EP1431927A1 - Méthode pour estimer la durée de vie résiduelle d'un appareil - Google Patents

Méthode pour estimer la durée de vie résiduelle d'un appareil Download PDF

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Publication number
EP1431927A1
EP1431927A1 EP03405822A EP03405822A EP1431927A1 EP 1431927 A1 EP1431927 A1 EP 1431927A1 EP 03405822 A EP03405822 A EP 03405822A EP 03405822 A EP03405822 A EP 03405822A EP 1431927 A1 EP1431927 A1 EP 1431927A1
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EP
European Patent Office
Prior art keywords
wear
map
flights
characteristic parameter
value
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
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Application number
EP03405822A
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German (de)
English (en)
Inventor
Guido Dr. Vezzu
William Dr. Gizzi
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Sulzer Markets and Technology AG
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Sulzer Markets and Technology AG
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Publication date
Application filed by Sulzer Markets and Technology AG filed Critical Sulzer Markets and Technology AG
Priority to EP03405822A priority Critical patent/EP1431927A1/fr
Publication of EP1431927A1 publication Critical patent/EP1431927A1/fr
Withdrawn legal-status Critical Current

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    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
    • G07C3/00—Registering or indicating the condition or the working of machines or other apparatus, other than vehicles

Definitions

  • the invention relates to a method for estimating the remaining service life of a Device that is subject to wear during operation.
  • the invention further relates to the use of such a method for Maintenance planning.
  • the present invention is dedicated to this task. So it should be a Method for estimating the remaining life of a device be proposed in which the specific operating conditions and thus the effective or real life of the device is taken into account.
  • the wear is based on quantifies at least one characteristic parameter that is sensitive regarding wear.
  • a map is created for the device, which is the relationship between the characteristic parameter, the amount of time and the wear. In the case of only one characteristic parameter, this map can be viewed as a surface in a three-dimensional space, which space through the characteristic parameters, the time size and the wear is spanned.
  • Data is recorded on the device from which an actual value can be obtained can be determined for the parameter depending on the time.
  • the map can then be used to determine how far the wear has progressed quantitatively, for example in percent.
  • Extrapolation to the maximum permissible limit for the characteristic parameters can then be estimated the remaining life become.
  • the method according to the invention thus actually takes into account the effectively already used lifetime, based on that Estimating remaining life. So it's not just the time size are taken into account, but also the operating and, if necessary takes into account the environmental conditions under which the device was operated at the current time. This is operational Estimation of the remaining life, which is the history of the device taken into account, enables a much more efficient use of the Device because maintenance only needs to be carried out when they are actually necessary. The reliable prediction of the Wear development thus enables a condition-based Maintenance planning.
  • the remaining life for different stages in the Lifecycle determined that is, with increasing consumption of Lifetime - measured by the time size - becomes the remaining lifespan re-estimated several times.
  • the map is also Created with a priori knowledge of wear behavior.
  • Devices such as aircraft engines (jet engines) very much represent complex systems, it is usually - if at all - only with greater effort possible a sufficiently precise physical or perform deterministic modeling of the device.
  • a priori know-how for the creation of the map consulted.
  • the experiences, observations or measurements that you have collected on the same or similar devices used to determine the qualitative and / or quantitative behavior of the characteristic parameters with increasing wear describe. Simplified by using such a priori knowledge the creation of the map significantly.
  • the use of the Prior knowledge usually means that the map of the device describes better or more precisely.
  • the a priori knowledge preferably includes the qualitative and / or quantitative course of wear curves showing the relationship specify between the characteristic parameter and the time variable.
  • the map is particularly preferably by means of a linguistic Fuzzy model created.
  • this can be a purely qualitative one Model for determining the wear that is then generated the basis of measured life cycles regarding its quantitative Properties is sufficiently optimized.
  • the data recorded by measurement technology is used for Determination of the actual values for the characteristic parameter one each Filtering or averaging. Often they are metrologically recorded data from a noise or other Interference size superimposed, so that their direct use, especially in Fuzzy models, no robust statement regarding the degree of wear allowed.
  • a model is created from the data recorded using the measurement, with which an actual value is determined for the characteristic parameter.
  • the inventive method is particularly suitable for Estimating the remaining life of an engine, particularly an aircraft engine.
  • the inventive method is particularly well suited for Maintenance planning, especially of an aircraft or a variety of Aircraft (fleet management).
  • the method according to the invention is described below with an example Character with reference to an aircraft jet engine explained.
  • the engine is a representative example of one Device which is subject to wear during operation and for which should be used to estimate the remaining life. It goes without saying the invention is not limited to this application, but is suitable in similarly also for other devices such as land-based turbines, turbomachines or other mechanical Systems that are subject to wear during operation and therefore need to be serviced.
  • lifespan is the section between two ordinary ones Revisions or maintenance meant, that means immediately after the Maintenance, the degree of wear is assessed as “new”.
  • the sensitive to the wear of the Aircraft engine is, the change in the gas outlet temperature of the Engine selected. In the following, this change in temperature is indicated by T designated.
  • time variable which is representative of the operating time or the Is the number of flights selected in the following with A referred to as.
