scholarly journals Power Transformer Voiceprint Operation State Monitoring Considering Sample Unbalance

2021 ◽  
Vol 2137 (1) ◽  
pp. 012007
Author(s):  
shoulong Chen ◽  
Ping He ◽  
HongHua Xu ◽  
LaiBin Yin ◽  
LingYan Wang ◽  
...  
Keyword(s):  
Feature Vector ◽  
Recognition Accuracy ◽  
Power Transformer ◽  
Frequency Multiplier ◽  
Operating Conditions ◽  
Utilization Rate ◽  
Signal Acquisition ◽  
State Monitoring ◽  
Light Load ◽  
Component Amplitude

Abstract The voiceprint characteristics of transformers are closely related to the operating conditions, but there is currently a lack of effective research on the voiceprint characteristics of transformers during operation. First of all, this article collects three operating conditions of load, light load, and no load on the basis of the transformer voiceprint signal acquisition platform. Secondly, in view of the characteristics of the transformer’s voiceprint, the 50Hz frequency multiplier component amplitude is extracted to form a feature vector, which solves the problem of low utilization rate of common feature extraction information. Finally, in view of the problem of transformer voiceprint failure and sample imbalance caused by fewer abnormal samples, a pattern recognition based on the RUSBoost algorithm is proposed. The algorithm has good recognition accuracy and applicability for transformer voiceprint samples with imbalance problems. The research results provide effective support for the monitoring and identification of the mechanical condition of transformers with sample unbalanced voiceprints, and the analysis of the operating conditions can effectively eliminate the errors that may be caused by their own different operating conditions.

scholarly journals An Improved High-Intelligence Method of Gas and Oil Pipeline Prewarning System in Real Soil Environment

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Fang Wang ◽  
Jichuan Xing ◽  
Jinxin Li ◽  
Feng Zhao ◽  
Shufeng Zhang
Keyword(s):  
Optical Fiber ◽  
Real Time ◽  
Recognition Accuracy ◽  
Signal Acquisition ◽  
Soil Environment ◽  
Long Distance ◽  
Vibration Signals ◽  
Oil Pipeline ◽  
Time Performance ◽  
High Intelligence

With the development of technology, the total extent of global pipeline transportation is also increased. However, the traditional long-distance optical fiber prewarning system has poor real-time performance and high false alarm rate when recognizing events threatening pipeline safety. The same vibration signal would vary greatly when collected in different soil environments and this problem would reduce the signal recognition accuracy of the prewarning system. In this paper, we studied this effect theoretically and analyzed soil vibration signals under different soil conditions. Then we studied the signal acquisition problem of long-distance gas and oil pipeline prewarning system in real soil environment. Ultimately, an improved high-intelligence method was proposed for optimization. This method is based on the real application environment, which is more suitable for the recognition of optical fiber vibration signals. Through experiments, the method yielded high recognition accuracy of above 95%. The results indicate that the method can significantly improve signal acquisition and recognition and has good adaptability and real-time performance in the real soil environment.

Multimodal biometric system combining left and right palmprints

2019 ◽  
Vol 48 (1) ◽  
pp. 2-13
Author(s):  
Chérif Taouche ◽  
Hacene Belhadef
Keyword(s):  
Feature Vector ◽  
Recognition Accuracy ◽  
Search Algorithm ◽  
Palmprint Recognition ◽  
Multimodal Biometrics ◽  
Chi Square ◽  
Content Type ◽  
Set Size ◽  
Promising Area ◽  
Left And Right

Purpose Palmprint recognition is a very interesting and promising area of research. Much work has already been done in this area, but much more needs to be done to make the systems more efficient. In this paper, a multimodal biometrics system based on fusion of left and right palmprints of a person is proposed to overcome limitations of unimodal systems. Design/methodology/approach Features are extracted using some proposed multi-block local descriptors in addition to MBLBP. Fusion of extracted features is done at feature level by a simple concatenation of feature vectors. Then, feature selection is performed on the resulting global feature vector using evolutionary algorithms such as genetic algorithms and backtracking search algorithm for a comparison purpose. The benefits of such step selecting the relevant features are known in the literature, such as increasing the recognition accuracy and reducing the feature set size, which results in runtime saving. In matching step, Chi-square similarity measure is used. Findings The resulting feature vector length representing a person is compact and the runtime is reduced. Originality/value Intensive experiments were done on the publicly available IITD database. Experimental results show a recognition accuracy of 99.17 which prove the effectiveness and robustness of the proposed multimodal biometrics system than other unimodal and multimodal biometrics systems.

