Minimizing the nonlinearity error in the static characteristics of a semiconductor thermistor thermometer

1986 ◽  
Vol 29 (8) ◽  
pp. 757-760
Author(s):  
G. A. Lushchaev ◽  
E. I. Fandeev ◽  
Yu. I. Kanyuka ◽  
V. A. Karchkov ◽  
V. A. Skorchenko
Keyword(s):  
Static Characteristics ◽  
Nonlinearity Error ◽  
Semiconductor Thermistor

scholarly journals Application of Sensitivity Analysis to the Correction of Static Characteristics of a Phase Angle Modulator

2011 ◽  
Vol 18 (2) ◽  
pp. 249-260 ◽  
Author(s):  
Ryszard Sroka
Keyword(s):  
Sensitivity Analysis ◽  
Phase Angle ◽  
Static Characteristic ◽  
Real System ◽  
Measuring System ◽  
Static Characteristics ◽  
Nonlinearity Error ◽  
System Sensitivity ◽  
Error Sensitivity ◽  
Error Sensitivity Analysis

Application of Sensitivity Analysis to the Correction of Static Characteristics of a Phase Angle ModulatorThe paper presents definitions and relative measures of the system sensitivity and sensitivity of its errors. The model of a real system and model of an ideal measuring system were introduced. It allows to determine the errors of the system. The paper presents also how to use the error sensitivity analysis carried out on the models of the measuring system to the correction of the nonlinearity error of its static characteristic. The corrective function is determined as a relation between the input variable of the tested system and its chosen parameter. The use of the proposed method has been presented on the example of a phase angle modulator. The obtained results have been compared with the results of analytic calculations. The idea of a phase angle modulator is also presented.

scholarly journals Smoke recognition network based on dynamic characteristics

2020 ◽  
Vol 17 (3) ◽  
pp. 172988142092566
Author(s):  
Dahan Wang ◽  
Sheng Luo ◽  
Li Zhao ◽  
Xiaoming Pan ◽  
Muchou Wang ◽  
...  
Keyword(s):  
Dynamic Characteristics ◽  
State Of The Art ◽  
The State ◽  
Detection Accuracy ◽  
Static Characteristics ◽  
Good Tool ◽  
Early Signal ◽  
Fuzzy Objects ◽  
The Difference ◽  
Smoke Recognition

Fire is a fierce disaster, and smoke is the early signal of fire. Since such features as chrominance, texture, and shape of smoke are very special, a lot of methods based on these features have been developed. But these static characteristics vary widely, so there are some exceptions leading to low detection accuracy. On the other side, the motion of smoke is much more discriminating than the aforementioned features, so a time-domain neural network is proposed to extract its dynamic characteristics. This smoke recognition network has these advantages:(1) extract the spatiotemporal with the 3D filters which work on dynamic and static characteristics synchronously; (2) high accuracy, 87.31% samples being classified rightly, which is the state of the art even in a chaotic environments, and the fuzzy objects for other methods, such as haze, fog, and climbing cars, are distinguished distinctly; (3) high sensitiveness, smoke being detected averagely at the 23rd frame, which is also the state of the art, which is meaningful to alarm early fire as soon as possible; and (4) it is not been based on any hypothesis, which guarantee the method compatible. Finally, a new metric, the difference between the first frame in which smoke is detected and the first frame in which smoke happens, is proposed to compare the algorithms sensitivity in videos. The experiments confirm that the dynamic characteristics are more discriminating than the aforementioned static characteristics, and smoke recognition network is a good tool to extract compound feature.

scholarly journals Dynamic Modeling and Characteristic Analysis of Cantilever Piezoelectric Bimorph

2019 ◽  
Vol 2019 ◽  
pp. 1-9
Author(s):  
Heng Chen ◽  
Jun-shan Wang ◽  
Chao Chen ◽  
Shi-xiang Liu ◽  
Hai-peng Chen
Keyword(s):  
Axial Force ◽  
Dynamic Characteristics ◽  
Dynamic Equations ◽  
Steady State Response ◽  
Static Characteristics ◽  
Piezoelectric Bimorph ◽  
Characteristic Analysis ◽  
Generalized Coordinates ◽  
State Response ◽  
Millisecond Range

The analytical model of an axially precompressed cantilever bimorph is established using the Hamilton’s principle in this study, and the static characteristics are obtained. The dynamic equations of the cantilever bimorph in generalized coordinates are established using a numerical method, and the dynamic characteristics are analyzed. Finally, simulations are performed and experiments are conducted to verify the validity of the theory. The results show that increase of axial force has significant amplification effects on the steady-state response amplitude of the displacement, and it reduces the resonance frequency. The response time is still in the millisecond range under a large axial force, which indicates that the bimorph has excellent dynamic characteristics as an actuator.

scholarly journals Method of Sliding Bearings Static Characteristics Calculation

2014 ◽  
Vol 11 (11) ◽  
pp. 1959-1963 ◽  
Author(s):  
Vladimir Nikolaevich Beschastnyh ◽  
Pavel Viktorovich Bulat
Keyword(s):  
Static Characteristics ◽  
Sliding Bearings

scholarly journals Studies on Carbon Dioxide Power Plant : 1st Report, Experimental Results of Static Characteristics

1980 ◽  
Vol 23 (176) ◽  
pp. 238-246 ◽  
Author(s):  
Koji AKAGAWA ◽  
Terushige FUJII ◽  
Tadashi SAKAGUCHI ◽  
Kosuke KAWABATA ◽  
Keisuke OGURA ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Power Plant ◽  
Experimental Results ◽  
Static Characteristics

Analysis of static characteristics of a bipolar-mode SIT (BSIT)

1982 ◽  
Vol 29 (8) ◽  
pp. 1233-1244 ◽  
Author(s):  
J. Nishizawa ◽  
T. Ohmi ◽  
Hsiao-Liang Chen
Keyword(s):  
Static Characteristics ◽  
Bipolar Mode

scholarly journals Static Characteristics of Robotic Parallel Crank Mechanisms.

1991 ◽  
Vol 57 (543) ◽  
pp. 3698-3703
Author(s):  
Hiroshi TACHIYA ◽  
Akiyoshi CHATANI ◽  
Akihiro HOJO ◽  
Yasuyuki EBATA
Keyword(s):  
Static Characteristics
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