Method and machine controller for monitoring the temperature of an electromechanical machine

Abstract

According to the invention, structural data (SD) relating to geometry, heat conductivity and electrical conductivity of elements of the machine (M) to be monitored are input. Predefined temperature-critical points (P1, P2) are located on the machine in relation to the structural data (SD). By means of a first thermal simulation model (ST) comprising a plurality of spatially resolved trial functions (FE1, FE2, ...), a plurality of temperature curves (TV) are simulated in the machine in a spatially resolved manner. On this basis, a reduced thermal simulation model (RST) with a reduced plurality of trial functions (F1, F2, ...) is generated and adjusted in such a way that it reproduces the temperature curves (TV) at the temperature-critical points (P1, P2). During operation of the machine, electrical operating data (U, I) of the machine is recorded and, based on the structural data (SD) and the electrical operating data (U, I), electrical energy losses (QE) in the machine are continuously simulated by an electrical simulation model (SE) of the machine in a spatially resolved manner. In addition, based on the structural data (SD) and the simulated electrical energy losses (QE), temperatures (RT1, RT2) at the temperature-critical points (P1, P2) are continuously determined by the reduced thermal simulation model (RST) and output in order to monitor the temperature of the machine.

Description

[0001] Description

[0002] Method and machine control for temperature monitoring of an electromechanical machine

[0003] Safe operation of electromechanical machines, such as electric motors, particularly in the higher power range, often requires temperature monitoring of critical machine components or temperature-critical points within the machine. For example, the insulation of a stator winding of an electric motor should not be exposed to high temperatures to avoid compromising its function.

[0004] However, the temperatures of many temperature-critical points or machine components cannot be measured directly, or are difficult to measure. Therefore, it is generally technically very complex to install temperature sensors on a motor rotor and transmit sensor signals from there to a monitoring device.

[0005] In order to at least obtain estimates of expected operating temperatures, historical operating data from a machine is often used. However, this usually requires large amounts of historical operating data for the machine in question, covering a wide range of operating conditions.

[0006] It is also known to evaluate measured values ​​from temperature sensors installed at more easily accessible locations on the machine being monitored. These measured values ​​can then be used to determine the temperatures of less accessible machine components using physical simulation models.

[0007] It is an object of the present invention to provide a method and a machine control for temperature monitoring of an electromechanical machine, which allows more efficient and / or less complex temperature monitoring.

[0008] This object is achieved by a method having the features of patent claim 1, by a machine control having the features of patent claim 10, by a computer program product having the features of patent claim 11 and by a computer-readable storage medium having the features of patent claim 12.

[0009] To monitor the temperature of an electromechanical machine based on the machine's electrical operating data, structural data on the geometry, thermal conductivity and electrical conductivity of elements of the machine are read in. In addition, predetermined temperature-critical points on the machine are located with reference to the structural data. Furthermore, a large number of temperature profiles in the machine are simulated in a spatially resolved manner using a first thermal simulation model comprising a large number of spatially resolved approach functions based on the structural data. Based on this, a reduced thermal simulation model with a smaller number of approach functions than the first thermal simulation model is generated and adjusted in such a way that it essentially reproduces the temperature profiles specifically at the temperature-critical points.During ongoing operation of the machine, the electrical operating data is then recorded, and based on the structural data and the recorded electrical operating data, electrical energy losses in the machine are continuously simulated with spatial resolution using an electrical simulation model of the machine. Furthermore, based on the structural data and the simulated electrical energy losses, temperatures at the temperature-critical points are continuously determined using the reduced thermal simulation model and output for temperature monitoring of the machine. To carry out the method according to the invention, a machine control system, a computer program product, and a computer-readable, preferably non-volatile storage medium are provided.

[0010] The method according to the invention and the machine control according to the invention can be carried out or implemented, for example, by means of one or more computers, processors, application-specific integrated circuits (AS IC), digital signal processors (DSP) and / or so-called "field programmable gate arrays" (FPGA).

[0011] A particular advantage of the invention is that temperatures prevailing in or on the machine can be determined based on electrical operating data, which is often already available in a machine control system. Therefore, in many cases, installing temperature sensors on or in the machine itself is no longer necessary. Furthermore, the simulations can also be used to determine and / or monitor temperatures in hard-to-reach areas of the machine, particularly inside the machine.

[0012] By focusing the temperature determination on predefined temperature-critical points, a reduced thermal simulation model can often be generated that is significantly simplified compared to the first thermal simulation model. Such a reduced thermal simulation model generally requires significantly fewer computing resources. For real-time monitoring of the machine, the reduced thermal simulation model can therefore often be executed in real time with relatively low computing effort.