scholarly journals Experimental Study on the Skidding Damage of a Cylindrical Roller Bearing

Materials ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4075 ◽  
Author(s):  
Qing Zhang ◽  
Jun Luo ◽  
Xiang-yu Xie ◽  
Jin Xu ◽  
Zhen-huan Ye
Keyword(s):  
High Speed ◽  
Large Scale ◽  
Failure Modes ◽  
Roller Bearing ◽  
Weight Ratio ◽  
Operating Conditions ◽  
Roller Bearings ◽  
Light Load ◽  
Cylindrical Roller Bearing ◽  
Cylindrical Roller

As large-scale rotating machines develop toward high rotating speed and high power–weight ratio, skidding damage has become one of the major initial failure modes of cylindrical roller bearings. Therefore, understanding the skidding damage law is an effective way to ensure the safety of machines supported by cylindrical roller bearings. To realize the skidding damage, a high-speed rolling bearing test rig that can simulate the actual operating conditions of aviation bearings was used in this paper, and the skidding damage dynamic behaviors of cylindrical roller bearings were investigated. In addition, to ensure the accuracy of the obtained skidding damage mechanism, the cylindrical roller bearing was carefully inspected by microscopic analysis when the skidding damage occurred. Out results show that instantaneous increases in friction torque, vibration acceleration, and temperature are clearly observed when the skidding damage occurs in the cylindrical roller bearing. Furthermore, under the conditions of inadequate lubrication and light load, the critical speed of skidding damage is rather low. The major wear mechanisms of skidding damage include oxidation wear, abrasive wear, and delamination wear. The white layers are found locally in the inner ring and rollers under the actions of friction heat and shear force.

Recognition of Online Handwritten Bangla Characters Using Supervised and Unsupervised Learning Approaches

2020 ◽  
Vol 10 (3) ◽  
pp. 18-30
Author(s):  
Prosenjit Mukherjee ◽  
Shibaprasad Sen ◽  
Kaushik Roy ◽  
Ram Sarkar
Keyword(s):  
Character Recognition ◽  
Supervised Classification ◽  
Clustering Algorithm ◽  
Feature Vector ◽  
Recognition Accuracy ◽  
Learning Approaches ◽  
Current Experiment ◽  
Unsupervised Approach ◽  
Mean Structure ◽  
Euclidian Distances

This paper explores the domain of online handwritten Bangla character recognition by stroke-based approach. The component strokes of a character sample are recognized firstly and then characters are constructed from the recognized strokes. In the current experiment, strokes are recognized by both supervised and unsupervised approaches. To estimate the features, images of all the component strokes are superimposed. A mean structure has been generated from this superimposed image. Euclidian distances between pixel points of a stroke sample and mean stroke structure are considered as features. For unsupervised approach, K-means clustering algorithm has been used whereas six popular classifiers have been used for supervised approach. The proposed feature vector has been evaluated on 10,000-character database and achieved 90.69% and 97.22% stroke recognition accuracy in unsupervised (using K-means clustering) and supervised way (using MLP [multilayer perceptron] classifier). This paper also discusses about merit and demerits of unsupervised and supervised classification approaches.

Analysis of Gas Utilization Efficiency in Injection Refining Process

2011 ◽  
Vol 391-392 ◽  
pp. 703-708
Author(s):  
Yan Liu ◽  
Ting An Zhang ◽  
Sano Masamichi ◽  
Ji Cheng He
Keyword(s):  
Gas Flow ◽  
Bubble Diameter ◽  
Operating Conditions ◽  
Utilization Efficiency ◽  
Utilization Rate ◽  
Theoretical Formula ◽  
Practical Situation ◽  
First Order ◽  
Physical Conditions ◽  
Gas Utilization

According to practical situation of Mg-based desulphurization, this paper has defined the formula of bubble effectiveness with low ratio of height to diameter, and derived the theoretical formula of the bubble utilization rate relating to gas flow rate, bubble diameter and mass transfer coefficient. When the absorption rate is treated as first order reaction, the theoretical formula is presented which includes physical conditions, equipment conditions and operating conditions. It indirectly reflects the three conditions on the effective of bubble utilization rate. The calculation formula of bubble utilization rate at different sizes and different residence time distribution is derived.

