Effect of the measured voltage waveform on the readings of a diode peak voltmeter

1960 ◽  
Vol 1 (6) ◽  
pp. 702-706
Author(s):  
A. M. Fedorov
2020 ◽  
Vol 34 (4) ◽  
pp. 1-6
Author(s):  
Jong-Min Lim ◽  
Chung-Seog Choi

In this study, the authors measured voltage and current waveforms in real time during a serial arc discharge. The analysis results of the arc discharge radiation patterns exhibited intermittent discharge, arc growth, creation of a heat generating area, occurrence of plume, and formation of a red heat area, which proceeded in that order. When the serial arc discharge was introduced, the current and voltage waveforms exhibited periodicity as sine waves. It was also observed that a restriking transient voltage occurred when the waveform changed from positive (+) to negative (-) and vice versa. When the discharge proceeded, the amount of heat generated for 1 s and 600 s was approximately 0.317 mJ, and 190 mJ, respectively. The duration of the short circuit was approximately 1.66 ms, and in the case of the voltage waveform, it was evident that the electric potential increased to 49.9 V in the same cycle. Furthermore, when the discharge proceeded, the effective value (RMS value) of the current was approximately 1.72 A with a maximum current of approximately 2.53 A, whereas the effective value of the voltage was approximately 42.8 V with a maximum of approximately 208 V.


2012 ◽  
Vol 132 (6) ◽  
pp. 588-596
Author(s):  
Tadashi Naitoh ◽  
Keiki Takeda ◽  
Atsushi Toyama ◽  
Tatsuhiko Maeda

2014 ◽  
Vol E97.C (3) ◽  
pp. 194-197 ◽  
Author(s):  
Yoshitaka TAKAHASHI ◽  
Hiroshi SHIMADA ◽  
Masaaki MAEZAWA ◽  
Yoshinao MIZUGAKI

2020 ◽  
Vol 14 (2) ◽  
pp. 205-220
Author(s):  
Yuxiu Jiang ◽  
Xiaohuan Zhao

Background: The working state of electronic accelerator pedal directly affects the safety of vehicles and drivers. Effective fault detection and judgment for the working state of the accelerator pedal can prevent accidents. Methods: Aiming at different working conditions of electronic accelerator pedal, this paper used PNN and BP diagnosis model to detect the state of electronic accelerator pedal according to the principle and characteristics of PNN and BP neural network. The fault diagnosis test experiment of electronic accelerator pedal was carried out to get the data acquisition. Results: After the patents for electronic accelerator pedals are queried and used, the first measured voltage, the upper limit of first voltage, the first voltage lower limit, the second measured voltage, the upper limit of second voltage and the second voltage lower limit are tested to build up the data samples. Then the PNN and BP fault diagnosis models of electronic accelerator pedal are established. Six fault samples are defined through the design of electronic accelerator pedal fault classifier and the fault diagnosis processes are executed to test. Conclusion: The fault diagnosis results were analyzed and the comparisons between the PNN and the BP research results show that BP neural network is an effective method for fault detection of electronic throttle pedal, which is obviously superior to PNN neural network based on the experiment data.


2013 ◽  
Vol 392 ◽  
pp. 409-412
Author(s):  
Xian Bin Dai ◽  
Xiao Hua Yuan ◽  
Wei Du

This paper introduces the working principle of the research of simulation in the main circuit of Static Var Generator based on Cascade H-Bride and takes the three-phase Static Var Generator based on cascade H-Bride with rated capacity 10kVar,rated voltage 380V for example to proceed the MATLAB simulation. The research shows that the more amount of cascade H-Bride, the more number of output voltage levels in the main circuit of Static Var Generator, the smaller value of voltage waveform distortion factor, and the less harmonic content be inject in electric network, which improves power index.


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