO) communication. HPF is applied to reduce the scintillation effect by filtering out the low-frequency components of the received signal. However, the performance is limited owing to the signal distortion from HPF and remnant scintillation effect due to insufficient filtering. Therefore, the DL model is adopted to improve the performance of HPF-based scintillation effect compensation. The multilayer perceptron (MLP) model is used to adaptively select the peak frequency component of the received signal as the optimized cutoff frequency of HPF. Furthermore, recurrent neural network (RNN) and long short-term memory (LSTM) models are cascaded after HPF to compensate for the remnant scintillation effect and recover the signal distortion without the optimization of HPF cutoff frequency. The simulation was conducted under different turbulence channels and data rates. Simulation results showed that MLP-assisted adaptive optimized cutoff frequency and cascaded LSTM and HPF methods were close to the adaptive-threshold decision with precise channel state information under various turbulence channel degrees.

Calibration complex of radio measuring equipment

Modern trends in the development of radio measuring equipment require improvement of the principles of metrological support of these devices and corresponding reference base. The new approach is based on the digitalisation of equipment, programming of measurement procedures, and the transition from single measurement standards to measurement complexes. The paper describes the complex developed at the NSC “Institute of Metrology” and designed for verification and calibration of a wide range of radio measuring equipment, where all these approaches are realised, presents methodological, software and hardware features of its construction, as well as the advantages and possibilities of this approach in metrological practice. On the example of the method of “Bessel Function Zeros”, which was somewhat forgotten due to the cumbersome nature of its implementation by analogue methods and equipment, it is shown that with the new approach this method gets a “second birth”, moreover, at a higher metrological level. It is shown that the use of direct digital synthesis oscillators can significantly improve the “electronic counting frequency meter” method, in particular, prevent the phenomenon of “frequency capture”, which limited the capabilities of the method and introduced additional measurement uncertainty. Moreover, the additional properties of the complex associated with the use of the R&S FSL spectrum analyser with the K7 analogue signal demodulator option are explained in more detail. A list of other methods realised in the complex is given, among which the “combination frequencies” method, deserves a special attention, providing the highest resolution in measuring nonlinear distortions of both quasi-harmonic and modulated signals. It is shown that the complex is a flexible apparatus, the work programme of which can be adjusted and supplemented. Information on the structure of the complex, hardware solution of a number of nodes, programming language, etc. is given.

Perfect transmission through lossy layers via ideal acoustic sources

Complementary acoustic metamaterials (CAMMs) have been proposed as a means of enhancing the transmission of acoustic imaging signals through aberrating layers. Aberrating layers with high impedance contrast compared to the surrounding material disrupt the acoustic field and hence distort acoustic images. However, conventional CAMMs are passive and thus unable to compensate for signal distortions associated with loss. This work presents an approach inspired by CAMMs that is not bound by the limits of passivity to compensate for both acoustic scattering and energy attenuation by augmenting a plane wave incident on a lossy material with monopolar and dipolar source fields to allow for perfect transmission, thus rendering the lossy medium acoustically transparent. We present a general approach to derive expressions for source magnitudes that are dimensionless with respect to frequency, system geometry, and the background medium. We validate these results with three-dimensional finite element simulations, where the appropriate monopolar and dipolar source fields are generated by prescribing velocities on finite-dimensional boundaries. We show the limitations of this approach with regard to frequency, system geometry, and lossy material characteristics via a parametric study.

Diffusion MRI Metrics Characterize Postoperative Clinical Outcomes After Surgery for Cervical Spondylotic Myelopathy.

