Transient Component Research Articles

Can the two-parameter recursive digital filter baseflow separation method really be calibrated by the conductivity mass balance method?

Abstract. The two-parameter recursive digital filter method (Eckhardt) and the conductivity mass balance (CMB) method are two widely used baseflow separation methods favored by hydrologists. Some divergences in the application of these two methods have emerged in recent years. Some scholars believe that deviation of baseflow separation results of the two methods is due to uncertainty of the parameters of the Eckhardt method and that the Eckhardt method should be corrected by reference to the CMB method. However, other scholars attribute the deviation to the fact that they contain different transient water components. This study aimed to resolve this disagreement by analyzing the effectiveness of the CMB method for correcting the Eckhardt method through application of the methods to 26 basins in the United States by comparison of the biases between the generated daily baseflow series. The results showed that the approach of calibrating the Eckhardt method against the CMB method provides a “false” calibration of total baseflow by offsetting the inherent biases in the baseflow sequences generated by the two methods. The baseflow sequence generated by the Eckhardt method usually includes slow interflow and bank storage return flow, whereas that of the CMB method usually includes high-conductivity water flushed from swamps and depressions by rainfall, but not low-conductivity interflow and bank storage return flow. This difference results in obvious peak misalignment and periodic deviation between the baseflow sequences obtained by the two methods, thereby preventing calibration. However, multi-component separation of streamflow can be achieved through comparison. Future research should recognize the deviations between the separation results obtained by the different methods, identify the reasons for these differences, and explore the hydrological information contained therein.

Rotation Speed Control of the Rotary Valve in MWD Tools Based on Speed Feedforward Compensation

The rotary valve speed control, seriously affected by the nonlinear characteristic of rotary valve load torque, affects the generation of drilling fluid pressure phase shift keying (PSK) signal and its quality. The calculation model feedforward of the load torque acts on the speed control system and enables the motor voltage to change according to the law of calculation model, and the linearization correction of the speed system is performed. Additionally, the flow measurement is introduced into the calculation model of the load torque to track the load torque change with the flow, suppressing the influence of large changes in flow rate on open-loop control of rotary valve speed. The closed-loop proportional-integral-derivative (PID) control is formed by negative feedback of speed, and the PID parameter value rule is established based on the rapid decay control of transient component in the rotary valve speed step response, which speeds up the tracking of the rotary valve speed following the control voltage pulse and reduces the distortion of the drilling fluid pressure PSK signal, increasing the frequency of the drilling fluid pressure carrier and improving the transmission rate of downhole information. Simulink simulation indicates that the closed-loop PID control of rotary valve speed can track the change of control voltage pulse quickly and strongly suppress the interference influences from flow measurement error and load torque calculation model deviation.

Rolling bearing fault diagnosis using transient-extracting transform and linear discriminant analysis

It is difficult to find the rolling bearing fault and its detailed information in the early stage due to its complex structure, heavy load, harsh working environment, and long-term high-speed working condition. This paper proposes a fault diagnosis method based on Transient-extracting Transform (TET) and Linear Discriminant Analysis (LDA). Firstly, the transient component of vibration signal in the time-frequency domain is extracted using the TET method. And then, 10 statistical features of the original signal and its transient component are obtained respectively by computing the mean, standard deviation, skewness, etc. Next, LDA is used to extract their fisher features, which can reduce the dimensionality of features and improve the fault recognition accuracy and efficiency. Finally, the diagnosis is accomplished by the Nearest Neighbor Classifier (NNC). The experimental results demonstrate that the proposed method can effectively identify rolling bearing faults with different positions, damage levels and damage types.

Dynamic Degradation Quantification of Wind Turbine High Speed Shaft Bearing Based on Oscillation Based Sparsity Indices

Wind turbine (WT) high speed shaft (HSS) bearing fault is important due to its significant number of failures. However, due to its non-stationary operation under varying speed condition, it is a challenging issue to quantify the degradation of WT-HSS bearing by conventional bearing indices. Aiming at the aforementioned issue, in this paper, tunable Q factor wavelet transform (TQWT) preprocessed sparsity indices are proposed to achieve the dynamic degradation quantification of WT-HSS bearing. Firstly, based on the ability of TQWT in dynamic extraction of fault component of a bearing signal under varying speed condition, low oscillatory transient signal component is separated from a noisy commercial WT-HSS bearing signal by continuously adjustable tunable Q factor wavelet transform (TQWT). Then, considering the suitability of sparsity indices in quantifying extracted fault component based on its energy concentration, four representative sparsity indices namely kurtosis, gini index, negative entropy and reciprocal smoothness index are used to quantify the separated low oscillatory signal component as a measure of WT-HSS bearing health. The proposed indices show a better performance than original sparsity indices and an improved version of sparsity indices based on adaptive weighted signal preprocessing in dynamic degradation quantification of a commercial WT-HSS bearing.

