scholarly journals Aircraft Aerodynamic Parameter Detection Using Micro Hot-Film Flow Sensor Array and BP Neural Network Identification

Sensors ◽  
2012 ◽  
Vol 12 (8) ◽  
pp. 10920-10929 ◽  
Author(s):  
Ruiyi Que ◽  
Rong Zhu
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Sensor Array ◽  
Film Flow ◽  
Flow Sensor ◽  
Aerodynamic Parameter ◽  
Network Identification ◽  
Hot Film

Study on the Dynamic Characteristics of Hot-Film Flow Sensor Based on the Sampling Air Channel

2014 ◽  
Vol 494-495 ◽  
pp. 197-200 ◽  
Author(s):  
Wei Liu ◽  
Li Feng Zhao
Keyword(s):  
Dynamic Response ◽  
Film Flow ◽  
Coupling Model ◽  
Response Characteristic ◽  
Flow Sensor ◽  
Intake Manifold ◽  
Film Sensor ◽  
Response Characteristics ◽  
Dynamic Response Characteristics ◽  
Hot Film

The hot-film flow sensors accurately measure the intake flow of engine. The air flow in the engine intake manifold is typical unsteady flow whose flow velocity changes remarkably. Therefore, the flow sensor should have a faster dynamic response characteristic. A thermosetting coupling model of a hot-film sensor was established based on CFD which is used to simulate dynamic response characteristics; the temperature field of the hot-film flow sensor probe was simulated. In addition, the dynamic response characteristics of the sensor simulated using the step pulse, and tested the dynamic response characteristics based on flow test equipment.

Ant Colony Algorithm and Application in Inspection of Concrete Structure Defects

2012 ◽  
Vol 204-208 ◽  
pp. 3201-3205
Author(s):  
Wei Hua Zheng ◽  
Zong Hua Wang
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Ant Colony Algorithm ◽  
Bp Algorithm ◽  
Ant Colony ◽  
Ant Colony Optimization Algorithm ◽  
Structure Defects ◽  
Network Training ◽  
Network Method ◽  
Network Identification

BP neural network detecting concrete defect, convergence is slower and accuracy is not high. In order to overcome the defect of BP algorithm, using a combination of Ant Colony optimization algorithm and BP neural network method, a mathematical model of Ant Colony neural network was established, enables Ant Colony neural network training, and verify the validity of the method. And concluded: using ant Colony neural network identification of concrete defects, the identification of the location more effective than on size.

Aircraft flight parameter detection based on a neural network using multiple hot-film flow speed sensors

2007 ◽  
Vol 16 (4) ◽  
pp. 1239-1245 ◽  
Author(s):  
Haiping Fei ◽  
Rong Zhu ◽  
Zhaoying Zhou ◽  
Jindong Wang
Keyword(s):  
Neural Network ◽  
Film Flow ◽  
Flow Speed ◽  
Aircraft Flight ◽  
Hot Film

scholarly journals A BP Neural Network Method for Grade Classification of Loose Damage in Semirigid Pavement Bases

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Bei Zhang ◽  
Jianyang Liu ◽  
Yanhui Zhong ◽  
Xiaolong Li ◽  
Meimei Hao ◽  
...  
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Electromagnetic Waves ◽  
Fdtd Method ◽  
Simulated Data ◽  
Radar Data ◽  
Base Layer ◽  
Identification Method ◽  
Network Identification ◽  
Base Course

This study aims to address the problem that loose damage of the pavement base course cannot currently be quantitatively identified, and thus the classification and recognition of the extent of looseness mainly rely on empirical judgments. Based on the finite-difference time-domain (FDTD) method, a backpropagation (BP) neural network identification method for loose damage of a semirigid base is presented. The FDTD method is used to simulate a semirigid base road model numerically with different degrees of looseness, and the eigenvalue parameters for recognition of the presence and extent of the looseness of the base layer are obtained. Then, a BP neural network identification method is used to classify and identify the loose damage of the base course. The results show that the classification and recognition of simulated electromagnetic waves have an accuracy of over 90%; the classification and recognition of radar data from an actual project have a recognition accuracy of over 80%. The good agreement between the classification and recognition results for the simulated data and measured data verifies the feasibility of the classification and recognition method, which can provide a new method for the use of ground-penetrating radar to detect loose damage and the extent of looseness in the base.

Solvent-free fabrication of biodegradable hot-film flow sensor for noninvasive respiratory monitoring

2017 ◽  
Vol 50 (21) ◽  
pp. 215401 ◽  
Author(s):  
Toan Dinh ◽  
Hoang-Phuong Phan ◽  
Tuan-Khoa Nguyen ◽  
Afzaal Qamar ◽  
Peter Woodfield ◽  
...  
Keyword(s):  
Film Flow ◽  
Solvent Free ◽  
Flow Sensor ◽  
Respiratory Monitoring ◽  
Hot Film

scholarly journals Application technology of hot film flow sensor in intelligent electronic cigarette

2020 ◽  
Vol 1653 ◽  
pp. 012038
Author(s):  
Bin Zhang ◽  
Pengfei Ma ◽  
Xiaoyin Zheng ◽  
Guocai Qiu ◽  
xinzhun Chen
Keyword(s):  
Film Flow ◽  
Electronic Cigarette ◽  
Flow Sensor ◽  
Application Technology ◽  
Hot Film
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