2016 IEEE International Instrumentation and Measurement Technology Conference Proceedings / Institute of Electrical and Electronics Engineers.

Format:

Book

Author/Creator:

Institute of Electrical and Electronics Engineers, author, issuing body.

Language:

English

Subjects (All):

Electronic instruments--Congresses.

Electronic instruments.

Physical Description:

1 online resource

Place of Publication:

Piscataway, NJ : IEEE, 2016.

Summary:

The measurement of the operating deflection shape (ODS) of power transmission belts is of great importance for the fault diagnosis and prognosis of industrial belt drive systems. This paper presents a novel method based on an electrostatic sensor array to measure the ODS of a belt moving both axially and transversely. Finite element simulations are performed to study the sensing characteristics of a strip-shaped electrode and the results reveal that the transverse velocity determines the sensor signal. Construction of the ODS is achieved in the frequency domain using the ODS frequency response function. Experiments conducted on a purpose-built test rig show that the belt vibrates at resonant frequencies that are well separated and identifiable using a peak picking method. The ODSs for different vibration modes exhibit similar deformation patterns and the axial motion of the belt determines that the ODSs propagate along the belt length, rather than stay fixed in space.

Contents:

[Front cover]

[Copyright notice]

Table of Contents

[Front matter]

A Calibration Method for Vehicular Dual-channel Radar Doppler Velocimeter with Janus Configuration

Real-Time Bluetooth Low Energy (BLE) Electrocardiogram Monitoring Device

Signal processing method for flight time measurement of gas ultrasonic flowmeter

Fault Diagnosis Method of Diesel Engine Injector Based on Hierarchical Weighted Permutation Entropy

Area Yield Performance Evaluation of a Nonchemical Weeding Robot in Organic Farming

Inter-Batch Gap Filling Using Compressive Sampling for Low-Cost IoT Vibration Sensors

Multi-State Appliances Identification through a NILM System Based on Convolutional Neural Network

Estimating Parameters of a Sine Wave by the Method of Variable Projection.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

9781467392204

1467392200