Time-domain Curves Research Articles

An entropy-based assessment of acoustic information confusion at unstable flow occurrence in a centrifugal compressor

Centrifugal compressors play a crucial role in energy and power systems, and compressor surge significantly impact their safe operation. Monitoring typical surge inception characteristics in a compressor can effectively serve as an early warning indicator, thereby enhancing safety. This paper presents the results of an acoustic experiment conducted on a centrifugal compressor setup. Four microphones were positioned in front of the compressor inlet to record the noise emitted as the compressor entered its surge region from a near-surge state. An entropy-based method is proposed to extract surge inception from acoustic signals by evaluating the informational complexity. Four types of entropy, including approximate entropy, sampling entropy, fuzzy entropy, and information entropy, were calculated from the acoustic signals. Their time-domain curves exhibit a clear increasing trend prior to surge inception. Further analysis reveals differing growth rates of the entropy curves among the four microphones, confirming the impact of microphone position on the capture of flow information and, consequently, on surge warning accuracy. Eventually, an entropy-weight method is proposed to eliminate the effects of positions and enhance surge warning capabilities by accounting for multiple acoustic signals.

Research on vertical vibration characteristics of rolling mill based on magnetorheological fluid damper absorber

The study of rolling mill vibration theory has always been a scientific frontier in the field of rolling forming, which is very important to the quality of sheet metal and the stable operation of equipment. A magnetorheological fluid damper absorber is designed to control the nonlinear vertical vibration of rolling mill. Considering the fractional order and delay factors in the control effect of magnetorheological fluid, the fractional order delay nonlinear vertical vibration equation with magnetorheological damping damper is established. The amplitude-frequency characteristic equations of the main resonance and sub-resonance of the system are solved by multi-scale method. The effects of stiffness coefficient, damping coefficient, time delay, fractional order, and exciting force on the vibration characteristics of roller system are analyzed by comparing the amplitude-frequency curve, time-domain curve and phase diagram. The transition set of the steady-state response of the system and the corresponding bifurcation topology structure are analyzed by using the singularity theory. A magnetorheological fluid damper absorber platform of rolling mill is built based on modern test technology, and the influence laws of the control threshold, control current, type of magnetorheological fluid and reduction rate are analyzed. The correctness and feasibility of the design of the magnetorheological fluid damper absorber are verified, which provided theoretical guidance and technical support for the nonlinear dynamic analysis and stability control of the rolling mill.

Effect of reinforcement layer on dynamic wetting behavior and accumulative deformation of granite residual soil subgrade

This paper contributes to investigate the impact of reinforcement layer on the dynamic wetting behavior and accumulative deformation of granite residual soil subgrade of expressways in southern China. The wetting test combined with vehicle test and vibration test were conducted in two selected test sections with a reinforcement layer (WRL) and without a reinforcement layer (NRL), respectively. The influence of vehicle speed, moving load, repeated loading, and loading number on the dynamic stress, dynamic acceleration, and dynamic displacement of both the NRL and WRL subgrades was explored under different wetting conditions. The impact of the wetting number and traffic loading on the time-domain characteristics of the dynamic response and the accumulative deformation were revealed. The results indicate that the WRL subgrade can effectively reduce the dynamic response compared to the NRL subgrade. The influence depth of the WRL subgrades is 1.3 m, while the influence depth of the NRL subgrades is 3.3 m. Dynamic stress, dynamic acceleration, and dynamic displacement increase with increasing the wetting number, moving load, and repeated loading. The peak values of the dynamic stress and dynamic acceleration time-domain curves for the NRL subgrade are 27 % and 24 % higher than those of the WRL subgrade, respectively. At 3 million loading numbers, the accumulative deformation of the NRL subgrades is 53.7 % higher than that of the WRL subgrade. The dynamic stress, dynamic acceleration, and dynamic displacement of the NRL subgrade are generally higher than those of the WRL subgrade. The predictive models are established to correlate the wetting, dynamic load, and the dynamic response for both NRL and WRL subgrades. The dynamic stress, dynamic acceleration, and dynamic displacement measured in the vibration test are generally higher than those measured in the vehicle test. The research results provide a reference for the design of durability subgrade in granite residual soil regions.

