The term monitoring is used in the technical literature also in connection with the control of
aeroengines. There is a confusing multitude of modifications and additions. As far as possible it should be tried to highlight
its features. The control as condition
monitoring, respectively trend
monitoring, takes place also under the terms `engine monitoring', `engine condition monitoring' and `engine health monitoring'. It uses the
operation data of the aeroengine to identify in time symptoms of
failures, drop of efficiency (deterioration) or
wear. The whole frame in which a monitoring is applied, stands in connection with the term `managing'. To
this belongs `engine health management (EHM, Ill. 25.1-7) or `propulsion health management' (PHM,
`Trend monitoring' has in civil and military operation a key role. It is of high importance for the so called `condition based maintenance' (`on condition maintenance', Ill 21-1). Is the control of the systems, for certain problems/failures concerned, we speak rather about `health monitoring'. Monitoring can serve different purposes:
For the aeroenine monitoring different methods are used, coordinated for the purpose (Ill. 25.1-3).
Ill. 25.1-1 (Lit. 25.1-1): The left diagram shows schematically the connection between reliability and costs. Expecially in the civil sector the operator demands a high reliability at the possible lowest costs through the foreseen operation time. These rise, depending from the claim at the reliability. This is composed as follows:
For problems and failures, sufficient reliability acts as „problem costs“. The highest effect is observed at the beginning of an improvement of the reliability. The higher already the reliability, the lower is the cost advantage that can be expected. Typical cost intense problems are:
The reliability is operator specific caused by influences like
From the cooperation of „problem costs” and costs of the reliability the curve of the
„total costs“ arises. It passes at a certain
cost optimal reliability a cost minimum and is usually pursued.
The optimization of these influences enables to maintain or even improve the reliability during sinking costs. Such an approach must occur carefully in an iterative process, because of the complexity of the influences and reciprocative influencing of each other.
For an optimal cost/reliability relationship the following activities are of special interest:
The diagramm right shows the costs per opreation hour for aeroengines of the same type but
significant different introduction dates. It can be seen, how the operator benefits from a markedly
lower cost level of later introduced aeroengine
The rise of costs is especially steep during introduction of a new aeroengine type. After several years (here about four years) a maximum,in which the weak points are fully effective, is reached. Here remedies are not yet sufficient introduced. After once more several years, the curve levels. This shows, that a certain reliability optimum was reached with the remedies. From these improvements obviously benefit the later aeroengine modifications. Also profits the cost trend from the whole fleet of new and old aeroengine versions.
Ill. 25.1-2 (Lit. 25.1-3): These informations refer to the
proving of a monitor system of a big
The gas temperature crucial influences the lifetime of the hot parts. It enables conclusions at the condition of the aeroengine. With worsened efficiencies (deterioration, volume 2, Ill. 7.0-2) the gas temperatur rises at constant power.
Usually it is limited on the basis of displays from exhaust gas temperature at the cockpit instruments. Maximimum limiting temperatures must only be expected at maximum power, i.e. during start. The operating stays most the time below these temperature limits. With this, the chance to indicate failures with the passing of temperature limits at the cockpit instruments, is rather low (diagram left).
An information to the maintenance does not take place before the pilot recognizes a problem at maximum power or markedly power drop.
The use of electronic memories enables the digital recording of all relevant data from the flight aud the aeroengines. To these belong besides further gas temperatures
These data are only analyzed with the use of computers
at once in the flight (real time) and
afterwards on ground (during maintenance). So
beginning problems can better be identified. This is also true
for the information of the pilot. This increases the flight safety markedly.
To this here some examples from the testing of the monitoring system:
The system enabled many further important findings:
A long time analysis enables the safe and cost
effective exchange of components. Especally
concerned are rotor disks, which reached their lifetime (diagram right). Thereby, the
mission specific operation profile is of especial inportance for the
With suitable algorithms so also a monitoring of the turbine blading with regard to thermal fatigue and/or oxidation is possible.
Ill. 25.1-3(Lit. 25.1-4): Engine condition
monitoring can take place task specific in different
ways (chart below).
Monitoring of aeroengines during flight: It serves the identification and analysis of problems as well as the determination of the component life time. For problem analysis, the data are today transferred by broadcasting for the analysis by computer and/or evaluation on ground.