[0013] Advantageous embodiments and further developments of the invention are specified in the dependent claims. According to an advantageous embodiment of the invention, an operating current and / or an operating voltage of the machine or a component thereof can be quantified using the electrical operating data. Alternatively or additionally, the electrical operating data can quantify an intermediate circuit voltage, a frequency and / or a degree of modulation. The above electrical operating data are already available in many machine control systems, so that temperature monitoring of the machine often does not require any additional installations on or in the machine to be monitored.

[0014] According to a further advantageous embodiment of the invention, the approach functions of the reduced thermal simulation model can be selected from the approach functions of the first thermal simulation model and / or parameterized in such a way that a deviation between the temperature profiles determined by the reduced thermal simulation model and those determined by the first thermal simulation model is minimized specifically at the temperature-critical points. By focusing on the temperature-critical points or by neglecting or simplifying the consideration of non-critical points, the number of approach functions required for the reduced thermal simulation model is generally significantly reduced.The reduction process can in particular be carried out in such a way that the deviation is minimized specifically, preferably or exclusively at the temperature-critical points and the minimized deviation does not exceed a predetermined deviation threshold.

[0015] Furthermore, an ambient temperature of the machine and / or an air speed in the machine's surroundings can be continuously recorded by sensors. The temperatures at the temperature-critical points can then be determined as a function of the ambient temperature and / or the air speed. In this way, simulation accuracy can be significantly improved in many cases. Furthermore, based on the structural data and mechanical operating data of the machine, mechanical energy losses in the machine can be simulated with spatial resolution using a mechanical simulation model of the machine. The temperatures at the temperature-critical points can then be determined based on the simulated mechanical energy losses. The mechanical simulation model can, in particular, simulate friction losses, e.g. in the machine's axle bearings.For this purpose, the structural data may include friction coefficients for the machine elements affected by friction losses.

[0016] Furthermore, the mechanical operating data can quantify a rotational speed, a torque, a movement speed, and / or an exerted force of the machine or a component thereof. Such mechanical operating data is already available in many machine control systems, so that temperature monitoring often requires no additional installations on or in the machine to be monitored.

[0017] According to an advantageous development of the invention, structural data relating to the electrical conductivity and / or thermal conductivity of the machine elements can be modified as a function of the determined temperatures. A simulation of the electrical energy losses and / or a determination of the temperatures at the temperature-critical points can then be carried out using the modified structural data. This allows, in particular, a temperature dependence of electrical resistances to be taken into account when simulating the electrical energy losses and / or a temperature dependence of thermal conductivity to be taken into account when determining the temperatures. In this way, simulation accuracy can generally be significantly increased.

[0018] Furthermore, depending on the temperatures determined at the temperature-critical points, the machine can be regulated down, information about optimized machine operation can be provided, a recommendation for optimized machine operation can be issued, and / or a cooling device can be activated. In many cases, the above measures can significantly reduce wear on the machine and / or increase its service life.

[0019] According to a further advantageous embodiment of the invention, a position of a given machine component can be determined based on the structural data. The determined position can then be used as a temperature-critical point, with the determined temperature at this position being output as a component-specific temperature value. In this way, one or more critical machine components, e.g., a rotor, a stator, a winding, an axle bearing, and / or the insulation of an electric motor, can be individually monitored.

[0020] An embodiment of the invention is explained in more detail below with reference to the drawings, each of which illustrates in schematic form:

[0021] Figure 1 shows a temperature monitoring of an electric motor by a motor control and

[0022] Figure 2 shows the generation of a reduced thermal simulation model for the engine control system.

[0023] Figure 1 illustrates temperature monitoring of an electric motor M as an electromechanical machine by a motor controller CTL as a machine controller according to the invention. Alternatively, the electromechanical machine M to be monitored can also be a robot, a machine tool, a turbine, a production machine, a motor vehicle, a 3D printer or a component thereof or can comprise such machines or components. The motor controller CTL can in particular comprise an inverter. In addition, the motor controller CTL has one or more processors PROC for carrying out a method according to the invention and one or more memories MEM for storing data to be processed.

[0024] In Figure 1, the motor control CTL is shown external to and coupled to the electromechanical machine M. Alternatively, the motor control CTL can also be fully or partially integrated into the electromechanical machine M.