Dynamic ancillary services: From grid codes to transfer function-based converter control

Conventional grid-code specifications for dynamic ancillary services provision such as fast frequency and voltage regulation are typically defined by means of piece-wise linear step-response capability curves in the time domain. However, although the specification of such time-domain curves is straightforward, their practical implementation in a converter-based generation system is not immediate, and no customary methods have been developed yet. In this paper, we thus propose a systematic approach for the practical implementation of piece-wise linear time-domain curves to provide dynamic ancillary services by converter-based generation systems, while ensuring grid-code and device-level requirements to be reliably satisfied. Namely, we translate the piece-wise linear time-domain curves for active and reactive power provision in response to a frequency and voltage step change into a desired rational parametric transfer function in the frequency domain, which defines a dynamic response behavior to be realized by the converter. The obtained transfer function can be easily implemented e.g. via a proportional-integral (PI)-based matching control in the power loop of standard converter control architectures. We demonstrate the performance of our method in numerical grid-code compliance tests, and reveal its superiority over classical droop and virtual inertia schemes which may not satisfy the grid codes due to their structural limitations.

Fast Three-Dimensional Profilometry with Large Depth of Field.

By applying a high projection rate, the binary defocusing technique can dramatically increase 3D imaging speed. However, existing methods are sensitive to the varied defocusing degree, and have limited depth of field (DoF). To this end, a time-domain Gaussian fitting method is proposed in this paper. The concept of a time-domain Gaussian curve is firstly put forward, and the procedure of determining projector coordinates with a time-domain Gaussian curve is illustrated in detail. The neural network technique is applied to rapidly compute peak positions of time-domain Gaussian curves. Relying on the computing power of the neural network, the proposed method can reduce the computing time greatly. The binary defocusing technique can be combined with the neural network, and fast 3D profilometry with a large depth of field is achieved. Moreover, because the time-domain Gaussian curve is extracted from individual image pixel, it will not deform according to a complex surface, so the proposed method is also suitable for measuring a complex surface. It is demonstrated by the experiment results that our proposed method can extends the system DoF by five times, and both the data acquisition time and computing time can be reduced to less than 35 ms.

Bridging Time and Frequency for Low-Order, Model-Based PID Control

In the context of traditional PID model-based control, where sinusoidal or PRBS excitation on a real plant is not advisable or desirable, this paper outlines a method to obtain some relevant information by merely comparing model-based and actual time-domain reaction curves. This comparative analysis yields valuable information that can be subsequently translated into a practical estimate of uncertainty in the frequency domain. This, in turn, will enable the control designer to gain some insight into imposing realistic boundaries for closed-loop response specifications, which will ultimately be consistent with what can be expected from the actual plant response. The conditions for robust stability and robust performance are outlined and further assessed through academic simulation experiments.

A prospective study: Advances in chaotic characteristics of serum Raman spectroscopy in the field of assisted diagnosis of disease

Chaos theory is an important branch of mathematics and its theory has been widely applied in many fields such as physics and medicine. Based on existing spectroscopic techniques, this paper used chaos theory as a research method for nonlinear time series to analyze Raman spectral time domain curves in order to improve the performance of disease diagnostic models and explore a new paradigm of spectroscopic technology for intelligent assisted disease diagnosis. We quantitatively identified the chaotic characteristics of time domain Raman spectra by three methods, extracted chaotic features such as correlation dimension and Kolmogorov entropy, and used the chaotic features as input to Extreme Learning Machine (ELM), Back Propagation Neural Network (BPNN), K-Nearest Neighbor (KNN) and Support Vector Machine (SVM) to diagnose patients with lung cancer (LC), glioma, renal cell carcinoma (RCC) and esophageal cancer (EC). The Raman spectra were also analyzed by traditional spectral feature extraction & modelling method, and the results of traditional spectral feature extraction & modelling method and chaotic feature modelling method were compared. The experimental results showed that the extraction of effective chaotic features in the full spectral range could achieve comparable diagnostic results with the traditional spectral feature extraction & modelling method. To further validate the effectiveness of chaos theory in Raman spectral data, the full spectrum was divided into three consecutive subsequences of 500–1000, 1000–1500, and 1500–2000 cm−1, and the above experimental steps were repeated respectively, and the results of the traditional spectral feature extraction & modelling method and chaotic feature modelling were compared. The results showed that as the spectral range was split into consecutive subsequences, the diagnostic performance of the chaotic features in each subsequence performed better than that of conventional spectral analysis techniques. In this study, the technique bridges the gap in the application of chaotic signals to Raman spectroscopy techniques, focuses on global features in the time domain profile of Raman spectra, and demonstrates the significant value of chaos theory in artificial intelligence-assisted spectroscopic medical diagnosis.