Usually for the analysis serves a continual recording of parameter data, we speak from „gas path analysis”. These document the aerodynamic and thermodynamic behavior (e.g., compressor behavior/condition).
A monitoring in „real time“ can be registrated by the pilot with the help of the cockpit instruments and, if necessary,by warning signals.
Also the displays of electrical magnetic chip detektors (Ill. 22.3.4-7), which control the oil circuit continuously for magnetic particles, can be couted to the monitoring processes during flight.
The monitoring of aeroengines takes place in time intervals at the ground, often directly after landing. the stored data can be called through a line or an integrated memory/storage or from the removed memory.
Also other processes can be counted to the monitoring of an aeroengine. They stay in connection with the monitoring of deteriorations or the review of failures („health monitoring”, Ill. 25.1-6 and Ill. 25.1-11). The progression of failures can only be controlled for sufficient slow failure mechanisms.
Test runs on the ground in the as mounted condition mostly serve the problem analysis or
function proofs. To these belong seal runs, which are used to test the systems of oil and fuel for leaks (Ill.
19.2-2.2 and Ill. 23.4.1-9).
Checks in the framework of maintenance play an important roll in the aeroengine monitoring. Mostly used are controls of the filters and sieves in the systems of oil and fuel (Ill. 22.2.2-2.1 and Ill. 18.104.22.168-2). Thereby the control for deposits respectively chips (Ill. 22.3.4-8) is for the condition of the concerned systems an extremely significant tool.
To this belongs also the monitoring of the lubrication oil (Ill. 22.3.4-1) for aging and signs of problems in the oil system. For this also magnetic chip detectors, respectively magnetic plugs (Ill. 22.214.171.124-4 and Ill. 22.3.4-8) are used.
With these, failures on components of magnetic materials can be discovered or identified. These are primarily anti friction bearings and gear wheels.
Ill. 25.1-4 (Lit.25.1-2 and 25.1-5 ): The
scheme of a monitoring system derives from the 90s
(ground based engine monitoring). It provides monitoring data for the aeroengines of
a large two engined airliner type. During flight,
already a primarily analysis of the data takes place. For this a printout was automatically read from an OCR program. These data
served a later analysis at the ground. In newer systems, data are transferred from the flight by
radio for the analysis on ground (Ill. 25.1-3). If necessary feedbacks take place.
The aeroengine data from the fleet of the operator are collected and secured. They serve the analysis under the aspects of reliability, safety and effectivity/cost minimization. This optimization potential is especially interesting for the logistics. For example the „story of the aeroengine“ serves the plannings of the OEM. Concerned are plannings of overhaul, occupancy of the test rigs and work (overhaul, spare parts, repair).
The measurement data of the acceptance run after the overhaul will be compared with those already available. So measurements at the test rig and efficiencies of the modules can be evaluated.
Monitoring data also serve the daily central problem analysis (trouble shooting).
The chart below shows a military monitoring system. Here the measurement data (23 analogous continuous + 5 temporary) enter the electronic control unit of the fighter aeroengine. Additionally data from outside the aeroengine (anti icing, lubrication) and from the avionics are available for analysis. These are used for the following purposes.
First experiences in the 80s, to introduce the system, showed the following advantages:
Flight: The safety, especially for single engined fighters could be markedly improved. This primarily was owned to early warning for the pilot during problems in the oil system. So he could react at the situation more targeted. The experiences show, that false alarm signals could be reduced by a power of ten (chapter 19.2.1).
Analysis of problems/failures: The statements got more certain. That is concerned besides mechanical problems (e.g., at pumps and actuating systems) especially for elektronic (e.g., sensors/probes, ignition devices, control units). For this the analysis program is of crucial importance (Ill. 19.2.1-12).
Advantages for the OEM:
With the help of the data it was possible for him, to identify operation problems and to solve those with targeted measures.
