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NORPIE 2004 Trondheim, 14 June www.lut.fi Requirements for Embedded Analysis Concept of Bearing Condition Monitoring Petr Spatenka Tuomo Lindh Jero Ahola Jarmo Partanen

NORPIE 2004 Trondheim, 14 June Requirements for Embedded Analysis Concept of Bearing Condition Monitoring Petr Spatenka Tuomo Lindh Jero Ahola

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NORPIE 2004Trondheim, 14 June

www.lut.fi

Requirements for Embedded Analysis Concept of Bearing Condition Monitoring

Petr SpatenkaTuomo Lindh

Jero AholaJarmo Partanen

Introduction

• Maintenance cost is a significant part of total expenses Importance of condition monitoring (CM)

• Up to1/3 of all maintenance cost ineffectively wasted– Unnecessary maintenance– Improperly carried out maintenance

• CM with diagnostics allow maintenance based on current condition

• 40% of failures of el. motors caused by bearings

Objectives

• Find feasible concept for bearing CM• Specify the requirements for the concept• Design reliable testing platform

Industrial Information Infrastructure

• Embedded sensor situated at field level

• Analysis including feature extraction and diagnosis done locally by embedded sensor

• Communication busses at all levels

• Possibility to monitor and control the plant globally through internet

Embedded Analysis Concept Requirements

• System must be easily incorporable into existing infrastructure

• Key issues: reliability and efficiency• Embedded sensor suppose to be a stand-

alone system• Whole CM algorithm has to fit into the

embedded sensor

Diagnostics Algorithm Requirements

• Detect departures from normal behavior– Single-point defects (characterized by unique

spectral components)– Generalized roughness (characterized by

broadband increase in bearing vibrations)• Alarm of future damage if no action is taken• Fault must be detected at time when the machine

can still be safely used

Diagnostic Algorithm Requirements (Ex. 1: Vibration Patterns of 9-ball Bearing)

Case b) might eventually be misclassified as one larger defect

a) One scratch in inner race b) Two scratches in inner race

Diagnostic Algorithm Requirements (Cont.)

• Stochastic nature of defect grow• Parameter changes – mech. damping, speed,

torque load, degree of unbalance, etc.• Flowing fluids (water, steam, etc.) can also induce

vibrations

Diagnostic Algorithm Requirements (Ex. 2: Effect of Lubrication)

a) Standart lubrication b) More grease applied

• Peak due to the inner race fault decreased by more than 70%

• Increase in bearing vibration may indicate malfunction of lubricating system

9-ball bearing with 1 scratch in outer race, and 2 scratches in inner race

Hardware Requirements

• High processing capacity • Minimal power dissipation• Sensitivity

– 12-bit A/D conversion– 32-bit floating-point number representation

• Memory– Sampled data and analysis (SRAM, SDRAM)– History recording (Non-volatile type)

Hardware Requirements

• Communication link• Environmental stresses immunity

– Electromagnetic interference– Mechanical stresses (vibrations)– Climatic stresses (high temperature, humidity)

Developed Pilot System

Developed Pilot System (Cont.)

DSP based testing platform

Developed Pilot System (Cont.)

• Envelope spectrum analysis algorithm implemented

• Tests in laboratory environment approved suitability for CM tasks

• The pilot system is currently in testing run in Lappeenranta water plant, and is controlled remotely via GSM-modem connection

Future Objectives

• Install the developed DSP based platform to industrial plants

• Collect statistically significant number of measurements

• Develop reliable diagnostic algorithm• Implement the algorithm into the DSP platform• Test the embedded sensor in industrial

environment

Summary

• Motivation for condition monitoring• Embedded analysis concept• Requirements

– Embedded analysis concept– Diagnostic algorithm– Hardware

• Developed pilot system