A visual measurement algorithm for vibration displacement of rotating body using semantic segmentation network

Compared with the traditional vibration displacement measurement methods, visual vibration measurement offers several advantages such as long-distance capability, non-contact operation and easy installation. However, the phenomenon of low fitting accuracy of the bounding box often occurs when detecting rotating objects, resulting in a slight deviation in the relative offset of the center vibration point of the target between frames, which will cause a serious deviation in the regression of vibration displacement offset. In this paper, a high-speed industrial camera is employed as the image acquisition medium, and a deep learning-based semantic segmentation method is introduced to address visual vibration measurement challenges in rotating body. Specifically, the CSP module integrates different depth semantic information which is introduced into the Mobiledets backbone network in a targeted manner. This is not only strengthens the performance of the network for segmenting vibration objects, but also dramatically improves the practical performance of the algorithm. The conventional Relu activation function is substituted with Mish activation function, making the network more adept at segmenting rotating body in challenging backgrounds with varying illumination, blur, and similarity. The CSP+Mobiledets backbone network constructed in this study outperforms the U-Net network in terms of feature extraction effectiveness. Adding Dice-loss to the original loss function can more effectively solve the severe imbalance problem of samples caused by long-distance image acquisition. We take the most representative rotating body-rotor as the experimental subject. The displacement curve obtained by the existing algorithm has the best degree of fit with the signal curve collected by the eddy sensor. The results of different segmentation algorithms and detection algorithms on time domain curve plot, frequency domain plot and axis orbit plot are collectively compared. Furthermore, the results also provide valuable guidance for visual measurement of the vibration displacement of the rotating body in specific industrial scenarios.

Similarity and vibration signal prediction of planetary gear transmission system based on hierarchy analysis

Large high-power gear transmission systems, especially complex gear systems, have problems such as high processing costs, long manufacturing cycles, and difficult testing, resulting in the inability to implement performance evaluation and structural optimization of gear systems. To solve this problem, the similarity and vibration signal prediction method of planetary gear transmission system (PGTS) is studied based on hierarchical analysis. The similarity relationship analysis is completed based on the similarity theory of complex systems. According to the hierarchical idea, the PGTS can be divided into subsystems at different levels from top to bottom, which can be divided into the component layer at least. The concepts of functional similarity and structural similarity are proposed, and the similarity conditions of each subsystem are formulated. Based on the equation analysis method, the dynamic similarity relationship of the PGTS is deduced. Furthermore, the parameter design and working condition design of the scale model is completed. The scale model can predict the time and frequency domain curves of each vibration signal of the prototype. Under different working conditions, the scale model can accurately predict the vibration signal and floating amount of the prototype. The similarity analysis method applicable to PGTSs has been verified.

φ-OTDR signal compression scheme based on the compressed sensing theory.

In this paper, based on the compressed sensing theory and the orthogonal matching pursuit algorithm, we have designed a data compression scheme, taking the Space-Temporal graph, time domain curve, and its time-frequency spectrum of phase-sensitive optical time-domain reflectometer as the target signals. The compression rates of the three signals were 40%, 35%, and 20%, while the average reconstruction times were 0.74 s, 0.49 s, and 0.32 s. The reconstructed samples effectively retained the characteristic blocks, response pulses, and energy distribution that symbolize the presence of vibrations. The average correlation coefficients of the three kinds of reconstructed signals with the original samples were 0.88, 0.85, and 0.86, respectively, and then a series of quantitative metrics were designed to evaluate the reconstructing efficiency. We have utilized the neural network trained by the original data to identify the reconstructed samples with an accuracy of over 70%, indicating that the reconstructed samples accurately present the vibration characteristics.