Ill. 25.1-5.1 (Lit. 25.1-5): Accident statistics (1998) in the civil aviation show, that in 12 % of all cases, problems with the propulsoin have been involved. About 6 % of these could be traced back at causative mechanical problems and maintenance faults of the propulsion (volume 1, Ill. 2-7 and Ill. 2-9). 18 % of the 12% share of the aeroengines have been connected with fragment exit (uncontained). At 15 % the aeroengine problem was combined with an unsuitable reaction of the pilot.
In many cases precedes the disk failure a slow cyclic crack
growth (Ill. 24-2 and volume 3, Ill. 12.2-1).
There are absolutely cases, which could be prevented with a continuous monitoring of the aeroengine for failure relevant deviations (health monitoring). Thereby it is important, to indicate first signs sufficient early before a dangerous failing . For this offer itself the data of the condition monitoring (Ill. 25.1-3 and Ill. 25.1-4).
At the health monitoring, false alarms are especially problematic, because the trigger thresholds, due to the recognizability and with this sufficient safety, should be adjusted as low as possible. So the probability of a false alarm increases by uncritical signals. The picture shows the model (Ill. 25.1-6) of a „health monitoring” systems, that at this time obviously was in the development. From this, it is expected the avoidance of the mentioned problems and a sufficient certain realization chance. This model is distributed on three levels.
In the most cases, fractures of disks preceded by a relatively slow cyclic crack growth. This crack acts at the unbalance. So it is obvious to use the effect as warning signal (Ill. 25.1-5.2). This takes place by vibrations analysis (Ill. 25.2.1-6) of the signals from the acceleration probes (Ill. 25.2.1-5). Most sensitive are sensors/probes, positiooned directly at the outer ring of the bearing. This method is already used successful at industrial gas turbines and cyclic spin test rigs. They have additional the potential to record problems like bearing failures, locally tip rub of rotorblades at the circumference and other unbalances (e.g., oil accumulations, volume 3, Ill. 126.96.36.199-12).
Ill. 25.1-5.2 (Lit. 25.1-5): At least in the development are processes, which should enable to
suggest from the vibration characteristics of a rotor at possible
cracks in disks or rings. Thereby the
vibrations are measured at a suitable location with acceleration probes. For this, the
outer ring of the main bearing from the rotor in question offer itself.
The model of this monitoring process can be described as follows:
An always existing allowable „original“ rotor unbalance (assembly influence, production tolerances, abrasion/wear) produces a radial force. This increases quadratic with the rotation speed (sketch left). A crack in the outer zone of the disk openes under the tangential stresses from the zentrifugal forces (sketch right). The gaping produces at the large diameter a corresponding unbalance at the opposite side. This grows with the rotor speed, different (faster by the change of streess distribution/stress rearrangement, plastic deformation, crack growth) than the still present „original” unbalance. Both unbalances superimpose to a resultant. Its direction and size differs, depending of the rotation speed, from the „original“ unbalance. The consequences are a shift of the phase and amplitude of the shaft vibrations. This is sufficient for a computer supported analysis as early sign for a crack.
Requirement for a sufficient early detection of the crack is, that it produces an analyzable change of the unblance. In fact this can be expected for a crack in the outer zone/rim of a disk with a sufficient large diameter and elastic flexibility. However, this does not apply for thick/stiff disks with small diameter. They are typically for turbine wheels (mostly integrally casted) of small gas turbines (e.g., helicoper aeroengines). Does a crack start in the region of the hub, the chance of an identification is probalbly rather low, because of the high stress level. At this high stress level already a small crack leads, even with a minimum unbalance,m to a burst. Additionally with the flat stress gradient a fast crack growth must be expected. So an early enough premonition is not guaranteed (volume 3, Ill. 12.2-10).
Such a „health monitoring” (Ill. 25.1-5.1) can be promising, at least in some cases. This shows the disk fracture in Ill. 24-2. Similar conditions are existent at cases in volume 4, Ill. 188.8.131.52-9.1 and Ill. 184.108.40.206-15. The crack started always at the rim or from an exterior zone.
At industrial gas turbines, the described monitoring process has already proved. It is thinkable, that it can be successfully used, at least in suspicious cases,m during test runs on wing or at test rigs.
This process is not only interesting for aeroengines on test rigs, but also for spintest rigs for better crack analysis/investigation results (fracture analysis) without damges from the fracture.
