scholarly journals Research on Reactor Condition Evaluation Method Based on Acoustic Vibration Characteristic Parameters and Weight Factors

2021 ◽  
Vol 243 ◽  
pp. 02003
Author(s):  
Peng-fei Jia ◽  
Shu-guo Gao ◽  
Xing-hui Zhang ◽  
Ling-ming Meng ◽  
Li-hua Li ◽  
...  
Keyword(s):  
Evaluation Method ◽  
Detection Method ◽  
Power Level ◽  
Characteristic Parameter ◽  
Acoustic Vibration ◽  
Signal Spectrum ◽  
Characteristic Parameters ◽  
Term Operation ◽  
Vibration Detection ◽  
Distribution Rule

Compared with the traditional reactor abnormal state detection method, the acoustic vibration detection method combines the advantages of acoustic detection and vibration detection, which has the advantages of simple installation, strong portability and good signal integrity, and has a broad application prospect. In this paper, the characteristic parameters of reactor acoustic vibration, including sound pressure level, sound power level, acoustic signal spectrum, vibration amplitude, vibration acceleration value, vibration signal spectrum, harmonic proportion and frequency complexity, are obtained to analyze the range and distribution rule of each characteristic parameter under long-term operation condition of reactor, and the weight factor of each characteristic parameter is determined by analytic hierarchy process On the basis of fuzzy reasoning, the state evaluation model of reactor is established.

scholarly journals Research on Defect Diagnosis Method of Reactor Acoustic Vibration Method Based on Deep Learning

2021 ◽  
Vol 243 ◽  
pp. 02005
Author(s):  
Peng-fei Jia ◽  
Shu-guo Gao ◽  
Xing-hui Zhang ◽  
Ling-ming Meng ◽  
Yang Yang ◽  
...  
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Evaluation Method ◽  
Vibration Signal ◽  
Acoustic Vibration ◽  
The State ◽  
Characteristic Parameters ◽  
Defect States ◽  
Defect Simulation ◽  
Function Relationship

Although the state evaluation method based on characteristic parameters and weight factors can extract the characteristic quantities in time domain and frequency domain according to the collected acoustic and vibration signals of reactors, it is necessary to analyze a large number of test data to establish the functional relationship between the characteristic quantities and the defect states, and to establish the function relationship between the characteristic quantities and the defect states, and to establish the function relationship between the characteristic quantities and the defect states The method can directly learn the data samples, and self-study the correlation rules of characteristic parameters and defects through the training of neural network. In this paper, the deep learning neural network model is constructed, and the data obtained from reactor defect simulation experiment and field measurement are used as samples to train the deep learning network. Through the training of neural network, the characteristics of acoustic vibration signal are automatically learned, and the characteristics are stored in the parameters of neural network. Finally, the state of reactor is realized by the classifier at the end of the network assessment

Detection method for stability of microcontroller accessories based on biosensor

2021 ◽  
pp. 1-14
Author(s):  
Yan Ren ◽  
Jiayong Liu
Keyword(s):  
Process Design ◽  
Detection Method ◽  
Detection Accuracy ◽  
Stability Testing ◽  
Term Operation ◽  
Existing Problems ◽  
Testing Method ◽  
And Performance ◽  
The Stability

In order to solve the problem of poor accuracy of traditional microcontroller attachment stability testing method, a microcontroller attachment stability testing method based on biosensor was designed to solve the existing problems. The reliability test index of the microcontroller is established, then the interference of the microcontroller accessory is detected and responded, and the interference detection signal of the microcontroller accessory is selected. The process design of stability detection of microcontroller accessories based on biosensor is completed. The experimental results show that the stability detection method based on biosensor designed in this paper can ensure the stability detection accuracy of microcontroller accessories above 80%, which is more accurate than traditional methods. It can be used to evaluate the stability, reliability and performance of microcontroller accessories in long-term operation.

scholarly journals Effect of interference on fretting wear of planetary frame axle hole

2020 ◽  
Vol 12 (5) ◽  
pp. 168781402091922
Author(s):  
Zhipeng Lyu ◽  
Fuyuan Wang ◽  
Sizhu Zhou ◽  
Si Liu
Keyword(s):  
Slip Velocity ◽  
Dominant Role ◽  
Axial Direction ◽  
Characteristic Parameter ◽  
Middle Part ◽  
Fretting Wear ◽  
Wear Depth ◽  
Relative Slip ◽  
Finite Element Software ◽  
Distribution Rule