Numerical Analysis of Pressure Load on Hypersonic Wing

The flight vibration environment of hypersonic vehicles has always been a hot topic in the field of aerospace at home and abroad. In this paper, the simple wing model and the outer flow field grid of the wing are established by using fluent software. A series of environmental parameter conditions are set in the hypersonic flow field, and the steady and unsteady flow fields are analyzed. The distribution characteristics of the pressure load on the wing surface in the hypersonic flow field are obtained. The results show that the pressure load measured at the head position of the wing model is larger, and the pressure load at the fuselage position is smaller and changes more gently. With the increase of Mach number, the pressure load on the wing model will also increase. Then MatLab software is used to convert the time domain curve of wing surface pressure load into a power spectral density curve, which provides load input for subsequent random vibration response simulation on finite element software.

Influence of clearance and structural coupling parameters on shimmy stability of landing gear

AbstractThere are many factors causing the shimmy of the aircraft landing gear and structural clearance of landing gear is a typical factor. Some aircraft in service or operation did not shimmy before, but suddenly appeared after a period of use. To solve the problem of clearance shimmy during the service of a certain aircraft, we established a dynamic model of rotating gear with clearance based on the flexible multi-body dynamics model of landing gear and L-N contact theory. We defined different types of clearance and established a mechanical model of aircraft pendulum vibration considering the clearance of landing gear structure for dynamic simulation, and studied the effects of different clearance types, clearance size of motion pair and different clearance positions on the stability of pendulum. The results show that the axial clearance has little effect on the shimmy performance of landing gear; the radial clearance has a certain effect on the shimmy performance of medium speed running, which slightly improves the shimmy damping required by medium speed running; the rotational clearance affects the shimmy performance of the nose landing gear by affecting the force transmission of structural components. The required shimmy damping coefficient increases at low speed and decreases at high speed. The main reason for the return clearance is that during the return, the shimmy damper does not work, which leads to the decrease of the shimmy damping performance and the increase of the required shimmy damping coefficient in the whole speed range. Meanwhile, the structural clearance will increase the shimmy frequency of the nose landing gear. By analysing the yaw angle of the nose landing gear and the time domain curve of the yaw angle of the yaw damper, we can determine which structure of the landing gear and which type of clearance is the cause of the yaw. Finally, the coupling effect caused by the main structural parameters of the landing gear in “gap shimmy” was analysed according to different mechanical stability distances and strut stiffness of the nose landing gear, providing reference for aircraft anti-shimmy design, nose landing gear fault diagnosis and nose landing gear maintenance support.

Mechanical characteristics of a tunnel boring machine cutterhead during rock breaking: Physical model tests and transient dynamic analysis

During tunnel excavation using a tunnel boring machine (TBM), the interaction between the cutter and the rock causes the cutterhead to generate abrupt vibrations, which could lead to engineering problems, such as bearing seal failure and even cutterhead cracking. In this study, large-scale physical model tests with various cutter spacings were performed to study the vibration and load characteristics of the cutterhead during the rock-breaking process. Through a TBM modal comprehensive test bench, the real-time acceleration of the cutterhead was obtained using a monitoring system. The test results showed that the complete time-domain curves were stepped and periodic. When the cutterhead was stuck or rock peeled off during the excavation, the monitoring curves showed abrupt vibrations, which were mainly concentrated at 0–3 Hz and were typical low-frequency vibrations. Taking measured data as the driving parameter, the real-time mechanical characteristics of the cutterhead were determined through transient dynamic analysis. Numerical simulation results showed that the vibration trend during excavation was the superposition of random vibrations generated by rock breaking and tunneling without rock cutting. During the tunneling process, the wear of the edge cutters should be highlighted in actual construction. The related methods and results can provide an essential reference for the selection of cutterheads.