A Particle Swarm Optimization for Optimal Tolerance Design of Power Transformer Core Column Cross-Section

2010 ◽  
Vol 439-440 ◽  
pp. 74-79
Author(s):  
Jia Di Wan ◽  
Yuan Biao Zhang ◽  
Lei Cai ◽  
Chuan He
Keyword(s):  
Particle Swarm Optimization ◽  
Power Transformer ◽  
Sheet Material ◽  
Particle Swarm ◽  
Probabilistic Methods ◽  
Power Transformers ◽  
Utilization Rate ◽  
Tolerance Design ◽  
Swarm Optimization ◽  
Passing Rate

This paper presents a solution of the Optimal Tolerance Design Problems for the production of power transformers. Based on statistical and probabilistic methods, it establishes a multi-objective and multi-constraint mathematical model. We then present a solution that maximizes the effective utilization rate of sheet material, for producing core columns of power transformers, and the passing rate of quality controls of matching coils and cores. It also minimizes the Tolerance cost of the product. The solution uses Particle Swarm Optimization (PSO), which is very effective as shown by simulation results.

scholarly journals Analysis of Operating Modes of Oil-Immersed Power Transformers with a Voltage of 10 (6) / 0.4 kV

2021 ◽  
Vol 24 (4) ◽  
pp. 80-91
Author(s):  
A.E. Fokeev ◽  
I.N. Tumakov
Keyword(s):  
Ambient Temperature ◽  
Thermal Aging ◽  
Power Transformer ◽  
Spectral Composition ◽  
Operating Conditions ◽  
Power Transformers ◽  
Load Factor ◽  
Calculation Algorithm ◽  
Load Current ◽  
Aging Rate

The rate of thermal aging of the power transformers windings insulation depends on the effects of the electric field, mechanical stresses, temperature and processes that cause changes in these factors. A calculation algorithm is considered that allows determining the temperature of the most heated point of the windings of an oil power transformer at known values of the load current and ambient temperature. Calculation of the most heated winding point temperature and the rate of thermal aging of insulation for an oil power transformer at different ambient temperatures during the year, different values and different spectral composition of the electric load current showed that in some cases it is possible to violate the permissible operating conditions of power transformers. According to the calculation results, the dependences of the thermal aging rate of insulation on the ambient temperature are constructed, with different load parameters and different load coefficients of power transformers. For the considered modes, in the warm season, the value of the thermal aging rate of insulation significantly exceeds the nominal value. Based on mathematical models of oil power transformers with natural and forced oil circulation, expressions are obtained for determining the coefficient of reduction of the oil power transformers permissible load when the ambient temperature exceeds the normal value of 20 °C. On the basis of these expressions, for practical use, the dependences of the coefficient of reduction of the permissible load on the ambient temperature are constructed. The influence of ambient temperature must be taken into account when choosing the power of oil power transformers, for which it is assumed to operate in full redundancy mode or high load factor values (³ 0.8) in normal mode. To ensure the normative service life of the insulation of the windings, it is necessary to determine the design power of oil power transformers using the coefficient of reduction of the permissible load under the influence of higher harmonics of the current and the coefficient of reduction of the permissible load under the influence of ambient temperature.

scholarly journals A Model for Optimal Treatment of Cassava Wastewater Using Anaerobic Baffled Reactor

2021 ◽  
Vol 18 (2) ◽  
pp. 129-134
Author(s):  
A.O. Ibeje ◽  
E. Onukwugha
Keyword(s):  
Experimental Data ◽  
Wastewater Treatment ◽  
Aspect Ratio ◽  
Operating Conditions ◽  
Optimum Operating ◽  
Utilization Rate ◽  
Treatment Processes ◽  
Cyanide Inhibition ◽  
Cassava Wastewater ◽  
Influent Flow