Transient waveform matching based on ascending multi-wavelets for diagnostics and prognostics of bearing deterioration

Run-to-failure experiment is efficient and effective to investigate bearing deterioration process. Periodic transient waveform carries rich information of health conditions of bearings but the transient waveform matching is a challenging problem for evaluating bearing fatigue life because the shapes and parameters of the waveform vary with the evolution of the bearing degradation. A wavelet function such as a Morlet wavelet is able to extract essential features from the transient waveform but limited to a single transient component. The multi-wavelet may provide a solution to fit a variety of primary components in the transient waveform, so as to track the degradation trend of the bearing; however, very limited work has been done to address this issue. To bridge the research gap in the transient waveform matching, a novel ascension multi-wavelet method is proposed in this paper for diagnosing the undergoing degradation state and predicting the remaining useful life (RUL) of the bearings. Firstly, the transient waveform was matched using the combination of multiple wavelets. Then, the entropy of the multiple-wavelet signal was calculated to quantify the periodic transients to generate a monotone trend of the bearing degradation. The degradation state of the bearing was identified using the entropy. Lastly, the ensemble learning method was employed to establish an RUL predictor. Both simulation and experiments were carried out to evaluate the proposed method. The analysis results demonstrate satisfactory diagnostics and prognostics performance of the proposed method. The RUL prediction accuracy of the multi-wavelet matching is better than that of the single-wavelet matching.

Analysis of Transient Interactions between a PWR Nuclear Power Plant and a Faulted Electricity Grid

This paper presents the transient stability analysis of a pressurised water-type nuclear power plant following faults and disturbances affecting the electricity grid to which it is connected. The modelled nuclear plant consists of various integrated subsystems, such as core neutronics and thermal-hydraulics, piping and plenum, pressuriser, steam generator, turbine, governor, and dynamics shaft, in addition to the turbine-speed controller. The nonlinear nuclear power plant model is linearised at the operating point to acquire a linear model for controller design. The turbine-speed control loop effectively enacts a closed-loop implementation of the nuclear power plant connected to the electric grid. The various transient stability enhancement components such as the power system stabiliser, static var compensator, and static synchronous compensator are employed to test performance during severe contingencies. The interaction between the nuclear power plant, electric grid, and protection system is studied under various scenarios such as single-phase fault, three-phase fault, and permanent load loss. The performance of the nonlinear plant is further observed during load-following operation. The dynamic behaviour of the overall system is analysed using simulations in the MATLAB/Simulink/Simscape environment.

Transient impulses enhancement based on adaptive multi-scale improved differential filter and its application in rotating machines fault diagnosis

Transient impulses caused by local defects are critical for the fault detection of rotating machines. However, they are extremely weak and overwhelmed in the strong noise and harmonic components, making the transient features are very difficult to be extracted. This paper proposes an adaptive multi-scale improved differential filter (AMIDIF) to enhance the identification of transient impulses for rotating machine fault diagnosis. In this scheme, firstly, the AMIDIF is performed to decompose the measured signal of rotating machine into a series of multi-scale improved differential filter (MIDIF) filtered signals. Subsequently, in view of the MIDIF filtered signals exhibit varying extents of validity in revealing fault features, a weighted reconstruction method using correlation analysis is proposed in which the weighted coefficients are counted and distributed to the corresponding MIDIF filtered signals to highlight the effective MIDIF filtered signals and weaken the invalid ones. Finally, the transient impulse components of rotating machinery are obtained by multiplying the weighted coefficients and the MIDIF filtered signals under different scales. Furthermore, the fault types of rotating machines are inferred from the fault defect frequencies in the envelope spectrum of the transient impulses. Simulation analysis and experimental studies are implemented to verify the performance of the AMIDIF compared with the state-of-the-art methods including spectral kurtosis (SK), multi-scale average combination different morphological filter (ACDIF) and multi-scale morphology gradient product operation (MGPO). The results prove that the AMIDIF has excellent performance in extracting transient features for rotating machines fault diagnosis.