  • A the number of operating hours.
  • a wear of V 0.6 means, for example, that the Degree of wear is 60% of the maximum permissible wear.
  • a temperature increase of 40 K selected. This value is based on experience as a priori know-how be introduced.
  • Fig. 1 shows several typical wear curves K1-K4, each one possible relationship between the temperature change T as characteristic parameters and the number A of flights as a time variable specify.
  • Such wear curves represent a priori knowledge, which in the present embodiment for creating the map is used.
  • the wear curves are based on experience or metrologically recorded data that can be seen on the same or similar Engines.
  • One way to quantify wear is to: the path integral normalized to one over the entire wear curve. Then defines the path length for each point on the wear curve appropriate wear. For example, if you've completed A1 flights, the quantified wear results from the path integral over the Wear curve from 0 to A1.
  • Embodiment of the inventive method in the course of progressive consumption of life estimate the Remaining lifespan improved by the fact that the prediction constantly (the means, for example, after every flight) on the correct wear curve is adjusted.
  • this is the characteristic Parameters and the size of the time, which is the lifetime used up to now measures as inputs and wear as output as necessary and sufficient information to estimate the remaining life use.
  • a map KF is first (see Fig. 3) created that a relationship between the characteristic parameters (here the temperature increase T), the Time size (here the number A of flights) and the wear V.
  • This map is preferably created with the aid of a priori know-how, So for example using wear curves K1-K4 as they are shown in Fig. 1.
  • A is particularly preferred for the implementation of this a priori knowledge linguistic fuzzy model (MAMDANI model) used. Because such fuzzy Models or the fuzzy logic per se are sufficiently known to the specialist are only briefly explained here, as in the embodiment of The inventive method, the map KF with the help of a linguistic fuzzy model is created.
  • MAMDANI model priori knowledge linguistic fuzzy model
  • the linguistic fuzzy model stands for the one described here Embodiment following information as a priori know-how Disposition: Knowledge of the qualitative and quantitative course of Wear curves (see Fig. 1); additional requirements for the Forecast in peripheral areas.
  • Each of the input and output sizes is characterized by a fuzzy set.
  • Fig. 2 shows the Membership function of the fuzzy set for the Input variable temperature increase T.
  • For the linguistic variable T are linguistic values "small”, “medium” and “large” are provided.
  • a map KF can then be created as in Fig. 3 is shown as a mesh.
  • a "draft" for the Map KF is created and this is then refined.
  • the result resulting map KF for the embodiment described here is in Fig. 3 shown.
  • the change in the gas outlet temperature T is recorded at regular intervals, for example during each flight.
  • This leads to a data record of the form [T i ; A i] with i 1, ..., n, where T denotes i the temperature change for the flight with the number A i.
  • T denotes i the temperature change for the flight with the number A i.
  • the historical measurement data or the actual values for the temperature increase T up to the present are available for the engine at the time at which the remaining service life is to be estimated.
  • Each pair of values (T k , A k ) from an actual value for the temperature increase and the associated service life, measured by the number of flights A k corresponds to a point in the plane spanned by the A axis and the T axis (see Fig 3).
  • T k , A k Only one such point with the coordinates (T k , A k ) is drawn in the TA plane as a cross in FIG. 3.
  • This point is now projected onto the map KF, that is to say upward onto the map KF represented by the network.
  • the wear V k belonging to (T k , A k ) can be read off directly.
  • a pessimistic one Development of the temperature increase derived from the number of flights that are normally required at least around the limit G 40K for the To achieve temperature increase T.
  • Fig. 5 shows the plane spanned by the A-axis and the T-axis.
  • a k , T k the most current point, i.e. the one that corresponds to the present, in which the estimate is made.
  • the gradient with which the line E is "appended" to the point (T k , A k ) has been determined as follows.
  • the line E is mapped into the map KF, whereby it generally becomes a curved line.
  • Map KF again - analogous to the representation in Fig. 4- on the of the V-axis and the plane spanned by the A axis, the result is that in FIG. 6 shown representation.
  • the projection E 'of the extrapolation is now too see that is shown in dashed lines.
  • the estimate of the remaining service life is now given by Difference formation from the final value AG and the current value for the Number of flights, the most recent of the historical values. In Fig. 6 this is the last point of the solid curve.
  • FIG. 7 illustrates the estimate of the Remaining life for seven stages in the life cycle of an engine.
  • Fig. 7 is in the same way as in Fig. 4 and 6 shows the plane spanned by the V-axis and the A-axis, which results from the projection of the map.
  • the historical data the means those data that are based on measurement data, are each shown as solid lines, the extrapolations that the Underlying the estimate are shown in dashed lines.
  • the transition from the solid to the dashed line indicates the respective present, in who made the estimate.
  • To the right of the illustrations is the Estimated remaining lifespan RL in number of flights. In the top one
  • the presentation in which no historical data are yet available is Residual life essentially determined by the selected gradient.
  • the forecast horizon can be selected by choosing a smaller one Extend or extend gradients for extrapolation. This would in practice, however, does not lead to a significantly greater benefit, however increase the risk of an overly optimistic estimate of the remaining life.
  • map uses a priori know-how must be created.
  • Other methods are possible to to determine a map which shows the relationship between the characteristic parameters, the time size and the wear indicates. So can, for example, depending on the application, use ab initio calculations be carried out, or design calculations, Dimensioning calculations, physical modeling, data-based Modeling, system behavior calculations. It is also possible that Map in the form of polynomials, look-up tables, multilayer perceptrons (neural networks), radial basis functions, Singleton and Takadi-Sugeno Describe fuzzy models as well as hanging hyperplanes.