Advanced diffusion-weighted MRI (DWI) modeling, such as diffusion tensor imaging (DTI) and diffusion basis spectrum imaging (DBSI), may help guide rehabilitation strategies after surgical decompression for cervical spondylotic myelopathy (CSM). Currently, however, postoperative DWI is difficult to interpret, owing to signal distortions from spinal instrumentation. Therefore, we examined the relationship between postoperative DTI/DBSI-extracted from the rostral C3 spinal level-and clinical outcome measures at 2-year follow-up after decompressive surgery for CSM. Fifty patients with CSM underwent complete clinical and DWI evaluation-followed by DTI/DBSI analysis-at baseline and 2-year follow-up. Clinical outcomes included the modified Japanese Orthopedic Association score and comprehensive patient-reported outcomes. DTI metrics included apparent diffusion coefficient, fractional anisotropy, axial diffusivity, and radial diffusivity. DBSI metrics evaluated white matter tracts through fractional anisotropy, fiber fraction, axial diffusivity, and radial diffusivity as well as extra-axonal pathology through restricted and nonrestricted fraction. Cross-sectional Spearman's correlations were used to compare postoperative DTI/DBSI metrics with clinical outcomes. Twenty-seven patients with CSM, including 15, 7, and 5 with mild, moderate, and severe disease, respectively, possessed complete baseline and postoperative DWI scans. At 2-year follow-up, there were 10 significant correlations among postoperative DBSI metrics and postoperative clinical outcomes compared with 3 among postoperative DTI metrics. Of the 13 significant correlations, 7 involved the neck disability index (NDI). The strongest relationships were between DBSI axial diffusivity and NDI (r = 0.60, P < .001), DBSI fiber fraction and NDI (rs = -0.58, P < .001), and DBSI restricted fraction and NDI (rs = 0.56, P < .001). The weakest correlation was between DTI apparent diffusion coefficient and NDI (r = 0.35, P = .02). Quantitative measures of spinal cord microstructure after surgery correlate with postoperative neurofunctional status, quality of life, and pain/disability at 2 years after decompressive surgery for CSM. In particular, DBSI metrics may serve as meaningful biomarkers for postoperative disease severity for patients with CSM.

Impact time domain decomposition: An adaptive decomposition method for multi-source impact signals based on envelope energy gradient characteristics

Reciprocating mechanical vibration signals are characterised by multi-source impact coupling and varied time-domain intervals. Different sub-impacts contain rich information closely related to the operational states during different strokes of the working cycle. Therefore, accurate and efficient decomposition of different sub-impacts in the time domain is an important aspect of state monitoring and fault diagnosis in reciprocating machinery. Existing time-domain decomposition methods that primarily focus on the concentration of signal energy lack robustness against noise. Furthermore, these methods suffer from issues, such as excessive reliance on prior parameters, low computational efficiency, and signal distortion. In this study, impact time domain decomposition (ITDD), a novel adaptive decomposition method is introduced. ITDD uses the envelope energy gradient (EEG) characteristics of a signal to extract sub-impacts. An impact-adaptive localisation strategy is designed based on the EEG characteristics of the noisy signals. A dimensionless evaluation metric called the impact distortion index is then constructed to optimise the smoothed EEG sequence. Finally, a residual amplitude estimation method for adaptively setting the impact identification thresholds is proposed. The effectiveness and superiority of the ITDD over existing time-domain decomposition algorithms are demonstrated using simulations and actual analyses of reciprocating machinery signals. These results indicate that the ITDD can precisely and efficiently decompose multi-source impact signals, and it significantly enhances decomposition precision and speed compared to existing methods, with a decomposition time < 1 s, thus demonstrating substantial potential for engineering applications.

50 GHz Four-Port Coupling-Reduced Probe Card Utilizing Pogo Pins Housed in Custom Metallic Socket.

A design for a pogo-pin probe card featuring a metallic socket is proposed to eliminate signal leakage and coupling loss in a multi-port environment. The proposed metallic pogo-pin socket includes a metal wall structure between adjacent pogo pins, ensuring complete isolation. This metal wall offers an advantage in removing coupling issues between pogo pins that can occur with typical dielectric pogo-pin sockets. The designed probe card is fabricated as a prototype and verified for its performance. Measurement results using a test through line show that coupled power is minimized, providing a low-loss transmission performance of -2.14 dB to an RF chip at 50 GHz, all within a compact size. Although the dielectric spacer used to secure the pogo pins allows for some leakage, it can maintain a low coupling performance of under -15 dB in the millimeter-wave band. The prototype probe card can deliver an RF signal to a 5G circuit with a low loss of -0.7 dB at 28 GHz and -1.9 dB at 39 GHz frequency. The designed probe card is capable of transmitting multiple RF signals to the RF system without signal distortion in a multi-port environment.