Children with developmental language disorder: a frequency following response in the noise study

IntroductionChildren with developmental language disorder have been reported to have poor temporal auditory processing. This study aimed to examine the frequency following response. ObjectiveThis work aimed to investigate speech processing in quiet and in noise. MethodsTwo groups of children were included in this work: the control group (15 children with normal language development) and the study group (25 children diagnosed with developmental language disorder). All children were submitted to intelligence scale, language assessment, full audiological evaluation, and frequency following response in quiet and noise (+5QNR and +10QNR). ResultsResults showed no statically significant difference between both groups as regards IQ or PTA. In the study group, the advanced analysis of frequency following response showed reduced F0 and F2 amplitudes. Results also showed that noise has an impact on both the transient and sustained components of the frequency following response in the same group. ConclusionChildren with developmental language disorder have difficulty in speech processing especially in the presence of background noise. Frequency following response is an efficient procedure that can be used to address speech processing problems in children with developmental language disorder.

Is There a Speed Limit for the Thermal Steady‐State Assumption in Continental Rifts?

AbstractThe lithosphere is often assumed to reside in a thermal steady‐state when quantitatively describing the temperature distribution in continental interiors and sedimentary basins, but also at active plate boundaries. Here, we investigate the applicability limit of this assumption at slowly deforming continental rifts. To this aim, we assess the tectonic thermal imprint in numerical experiments that cover a range of realistic rift configurations. For each model scenario, the deviation from thermal equilibrium is evaluated. This is done by comparing the transient temperature field of every model to a corresponding steady‐state model with an identical structural configuration. We find that the validity of the thermal steady‐state assumption strongly depends on rift type, divergence velocity, sampling location, and depth within the rift. Maximum differences between transient and steady‐state models occur in narrow rifts, at the rift sides, and if the extension rate exceeds 0.5–2 mm/a. Wide rifts, however, reside close to thermal steady‐state even for high extension velocities. The transient imprint of rifting appears to be overall negligible for shallow isotherms with a temperature less than 100°C. Contrarily, a steady‐state treatment of deep crustal isotherms leads to an underestimation of crustal temperatures, especially for narrow rift settings. Thus, not only relatively fast rifts like the Gulf of Corinth, Red Sea, and Main Ethiopian Rift, but even slow rifts like the Kenya Rift, Rhine Graben, and Rio Grande Rift must be expected to feature a pronounced transient component in the temperature field and to therefore violate the thermal steady‐state assumption for deeper crustal isotherms.

Adapted Fringe Projection Sequences for Changing Illumination Conditions on the Example of Measuring a Wrought-Hot Object Influenced by Forced Cooling

Optical 3D geometry reconstruction, or more specific, fringe projection profilometry, is a state-of-the-art technique for the measurement of the shape of objects in confined spaces or under rough environmental conditions, e.g., while inspecting a wrought-hot specimen after a forging operation. While the contact-less method enables the measurement of such an object, the results are influenced by the light deflection effect occurring due to the inhomogeneous refractive index field induced by the hot air around the measurand. However, the developed active compensation methods to fight this issue exhibits a major drawback, namely an additional cooling of the object and a subsequent transient illumination component. In this paper, we investigate the cooling and its effect on temporal phase reconstruction algorithms and take a theoretical approach to its compensation. The simulated compensation measures are transferred to a fringe projection profilometry setup and are evaluated using established and newly developed methods. The results show a significant improvement when measuring specimens under a transient illumination and are easily transferable to any kind of multi-frequency phase-shift measurement.Dataset License: CC-BY

Fault Stage Feature Extraction Method Based on Antinoise Gradient Operator Morphological Filters

The cyclical impact signal aroused by mechanical fault contains feature information, such as fault type and fault stage. However, a transient impact component is usually modulated on the fundamental frequency and mixed with a large amount of noise. Thus, it is difficult to be extracted effectively. A feature extraction method of faults stage is presented based on morphological filter theory. An antinoise morphological gradient operator is applied to signal filtering. This operator can weaken the noise and clearly highlight the impact characteristics of different fault stages. The kurtosis of the spectrum band, including the passing frequencies of mechanical components, is used to differentiate fault stages. The applications on simulation signals and bearing test data indicate that this method can realize accurate extraction of fault characteristic frequency submerged in noise and effective distinction of different fault stages.