Ill. 25.1-6 (Lit. 25.1-4, Lit. 25.1-5 and Lit. 25.1-6): The model based
(model based controls and diagnostics = MBCD) can be a powerful and information certain tool of the aeroengine monitoring.
Such systems have proved since years at industrial gas turbines. The advances of the computing technology now enable aso the use in airplanes.
The architecture is complicated. It needs advanced software and hardware components. Above this, extensive knowledge/experience about certain influences is needed.
This process is not only interesting for aeroengines on test rigs, but also for spintest rigs for better crack analysis/investigation results (fracture analysis) without damges from the fracture. The system uses a software based aero-thermodynamic aeroengine model („2“). This continuous working, electronic evaluation algorithm, respectively monitoring filter („2”), adjusts the model. So unusual behaviour/efficiencies of components, drift of sensors/probes and actuation systems can be recorded.
With this it gets possible
Ill. 25.1-7 (Lit. 25.12-6): In a greater term we speak from
engine health management (EHM). It servrs for the identification of
failures and problems in time. So an unacceptable risk can be
avoided, land suitable cost effective measures can be taken. For this, systems of the aeroengine can be
monitored for certain problems and failures. In contrast during condition monitoring trends are observed. In
this case we speak about so called health
The potential of the process can be realised from the chart. From a networking/combination of the informations (data fusion, Ill. 25.1-12), from different monitorings and the single steps of the EHM, certain and detailed conclusions can be expected. Particularly the consequences of faults from measurement and transmission errors of the data from sondes/probes may be limited.
This process finds today an application primarily at four main fields:
Till now EHM suffers itself from problems, in spite of its high potential.
Traditionally, the trigger thresholds from
statistical evaluated data of the fleet operation,
serve the failure identification (diagram above left). Further developments use additionally physical
(theoretical) models (Ill. 25.1-6), the tracing of individual aeroengine
data, predicted algorithms and systematic decision
supports. For such an evaluation the measurement data are compared with thr model results.
The EHM seems till now to identify and define its own problems. Ill. 25.1-8 contains to this a compilation of definitions of impotant terms from the EHM field. Usually these are used in the expert literature.
In spite of the difficulties, false alarms can be minimized with an improvement of the identification of a deviation and the use of standard trigger threshold. For this are promising:
Ill. 25.1-8 (Lit. 25.1-6): Obviously the effectivity and certainty of the
health monitoring suffers under different
definitions, respectively ambiguities of important
terms. Because of this, in the following important definitions are specified.
Abnormal condition is a measurably deviation of the current operation
condition from the normal. A measurable deviation lays outside the specified tolerance. Because this is a difference, such a
deviation is called „residual”.
We distinguish between three conditions:
Diagnosis/ diagnostics refer to processes to find unusual conditions.
Prognosis stay for the process, which enables a conclusion at future effects of the unusual condition.
The severity of a fault rises with the frequentness in a system or an equipment (diagramm left).
The diagram shows the position of fault and failure in the failing/deterioration process.
From a precursor we speak, when first signs of the unusual condition are observed. It is an It is an indication for the sensitivity of the monitoring systems (Ill. 25.1-7).
The trajectory of degradation shows with the drop of the operation property/performance through the lifetime. With the failure it reaches than the unacceptable condition.
Ill. 25.1-9 (Lit. 25.1-11): In this case the data are used from the `digital electronic engine control' (= DEEC) for the trend monitoring. The service firm/company analysis with a `gas path analysis'
by specalists for hints at failures on components like disks.
Most frequent problems for the shown aeroengine type are in this succession:
In the shown case the data analysis showed changes of important parameters from the gas producer. These can already more than halve the lifetime of the hot parts (volume 3, Ill. 12.5-4). Failures in the hot part area showed during the disassembly of the aeroengine. The estimated repair costs correlated several middle class cars. If the failure would not have been identified in time by monitoring, it could have been tripled. Further costs would have been the expected result of a sudden failing during operation.
Ill. 25.1-10 (Lit. 25.1-2 und Lit. 25.1-4): This example should give an impression of the
data from a monitoring. Concerned is a frequent aeroengine type which had at the beginning not yet a `full
authority digital electronic control (= FADEC).
