On the inverse problem of reflection Green’s function seismograms over stratified acoustic media: Estimation of background models

A theory is presented for estimating the background velocity and density of an acoustic stratified medium by iterative least-squares waveform inversion in the frequency-horizontal slowness domain of low-frequency precritical reflection incidence seismograms of time length [Formula: see text]. The initial model is constant. The prerequisites for the method are that the reflection seismograms should be Green’s function seismograms and that the fundamental frequency component [Formula: see text] is present. Then, the gradients of the objective function provide the low-wavenumber trend of the medium. A matrix formulation for the model update is expressed mathematically by the classic seismogram residual, Jacobian, gradient, and Hessian in the Levenberg-Marquardt approximation. The first iteration, which is equal to a constant-parameter migration inversion (CPMI), is thoroughly analyzed, and expressions for band-limited gradients and block Hessians are found. For primary precritical reflection incidence seismograms of infinite bandwidth, it is shown theoretically that the partial gradients in the CPMI model become a reflection strength-weighted sum of shifted discrete sign functions, typical of step or staircase functions, which provide interface locations in Born depth and amplitudes that can be mapped to velocity and density information. For frequency-band-limited primary reflection seismograms, the partial gradients become a reflection strength-weighted sum of wavenumber-band-limited discrete sign functions. When the fundamental frequency component in the seismograms is present, the band-limited discrete sign functions are oscillatory but keep the information of the step function characteristic of the partial gradient. When the fundamental frequency component in the seismograms is absent, the band-limited discrete sign functions keep information of where the steps are located but lose the information of the amplitudes of the steps. The Hessian elements are nonstandard with the Hessian modeled over a broader frequency range than the frequencies of the observed low-frequency seismogram to avoid it becoming close to singular. The main mathematical findings are illustrated by a simple model and seismograms, for which the background models are found after two iterations. For the sake of completeness, the background models are classically used as initial models in a Levenberg-Marquardt least-squares inversion scheme to estimate the layer velocities and densities from broadband seismograms.

Online measuring and estimating methods for the unbalancing vector of thin-disc workpiece based on the adaptive influence coefficient

The thin-disc part is the common part of the rotary mechanism. Because of the large rotating radius of the thin-disc part, the huge unbalancing vector may be formed even if the unbalancing mass is small. So, the unbalance of the thin-disc part is the important exciting factor of the rotary mechanism vibration. Based on the structural characteristics of the thin-disc part, the measuring and estimating methods for the unbalancing vector of the thin-disc workpiece are proposed based on the single-face influence coefficient method. The least square method is introduced to fit the fundamental frequency component from the vibration monitoring signal, and the fundamental frequency component is taken as the unbalancing vibration signal of spindle first. The influence coefficient between the trial weight face and vibration monitoring point on the spindle is tested by trial weight experiments second. The unbalancing vibration difference of the spindle, before and after the thin-disc workpiece is clamped, is monitored and used to estimate the unbalancing vector of the thin-disc workpiece based on the linear reversible principle of unbalancing excitation and vibration response. The signal separation accuracy of the least square method for unbalancing vibration has been proved by simulation and experiment methods. Considering that the accuracy of the influence coefficient may be influenced by the change of the spindle system kinetic characteristic parameters, the signal measurement, analysis error, etc., the adaptive method for the influence coefficient is proposed and proved by the experiment method in the article. The research results show that the unbalancing vector of the thin-disc workpiece can be measured and estimated before the workpiece is taken down from the machine tool spindle. The proposed method can be used to measure and estimate the unbalancing vector of the thin-disc workpiece without dynamic balancing machine, and the measuring efficiency and accuracy can be improved; the measuring cost can be reduced.

Fundamental Frequency Suppression for the Detection of Broken Bar in Induction Motors at Low Slip and Frequency

Broken rotor bar (BRB) is one of the most common failures in induction motors (IMs) these days; however, its identification is complicated since the frequencies associated with the fault condition appear near the fundamental frequency component (FFC). This situation gets worse when the IM slip or the operation frequency is low. In these circumstances, the common techniques for condition monitoring may experience troubles in the identification of a faulty condition. By suppressing the FFC, the fault detection is enhanced, allowing the identification of BRB even at low slip conditions. The main contribution of this work consists of the development of a preprocessing technique that estimates the FFC from an optimization point of view. This way, it is possible to remove a single frequency component instead of removing a complete frequency band from the current signals of an IM. Experimentation is performed on an IM operating at two different frequencies and at three different load levels. The proposed methodology is compared with two different approaches and the results show that the use of the proposed methodology allows to enhance the performance delivered by the common methodologies for the detection of BRB in steady state.