Determination of the shedding frequency of cavitation cloud in a submerged cavitation jet based on high-speed photography images

To accurately determine the shedding frequency of the cavitation cloud in a submerged cavitation jet, the spectral analysis and the proper orthogonal decomposition (POD) for high-speed photography images are performed. The spectrums of 6 different kinds of image signals (the area-averaged gray level, the line-averaged gray level, the point gray level, the cavitation length, width, and area) are calculated and compared. The line-averaged gray level is found to be optimal in determining the shedding frequency but an accurate frequency can only be obtained in the stable-frequency zone where the cavitation cloud sheds. In repeated experiments, the plateau-shape distribution of the main frequency is established with a deviation of 10.8%. A revised Reynolds number Re′ is defined and the shedding frequency can be correlated to Re′ by a power law when the cavitation number is less than 0.02. This relationship is validated by the experimental data in literature. The first mode of the POD characterizes the ensemble-average of the cavitation cloud while the second mode is the major part of the cavitation cloud transient components. The modes 2–5 are organized in pairs, which confirms the periodic feature of the cavitation cloud in the submerged cavitation jet. Near the nozzle exit, the modes 2–5 are symmetrically distributed in the jet shear layer. The shedding frequency of the cloud cavitation can also be precisely determined by performing the spectral analysis of the weighting coefficients of the mode 2. This paper shows that the two parameters, namely, the line-averaged gray level and the weighting coefficients of the mode 2, can be confidently used to calculate the shedding frequency of the cavitation cloud in a submerged cavitation jet.

Transmission Line Modeling and Algorithm Analysis Considering Parameter Asymmetry and Transient High-frequency Components

When the power system is disturbed or the operation mode is changed, the electromagnetic transient process will occur, which will lead to the high frequency transient component and affect the protection and control of the power system. Therefore, attention should be paid to the analysis of high-frequency transient components when modeling and analyzing the system model. In view of the fact that the symmetrical-component theory is not suitable for asymmetric transmission lines and the phasor method is not suitable for transient analysis and calculation, this paper uses the phase coordinate approach and Laplace transform to derive the node voltage equation of three-phase π type transmission lines in frequency domain, which can be used to calculate the transient response of transmission lines caused by the change of operation mode or disturbance. And vectorized NILT is used to calculate the time domain solution, which greatly improves the calculation speed. The calculated results are basically consistent with those of ATP-EMTP, and can fully reflect the transient characteristics. This method lays a foundation for analyzing the influence of high frequency transient components on power system and fault analysis considering transient process.

A generalized true random-effects model with spatially autocorrelated persistent and transient inefficiency

This study extends the generalized true random-effects model to account for spatial dependence in persistent and transient inefficiency. For this purpose, a model with spatially autocorrelated persistent and transient inefficiency components is specified. Additionally, spatial dependence is also modeled in the noise component to account for uncontrolled spatial correlations. The proposed model is applied to a panel dataset of Wisconsin dairy farms observed between 2009 and 2017 and estimated using Bayesian techniques. Apart from the traditional output-input quantities, the utilized dataset also contains information on the exact location of farms based on their latitude and longitude coordinates as well as on environmental factors. The empirical findings suggest low levels of both persistent and transient inefficiency for farms. Additionally, all components exhibit spatial dependence with its magnitude being more than double for persistent inefficiency.

Mathematical Analysis of Maxwell Fluid Flow through a Porous Plate Channel Induced by a Constantly Accelerating or Oscillating Wall

Exact expressions for dimensionless velocity and shear stress fields corresponding to two unsteady motions of incompressible upper-convected Maxwell (UCM) fluids through a plate channel are analytically established. The porous effects are taken into consideration. The fluid motion is generated by one of the plates which is moving in its plane and the obtained solutions satisfy all imposed initial and boundary conditions. The starting solutions corresponding to the oscillatory motion are presented as sum of their steady-state and transient components. They can be useful for those who want to eliminate the transients from their experiments. For a check of the obtained results, their steady-state components are presented in different forms whose equivalence is graphically illustrated. Analytical solutions for the incompressible Newtonian fluids performing the same motions are recovered as limiting cases of the presented results. The influence of physical parameters on the fluid motion is graphically shown and discussed. It is found that the Maxwell fluids flow slower as compared to Newtonian fluids. The required time to reach the steady-state is also presented. It is found that the presence of porous medium delays the appearance of the steady-state.

