Partial Discharge Pulse Segmentation Approach of Converter Transformers Based on Higher Order Cumulant

As one of the most effective methods to detect the partial discharge (PD) of transformers, high frequency PD detection has been widely used. However, this method also has a bottleneck problem; the biggest problem is the mixed pulse interference under the fixed length sampling. Therefore, this paper focuses on the study of a new pulse segmentation technology, which can separate the partial discharge pulse from the sampling signal containing impulse noise so as to suppress the interference of pulse noise. Based on the characteristics of the high-order-cumulant variation at the rising edge of the pulse signal, a method for judging the starting and ending time of the pulse based on the high-order-cumulant is designed, which can accurately extract the partial discharge pulse from the original data. Simulation results show that the location accuracy of the proposed method can reach 94.67% without stationary noise. The field test shows that the extraction rate of the PD analog signal can reach 79% after applying the segmentation method, which has a great improvement compared with a very low location accuracy rate of 1.65% before using the proposed method.

SOURCE LOCATION MECHANISM OF MICROSEISMIC MONITORING USING P-S WAVES AND ITS EFFECT ANALYSIS

Seismic source location is the most fundamental and most important problem in microseismic monitoring. However, only P wave has been mostly applied in the existing microseismic monitoring networks, with low location accuracy and poor stability of location result for the microseismic events occurring beyond monitoring networks. The seismic source location was implemented using P wave and S wave in this study to expand the effective monitoring area of a microseismic monitoring network and improve its location accuracy for microseismic events nearby the monitoring network. Then, the seismic source location mechanism using P-S wave was revealed through theoretical derivation and analysis. Subsequently, the program development and numerical simulation were combined to analyze and compare systematically the location effects of differently distributed monitoring networks, those consisting of different quantities of sensors, and those with S wave contained in some sensors under two circumstances: combination of P wave and S wave and single use of P wave. Results demonstrate that adding S wave in the plane enhances the accuracy control in the radius direction of the monitoring network. After S wave is included, the location accuracy within a certain area beyond the monitoring network is improved considerably, the effective monitoring area of the whole network is expanded, and the unstable location zones using only P wave are eliminated. The location results of differently distributed monitoring networks and the influence laws of the quantity of sensors constituting the networks on the location results are acquired. This study provides evidence for microseismic monitoring to realize accurate and stable location within a larger range. Keywords: seismic source location, P wave and S wave, mechanism, location effect

Systematic Error Correction for Geo-Location of Airborne Optoelectronic Platforms

In order to improve the geo-location accuracy of the airborne optoelectronic platform and eliminate the influence of assembly systematic error on the accuracy, a systematic geo-location error correction method is proposed. First, based on the kinematic characteristics of the airborne optoelectronic platform, the geo-location model was established. Then, the error items that affect the geo-location accuracy were analyzed. The installation error between the platform and the POS was considered, and the installation error of platform’s pitch and azimuth was introduced. After ignoring higher-order infinitesimals, the least square form of systematic error is obtained. Therefore, the systematic error can be obtained through a series of measurements. Both Monte Carlo simulation analysis and in-flight experiment results show that this method can effectively obtain the systematic error. Through correction, the root-mean-square value of the geo-location error have reduced from 45.65 m to 12.62 m, and the mean error from 16.60 m to 1.24 m. This method can be widely used in systematic error correction of relevant photoelectric equipment.

Transdimensional simultaneous inversion of velocity structure and event locations in downhole microseismic monitoring

In downhole microseismic monitoring, the velocity model plays a vital role in accurate mapping of the hydraulic fracturing image. For velocity model uncertainties in the number of layers or interface depths, the conventional velocity calibration method has been shown to effectively locate the perforation shots; however, it introduces non-negligible location errors for microseismic events, especially for complex geological formations with inclinations. To improve the event location accuracy, we exploit the advantages of the reversible jump Markov chain Monte Carlo (rjMCMC) approach in generating different dimensions of velocity models and propose a transdimensional Bayesian simultaneous inversion framework for obtaining the effective velocity structure and event locations simultaneously. The transdimensional inversion changes the number of layers during the inversion process and selects the optimal interface depths and velocity values to improve the event location accuracy. The confidence intervals of the simultaneous inversion event locations estimated by Bayesian inference enable us to evaluate the location uncertainties in the horizontal and vertical directions. Two synthetic examples and a field test are presented to illustrate the performance of our methodology, and the event location accuracy is shown to be higher than that obtained using the conventional methods. With less dependence on prior information, the proposed transdimensional simultaneous inversion method can be used to obtain an effective velocity structure for facilitating highly accurate hydraulic fracturing mapping.

Study on the influence of elbow with different curvature radii on pipeline leak location

Experimental and numerical methods are used to locate the pipeline leakage in the present work. The weak compressibility of the fluid is taken into account when simulating the propagation of negative pressure wave (NPW) in the pipeline. The NPW attenuation coefficient is used to describe the influences of curvature radius on location accuracy. The results indicate that when the curvature radius is small, the location accuracy of pipeline leakage is low. When the radius of curvature increases or the inlet pressure increases, the accuracy of pipeline leak location is improved. Besides, with the change of inlet pressure, pressure, and velocity distributions in the elbow with different curvature radii are investigated. When the curvature radius of the elbow is three to four times of pipe diameter, the measurement accuracy of leakage location is the best. When the inlet pressure of the pipeline is 0.7 MPa, the sensitivity of the pipeline detection is the highest. The cavitation corrosion at the elbow is the most obvious. Therefore, the elbow is the area where pipeline leakage occurs most frequently.

Research on Location Algorithm Based on Beacon Filtering Combining DV-Hop and Multidimensional Support Vector Regression

The DV-Hop algorithm is widely used because of its simplicity and low cost, but it has the disadvantage of a large positioning error. In recent years, although some improvement measures have been proposed, such as hop correction, distance-weighted correction, and improved coordinate solution, there is room for improvement in location accuracy, and the accuracy is affected in anisotropic networks. A location algorithm based on beacon filtering combining DV-Hop and multidimensional support vector regression (MSVR) is proposed in this paper. In the process of estimating the coordinates of unknown nodes, received signal strength indication (RSSI), MSVR, and weighted least squares method are combined. In addition, the verification error of beacon nodes is proposed, which can select the beacon nodes with smaller errors to reduce the location error. Simulation results show that in different distributions, the location accuracy of the proposed algorithm is at least 34% higher than that of the classical DV-Hop algorithm and at least 28% higher than that of the localization based on multidimensional support vector regression (LMSVR) algorithm. The proposed algorithm has the potential of application in small-scale anisotropic networks.

Geo-Fence Technique for Prevention of Human Kidnapping

This paper presents how IoT and its related technologies are used to tame human kidnapping. IoT design, geo-fencing, API integration, and GPS signal formed the backbone of the proposed system. While the GSM base stations provide signals for the system, the frontends are the mobile phone devices, application interface, and the GPS. The location signal is transmitted to the server when the subject enters or exits the geofence for movement and direction tracing. The IoT component hosts the web application, MySQL and GMS are used to provide backend solutions, and the GPS guarantees communication and placement of the subject on the search map. The implementation involved suitable platforms and engines and followed up with case study of kidnapping scenarios involving 20 randomly selected individuals. The study established the practical function of the system and its good performances in areas of availability, concealment, security, location accuracy, seamless data transmission, among others. Comparative analysis with related works also established the relative strength of the new method.