Tribo-Condition Monitoring for optimized performance and longer service life
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1 Tribo-Condition Monitoring for optimized performance and longer service life Pär Marklund Division of Machine Elements Luleå University of Technology, Sweden
2 Introduction - Condition Monitoring * Condition monitoring is the process of determining the condition of machinery while in operation. The key to a successful condition monitoring includes: Knowing what to listen for How to interpret it When to put this knowledge to use (What to measure) (How to interpret it) (What to do with the informa5on) *
3 Condition Monitoring - what to measure Different aims with the condition monitoring: Detecting faults and problems with the system Monitoring performance Detecting faults, e.g.: Wear detection Detection of malfunctions in electrical systems Monitor performance, e.g.: Speed Rpm Some sensor can both monitor performance and detect faults Temperature Vibration
4 Condition Monitoring - how to interpret it Different measurements - Different sensors A combination of sensors = Better understanding E.g. The temperature in itself does not say much about a machine, but in combination with operational parameters and other fault detecting systems it might become a useful indicator of both operation conditions, faults and performance. Today still technicians are needed to interpret and take decisions + But what about tomorrow?
5 Condition Monitoring - what to do with the information Better operation: If it runs to fast slow down If it starts to break reduce the load Better Maintenance Connect Condition Monitoring to the Maintenance strategy If a machine is producing something of high value, it might be worth a higher risk of machine failure to keep it running at full speed??
6 Different types of maintenance Fault based Corrective maintenance Mileage based Preventive maintenance Time based Preventive maintenance Condition based Predictive maintenance Ø Fault indicators Vibrations Temperature change Ø Tribological indicators Viscosity change Contamination Additive consumption Acoustic emission
7 An example as motivation for condition based maintenance Rolling element bearings are the most common way to support rotating shafts. Bearings are normally dimensioned according to the L10 life model, meaning that: 10% of the bearings will fail prematurely Most bearings will outlive the calculated service life Some bearings live MUCH longer than expected life Most bearings fail because Someone does something * and this does not follow the L10 life model Without Condition Monitoring: Most bearings are over-dimensioned and are working perfectly when scrapped (e.g. time based maintenance) The new replacements might have a shorter life expectancy than the replaced unit Other bearings might fail before service *Brian Murray, SKF
8 Tribo-Condition Monitoring (TriCoMo) Tribology is extremely important to optimize a mechanical system and minimize the risk of failure. Condition monitoring of tribological properties è Early warning of faults Possibility to avoid faults Example: A bearing that operates under poor lubrica5on TriCoMo Re-lubrica5on No faults are developed. Con5nuous opera5on! Tradi5onal CoMo Small faults are detected Re-lubricate or replace, but already broken
9 Direct Measurements To measure what you want to know Temperature Load * Torque * Film thickness * Viscosity * Additive content * Friction force * Lubricant contamination Example: If you want to know how cold it is outside You simply measure the temperature! *In many cases difficult/expensive to measure directly in the machine under operation
10 Indirect measurements To measure something that indicates what you want to know New and types of sensors Tribology research Measurements Measurements Measurements Transfer func5on or Simula5on model Requested output
11 Indirect measurements To measure something that indicates what you want to know New and types of sensors Machine learning or Intelligence Measurements Measurements Measurements Transfer func5on or Simula5on model Requested output
12 Indirect measurements To measure something that indicates what you want to know Measure Indirect measure Temperature Vibrations Viscosity, film thickness, additive function, ageing Wear, pitting, poor operation Acoustic Emissions (High frequency vibrations) Poor lubrication, contamination
13 Sensor Positioning Facts: You need a signal that contains information Better signal = Better analysis = Better results Often overconfidence in various signal processing techniques Methods claims to find faults in signals where the information is not present An acous5c emission signal measured here will not contain any informa5on about this bearing... regardless analysis method
14 Sensor Positioning A good signal is essential for successful condition monitoring, regardless type of signal The sensor position Close to the monitored contact/component Strong signal Limited noise An acous5c emission signal measured here will not contain any informa5on about this bearing... regardless analysis method
15 Sensor Positioning Unfortunately condition monitoring is often an add-on to existing machines and not fully integrated Expensive installation Sensor position far from the point of interest Low signal to noise ratio Poor starting point for Signal processing Signal analysis One supplier of the machine and another supplier of the CoMo system
16 Integrated sensors A vision of how to measure in the optimum position I need more grease! I m unaligned I feel fine but the rest of the machine needs maintenance I m running at 1434 rpm The load is 455 N I m 75ºC My Remaining Useful Life is revolu5ons Remote diagnos5cs Planning of service Prognosis Sta5s5cs Safety and reliability
17 The future for TriCoMo! The society is moving towards: Predictive maintenance Industry 4.0 Internet of Things Autonomous vehicles TriCoMo is needed to enable all these trends to develop further There is today a lack of knowledge and a huge gap to fill in this area between electronics/ sensors, tribology, machine learning and maintenance
18 Short examples of TriCoMo Example 1: New types of sensors Acoustic Emission Example 2: New analysis methods for conventional sensors Lubricant ageing estimation from temperature log
19 Example 1: New types of sensors Acoustic Emission (AE) AE has been around for decades but is still not very common in industry Used frequency ranges by researchers which used the term Emission Figur 2.3, page 14: Schnabel, S., High Frequency Wave Emission Caused by a Single Elasto-hydrodynamically Lubricated Contact: Fundamental Sources and Principles, PhD Thesis, Luleå University of Technology, 2016
20 Example 1: New types of sensors Acoustic Emission (AE) Differences compared to Vibration CoMo Higher demands on sensors and signal acquisition system Huge amounts of data Higher damping of the signal è Sensor position is extremely important!
21 Example 1: New types of sensors Acoustic Emission (AE) Advantages and disadvantages compared to Vibration CoMo Higher demands on sensors and signal acquisition system Huge amounts of data Higher damping of the signal è Sensor position is extremely important! Indication of the tribology in the contact and therefore an AE Vibra5ons earlier warning Vs. Contaminated grease Schnabel, S., Marklund, P., Larsson, R., Study of the short term effect of Fe 3 O 4 par@cles in rolling element bearings. Proc. of MechEng, Part J: Journal of Engineering Tribology, 228(10): , September 2014
22 Example 2: New analysis methods for conventional sensors - Lubricant ageing estimation from temperature log Example: To be able to precisely control the torque transfer through a wet clutch you need to Measure the axial load and know the friction coefficient, or Measure the output, i.e. the torque Friction coefficient will change during ageing L Solution: Investigate friction change due to ageing COF = f (temp, time) Log temperature during operation Simulate aged friction coefficient Compensate for friction change in control software Berglund, K., Marklund, P. et.al., Predic@ng boundary fric@on of ageing limited slip differen@al, Proc. of the IMecE, Part D: Journal of Automobile Engineering. Vol 230, Issue 12, pp
23 Conclusions Tribo- Condition Monitoring TriCoMo can give earlier warnings compared to traditional condition monitoring Sensor position is extremely important In TriCoMo even more than for e.g. vibration CoMo TriCoMo often require indirect measurements and defined transfer functions or simulations in order to measure the tribology in the contact.
24 Acknowledgements And all my colleagues at the division of Machine Elements, Luleå University of Technology
25 Questions?
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