The major components of the effluents from cassava processing industries are cyanide and starch. However it is suspected that cyanide inhibits the treatment of cassava wastewater. The experimental data were successfully fitted to a polynomial model which was used to optimize the treatment processes at a laboratory scale. The Monod and Michealis-menten models for cassava wastewater treatment was successfully calibrated and validated in an ABR system. For Michealis-Menten model, the maximum substrate utilization rate is estimated in the range: 2866.88 to 1432.84 mgl-1 and for Monod’s model, it is estimated in the range: 493 to 1242 mgl-1, which is more realistic, hence validating the empirical model as more accurate than the former, which is theoretical. The result revealed that the inhibitor constant decreased from 9.9989 to 1.6101mgl-1 as the number of baffles increased from 3 to 10. To reach a maximum COD removal efficiency of 99%, it was found that the aspect ratio of 10, 20 baffles, cyanide inhibition constant of 30 mg/l and influent flow rate of 0.8 l/min, are the required optimum operating conditions of the anaerobic baffled reactors.

scholarly journals Fire-Fly Algorithm Based ANN Classification of Power Transformer Faults

2020 ◽  
Vol 9 (4) ◽  
pp. 1880-1884
Keyword(s):  
Wavelet Transforms ◽  
Performance Metrics ◽  
Feature Vector ◽  
Learning Algorithm ◽  
Power Transformer ◽  
Gas Analysis ◽  
Phase Detection ◽  
Double Line ◽  
Waveform Data

Monitoring and estimating the states of the transformer during faulted phase condition is essential to continuity of supply. Varied techniques are proposed for faulted phase detection to improve condition assessment. In this paper, we propose a novel method to detect and classify power transformer faults using wavelet transform Multi Resolution Analysis (MRA) as feature extracted parameter vector and Fire-Fly Algorithm (FFA) based Artificial Neural network training as classification method. The observed Dissolved Gas Analysis (DGA) waveform data is analyzed with wavelet transforms (WT) to identify abnormalities which is supported by MRA. In MRA, the current, voltage and temperature of winding and oil are decomposed into high and low frequency components. The magnitude of components, signifies the feature vector, gives a detection criteria. After detecting feature vector, dominant coefficients of WT can be used to train the ANN with FFA based learning algorithm. Different types of faults are created on transformer such as Single Line-Ground (SLG), Line-Line (LL), Double Line-Ground LLG, Three phase fault (LLLG) for the analysis using WT and ANN. The detection and classification of the fault signal are executed and examined in different winding location and different fault conditions. Finally, the presented precise model recognizes the faults based on performance metrics with high classification accuracy for various classes.

An Innovative Solution for Type Testing of Power Transformers

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Manohar Singh ◽  
Vishnuvarddhan Telukanta ◽  
K S Meera
Keyword(s):  
Power Transformer ◽  
Short Circuit ◽  
Operating Conditions ◽  
Power Transformers ◽  
Test Facility ◽  
Online Testing ◽  
Testing Laboratory ◽  
Power Testing ◽  
Grid Operation ◽  
The Impact

Abstract Type tests are essential to assess the short circuit withstand capabilities of transformer windings. The mechanical durability of power equipment are checked against the mechanical forces developed during making/breaking short circuit operations. These type tests are generally carried out in indoor transformer test laboratories. Testing of Power Transformer for size more than 200 MVA in 765/400 kV voltage class in an indoor laboratory is not economically feasible. Now a days, power transformer manufacturers are fabricating single phase auto- power transformers of size up to 630 megawatt volt ampere (MVA) rating. Type testing of these transformers in indoor laboratories is not feasible. In view of this, strong short circuit fault feeding capabilities of the national grids can be utilized for type testing of these power transformers in an online manner. However, this may affect the grid operation/control during weak grid operating conditions. Recently, National High Power Testing Laboratory is established for testing of power transformer upto of 630 MVA. This is a unique online transformer test facility for testing of 765/400/220/132 kV class power transformers. An offline simulation has been carried out in this article, to assess the impact of online type testing on the Indian National grid. In this article, an online testing scheme has been presented which enables the national grid operator to analysis the prevailing grid condition & subsequently to decide the safe rating of the power transformer for online testing. The simulated results are cross checked with field results and it is found that simulated results are close to actual field results. The concurrence of simulated and field results helped in successfully commissioning of the testing laboratory.

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