Voltage Transient Disturbance Detection Based on the RMS Values of Segmented Differential Waveforms

Voltage transient disturbance is one of the key voltage quality disturbances, which can be classified into oscillatory transient and impulsive transient. Currently, there is no simple, accurate and general method to detect, extract, and characterize the voltage transient disturbance. This paper proposes a time-domain voltage transient disturbance detection method based on the RMS (root mean square) values of segmented differential waveforms. Firstly, the abnormal voltage waveforms are detected and extracted, which will be used for further analysis. Secondly, the extracted abnormal voltage waveform data are pre-processed, and then each power frequency cycle are processed in segment. Thirdly, by considering the influence of the system frequency variation, the differential waveform can be obtained by calculating the difference between two consecutive cycles. Finally, the voltage transient disturbance is detected by calculating and comparing the segmented RMS values of differential waveforms and steady-state waveforms. The transient component is extracted as well. Four indicators, i.e., dominant frequency, polarity, magnitude and duration, are used to characterize the voltage transient disturbance. In order to verify the accuracy and feasibility of the proposed method, both simulated data from an improved IEEE-13 node test system and actual voltage transient signal from a laboratory experiment are used.

Long-horizon predictability and information decay in equity markets

We use machine learning to predict stock returns at forward horizons from 1 month ahead to 120 months ahead. Stock return predictability declines with the forecast horizon; it follows an asymptotic exponential decay process consisting of a permanent component (c. 20 bp/month) and a transient component (c. 240 bp/month) which decays at around 6% per month. Persistent but declining predictability at increasing horizons can be explained by persistent but declining benchmark risk factor exposures at each horizon. Limits to arbitrage linked to risk (but not implementation costs) also explains declining profitability.

Bearing Defect Recognition Based on Optimal Impulse Response Wavelet Denoising Technique

A rolling bearing defect detection and recognition technique based on optimal impulse response continuous wavelet transform (IRCWT) de-noising technique is proposed. In the proposed technique, the IRCWT is used as a tool for local time and frequency characteristics analysis, and the spectral kurtosis (SK) is used as the impulse index to extract transient pulse components from the processed rolling defect vibration data. Firstly, the IRCWT is used to process the sampling vibration data. And then SK is calculated to choose the best signal band-pass band from the time frequency analysis of vibration data, in order to restrain the interference noise and highlight the transient shock feature. Finally, the envelope spectrum is computed and the rolling bearing defect feature is extracted. The rolling element bearing defect recognition results show that the proposed approach can effectively detect the transient characteristics and distinguish the rolling element bearing localized defect.

Faulty Line Identification Method Based on Bayesian Optimization for Distribution Network

Selective ground-fault protection is greatly valued for the safe and reliable operation of power systems. With the wide adoption of fault indicator in distribution network, the amount of available fault data increases dramatically. The in-depth investigation of fault recording data helps improve the accuracy of faulty line identification. To perform fault data analysis with higher efficiency, a single-phase-to-ground fault identification model based on the k-Nearest Neighbor (kNN) classification algorithm is proposed in the paper. In this model, the eigenvectors consist of wavelet energy ratio, wavelet coefficients variance and wavelet power obtained by the decomposition of transient components. Furthermore, through the theoretical analysis and experimental comparison of three parameter adjustment algorithms, Bayesian Optimization algorithm is selected to find the optimal parameters of fault identification model, and realize the adaptive adjustment of model parameters. Finally, the validity and feasibility of the model are verified by the experimental data, and the accuracy and efficiency of fault identification are improved by using Bayesian Optimization algorithm.

Microstructure and mechanical behaviour of transient liquid phase spark plasma sintered B4C–SiC–TiB2 composites from a B4C–TiSi2 system

Almost fully-dense B4C–SiC–TiB2 composites with a high combination of strength and toughness were prepared through in situ reactive spark plasma sintering using B4C and TiSi2 as raw materials. The densification, microstructure, mechanical properties, reaction, and toughening mechanisms were explored. TiSi2 was confirmed as a reactive sintering additive to promote densification via transient liquid-phase sintering. Specifically, Si formed via the reaction between B4C and TiSi2 that served as a transient component contributed to densification when it melted and then reacted with C to yield more SiC. Toughening mechanisms, including crack deflection, branching and bridging, could be observed due to the residual stresses induced by the thermoelastic mismatches. Particularly, the introduced SiC–TiB2 agglomerates composed of interlocked SiC and TiB2 played a critical role in improving toughness. Accordingly, the B4C–SiC–TiB2 composite created with B4C-16 wt% TiSi2 achieved excellent mechanical performance, containing a Vickers hardness of 33.5 GPa, a flexural strength of 608.7 MPa and a fracture toughness of 6.43 MPa m1/2.