In order to study fretting wear damage law of planetary frame axle hole, the distribution of normal stress and relative sliding velocity at axle hole was obtained by finite element software, and a method of extracting fretting wear characteristic parameter data was put forward and verified. According to the modified model of fretting wear depth calculation, the wear depth of each step at axle hole was calculated, and the influence of interference on wear depth was analyzed. The results show that the stress distribution obtained by this method corresponds to the values of each node in the Workbench stress nephogram at that time and has the same distribution rule, which shows that the method is correct. The stress concentration near the inner part of the axle hole of the planetary frame is obvious. Along the circumferential and axial direction of the shaft hole, the relative slip velocity of both ends is larger, and the relative slip velocity of the middle part is smaller. Average wear in both axial and circumferential directions increases with the increase in interference, while wear in the axial direction plays a dominant role in the whole meshing process.

Nanoparticle monolayer-based flexible strain gauge with ultrafast dynamic response for acoustic vibration detection

Nano Research ◽  
2015 ◽  
Vol 8 (9) ◽  
pp. 2978-2987 ◽  
Author(s):  
Lizhi Yi ◽  
Weihong Jiao ◽  
Ke Wu ◽  
Lihua Qian ◽  
Xunxing Yu ◽  
...  
Keyword(s):  
Dynamic Response ◽  
Strain Gauge ◽  
Acoustic Vibration ◽  
Ultrafast Dynamic ◽  
Vibration Detection

Introductory: Perspectives on Reality and "The World" in the Realism Debate

Human Affairs ◽  
2009 ◽  
Vol 19 (2) ◽  
Author(s):  
Dimitri Ginev
Keyword(s):  
Characteristic Parameter ◽  
Characteristic Parameters ◽  
The World ◽  
Realism Debate

Introductory: Perspectives on Reality and "The World" in the Realism DebateOne of the "characteristic parameters" dividing up analytical and Continental philosophizing is the interpretation of the concepts of "reality" and "the world". The paper offers an analysis of this characteristic parameter with regard to the relations between epistemologically centred and hermeneutically oriented doctrines of realism.

Crack Growth Evaluation for Cracked Carbon and Stainless Steel Pipes Under Large Seismic Cyclic Loading

2015 ◽  
Author(s):  
Yoshihito Yamaguchi ◽  
Jinya Katsuyama ◽  
Yinsheng Li ◽  
Kunio Onizawa
Keyword(s):  
Crack Growth ◽  
Nuclear Power ◽  
Power Plants ◽  
Evaluation Method ◽  
Cyclic Response ◽  
Term Operation ◽  
Steel Pipes ◽  
Wave Forms ◽  
Growth Evaluation ◽  
Large Earthquakes

Japanese nuclear power plants have recently experienced several large earthquakes beyond the previous design basis ground motion. In addition, cracks resulting from long-term operation have been detected in piping lines. Therefore, it is very important to establish a crack growth evaluation method for cracked pipes that are subjected to large seismic cyclic response loading. In our previous study, we proposed an evaluation method for crack growth during large earthquakes through experimental study using small specimens. In the present study, crack growth tests were conducted on pipes with a circumferential through-wall crack, considering large seismic cyclic response loading with complex wave forms. The predicted crack growth values are in good agreement with the experimental results for both stainless and carbon steel pipe specimens and the applicability of the proposed method was confirmed.

scholarly journals Reduction of Multidimensional Image Characteristics Based on Improved KICA

2014 ◽  
Vol 2014 ◽  
pp. 1-6
Author(s):  
Jia Dongyao ◽  
Ai Yanke ◽  
Zou Shengxiong
Keyword(s):  
Independent Component Analysis ◽  
Evaluation Method ◽  
Principal Component ◽  
Characteristic Parameter ◽  
Component Analysis ◽  
Independent Component ◽  
Average Correlation ◽  
Analysis Algorithm ◽  
Correlation Degree ◽  
Kernel Independent Component Analysis

The domestic and overseas studies of redundant multifeatures and noise in dimension reduction are insufficient, and the efficiency and accuracy are low. Dimensionality reduction and optimization of characteristic parameter model based on improved kernel independent component analysis are proposed in this paper; the independent primitives are obtained by KICA (kernel independent component analysis) algorithm to construct an independent group subspace, while using 2DPCA (2D principal component analysis) algorithm to complete the second order related to data and further reduce the dimension in the above method. Meanwhile, the optimization effect evaluation method based on Amari error and average correlation degree is presented in this paper. Comparative simulation experiments show that the Amari error is less than 6%, the average correlation degree is stable at 97% or more, and the parameter optimization method can effectively reduce the dimension of multidimensional characteristic parameters.

