1. 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

2. 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

3. Objectives Find feasible concept for bearing CM Specify the requirements for the concept Design reliable testing platform

4. 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

5. 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

6. 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

7. 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 raceb) Two scratches in inner race

8. 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

9. Diagnostic Algorithm Requirements (Ex. 2: Effect of Lubrication) a) Standart lubricationb) 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

10. 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 )

11. Hardware Requirements Communication link Environmental stresses immunity –Electromagnetic interference –Mechanical stresses (vibrations) –Climatic stresses (high temperature, humidity)

12. Developed Pilot System

13. Developed Pilot System (Cont.) DSP based testing platform

14. 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

15. 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

16. Summary Motivation for condition monitoring Embedded analysis concept Requirements –Embedded analysis concept –Diagnostic algorithm –Hardware Developed pilot system