[0025] The motor controller CTL serves to operate and control the electric motor M . For this purpose, the motor controller CTL can in particular specify a motor speed RPM for the electric motor M and / or supply the electric motor M with a corresponding operating voltage U and / or a corresponding operating current I . The energy supply to the electric motor M can in particular be provided by an inverter (not shown) of the motor controller CTL . In addition, the motor controller CTL can detect currently measured motor speeds RPM, operating voltages U and / or operating currents I from sensors of the electric motor M . For reasons of clarity, measured and specified operating data are each designated by the same reference symbol in the figures.

[0026] Alternatively or in addition to the motor speeds RPM, the motor control CTL can record or use further mechanical operating data of the electromechanical machine M, for example a torque, a movement speed and / or a force exerted by the machine M or a component thereof. Accordingly, in addition to the operating voltages U or the operating currents I, the motor control CTL can record or use further current electrical operating data of the electromechanical machine M or a component thereof.

[0027] For the present embodiment, it is assumed that the machine M has two temperature-critical points P1 and P2, whose temperature must be specifically monitored. In the case of an electric motor, such a temperature-critical point can, in particular, be a predetermined point on a rotor, a stator, a winding, an axle bearing, or an insulation of the electric motor.

[0028] In addition to PI and P2, one or more other temperature-critical points may be provided for monitoring in or on the machine M. For reasons of clarity, however, only the points PI and P2 are explicitly shown in the figures as representative of all temperature-critical points to be monitored.

[0029] The motor control CTL is further linked to a database DB in which structural data SD are stored regarding a geometry, a thermal conductivity, and an electrical conductivity of elements of the machine M. Thermal conductivity can be equivalently expressed or represented by a thermal resistance, and electrical conductivity by an electrical resistance.

[0030] In addition, the structural data SD include friction coefficients for elements of the machine M affected by friction losses. These can, in particular, be friction coefficients for friction between a rotor axis and an axle bearing.

[0031] Examples of the machine elements described by the structural data SD are, in particular, machine components such as rotors, stators, windings, axle bearings or insulation of electric motors or parts of such machine components. In particular, the structural data SD describes machine elements with a specific influence on electrical conduction, thermal conduction and / or friction during operation of the machine M. These can be, for example, coatings, electrical lines, switching elements, thermal bridges or other structural elements of the machine M. The structural data SD specify the thermal conductivity, the electrical conductivity and / or the friction, preferably in spatially resolved form.

[0032] The engine control CTL comprises a first simulation module S1 with an electrical simulation model SE of the machine M, a second simulation module S2 with a mechanical simulation model SM of the machine M, and a third simulation module S3 with a reduced thermal simulation model RST of the machine M. The reduced thermal simulation model RST is generated from a predetermined, detailed thermal simulation model of the machine M. The generation of the reduced thermal simulation model RST is explained in more detail below in connection with Figure 2.

[0033] The first simulation module S1 is used for the continuous, spatially and temporally resolved simulation of electrical energy losses QE in the machine M using the electrical simulation model SE. The second simulation module S2 is used for the continuous, spatially and temporally resolved simulation of mechanical energy losses QM in the machine M using the mechanical simulation model SM. Finally, the third simulation module S3 is used for the continuous determination of temperatures RT1 and RT2 at the temperature-critical points PI and P2 using the reduced thermal simulation model RST.

[0034] The electrical simulation model SE and the mechanical simulation model SM can, if necessary, be combined to form an electromechanical simulation model. The simulation modules SI, S2, and S3 each execute a real-time simulation that runs during operation of the machine M.

[0035] To initialize the simulation models SE, SM and RST, the engine control unit CTL reads the structural data SD from the database DB and feeds the read-in structural data SD at least partially into the simulation modules SI, S2 and S3. As a result, the electrical simulation model SE is initialized using structural data SD relating to the geometry and electrical conductivity of machine elements. Similarly, the mechanical simulation model SM is initialized using structural data SD relating to the geometry and friction of machine elements. Finally, the reduced thermal simulation model RST is initialized using structural data SD relating to the geometry and thermal conductivity of machine elements.

[0036] Many efficient methods and models for physical simulation are available to perform the above simulations. In particular, finite element methods can be used for simulation. Thus, the electrical simulation model SE, the mechanical simulation model SM, the detailed thermal simulation model, and / or, if applicable, the reduced thermal simulation model can each be designed as a finite element model and implemented using a variety of well-known simulation libraries.