The „ground based engine monitoring“ (Ill. 25.1-6) serves the
„on condition” overhaul.
It can be seen, that the data can be assigned four fields. These cover the whole aeroengine with
its surrounding. This system has the potential to
identify as well trends, as also failures
(grey field) and problems.
With the introduction of a FADEC, electronic components of the system could be saved. These executed the signals and adopted the connection to the fuselage.
Ill. 25.1-11 (Lit. 25.1-6 and Lit. 25.1-7): The determination of the
lifetime consumption respectively residual
lifetime of aeroengine components with help of the monitoring is also called
`life usage monitoring'. If the monitoring of
rotor disks and rings is concerned, we speak about a
disk lifing system. Thereby the data of the
'condition monitoring' are used.
Such a system needs a reliable mathematical model (algorithm) for the failure mechanism to look on. To this belong sure knowledges of the material behavior like crack development and crack propagation. For disks are this primarily the cyclic load (LCF, volume 3, chapter 12.6) from start and shut down processes (main cycles) and power changes (mini cycles). Also static loads (creep, volume 3, chapter 12.5) in the stationary operation condition can be considered.
Requirement for the determination of the remaining rest lifetime of a rotor disk is the knowledge of the save lifetime under design according operation conditions.
The frame above shows an „early“ approach of a `disc lifing systems'. It serves the determination of the design, according lifetime potential. Thereby, rather a vague evaluation is concerned. Characteristical is the OEM specific use of cyclic spin tests. These can also serve the safeguard with a determination of the remaining lifetime. For this, used disks of aeroengines, are sampled („sampling”) and are cyclic spun (grey field above).
The frame below contains a new version of the `Disc Lifing Systems' with improvements. These refer primarily at the guarantee of quality from the new part (grey field below).
With this a recommendation for an `on-condition principle' of individual disks is given. This also includes the possibility of an increase of the lifetime. However for this it must be restrictive mentioned, that the 'retirement for cause' principle (black field) till now, is not used (chapter 25.2-1). This is due to not sufficient sure non destructive testing methods.
Ill. 25.1-12 (Lit. 25.1-8 and Lit. 25.1-9): Monitoring of data, which surpass direct sensor
measurements, is also termed propulsion health
mangement (PHM). The displayed system enables diagnosis
Data fusion is used for the summary of data for monitoring. These come from very different sources (datamining, upper frame). Plausibility considerations and free of contradiction as well as an independent examination increases the analysis certainty for failures and problems. This is especially true for exchangeable aggregates (`line replaceable units =LRUs diagnostics) like gears, pumps and mechanical control systems. Depending from the problem/failure; also statements about the point of time for an exchange can be made (prognostics). In this case we speak about iIntelligent engine health monitoring. Data Fusion can be composed from several steps:
Ill. 24.1-13 (Lit. 25.1-10): Here a monitoring system for helicopters in
military use is concerned (vibration management enhancement program =VMEP). This consists of three `blocks' and monitors at
the aeroengines especially vibrations (1st).
Measurement data during operation are analyzed on
ground by a computer program (2nd), which recommends corresponding maintenance steps. In a 3rd
`block' data are stored.
In this manner an identified indication error will be evaluated. This takes place with the assessment of the relation from signal to background disturbance (signal-to-noise ratio = SNR). If the fault is advanced, respectively a failure already occurred, the SNR is high and the failure signal easy to identify. Corresponding the failure definition (Ill. 25.1-8) a reaction must take place at once.
Beginning failures are difficult to identify, because of the weak signal. With this the increased probability of a false alarm exists Remedy can bring the combination of weak signals from several sensors with a suitable algorithm. We speak of `anomaly detectors'.
The diagrams have been compiled for three `condition indicators' (= CIs) for the aeroengine of a fighter helicopter. Obviously analysis of measurement data from acceleration sensors/probes in the fleet are concerned. In these, graphically overall evaluations and data of individual helicopters and components are contained. The combination of the three CI leads to the nine diagrams. A diagonal from below left to above right reveals the frequency distribution of the data from the individual sensors. Striking outliers of the measurement values (grey circle) occur at two sensors. Thew are identified by the analysis system as anomalies and therefore not evaluated as mismeasurement.