scholarly journals Feature Extraction of Ship Radiated Noise Based on Permutation Entropy of the Intrinsic Mode Function with the Highest Energy

2016 ◽  
Author(s):  
Yu-Xing Li ◽  
Ya-An Li ◽  
Zhe Chen ◽  
Xiao Chen
Keyword(s):  
Feature Extraction ◽  
Empirical Mode Decomposition ◽  
Characteristic Parameter ◽  
Intrinsic Mode Function ◽  
Permutation Entropy ◽  
Intrinsic Mode Functions ◽  
Characteristic Parameters ◽  
Radiated Noise ◽  
Mode Function ◽  
Mode Decomposition

In order to solve the problem of feature extraction of underwater acoustic signals in complex ocean environment, a new method for feature extraction from ship radiated noise is presented based on empirical mode decomposition theory and permutation entropy. It analyzes the separability for permutation entropies of the intrinsic mode functions of three types of ship radiated noise signals, and discusses the permutation entropy of the intrinsic mode function with the highest energy. In this study, ship radiated noise signals measured from three types of ships are decomposed into a set of intrinsic mode functions with empirical mode decomposition method. Then, the permutation entropies of all intrinsic mode functions are calculated with appropriate parameters. The permutation entropies are obviously different in the intrinsic mode functions with the highest energy, thus, the permutation entropy of the intrinsic mode function with the highest energy is regarded as a new characteristic parameter to extract the feature of ship radiated noise. After that, the characteristic parameters, namely, the energy difference between high and low frequency, permutation entropy, and multi-scale permutation entropy, are compared with the permutation entropy of the intrinsic mode function with the highest energy. It is discovered that the four characteristic parameters are at the same level for similar ships, however, there are differences in the parameters for different types of ships. The results demonstrate that the permutation entropy of the intrinsic mode function with the highest energy is better in separability as the characteristic parameter than the other three parameters by comparing their fluctuation ranges and the average values of the four characteristic parameters. Hence, the feature of ship radiated noise can be extracted efficiently with the method.

Characteristic Parameter Estimation of AMB Supported Coupled Rotor System

2017 ◽  
Author(s):  
Sampath Kumar Kuppa ◽  
Mohit Lal
Keyword(s):  
Frequency Domain ◽  
Equations Of Motion ◽  
Linear Equations ◽  
Characteristic Parameter ◽  
Estimation Of Parameters ◽  
Characteristic Parameters ◽  
Full Spectrum ◽  
Lagrange’S Equation ◽  
Amb System ◽  
The Time Domain

In this article, a rotor–bearing–coupling system supported by Active Magnetic Bearings (AMBs) is numerically simulated to estimate the characteristic parameters of AMB, residual unbalance, and misalignment parameters. The system is modeled with two rigid massless rotors each having a rigid disc and an AMB at its mid-span, mounted on flexible bearings and connected together with a flexible coupling. Proportional–Differential–Integrator (PID) is used to control the controlling current in AMB. Lagrange’s equation is used to obtain the linear equations of motion (EOMs) of the system. The developed EOM is solved by the fourth order Runga–Kutta method to generate the displacement and current responses. The time domain responses are converted into frequency domain by using Fast Fourier Transform (FFT) and full spectrum analysis is carried out to estimate the characteristic parameters of rotor AMB system. The estimation of parameters is performed based on least squares approach in frequency domain. The proposed methodology is tested against different levels of measurement error and modelling error to check the robustness of the algorithm.

The Study of Vibration Diagnosis Method for GIS

2013 ◽  
Vol 295-298 ◽  
pp. 2429-2432
Author(s):  
Pei Ding ◽  
Zhen Hua Yan ◽  
Fei Yue Ma ◽  
Liang Zhang ◽  
Jun Hao Li ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Field Test ◽  
Detection Method ◽  
Detection System ◽  
Vibration Signal ◽  
Normal Operation ◽  
Vibration Test ◽  
Test Results ◽  
Vibration Detection ◽  
Diagnosis Method

Gas insulated switchgear (GIS) will generate vibration during normal operation for the electromagnetic force. There will be generate abnormal vibration when the contacts are undesirable, the guide rod stressed unevenness. Therefore, it can be effective in fault diagnosis of this machineries through the vibration test of GIS in field. The vibration detection method of GIS equipment in field is studied in this paper, the composition of the vibration detection system is described. The field test has been done using vibration detection system and the test results show that through the vibration signal detected from the GIS equipment, the vibration characteristics of GIS can be clarified and make the fault diagnosis effectively.

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