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14th Annual Australian Gas Turbines Conference
30 – 31 October 2013 Hilton Hotel, Brisbane, Australia
GE LM2500 case study: Online lube oil debris monitoring
as an effective and reliable early detection system for bearing damage in aero-derivative gas turbines
Sjirk VAN DER GOOT, Rick NICOLAAS
1. Sjirk van der Goot, marketing & comunications director, VBR Turbine Partners, Industrieweg Oost 6, 6662 NE Elst (Gld), The Netherlands. Email: [email protected]
2. Rick Nicolaas, customer relations manager, VBR Turbine Partners, Industrieweg Oost 6, 6662 NE Elst (Gld), The Netherlands. Email: [email protected]
ABSTRACT
Aero-derivative gas turbines operate at very high speed and within very narrow tolerances. When bearing damage occurs there is a substantial risk of secondary damage, loss of production and loss of revenue.
Traditional monitoring methods to detect bearing damage (vibration, temperature, chip detectors) signal problems when bearing damage has already progressed to such a degree that secondary damage has occurred. This leaves hardly any time for preventive or corrective actions before engine shutdown.
Online lube oil debris monitoring provides a 24/7/365 assessment of the health status of all main bearings in a gas turbine. When a bearing problem should occur it signals the very start of the damage and it provides trending information about the development of the damage in the very early stages. This information enables gas turbine operators to undertake preventive and corrective actions while the engine is still running and to bring the engine to a scheduled stop before secondary damage has occurred.
This paper describes the principle of operation of an online lube oil debris monitoring system for effective and reliable early detection of bearing damage in aero-derivative gas turbines and a GE LM2500 case study.
Keywords : bearing damage, early detection, oil debris monitoring
1. INTRODUCTION
When bearing damage occurs in aero-derivative gas turbines it is very hard to detect such damage with the traditional monitoring methods (vibration, temperature, chip detectors). When the early stages of bearing damage remain unnoticed and the damage is allowed to progress further to the point that the engine has to come to an unscheduled stop there is a very substantial risk of expensive secondary damage and loss of production and revenue. An effective and reliable early detection system for bearing damage enables gas turbine operators to undertake preventive and corrective actions while the engine is still running and to bring the engine to a scheduled stop before costly secondary damage has occurred.
The content of this article is partly adapted from the white paper “Advanced Oil Debris Monitoring System for Gas Turbine Bearing Predictive Maintenance” (2010) by Richard Dupuis and Duka Kitaljevich.
2. BEARING DAMAGE
2.1 Common causes of bearing damage
The most common causes of bearing damage in aero-derivative gas turbines are:
* Over rolling of debris
* Corrosion pitting
* Dimensional discrepancies
2.2 Start of a bearing damage
For all bearings (both small scale and large scale) the initial damage starts with a series of particle bursts that introduces smaller and bigger (> 200um) metallic particles in the lube oil of the bearing.
2.3 Degree of bearing damage
The degree of bearing damage is proportional to the total quantity and mass of debris detected in the lube oil of the bearing.
2.4 Bearing damage progression rate
The bearing damage progression rate is affected by speed and load on the bearing.
3. EFFECTIVE EARLY DETECTION OF BEARING DAMAGE
3.1 Requirements for effective early detection of bearing damage
The requirements for effective early detection of bearing damage are:
* Identification of the actual start of the damage (earliest detection possible).
* Continuous assessment of the degree and the progression of the damage.
* Reliability of the damage detection (no false alarms, no missed alarms).
4. ONLINE LUBE OIL DEBRIS MONITORING (OLODM)
4.1 Online lube oil debris monitoring - description
An online lube oil debris monitor is a through-flow inductive sensor that installs in-line with the gas turbine lubrication oil system as shown in figure 4.1. The sensor has no moving parts and incorporates a magnetic coil assembly and signal conditioning electronics capable of detecting and categorizing ferro and non-ferro particles by size and type.
Figure 4.1: Online lube oil debris monitor – description
4.2 Online lube oil debris monitoring - principle of operation
The magnetic coil assembly of the through-flow inductive sensor consists of three coils that surround a magnetically and electrically inert section of tubing. The two outside field coils are driven by a high frequency alternating current source such that their respective fields are nominally opposed or cancel each other at a point inside the tube at the center sensor coil. This center sensor operates by monitoring the disturbance to the alternating magnetic field caused by the passage of a particle through the magnetic coil assembly as shown in figure 4.2.
Figure 4.2: Online lube oil debris monitor – principle of operation
As a particle traverses the sensing region it couples with the magnetic field, resulting in a disturbance signal. The magnitude of the disturbance measured as a voltage defines the size of the particle and the phase shift of the disturbance measured as a voltage defies whether the particle is ferromagnetic or non-ferromagnetic. Signal conditioning electronics process the raw signal from the sensor and extract information about the size and type of the metallic debris detected. The sensor electronics perform several functions including: data processing, communication, control and built-in-test.