Other outliers don't show this pecularity.
25.1-1 S.K.W.J. Demarteau, „Reliability Versus Cost in Operating Wide Body Jet Engines“,
Proceedings AGARD-CP-215 der AGARD Konferenz „Power Plant Reliability”, Page 5-1 bis 5-7
25.1-2 R.J.E. Dyson, M.J. Ashby, „Military Engine Monitoring Status at GE Aircraft Engines Cincinnati, Ohio“, Proceedings AGARD-CP-448 der AGARD Konferenz „Engine Condition Monitoring - Technology and Experience”, Page 21-1 up to 21-7, 22-1 up to 22-12 and 23-1 up to 23-15. 25.1-3 J.L.Pettigrew, „Gas Turbine Engine Monitoring Systems - Helicopter Experience“, SAE Technical Paper 871735 der „Aerospace Technology Conference and Exposition”, Long Beach, California, October 5-8, 1987 , Page 1-15.
25.1-4 W.H.Kuhl, „Triebwerkdiagnose der Zukunft - Gas Path Analysis: Brilliante neue Methode für die Triebwerksüberwachung“, Zeitschrift „Flug Revue + Flugwelt”, 8/1981, Page 34-36.
25.1-5 D.L.Simon, „An Overview of the NASA Avation Safety Program Propulsion Health Monitoring Element“, Paper NASA/TM-2000-210348 der „36th Joint Propulsion Conference and Exhibit”, July 2000, Page 1-11.
25.1-6 L.C.Jaw, „Recent Advancements in Aircraft Engine Health Management (EHM) - Technologies and Recommendations for the Next Step“, Paper GT2005-68625 der „Turbo Expo 2005: 50th ASME Internetional Gas Turbine & Aeroengine Technical Congress”, June 6-9, 2005, Reno-Tahoe, Nevada, Page 1-13.
25.1-7 R.H.Jeal, „Defects and their Effect on the Behaviour of Gas Turbine Discs“, Proceedings AGARD-CP-317 des 53rd Meeting of the AGARD Structures and Materials Panel, Noordwijkerhout, the Netherlands, „Maintenance and Service of High Temperature Parts”, 27 September - 2 October 1981, Page 6-1 up to 6-15
25.1-8 „What is Data Fusion?“, www.eng.man.ac.uk, Page 1-3.
25.1-9 A.J.Volponi, T.Brotherton, R.Luppold, D.L.Simon, „Development of an Information Fusion System for Engine Diagnostics and Health Management”, Paper NASA/TM-2004-212924 der „39th Combustion/27th Airbreathing Propulsion/21st Propulsion System Hazards/ 3rd Modeling and Simulation Joint Subcommittee Meeting“, Colorado Springs, Colorado, December 1-5, 2003, Page 1-17.
25.1-10 T.Brotherton, P.Grabill, R.Friend, B.Solomayer, J.Berry, „A Testbed for Data Fusion for Helicopter Diagnostics and Prognostics”, Proceedings Nr. 1364 der „2003 IEEE Aerospace Conference, Big Sky MT“, March 2003, Page 1-13.
25.1-11 B.Rosenhof, „Trend Monitoring is about Peace of Mind”, Zeitschrift „Aviation Today“, www.aviationtoday.com, August 1, 2005, Page 1-4.
25.1-12 „An Automatic Engine Condition Diagnostic System for Gas Turbine Engines”, Fa. Hamilton Standard, HSPC 71E02.
25.1-13 D.A.Frith, „Reliable Information From Engine Performance Monitoring“, SAE Technical Paper Series 881444, Paper der „Aerospace Technology Conference and Exposition, Anaheim, California, October 3-6, 1988, Page 1-10.
25.1-14 I.Davinson, „The Use of Fibre Optics in Gas Turbine Applications”, Proceedings zum Seminar „Condition Monitoring in Hostile Environments“, London, June 26, 1985, Page 1-11.
25.1-15 P.Brunnn, „Practical Condition Monitoring - Some Observations”, Proceedings der „Factory Management & Maintenance Engineering Conference“ 11-13 November 1980 National Exhibition Centre, Birmingham, England”, London, Page 1-10.