φ-OTDR pattern recognition based on CNN-LSTM

We proposed a pattern recognition strategy based on the long short-term memory network (LSTM) and convolutional neural network (CNN), with phase-sensitive optical time domain reflectometry (φ-OTDR) realizing vibration sensing and data acquisition in application scenarios. Given the time domain curve as well as its discrete wavelet transform (DWT) and short-time Fourier transform (STFT) as the input, the trained LSTM-CNN can effectively identify six kinds of target signals, which can assist users in taking appropriate measures. The significant improvement of LSTM on classification performance has been proven in comparison to the conventional artificial neural network (ANN) and CNN, providing an application example for the integration of LSTM and optical fiber sensing.

Atmospheric icing measurement and online ice type recognition for aircraft utilizing optical fiber sensor and machine learning algorithms

For the detection of atmospheric icing process, an ice type recognition and thickness measurement method based on optical fiber sensor is proposed and evaluated. Finite element models based on different structures are built for the four corresponding typical ice types in the atmospheric icing environment. Finite element analysis results show the characteristics of sensor response for different ice types and the potential of real-time ice type recognition using optical fiber sensor. In the laboratory test, under the atmospheric icing conditions, 1655 sets of valid data including glazed ice, mixed ice, rime ice and frost are collected. Cascade models based on machine learning algorithms are built and evaluated using a round-robin leave-one-out method. The model realizes instant ice type recognition and thickness measurement without relying on time-domain curve information. The evaluation results show that the proposed method achieves 92.8 % ice type recognition accuracy and 0.27 mm RMSE for ice thickness measurement.

Micro-expression spotting based on optical flow features

• The nose tip location-based image alignment method improves the performance of Micro-expression spotting. • The optical flow method can accurately capture micro-expression movements. • When a micro-expression occurs, a peak appears on the time-domain change curve. • Get complete micro-expression intervals after fusing local movements. Expression is the changes of facial organs due to facial muscle movement and an important way of human emotional interaction. Neurophysiological studies show that micro-expressions (MEs) are not controlled by subjective consciousness and reflect people's real emotions. That is why MEs have significant value in public security applications. This paper proposes an automatic ME spotting method of high accuracy and interpretability. Firstly, we design the nose tip location-based image alignment method to remove global displacement caused by head shaking. Secondly, according to the action unit definition in the face coding system (FACS), we select fourteen regions of interest (ROI) to capture subtle facial movements. The dense optical flow is introduced to estimate local movements and time-domain variations of the ROIs. Thirdly, we design a peak detection method on the time-domain variation curves to locate the movement intervals precisely. Lastly, we propose an overlapping index to measure the consistency of changes in different organs. Evaluation on the CAS(ME) 2 and SAMM Long Video database shows that our ME spotting method may achieve better accuracy with a relatively lower computation cost and can be applied to similar facial image processing applications.

Waveform Quality Evaluation Method of Variable-Frequency Current Based on Curve Fitting

Since total harmonic distortion (THD) is mainly used as the evaluation index for the waveform quality of periodic signals, it cannot be applied to variable-frequency signals. However, there is scarce research on the evaluation methods and indicators of variable-frequency signals in the literature. In this paper, an evaluation method of the waveform distortion (WD) of variable-frequency signals based on curve fitting is proposed. First, the variable-frequency current expression of the coefficients to be optimized is obtained through theoretical derivation. Second, the coefficients are optimized by curve fitting in the time domain through the nonlinear least-squares method. Then, the waveform distortion of the variable-frequency current (IWDVF) is calculated. In order to validate the proposed evaluation method, the simulation model of a synchronous motor driven by a cascaded H-bridge five-level inverter is built. The simulation results show that, for the same constant-frequency current, the current THD (ITHD) obtained by the FFT method is the same as the current WD (IWD) obtained by the curve fitting method, which verifies the equivalence of the two methods. The influence of different sampling frequencies on the IWD and ITHD is compared. The higher the sampling frequency, the more sampling points, and the more accurate the results. For the linear variable-frequency current, the IWDVF obtained by the curve fitting method is close to the average value of the ITHD obtained by FFT, which indicates that the time-domain curve fitting method is reasonable to solve the IWDVF. For nonlinear variable-frequency current waveforms, the curve fitting method can also reasonably calculate the IWDVF. The curve fitting method can solve the evaluation problem of the variable-frequency current, and provide an evaluation means for the optimal design of a modulation strategy aiming at the optimal waveform quality of the variable- frequency current.

