汇报题目：IEEE SENSORS 2019 (The 18^th IEEE SENSORS Conference) 参会报告

汇报时间：2019年11月15日（星期五）10:00

汇报地点：创新港1号巨构3061

汇报人：牛杭

会议名称：The 18^th IEEE SENSORS Conference

会议时间：27-30 October 2019

会议地点：Montreal，Canada

会议简介：

IEEE SENSORS 2019 is intended to provide a forum for research scientists, engineers, and practitioners throughout the world to present their latest research findings, ideas, and applications in the area of sensors and sensing technology. IEEE SENSORS 2019 will include keynote addresses and invited presentations by eminent scientists and engineers. The conference solicits original state-of-the-art contributions as well as review papers.

Topics for IEEE SENSORS 2019 include：

Ÿ Sensor Phenomenology, Modeling and Evaluation

Ÿ Sensor Materials, Processing and Fabrication (including Printing)

Ÿ Chemical, Electrochemical and Gas Sensors

Ÿ Microfluidics and Biosensors

Ÿ Optical Sensors

Ÿ Physical Sensors - Temperature, Mechanical, Magnetic and Others

Ÿ Acoustic and Ultrasonic Sensors

Ÿ Sensor Packaging (including on Flexible Materials

参加论文信息

Title：Fault Diagnosis of Planetary Gearboxes with Ring Gear Strain Signals Measured by Fiber Bragg Gratings

Author：Hang Niu, Xiaodong Zhang, Antonio Marcal,Wenlei Sun, Hongwei Wang

Abstract：Fault diagnosis of planetary gearboxes using acceleration signals is facing difficulties at present. In order to solve the problem, the strain signals of ring gear are adopted in this paper. First, the features of two typical faults are revealed in the outer surface strain and tooth root strain of ring gear respectively. Then, a fiber Bragg grating wavelength demodulation system with a high resolution is established to measure the strain of the ring gear. Finally, the fault diagnosis experiments are carried out. After signal processing, the feature frequency of the run-out error appears in the frequency spectrum of the surface strain signal, and the second derivative of the tooth root strain signal near the crack tooth gets larger amplitude, which shows the effectiveness of the fault diagnosis method based on strain signals.