Đang chuẩn bị nút TẢI XUỐNG, xin hãy chờ
Tải xuống
Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Neural-Network-Based Smart Sensor Framework Operating in a Harsh Environment | EURASIP Journal on Applied Signal Processing 2005 4 558-574 2005 Hindawi Publishing Corporation Neural-Network-Based Smart Sensor Framework Operating in a Harsh Environment Jagdish C. Patra Division of Computer Communications School of Computer Engineering Nanyang Technological University Singapore 639798 Email aspatra@ntu.edu.sg Ee Luang Ang Division of Computer Communications School of Computer Engineering Nanyang Technological University Singapore 639798 Email aselang@ntu.edu.sg Narendra S. Chaudhari Division of Information Systems School of Computer Engineering Nanyang Technological University Singapore 639798 Email asnarendra@ntu.edu.sg Amitabha Das Division of Computer Communications School of Computer Engineering Nanyang Technological University Singapore 639798 Email asadas@ntu.edu.sg Received 11 February 2004 Revised 5 July 2004 Recommended for Publication by John Sorensen We present an artificial neural-network- NN- based smart interface framework for sensors operating in harsh environments. The NN-based sensor can automatically compensate for the nonlinear response characteristics and its nonlinear dependency on the environmental parameters with high accuracy. To show the potential of the proposed NN-based framework we provide results of a smart capacitive pressure sensor CPS operating in a wide temperature range of 0 to 250 C. Through simulated experiments we have shown that the NN-based CPS model is capable of providing pressure readout with a maximum full-scale FS error of only 1.0 over this temperature range. A novel scheme for estimating the ambient temperature from the sensor characteristics itself is proposed. For this purpose a second NN is utilized to estimate the ambient temperature accurately from the knowledge of the offset capacitance of the CPS. A microcontroller-unit- MCU- based implementation scheme is also provided. Keywords and phrases intelligent sensors artificial neural networks autocompensation. 1. INTRODUCTION In many practical .