Fault Detection & Classification in UPFC Integrated Transmission Line Using DWT

Fault detection and classification in UPFC (Unified Power Flow Controller) integrated transmission line using single terminal based DWT (Discrete Wavelet Transform) is proposed. The current is extracted from the sending end bus and processed through wavelet transform to evaluate the spectral energy (SE) using db4 mother wavelet. Three level decomposition is framed to extract the fundamental frequency component from non-stationary signal, considering sampling frequency of 2kHz system. The fundamental frequency component of respective phase currents are used to compute SE at sending end. The SE of individual phase current is the key factor for deciding the fault pattern detection and classification. The advantage of using this it requires less cost and protect entire transmission line with minimal fault detection time. The various types of fault (L-G, L-L, L-L-G, L-L-L) are simulated by considering the parameter like fault resistance, source impedance, fault inception angle, multi-location fault, reverse power flow and UPFC system parameter. The scheme works reliable and efficient to detect and classify the fault within a cycle of sample period 40 or a cycle of time period 20ms compared to other conventional relaying scheme.

Induction motor current signature for centrifugal pump load

Sensorless monitoring technology based on motor current signature analysis is a nonintrusive and economical technique to monitor motor-driven equipment. Sensorless monitoring technology can be applied to a centrifugal pump system. This technology is also based on the motor current signature of centrifugal pump load; however, systematic research regarding motor current signature in overall normal operation points which is the applied basic for sensorless monitoring technology has been rarely performed. As such, we partially examined the motor current signature of a centrifugal pump load by experimental observation, theoretical analysis, and numerical simulation. Results show that stator current is a sinusoidal alternating current that strictly follows sine law associated with the cycle of the fundamental frequency of supply power. The trend of the root mean square and peak–peak of current is the same as flow–shaft power characteristics; hence, this trend could be used as indicator of the pump operational point monitor. The frequency characteristics of a centrifugal pump, such as blade passing frequency, rotation frequency, and broadband noise, could be reflected as sidebands around the fundamental frequency. The stator current spectrum is composed of fundamental frequency component, harmonics component, and noise. The fundamental frequency component is directly related to the pump load in which changes associated with the law of fundamental frequency component are relatively similar to flow–shaft power characteristics. Harmonics component and noise are caused by load fluctuation in which the amount of energy of these two components exhibits a lower value at the preferred operation point. By contrast, the amount of energy likely increases when pump operation is at an unstable operation point. These results further indicate that motor current signature analysis is a feasible and cost-effective method to monitor centrifugal pump operation status. Therefore, motor current signature analysis can be applied to monitor-related flow phenomena.

Research on on-Load Current Method for Detecting Fault of Transformer Core Based on the Vibration Analysis Method

When vibration signal analysis method is used to monitor the transformer, the core vibration signal is often obtained as the transformer runs under no-load condition. In this paper, a method extracting core vibration signal without operating transformer under no-load condition was introduced. The transformer vibration accelerative signals at different on-load current and no-load condition were measured. From the fitted curve of on-load current versus fundamental frequency component of vibration accelerated signal, the value of fundamental frequency component was obtained when the on-load current was zero, which was almost equivalent to the fundamental frequency component of vibration accelerative signal measured under no-load condition, thus the fundamental frequency component of core vibration can be obtained by using on-load current method. The core with fault was finally monitored by using the on-load current method compared with wavelet package transform method. From the result of experiment, it can be seen this method is very useful to estimate the condition of the transformer core.

Motor Broken-Bar Fault Diagnosis Based on Park Vector and Wavelet Neural Network

In the technology of motor fault diagnosis, current monitoring methods have become a new trend in motor fault diagnosis. This paper presents a motor fault diagnosis method based on Park vector and wavelet neural network. This method uses the stator current as the object of study. Firstly, it uses Park vector to deal with the stator current and filter out fundamental frequency component, thus the characteristics component of motor broken-bar will be separated from fundamental frequency component; Secondly, it uses five layers wavelet packet decomposition to pick up fault characteristic signal; Finally, we distinguish the fault by BP neural network, and use the simulation software of MATLAB to realize it. The test results show that: This method can detect the existence of motor broken-bar fault, and has a good value in engineering.

Analysis of Fault Recorder Data for Short-Circuit Current in a 500kV Busbar Short-Circuit Accident

The three-phase short-circuit fault of the 500 kV busbar of Waigaoqiao No.2 Power Plant was described, and the fault recorder data was analyzed for short-circuit current. The RMS of short-circuit current decaying fundamental frequency component, DC component and the attenuation time constant was obtained by Fourier transform, extrapolating with the exponential function. Finally, Corresponding suggestions for grid operation and management were also proposed.