Dynamic model of fine-pitch gear pair considering multi-clearance coupling

In this paper, the parallel shaft fine-pitch involute plastic-powder metallurgy engagement spur gear pair produced according to the recommended backlash value of DIN standard is taken as research object. The coupling between the backlash and the bearing radial clearance is considered. And the expression of the dynamic backlash is derived. A three-degree-of-freedom two-state dynamic mathematical model of the parallel shaft gear transmission system is established. The time-domain curves of gear displacement, velocity, engagement force and dynamic backlash are obtained. The results of mathematical model show that a larger backlash range than DIN standard recommended is more conducive to smooth transmission.

The relationship between cardiac damage biomarkers and heart rate variability following 60min of running.

Endurance exercise may cause transient alterations in cardiac tissue. The number of studies evaluating the relationship between changes in heart rate variability (HRV) and cardiac biomarkers following an endurance event is limited. We hypothesized that there would be a time-dependent correlation between biomarkers of cardiac damage and the reduction in parasympathetic indices of HRV within 24h after 60min of running in middle-aged recreational runners. The trained, middle-aged runners who participated in this study ran 60min at a half-marathon pace on a treadmill. Blood samples (before and 0, 4, and 24h after the running test) and HRV data (before and 0, 1, 4, and 24h after the running test) were obtained. After running, cardiac biomarkers (total creatine kinase, cardiac isoform of creatine kinase, creatine kinase-index [CK-Index], cardiac troponin [cTnI]) increased significantly, and HRV measures related to parasympathetic nervous system activity decreased significantly; these measures returned to baseline levels within 24h. Finally, there were significant correlations (all p < 0.05) between the change (4h post-running vs. pre-running) in the CK-Index and the changes (post- vs pre-running) in time-domain and nonlinear measures of HRV (r -0.61 to -0.67). In addition, significant correlations (all p < 0.05) were found between the area under the cTnI curve and change (1-h post- and pre-running) in time-domain and nonlinear measures of HRV (r -0.48 to -0.51). The correlation between HRV and cardiac biomarkers indicates that HRV analysis may be an alternative approach to determine the magnitude of cardiac stress after endurance exercises.

Research on the Relationship between Stall Propagation and Flange Leakage of Mixed-Flow Pumps

In order to explore the internal relationship between stall core propagation and flange leakage flow in the rotating stall of a mixed-flow pump, based on the k-ε turbulence model, a SIMPLEC algorithm and hexahedral structured grid are used to simulate the internal flow field of the mixed-flow pump. By setting the flange clearance as 0.2 mm, 0.5 mm and 0.8 mm, the propagation characteristics of the rotating stall and the unsteady characteristics of flange leakage flow of the mixed-flow pump under the condition of near stall are studied, and the influence of the flange clearance on the pressure fluctuation characteristics of the mixed-flow pump under the condition of near stall is analyzed. The results show that the stall core is located at the outlet of the impeller and propagates from the leading edge of the adjacent blade along the opposite direction of blade rotation to the next flow channel. The pressure gradient in the stall channel and the energy loss are large. When the flange clearance is 0.5 mm and 0.8 mm, the stall core changes from one to two, and the propagation mechanism of the stall core tends to be complex in the two adjacent flow channels. When the flange clearance is 0.8 mm, the propagation period decreases. The variation law of leakage flow is consistent with the propagation law of stall core. When the flow passage changes from stall state to non-stall state, the leakage flow also changes from one state to another, so the leakage flow can be used as a form of apparent stall. Under the condition of near stall, the pressure fluctuation curve of the adjacent monitoring points has a large phase difference consistent with the propagation period of the stall core, and has a strong pressure drop. When the flange clearance is 0.5 mm and 0.8 mm, the time domain curve of pressure fluctuation has two wave troughs in one cycle. In the near stall condition, the main frequency of the pressure fluctuation at the monitoring point is the stall frequency, and the amplitude of the main frequency at the middle of the outlet is the largest. The characteristics of flange leakage flow and pressure fluctuation can better reflect the flow situation in the pump when rotating stall occurs. The research results can provide a basis for judging whether stall occurs in the flow passage of the pump.