[0037] After the simulation models SE, SM and RST have been initialized, the described simulations can be carried out in real time using the recorded current operating data, here U, I and RPM of the machine M. For this purpose, the current electrical operating data, here the operating voltage U and the operating current I, are continuously fed into the first simulation module S1. The first simulation module S1 then continuously simulates the electrical energy losses QE in the machine M in a spatially and time-resolved form using the electrical operating data U and I and the initialized electrical simulation model SE. The simulated electrical energy losses QE are fed into the third simulation module S3 by the first simulation module S1.

[0038] Furthermore, the current mechanical operating data, in this case the current speed RPM, are continuously fed into the second simulation module S2. The second simulation module S2 uses the mechanical operating data RPM and the initialized mechanical simulation model SM to continuously simulate the mechanical energy losses QM in the machine M in a spatially and temporally resolved form. The simulated mechanical energy losses QM are fed by the second simulation module S2 into the third simulation module S3.

[0039] The energy losses QE and QM obviously act as heat sources in the machine M . The heat from these heat sources is distributed in the machine M according to its local thermal conductivity .

[0040] In addition, an ambient temperature and / or an air speed in an environment of the machine M are recorded by sensors and also fed into the third simulation module S3.

[0041] Finally, the third simulation module S3 continuously determines the temperatures RT1 and RT2 at the temperature-critical points PI and P2 in a time-resolved form based on the simulated, spatially and time-resolved energy losses QE and QM as well as on the ambient temperature or air velocity using the initialized reduced thermal simulation model RST.

[0042] Preferably, the determined temperatures RT1 and RT2 can be fed back to the simulation models SE, SM and RST in order to modify the structural data SD on which the models SE, SM and RST are based. In this way, temperature-dependent electrical resistances in the electrical simulation model SE, temperature-dependent thermal resistances in the reduced thermal simulation model RST and / or temperature-dependent mechanical properties of machine elements can be taken into account in the mechanical simulation model SM. This can significantly increase the accuracy of the simulations in many cases. The determined temperatures RT1 and RT2 are transmitted from the third simulation module S3 to a monitoring module MON of the engine control unit CTL. The monitoring module MON continuously checks on the basis of the transmitted temperatures RT1 and RT2 whether a permissible maximum temperature has been reached at the relevant temperature-critical point Pl orP2 is exceeded and / or a respective target temperature is maintained. This can be done, for example, by comparison with specified threshold values ​​and / or with specified temperature intervals.

[0043] Depending on these tests, the monitoring module MON can regulate down the machine M, control a cooling device of the machine M and / or issue an indication or a recommendation for optimized operation of the machine M. To control the machine M accordingly, the monitoring module MON generates a suitable control signal CS and transmits it to the machine M, as indicated by a dotted arrow in Figure 1.

[0044] The invention allows efficient and precise temperature monitoring of the machine or motor M based on currently measured operating data or operating data specified by the motor control CTL, here U, I, RPM, which are already available in many machine controls, motor controls or inverters.

[0045] In this way, temperature monitoring can be implemented which in many cases does not require complex sensors to be mounted on or in the engine.

[0046] In addition, the reduction of a detailed thermal simulation model to the reduced thermal simulation model RST described below can often significantly reduce the computational effort for the thermal simulation. Insofar as a sufficiently accurate thermal simulation often takes up a substantial or dominant share of the overall computational effort, this can be significantly reduced in many cases. Figure 2 illustrates a generation of the reduced thermal simulation model RST for the engine control unit CTL from a given detailed thermal simulation model ST. Insofar as the same or corresponding reference symbols are used in Figure 2 as in Figure 1, these reference symbols designate the same or corresponding entities which can be implemented or configured in particular as described above.Some of the components and data flows of the engine control CTL and the machine M shown in Figure 1 are no longer shown explicitly in Figure 2 for reasons of clarity.

[0047] The detailed thermal simulation model ST is implemented in the third simulation module S3 as a finite element model with a multitude of spatially resolved ansatz functions FEI, FE2, ... . For implementation, at least a portion of the structural data SD is fed to the third simulation module S3. Within the finite element model, the area of ​​the machine M for which a thermal simulation is to be performed is decomposed into a multitude of finite space elements. Localized ansatz functions, here FEI, FE2, ..., are then defined on these finite space elements within the finite element model. The individual ansatz functions FEI, FE2, ... describe the behavior to be simulated, in this case a temperature behavior, in a respective finite space element. For the decomposition into the finite space elements, for the design of the ansatz functions FEI, FE2, ...A variety of efficient program libraries are available for the execution of finite element-based simulations.

[0048] In the present case, the decomposition into finite space elements is carried out depending on the geometric data of the machine M contained in the supplied structural data SD. Based on this, a heat conduction equation discretized into finite space elements is established using spatially resolved data on the thermal conductivity of elements of the machine M contained in the supplied structural data SD. A variety of known and efficient methods are available for establishing and solving such a discretized heat conduction equation.