The influence of phase noise and nonlinear distortions of high-speed digital-to-analog converters on the parameters of digital communication systems

Problem statement. The trend in modern microwave electronics to transfer analog functions to the digital domain has led to the emergence and active use of high-speed digital-to-analog converters (DACs) in special operating modes in promising communication systems. However, optimization of power consumption and economic costs of signal generators (for example, through the use of simplified clock generators or by saving FPGA memory) leads to an increase in phase noise and nonlinear distortions in the output signal, which has a significant impact on the parameters of the communication system. Goal. Evaluation of phase noise and nonlinear distortions of signal generators based on high-speed digital-to-analog converters, as well as the study of their effect on the parameters of a digital communication system. Results. Expressions for estimating the spectral power density of phase noise of a signal generator based on a high-speed DAC are proposed. It is determined that the level of phase noise of the shaper is mainly determined by the noise of the clock generator. The jitter of the communication system was evaluated when using a surfactant generator and a PLL-based synthesizer as a clock generator. A mathematical model of the output signal of the shaper is proposed, taking into account nonlinear distortions caused by sampling, phase code truncation and amplitude quantization. A model of a communication system with multi-position quadrature amplitude modulation has been developed to evaluate parameters taking into account phase noise and nonlinear distortion of the shaper based on high-speed DACs. It is determined that the intrinsic phase noise of the signal generator leads to an increase in the probability of bit error (by about an order of magnitude compared to ideal formers). The use of surfactant generators as clock generators makes it possible to reduce the probability of bit errors of the communication system by 3-5 times compared with PLL-based synthesizers. Practical significance. It is shown that the displacement of points in the signal constellation is mainly influenced by nonlinear distortions of the output signal of high-speed DACs caused by truncation of the phase code, as well as incomplete suppression of spectral components located in the neighboring Nyquist zone. The proposed mathematical apparatus makes it possible to determine the optimal frequency ratios in the structure of the shaper, at which the lowest values of the displacement of the constellation points are achieved.

P‐76: The Influence of Bending FFC Transmission Line on High‐Speed Signal Channels

Generally, display devices interconnect FFC transmission lines with circuits to form a transmission line network system to achieve data communication between Tcon and Driver. Due to the limitations of the external shape and internal space structure of the display device, the FFC transmission cable presents a curved shape from 0 to 180 degrees during the wiring process. Under the action of spatial electromagnetic fields, the display device will involve the field‐circuit hybrid problem of electromagnetic coupling of the FFC transmission line's bent line and circuit conduction interference, which will cause severe electromagnetic interference(EMI), resulting in deterioration of the high‐speed channel signal at the receiving end and even inability to correctly restore and decode the signal, thus causing signal distortion, which in turn leads to display image distortion or pixel loss.

Modelling the Influence of the Tube Support Plate on the Eddy Current Testing of the Steam Generator: Sensitivity Study &amp; Validation

Eddy current testing (ECT) of Steam Generator (SG) tubes is part of the maintenance program of Nuclear Power Plants. Tube Support Plates (TSP) are usually only considered as extraneous signals for tube inspection. However, for long-term operation of SGs, there is a safety concern related to the build-up of deposits in the TSPs flow holes. The clogging-up of the TSPs flow holes affect the safe thermal-hydraulic operation of SGs. The deposits come from the feedwater train and are mostly iron oxides (magnetite) with a weak electrical conductivity and magnetite permeability.The ability of ECT probes to detect and characterize TSPs deposits is therefore of great interest. The most common and industrial ECT technique, the bobbin coil, averages the surrounding electromagnetic field over 360°, whereas the geometry of tri-foiled and quadri-foiled TSPs, and thus of clogging, is rather complex and non- axisymmetric, hence motivating the evaluation of the performance of conventional ECT rotating probes used for SGs tubes inspection. Although simulation is a powerful tool to support such a study, it requires dedicated models to be made available to NDT experts, and CEA develops ECT physical models in CIVA for this purpose. In addition to standard fast CIVA modules based on 3D semi-analytical or 2D numerical calculations restricted to canonical or axisymmetric parts, respectively, CEA develops a module dedicated to the simulation of SG tube inspection based on a 3D numerical simulation. This module allows tube deformation such as ovalization, bending or tube expansion. It also allows the addition of external objects such as anti-vibration bars, different geometries of tube support plates and now their clogging by deposits. This model is used to study various influent parameters and to perform benchmarks in the framework of a scientific collaboration between the CEA and the IRSN. Here, the specificity of the TSPs and their clogging justifies qualifying the simulation model before evaluating the influence of material and geometry properties of the deposit as well as the performance of the inspection techniques. We present the main features of the simulation module in CIVA, its experimental validation, and the main trends in the distortion of the simulated signal as a function of variation in the clogging description.