5. APPLICATION OF OLODM TO AERO-DERIVATIVE GAS TURBINES
5.1 The function of bearings in aero-derivative gas turbine engines
Gas turbine main bearings, as illustrated in figure 5.1, serve the critical function of supporting and controlling the position of the shaft and the associated rotor.
Figure 5.1: Typical aero-derivative gas turbine main bearings
In modern high performance engines, the clearance between the blades, the casing and the stators is kept at a minimum under all operating conditions. It follows that the degradation of the contact surfaces on a bearing can eventually lead to degraded “shaft position control” which in turn can cause very substantial secondary damage within the engine when blade contact takes place.
5.2 OLODM as applied in aero-derivative gas turbines
The application of online lube oil debris monitoring in aero-derivative industrial gas turbines typically includes individual sensors for each accessible bearing sump as shown in figure 5.2.
Figure 5.2: Typical bearing sumps of aero-derivative gas turbines
In this way alarm and warning limits can be established to account for the differences in bearing geometry in the engine and to allow for closer monitoring of damage progression. This configuration has the added advantage of identifying the damaged bearing prior to taking the engine out of service. This allows the operator to proactively plan the necessary maintenance actions by ordering spare parts and scheduling the repair servicing beforehand to minimize downtime, loss of production and loss of revenue.
5.3 OLODM data interpretation and analysis
Online lube oil debris monitoring is based on keeping track of cumulative mass of debris and particle size distribution relative to a warning and a alarm limit as shown in figure 5.3.
Figure 5.3: OLODM data interpretation and analysis
The monitoring system records the accumulation of mass and the size of the particles and triggers a first warning to provide an early indication that a bearing damage has initiated. When the mass accumulates (and therefore the damage progresses) it will trigger a second alarm to provide an indication that the engine should be shut down to prevent secondary damage.
When an engine is healthy the debris accumulation is near zero until a bearing spall is initiated. Following the initiation of the spall the progression rate of the damage is dependent upon load and speed. Typically it will take a few hundred hours of operation from the initiation of the damage to the second alarm level.
When the first warning limit is reached the machine does not need to be shut down but the engine should be monitored more closely to track the damage progression towards the second alarm limit. This first warning limit provides time for the operator to plan for a maintenance and repair shutdown and, in some cases, extend the remaining operating time by reducing the load on the engine.
When the second alarm limit is reached, or shortly thereafter, the engine should be shut down for inspection and servicing. Running the engine beyond the second alarm limit will eventually lead to secondary damage.
5.4 Time to engine failure after bearing damage initiation
Once a spall has been initiated, the primary factors which influence the time remaining to engine failure are the rotational speed and load on the bearing. Depending on the combined severity of speed and load the progression of the bearing damage from initiation to serious failure of the engine ranges from 10’s to 100’s of hours.
5.5 Prediction or early detection of bearing damage
In general, experience with OLODM applications on aero-derivative gas turbines in many fielded and marine applications has revealed that engines operate for many thousands of hours before bearing damage occurs. The occurrence of a bearing damage event cannot be predicted but very early bearing damage can now be reliably detected by OLODM.
6. ONLINE LUBE OIL DEBRIS MONITORING – A GE LM2500 CASE STUDY
6.1 Example of bearing damage in a GE LM2500 aero-derivative gas turbine
An example of a bearing damage event for a LM2500 aero-derivative gas turbine is presented in figure 6.1.
Figure 6.1: LM2500 aero-derivative gas turbine bearing damage event in the C-sump (bearing 5 & 6)
Prior to his event the engine ran for a significant period with virtually no debris being detected by the OLODM system. Once bearing damage occurred, the OLODM provided an early indication of the damage and tracked the progression of the damage. After the initial rapid rise of debris the engine power was reduced to 80% to slow down the progression of the damage in order to reach a scheduled maintenance period. Engine secondary damage was avoided and the damage was limited to the two C-sump bearings (5 & 6) between the gas generator turbine and power turbine. At the moment of engine shutdown the vibration and oil scavenge temperature monitoring did not provide any indication of bearing damage.
7. SUMMARY
Early bearing damage in aero-derivative industrial gas turbines is hard to detect with the traditional monitoring methods (vibration, temperature, chip detectors).
Effective early detection of bearing damage requires:
* Identification of the actual start of the damage (earliest detection possible).
* Continuous assessment of the degree and the progression of the damage.
* Reliability of the damage detection (no false alarms, no missed alarms).
Online lube oil debris monitoring fulfills all these requirements. It provides a warning in the very early development stages of the damage, it provides trending information about the progression of the damage over time and it provides an alarm when the damage has progressed to such a degree that it would be wise to shut down the engine to avoid the risk of secondary damage.
The OLODM information allows operators to proactively plan the necessary maintenance actions by ordering spare parts and scheduling the bearing replacement beforehand to minimize engine downtime, loss of production and loss of revenue.
In short: online lube oil debris monitoring is an effective and reliable early detection system for bearing damage in aero-derivative gas turbines.
REFERENCES
Dupuis, R. and Kitaljevich, D., 2010. Advanced Oil Debris Monitoring System for Gas Turbine Bearing Predictive Maintenance. White paper for GasTOPS Ltd.