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)
EP03405822A 2002-12-18 2003-11-19 Méthode pour estimer la durée de vie résiduelle d'un appareil Withdrawn EP1431927A1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
EP03405822A EP1431927A1 (fr) 2002-12-18 2003-11-19 Méthode pour estimer la durée de vie résiduelle d'un appareil

Applications Claiming Priority (3)

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EP02102786 2002-12-18
EP02102786 2002-12-18
EP03405822A EP1431927A1 (fr) 2002-12-18 2003-11-19 Méthode pour estimer la durée de vie résiduelle d'un appareil

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Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102004061273A1 (de) * 2004-12-10 2006-06-14 Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. Verfahren und Vorrichtung zur Bestimmung des Abnutzungsvorrates mindestens einer Komponente einer technischen Anlage
EP1739558A1 (fr) * 2005-06-29 2007-01-03 International Business Machines Corporation Procédé, programme et appareil de prédiction automatique de manque de performance d'une base de données
WO2007045537A2 (fr) * 2005-10-17 2007-04-26 Siemens Aktiengesellschaft Procede et dispositif pour determiner la longevite necessaire de composants individuels d'une installation de production d'energie a combustible fossile, en particulier d'une installation gaz et valeur
WO2012055699A1 (fr) * 2010-10-28 2012-05-03 Eads Deutschland Gmbh Système d'information de maintenance, capteur d'état à utiliser dans ce système et procédé pouvant être mis en oeuvre au moyen de ce système pour décider de la nécessité d'effectuer une maintenance
EP2937594A2 (fr) 2014-03-31 2015-10-28 Steinel Normalien Ag Vérin à gaz
DE102017214066A1 (de) * 2017-08-11 2019-02-14 Robert Bosch Gmbh Verfahren zum Betreiben einer wärmetechnischen Anlage
CN111801563A (zh) * 2018-03-01 2020-10-20 Mtu 腓特烈港有限责任公司 用于运行内燃机的方法、控制机构和内燃机
DE102022113608A1 (de) 2022-05-30 2023-11-30 E.ON Digital Technology GmbH Kontroll- und Überwachungsverfahren und /-vorrichtung für eine Industrieanlage