Помехоустойчивость когерентного приема двоичных сигналов с огибающей вида приподнятый косинус в гидроакустическом канале связи

Goals: The main purpose of this work is to develop a methodology for determining the parameters of binary signals, at which the signals become relatively invariant to frequency distortions in the marine environment. The frequency distortion of the signals is caused by the uneven frequency response of the attenuation of the marine environment. The main part of this technique is to assess the effect of frequency distortion of signals on the noise immunity of reception. In accordance with this, the error probabilities of signal receivers with various types of manipulation are determined, which are optimal in the absence of distortion. Methods: The provisions of applied hydroacoustics, the theory of random processes and the theory of transmission of discrete messages are used. The main content: The paper considered a model of a single-beam hydroacoustic communication channel, characteristic of the deep sea, when the receiver or transmitter is located in the depths of the sea. The transmission coefficient of the channel is used as a transmission coefficient with a Gaussian amplitude -frequency response and a linear phase-frequency response. The error probabilities of coherent receivers of binary signals with amplitude, frequency and phase manipulation with an envelope of the raised cosine type are determined. Coherent receivers optimal by the criterion of maximum likelihood under the action of white Gaussian noise and the absence of distortion in the marine environment are considered as receivers. A logarithmic measure of increasing the probability of error is introduced, which characterizes the deterioration of noise immunity due to frequency distortions in the channel. For some typical cases, the values of signal parameters that are relatively invariant to frequency distortions in the marine environment are determined. Results: Expressions of the error probability of coherent receivers of binary signals with amplitude, frequency and phase manipulation with an envelope of the raised cosine type are found. A logarithmic measure of the relative increase in the probability of error compared to the case of no distortion is introduced. The functional dependence of this measure on the duration of sending the signal, the carrier frequency and the initial phase of the signal, as well as on the communication range and the signal-to-noise ratio is determined. On the plane of the carrier frequency, signal duration, for each type of signal, the boundary of the region above which the signals are relatively invariant to frequency distortions in the marine environment is constructed, a comparison is made with the case of signals with a sinusoidal envelope. For communication ranges R = 1.5 km and 3 km and typical carrier frequencies, the minimum values of the duration of invariant signals are given. Expressions of the error probability of coherent receivers of binary signals with amplitude, frequency and phase manipulation with an envelope of the raised cosine type are found. A logarithmic measure of the relative increase in the probability of error compared to the case of no distortion is introduced. The functional dependence of this measure on the duration of sending the signal, the carrier frequency and the initial phase of the signal, as well as on the communication range and the signal-to-noise ratio is determined. On the plane of the carrier frequency, signal duration, for each type of signal, the boundary of the region above which the signals are relatively invariant to frequency distortions in the marine environment is constructed, a comparison is made with the case of signals with a sinusoidal envelope. For communication ranges R = 1.5 km and 3 km and typical carrier frequencies, the minimum values of the duration of invariant signals are given.

The Optimization Research on RF Chip Signal Processing Based on Deep Learning Algorithms

With the rapid development of wireless communication technology, radio frequency (RF) chips, as the core components of communication systems, directly influence the overall system performance through their signal processing capabilities. Traditional signal processing methods often struggle to achieve optimal results in the face of complex and variable communication environments. In recent years, deep learning technology, due to its powerful feature learning and pattern recognition capabilities, has shown tremendous potential in various fields. This paper addresses the signal processing issues of RF chips and proposes an optimization method based on deep learning algorithms. Firstly, the status and challenges of RF chip signal processing are analyzed, followed by the design of a deep learning model suitable for RF signal processing. Through data pre-processing and feature extraction, the generalization ability of the model is enhanced. Experimental results demonstrate that the proposed method outperforms traditional methods in signal noise suppression, interference cancellation, and signal distortion compensation, significantly improving the signal processing performance of RF chips. This research provides new ideas and methods for the application of deep learning in the field of RF chip signal processing and holds significant theoretical and practical importance for the future development of wireless communication systems.

