scholarly journals Real-time health status evaluation for electric power equipment based on cloud model

2020 ◽  
Vol 15 (1/2) ◽  
pp. 134
Author(s):  
Wenqing Zhao ◽  
Min Cui
Keyword(s):  
Health Status ◽  
Electric Power ◽  
Real Time ◽  
Cloud Model ◽  
Power Equipment

scholarly journals Low Cycle Fatigue Characteristics of Oxygen-Free Copper for Electric Power Equipment

Materials ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4237
Author(s):  
Takuma Tanaka ◽  
Togo Sugioka ◽  
Tatsuya Kobayashi ◽  
Ikuo Shohji ◽  
Yuya Shimada ◽  
...  
Keyword(s):  
Heat Treatment ◽  
Electric Power ◽  
Stress Amplitude ◽  
Low Cycle Fatigue ◽  
Ebsd Analysis ◽  
Fatigue Properties ◽  
Power Equipment ◽  
Cycle Fatigue ◽  
Fracture Surfaces ◽  
Heat Treated

The effect of heat treatment on tensile and low cycle fatigue properties of the oxygen-free copper for electric power equipment was investigated. The heat treatment at 850 °C for 20 min, which corresponds to the vacuum brazing process, caused the grain growth and relaxation of strain by recrystallization, and thus, the residual stress in the oxygen-free copper was reduced. The tensile strength and 0.2% proof stress were decreased, and elongation was increased by the heat treatment accompanying recrystallization. The plastic strain in the heat-treated specimen was increased compared with that in the untreated specimen under the same stress amplitude condition, and thus, the low cycle fatigue life of the oxygen-free copper was degraded by the heat treatment. Striation was observed in the crack initiation area of the fractured surface in the case of the stress amplitude less than 100 MPa regardless of the presence of the heat treatment. With an increase in the stress amplitude, the river pattern and the quasicleavage fracture were mainly observed in the fracture surfaces of the untreated specimens, and they were observed with striations in the fracture surfaces of the heat-treated ones. The result of the electron backscattered diffraction (EBSD) analysis showed that the grain reference orientation deviation (GROD) map was confirmed to be effective to investigate the fatigue damage degree in the grain by low cycle fatigue. In addition, the EBSD analysis revealed that the grains were deformed, and the GROD value reached approximately 28° in the fractured areas of heat-treated specimens after the low cycle fatigue test.

Using IS to Assess an Electric Power System's Real-Time Stability

2013 ◽  
Vol 28 (4) ◽  
pp. 60-66 ◽  
Author(s):  
Zhao Yang Dong ◽  
Yan Xu ◽  
Pei Zhang ◽  
Kit Po Wong
Keyword(s):  
Electric Power ◽  
Real Time ◽  
Time Stability ◽  
Real Time Stability

Forecasting Model of Short-Term Traffic Flow Based on Cloud Model

2011 ◽  
Vol 94-96 ◽  
pp. 38-42
Author(s):  
Qin Liu ◽  
Jian Min Xu
Keyword(s):  
Real Time ◽  
Traffic Flow ◽  
Cloud Model ◽  
Prediction Method ◽  
Absolute Error ◽  
Short Term ◽  
Guangzhou City ◽  
Time Prediction ◽  
Real Time Traffic ◽  
Absolute Percent Error

In order to improve the prediction precision of the short-term traffic flow, a prediction method of short-term traffic flow based on cloud model was proposed. The traffic flow was fit by cloud model. The history cloud and the present cloud were built by historical traffic flow and present traffic flow. The forecast cloud is produced by both clouds. Then, combining with the volume of the short-term traffic flow of an intersection in Guangzhou City, the model was calculated and simulated through programming. Max Absolute Error (MAE) and Mean Absolute percent Error (MAPE) were used to estimate the effect of prediction. The simulation results indicate that this prediction method is effective and advanced. The change of the historical and real time traffic flow is taken into account in this method. Because the short-term traffic flow is dealt with as a whole, the error of prediction is avoided. The prediction precision and real-time prediction are satisfied.

scholarly journals Development of a software for the control and the supervision of the climatic parameters under greenhouse

2021 ◽  
Vol 234 ◽  
pp. 00062
Author(s):  
Samir Didi ◽  
Abdelkrim El hassini
Keyword(s):  
Water Resources ◽  
Electric Power ◽  
Real Time ◽  
Programming Language ◽  
Automatic Process ◽  
Climatic Parameters ◽  
Graphic Interface ◽  
Greenhouse Crops

To meet the climatic needs of plants, there is a growing interest in the development of methods to automatically and continuously detect the constraints on plants, and to use water and nutrients under greenhouse crops in a rational way. The objective of this work is consecrated to the development of a software for the control and supervision of climatic parameters under greenhouses by an automatic process using LabVIEW. The system carried out makes it possible to measure the various values of the physical sizes resulting from various sensors (temperature, humidity, illumination, content of CO2, moisture of the ground,…). In order to visualize in real time, the evolution of the various climatic parameters, a graphic interface of supervision was developed by using the programming language LabVIEW. The latter makes it possible to integrate functions of control such as the modification of the instructions and the control commands to maintain the conditions adapted to the culture under greenhouse. The installation of such a strategy must take account of the economy of the water resources, nutritive elements and electric power while making it possible to the farmers to increase their productions as well in quantity and in quality.

scholarly journals Traffic sensor health monitoring using spatiotemporal graphical modeling

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Linjiang Wu ◽  
Chao Liu ◽  
Tingting Huang ◽  
Anuj Sharma ◽  
Soumik Sarkar
Keyword(s):  
Health Status ◽  
Real Time ◽  
Sensor Network ◽  
Health Monitoring ◽  
Series Data ◽  
Spatiotemporal Pattern ◽  
Graphical Modeling ◽  
Traffic Sensors ◽  
Wide Range ◽  
Sensor Health

Accurate traffic sensor data is essential for traffic operation management systems and acquisition of real-time traffic surveillance data depends heavily on the reliability of the traffic sensors (e.g., wide range detector, automatic traffic recorder). Therefore, detecting the health status of the sensors in a traffic sensor network is critical for the departments of transportation as well as other public and private entities, especially in the circumstances where real-time decision is required. With the purpose of efficiently determining the sensor health status and identifying the failed sensor(s) in a timely manner, this paper proposes a graphical modeling approach called spatiotemporal pattern network (STPN). Traffic speed and volume measurement sensors are used in this paper to formulate and analyze the proposed sensor health monitoring system and historical time-series data from a network of traffic sensors on the Interstate 35 (I-35) within the state of Iowa is used for validation. Based on the validation results, we demonstrate that the proposed approach can: (i) extract spatiotemporal dependencies among the different sensors which leads to an efficient graphical representation of the sensor network in the information space, and (ii) distinguish and quantify a sensor issue by leveraging the extracted spatiotemporal relationship of the candidate sensor(s) to the other sensors in the network.

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