scholarly journals Energy Saving Diagnosis Model of Petrochemical Plant Based on Intelligent Curvelet Support Vector Machine

2021 ◽  
Author(s):  
bin zhao ◽  
dou qin ◽  
Diankui Gao ◽  
lizhi xu
Keyword(s):  
Support Vector Machine ◽  
Energy Saving ◽  
Simulation Analysis ◽  
Diagnostic System ◽  
Curvelet Transform ◽  
Theory Model ◽  
Support Vector ◽  
Petrochemical Plant ◽  
Time Operation ◽  
Saving Effect

Abstract The energy and resources saving has become a major task of petrochemical enterprises, it is necessary to construct the energy saving diagnostic system for understand the real time operation information of petrochemical plant and provide theoretical basis for taking energy saving measures. The energy saving diagnosis process of petrochemical plant based on twin Curvelet support vector machine optimized by hybrid glowworm swarm algorithm is designed. The Curvelet kernel function is constructed based on curvelet transform to establish theory model of twin curvelet support vector machine. In order to improve the prediction precision of the twin curvelet support vector machine, the hybrid glowworm swarm optimization algorithm is constructed based on simulated annealing simulation to optimize the parameters of the twin Curvelet support vector machine. Finally, a petrochemical plant is used as research object to carry out diagnosis simulation analysis, and results showed that the proposed prediction model can effectively improve diagnostic effectiveness of the energy saving effect of petrochemical plant.

Support Vector Machine Based Diagnostic System for Breast Cancer Using Swarm Intelligence

2011 ◽  
Vol 36 (4) ◽  
pp. 2505-2519 ◽  
Author(s):  
Hui-Ling Chen ◽  
Bo Yang ◽  
Gang Wang ◽  
Su-Jing Wang ◽  
Jie Liu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Support Vector Machine ◽  
Swarm Intelligence ◽  
Diagnostic System ◽  
Support Vector

Energy Consumption Analysis on Office Building Ventilation

2012 ◽  
Vol 516-517 ◽  
pp. 1139-1143
Author(s):  
Ke Chun Sun ◽  
Wei Jun Zhang
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Air Conditioning ◽  
Room Temperature ◽  
Simulation Analysis ◽  
Simulation Software ◽  
Energy Simulation ◽  
Office Building ◽  
Saving Effect ◽  
Night Ventilation

Chongqing weather conditions as the representative, energy simulation software DesT-c Chongqing office building energy simulation analysis, simulated natural building under different ventilation conditions at room temperature, the energy consumption of building cooling load and air-conditioning system changes, with an emphasis on energy-saving effect of the night ventilation; The study showed that in Chongqing reasonable use of ventilation reduce building natural room temperature to a certain extent; Sensitive indicators of building air conditioning energy consumption than the heating energy consumption of ventilation was significantly; Night ventilation when the number of ventilators is less than 5 times / h, the energy saving effect is very significant.

scholarly journals Design of Fractal Features-Based Partial Discharge Pattern Recognition using Multi Support Vector Machine Method

2018 ◽  
Vol 159 ◽  
pp. 02048
Author(s):  
Rahayu ◽  
G.T. Anuraga ◽  
H. Prasetia ◽  
Umar Khayam
Keyword(s):  
Pattern Recognition ◽  
Support Vector Machine ◽  
High Voltage ◽  
Partial Discharge ◽  
Diagnostic System ◽  
Diagnostic Technique ◽  
Recognition System ◽  
Support Vector ◽  
Machine Method ◽  
Pattern Recognition System

Partial Discharge (PD) is one of the causes of insulation deteriorisation mode and impacts on the reliability of high voltage equipment. Therefore, PD measurement is used for diagnostic technique of high voltage equipment. Diagnostic output of high voltage equipment contain information about PD type, PD cause, PD location and PD severity. after identification, a proper preventive maintenance pattern can be performed. Therefore PD pattern recognition system is very important on PD diagnostic system to recognize the PD pattern and determine the level of hazard that occurs in specimen object or high voltage equipment‥ In this paper, PD pattern recognition system is designed with fractal geometry approach and support vector machine (SVM) algorithm. The coding and programming of graphical user interface of the application is done. Each PD type and hazard level on various insulating materials (solid, liquid and gas) have the dimensions of the fractal and the lacunarity. The type of PD (void, corona) and its danger level (bad, fair and good) can be identified with the support vector machine (SVM)

A New Method for Fault Detection of Rotating Machines in Motion Control Applications Using PROFIdrive Information and Support Vector Machine Classifier

2020 ◽  
Vol 143 (4) ◽  
Author(s):  
Andre Luis Dias ◽  
Afonso Celso Turcato ◽  
Guilherme Serpa Sestito ◽  
Murilo Silveira Rocha ◽  
Dennis Brandão ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Motion Control ◽  
Diagnostic System ◽  
Operating Conditions ◽  
Support Vector ◽  
Electric Motors ◽  
Rotating Machines ◽  
Worst Case ◽  
Control Applications ◽  
Mechanical Faults

Abstract Electric motors are widely used in the industry. Several studies have proposed methods to detect anomalies in their operation, but always using sensors dedicated to this purpose. In this sense, this work aims to fill gaps in related works presenting a method for the detection of faults in rotating machines driven by electric motors in motion control applications using PROFINET network and PROFIdrive profile. The proposed method does not require any additional or dedicated sensors to provide data to the diagnostic system. Instead, the proposed methodology is based on the analysis of data transmitted in the communication network, which already exists for control purposes. Support vector machine (SVM) is used as a classifier of five different mechanical faults. The results provide that the methodology is feasible and efficient under different machine operating conditions, achieving, in the worst case, 97.78% efficiency.

Engine Fault Diagnostic System Based on Non-Linear Support Vector Machine

2012 ◽  
Vol 229-231 ◽  
pp. 534-537
Author(s):  
Gao Huan Xu ◽  
Jun Xiang Ye
Keyword(s):  
Support Vector Machine ◽  
Fault Diagnosis ◽  
Diagnostic System ◽  
Support Vector ◽  
Linear Support Vector Machine ◽  
Diagnosis System ◽  
The Core ◽  
Wavelet Energy ◽  
Non Linear ◽  
Fault Diagnosis System

The car engine failures in the course of time and place have many possibilities. The engine fault diagnosis system developed in .NET platform. The core of the system make use of noise wavelet energy features and non-linear support vector machine classification. After the experiment, the system has fairly good results.

Application of Energy Consumption Simulation in Envelope Energy-Saving Reconstruction of Existing Building

2011 ◽  
Vol 99-100 ◽  
pp. 644-649
Author(s):  
Yan Qiu Cui ◽  
Rui Han Wei ◽  
Cai Ling Luo ◽  
Ji Kui Miao
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Simulation Analysis ◽  
Building Envelope ◽  
Simulation Software ◽  
Total Load ◽  
Existing Building ◽  
Envelope Reconstruction ◽  
Saving Effect ◽  
Energy Consumption Simulation

In order to quantify energy saving effect of existing building envelope reconstruction, the paper makes the envelope reconstruction project of Jinan Lixia Office Building as a case, uses energy consumption simulation software DeST-C to make dynamic simulation analysis on several aspects such as natural room temperature, cold and hot load before and after reconstruction of experimental building in cold area. After reconstruction, accumulative hot load of building obtained by calculation decreases 33%, accumulative cold load decreases 15.67%, total load decreases 21.04% in the whole year, and the results show energy saving reconstruction effect of existing building envelope is remarkable.

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