Evaluation of Joint Technique Iterative Clipping Filtering (ICF) and Neural Network Predistortion on SDR-based MIMO-OFDM System

Multiple-input, multiple-output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) is a communications technology that powers numerous modern communication systems, including 5G and WiFi-6. This technology is utilized in current communication systems due to its high performance and extensive channel capacity. MIMO-OFDM does have disadvantages, such as large Peak-to-Average Power Ratio (PAPR) values. If the signal is processed by a nonlinear Power Amplifier (PA) device, a high PAPR value signal can result in both in-band and out-of-band signal distortion. To combat high PAPR values, PAPR reduction strategies such as Iterative Clipping Filtering (ICF) are utilized. From this study, using ICF with iteration 2 and Clipping Ratios (CR) 3 and 4 can improve the system's minimum Bit Error Rate (BER) by about 22.8% and 91.1%, respectively. Choosing the correct CR will improve the system, but using the lower CR will make it worse than a system without ICF. This occurs in systems using ICF with iterations two and CR 2 and at the same SNR conditions as systems without ICF; using ICF with iterations two and CR 2 results in higher BER values. The use of Predistortion Neural Network (PDNN) can overcome this problem. By using PDNN, there is an improvement in the system where the minimum BER value can reach 0.1 × 10-5. The percentage decrease in BER from using PDNN for ICF with iterations two and CR 2, 3, and 4 is 99.88%, 99.86%, and 98.807%, respectively. Thus, the joint techniques of ICF and PDNN can significantly enhance the performance of MIMO-OFDM systems with nonlinear PA. Importantly, the experiment was conducted on an SDR device, ensuring the real-world applicability of the results.

Detection of Signal Integrity Issues in Vibration Monitoring Using One-Class Support Vector Machine

AbstractThis paper presents an analysis of the common signal integrity issues in vibration monitoring caused by sensor saturation and signal distortion, or sensor loosening and detachment, and the development of a method of detecting the occurrence of vibration signal integrity issues using a one-class support vector machine. For this, vibration signals with distortions due to sensor saturation and/or sensor detachment are analysed to determine parameters sensitive to common integrity issues. These features are then extracted from training data of good quality vibration signals. Principal Component Analysis is used to dimensionally reduce the parameters which are then used in the training of the one-class support vector machine. The proposed method was validated on trained and untrained health conditions. Additionally, model sensitivity was also tested on trained health conditions with varying defect sizes. The method successfully detected all signal integrity issues tested proving to be an effective pre-processing step in condition monitoring systems for increased reliability and accuracy.

Research on a dedicated thin-film thermocouple testing system for transient temperature measurement

The thin-film thermocouple (TFTC) is featured on small heat capacity and rapid response speed for transient temperature measurements under narrow space and difficult installation. Consequently, we propose a novel transient temperature testing system specifically designed for TFTC. This system features signal conditioning circuits with extended bandwidth and superior transfer speeds, a cold junction compensation method that supports customizable indexing tables, and an adaptive data filtering approach that precisely balances the smoothing of steady-state data with rapid responsiveness to transient data. This approach effectively mitigating the measurement distortion of transient temperature signals and the nonlinear phenomenon in cold junction compensation for TFTC. Utilizing NiCr/NiSi TFTC, we evaluated the system’s accuracy, demonstrating a precision range of −0.5 °C–0.25 °C within 20 °C–100 °C, and a response delay under 0.1 ms. Compared to traditional thermocouple measurement systems, our system exhibits a finer time-domain resolution. Lastly, we successfully applied this system to observe the response of TFTC under the thermal load of short-pulse laser shocks, measuring a time constant of only 1.16 ms for the TFTC. This novel transient temperature testing system provides a new approach for TFTC to achieve online dynamic measurement and online calibration, and provides technical support for TFTC measurement technology towards engineering applications.