scholarly journals Stacked Auto-Encoder Modeling of an Ultra-Supercritical Boiler-Turbine System

Energies ◽  
2019 ◽  
Vol 12 (21) ◽  
pp. 4035 ◽  
Author(s):  
Zhang ◽  
Liu ◽  
Kong ◽  
Lee
Keyword(s):  
Power Plants ◽  
High Efficiency ◽  
Simulation Analysis ◽  
Measurement Data ◽  
Time Measurement ◽  
Multivariable System ◽  
Training Process ◽  
Identification Methods ◽  
Real Time Measurement ◽  
Multilayer Perceptron Network

The ultra-supercritical (USC) coal-fired boiler-turbine unit has been widely used in modern power plants due to its high efficiency and low emissions. Since it is a typical multivariable system with large inertia, severe nonlinearity, and strong coupling, building an accurate model of the system using traditional identification methods are almost impossible. In this paper, a deep neural network framework using stacked auto-encoders (SAEs) is presented as an effective way to model the USC unit. In the training process of SAE, maximum correntropy is chosen as the loss function, since it can effectively alleviate the influence of the outliers existing in USC unit data. The SAE model is trained and validated using the real-time measurement data generated in the USC unit, and then compared with the traditional multilayer perceptron network. The results show that SAE has superiority both in forecasting the dynamic behavior as well as eliminating the influence of outliers. Therefore, it can be applicable for the simulation analysis of a 1000 MW USC unit.

Study on the Distribution Line Condition Monitoring Method Based on Real-Time Measurement Data

2012 ◽  
Vol 614-615 ◽  
pp. 911-915
Author(s):  
Jia Wen Liang ◽  
Xin Tao Wang ◽  
Li Shi ◽  
Jia Yang
Keyword(s):  
Real Time ◽  
Online Monitoring ◽  
Measurement Data ◽  
Time Measurement ◽  
Maintenance Cost ◽  
Monitoring Method ◽  
Real Time Measurement ◽  
Distribution Line ◽  
Line Resistance ◽  
Resistance Value

To develop an economic and effective online monitoring method is necessary as the normal running of distribution line is critical to ensure the reliability of power system. And the distribution line state monitoring technology improved steadily nowadays, the monitoring of operating status can be achieved by using online monitoring devices. However, its installation and maintenance cost a lot, it is poor in economy. A new method, in which line resistance was selected as a reference quantity, was proposed in this article. The monitoring of distribution line running status can be realized by analyzing the line resistance value that calculated by real-time measurement data. The method improves the utilization of information system and requires no additional investment costs. And the example verified the validity of the method; it is possible to learn about the operational status timely through analyzing the changes in line resistance value.

scholarly journals DISTRIBUTED REAL-TIME MEASUREMENT SYSTEMUSING TIME-TRIGGERED NETWORK APPROACH

2014 ◽  
pp. 22-29
Author(s):  
Piotr Bilski ◽  
Wiesław Winiecki
Keyword(s):  
Laboratory Test ◽  
Real Time ◽  
Virtual Instrument ◽  
Data Transfer ◽  
Measurement Data ◽  
Time Measurement ◽  
Network Approach ◽  
Future Prospects ◽  
Control Measurement ◽  
Real Time Measurement

The paper presents results of the examination of the deterministic network used by the distributed virtual instrument. Software technology applied to control measurement data transfer between the real-time components was presented. Configuration of the laboratory test stand, designed to examine deterministic network is described. Results of the research are presented and conclusions, as well as future prospects iterated.

scholarly journals Study on the Calculation of Cable Emergency Current Capacity Based on Real-time Measurement Data

2020 ◽  
Vol 1457 ◽  
pp. 012001
Author(s):  
P Y Wang ◽  
Z F Xu ◽  
T Xu ◽  
H R Li ◽  
L R Lai ◽  
...  
Keyword(s):  
Real Time ◽  
Measurement Data ◽  
Time Measurement ◽  
Real Time Measurement

Real-Time Measurement Method of Rail Vehicle Wheel Flange Wear Using Inductive and Temperature Sensors

2021 ◽  
Author(s):  
James Ndodana Njaji ◽  
Celestin Nkundineza
Keyword(s):  
Real Time ◽  
Measurement Data ◽  
Time Measurement ◽  
Displacement Sensor ◽  
Effect Of Temperature ◽  
Time Data ◽  
The Real ◽  
Railway Systems ◽  
Real Time Measurement ◽  
Rail Vehicles

Abstract Railway systems are expected to be in their most safe state ensuring safe operations of trains. The contact between rail and wheel is one of the most fundamental aspects in railway systems. Therefore, instruments and measurement systems that give critical information about operating railway systems are expected to work efficiently and effectively. Previous research on using inductive displacement sensor for wheel flange wear measurement has focused on the light rail vehicles, and considered effect of temperature negligible, as opposed to mainline vehicle where the wheel temperature variation is large. Also, the filtering of noises has been done using non-real time data. This paper focuses on the real-time measurement system for freight vehicle wheel flange wear by fusing measurement data from inductive displacement and thermocouple sensors, and filtering of the noises. A CAD model of the sensor support fixed on the bogie frame is presented. Several experimental measurements are carried in the lab on a moving disk heated at different temperatures. Then multiple regression analysis of the data is carried out to come up with the measurement model equation. This equation is used for calibration in LabVIEW program interfaced with data acquisition system for real time measurement. Experimental results show effect of temperature on the inductive sensor measurement data. This effect is taken into account to quantify the clearance between the disk and the sensor tip. The precision and accuracy are determined to be 0.06 Volts and 0.03 mm, respectively. This system is expected to enhance the real-time and/or online monitoring of the safety of rail vehicles. Also, it can be integrated with Automatic Train Protection (ATP) and the detection of track lateral irregularities from the wheel flange real time measurement data.

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