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2002018879A1 (fr) * 2000-08-25 2002-03-07 Battelle Memorial Institute Procede et appareil de prediction de la duree de vie restante d'un systeme operationnel
US20020107589A1 (en) * 2000-09-29 2002-08-08 Wolfgang Grimm Method and device for determining changes in technical systems such as electric motors caused by ageing

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2002018879A1 (fr) * 2000-08-25 2002-03-07 Battelle Memorial Institute Procede et appareil de prediction de la duree de vie restante d'un systeme operationnel
US20020107589A1 (en) * 2000-09-29 2002-08-08 Wolfgang Grimm Method and device for determining changes in technical systems such as electric motors caused by ageing

Cited By (15)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102004061273A1 (de) * 2004-12-10 2006-06-14 Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. Verfahren und Vorrichtung zur Bestimmung des Abnutzungsvorrates mindestens einer Komponente einer technischen Anlage
EP1739558A1 (fr) * 2005-06-29 2007-01-03 International Business Machines Corporation Procédé, programme et appareil de prédiction automatique de manque de performance d'une base de données
US8090545B2 (en) 2005-10-17 2012-01-03 Siemens Aktiengellschaft Method and apparatus for determination of the life consumption of individual components in a fossil fuelled power generating installation, in particular in a gas and steam turbine installation
WO2007045537A3 (fr) * 2005-10-17 2007-09-13 Siemens Ag Procede et dispositif pour determiner la longevite necessaire de composants individuels d'une installation de production d'energie a combustible fossile, en particulier d'une installation gaz et valeur
JP2009511807A (ja) * 2005-10-17 2009-03-19 シーメンス アクチエンゲゼルシヤフト 化石燃料式エネルギ発生設備の構成部品の寿命消費の検出方法と装置
CN101292076B (zh) * 2005-10-17 2011-04-20 西门子公司 确定燃油发电设备特别是燃气轮机和蒸汽轮机设备的单个组件的寿命消耗的方法和装置
WO2007045537A2 (fr) * 2005-10-17 2007-04-26 Siemens Aktiengesellschaft Procede et dispositif pour determiner la longevite necessaire de composants individuels d'une installation de production d'energie a combustible fossile, en particulier d'une installation gaz et valeur
WO2012055699A1 (fr) * 2010-10-28 2012-05-03 Eads Deutschland Gmbh Système d'information de maintenance, capteur d'état à utiliser dans ce système et procédé pouvant être mis en oeuvre au moyen de ce système pour décider de la nécessité d'effectuer une maintenance
US9477222B2 (en) 2010-10-28 2016-10-25 Eads Deutschland Gmbh Maintenance information device, condition sensor for use therein and method which can be carried out therewith for arriving at a decision whether or not to perform servicing or maintenance
EP2937594A2 (fr) 2014-03-31 2015-10-28 Steinel Normalien Ag Vérin à gaz
EP2937594B1 (fr) 2014-03-31 2017-12-13 Steinel Normalien AG Vérin à gaz
DE102017214066A1 (de) * 2017-08-11 2019-02-14 Robert Bosch Gmbh Verfahren zum Betreiben einer wärmetechnischen Anlage
CN111801563A (zh) * 2018-03-01 2020-10-20 Mtu 腓特烈港有限责任公司 用于运行内燃机的方法、控制机构和内燃机
CN111801563B (zh) * 2018-03-01 2022-08-30 罗尔斯·罗伊斯解决方案有限公司 用于运行内燃机的方法、控制机构和内燃机
DE102022113608A1 (de) 2022-05-30 2023-11-30 E.ON Digital Technology GmbH Kontroll- und Überwachungsverfahren und /-vorrichtung für eine Industrieanlage

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