[0049] However, a sufficiently accurate thermal simulation often requires a large number of finite elements, which generally entails considerable computational effort. For this reason, the detailed thermal simulation model ST is transformed by a transformation T into a simplified thermal simulation model, here RST, with a significantly smaller number of ansatz functions Fl, F2, ...

[0050] The reduced thermal simulation model RST is first geometrically initialized using the geometric data contained in the supplied structural data SD or using geometric structures of the detailed thermal simulation model ST. Furthermore, the temperature-critical points PI and P2 are localized with respect to the structural data SD. In particular, the coordinates of the temperature-critical points PI and P2 are determined with respect to a coordinate system defined in the structural data SD.

[0051] Based on this, approach functions Fl, F2, ... are selected and / or designed that are specifically focused on the temperature-critical points PI and P2 or adapted to them. The approach functions Fl, F2, ... can be generated at least partially by the transformation T from the approach functions FEI, FE2, .... When selecting and / or designing the approach functions Fl, F2, ..., the temperature-critical points PI and P2 are given preference over other points on the machine M that are less temperature-critical or have less influence on heat conduction. By thinning out, coarsening and / or neglecting approach functions at less critical points in this way, the number of approach functions Fl, F2, ... can in many cases be significantly reduced compared to the number of approach functions FEI, FE2, ...To further adapt the reduced thermal simulation model RST, a large number of spatially and temporally resolved energy losses Q acting as heat sources are fed to this and the detailed thermal simulation model ST as input data. The energy losses Q can, for example, include a large number of recorded or simulated electrical energy losses QE and / or mechanical energy losses QM of the machine M. In addition, ambient temperatures and / or air velocities in an environment of the machine M can also be represented as heat sources or heat sinks by the energy losses Q.

[0052] Based on the supplied large number of energy losses Q, a large number of corresponding, spatially and temporally resolved temperature profiles TV are simulated in the machine M using the detailed thermal simulation model ST. The simulated temperature profiles TV are transmitted from the third simulation module S3 to an evaluation module EV of the engine control unit CTL. The evaluation module EV evaluates the temperature profiles TV at the temperature-critical points PI and P2 and thus determines simulated temperature profiles TI and T2 at the temperature-critical points PI and P2.

[0053] Analogously, using the reduced thermal simulation model RST, a plurality of courses of the respective temperatures RT1 and RT2 at the temperature-critical points PI and P2 are determined based on the supplied plurality of energy losses Q.

[0054] The reduced thermal simulation model RST and / or its approach functions Fl, F2, ... are now set and / or parameterized so that the temperatures RT1 and RT2 reproduce the temperatures TI and T2 as accurately as possible. For this purpose, a deviation D of the curves of the temperatures RT1 and RT2 from the corresponding curves of the temperatures TI and T2 is determined. The deviation D can be determined in particular as a time integral or as a time sum of an amount or a square of a difference between a respective temperature pair (RT1, RT2) and the respective associated temperature pair (TI, T2). For example, according to D = integral [ (RT1 ( t ) -TI ( t ) ) 2 + (RT2 ( t ) -T2 ( t ) ) 2 ] dt .

[0055] The deviation D is fed back to the third simulation module S3, as indicated by dashed arrows in Figure 2. Based on the deviation D, the reduced thermal simulation model RST and / or its initial functions F1, F2, ... are adjusted and / or parameterized such that the deviation D is minimized. A variety of efficient optimization methods are available for such minimization problems.

[0056] Preferably, the minimum deviation D achievable in this way is compared with a predefined deviation threshold. As long as the deviation threshold is not exceeded by the minimum deviation D, the reduction process of the reduced thermal simulation model RST can be continued; in particular, by further thinning, coarsening, or deleting the approach functions Fl, F2, ...

[0057] In this way, the reduced thermal simulation model RST can be considerably simplified in many cases with a specified accuracy, so that a real-time simulation of the thermal behavior of the machine M in many cases requires only relatively low computing resources.

Claims

Patent claims 1. A computer-implemented method for temperature monitoring of an electromechanical machine (M) based on electrical operating data (U, I) of the machine (M), wherein a) structural data (SD) regarding a geometry, a thermal conductivity, and an electrical conductivity of elements of the machine are read in, b) predetermined temperature-critical points (Pl, P2) of the machine are located with reference to the structural data (SD), c) a plurality of temperature profiles (TV) in the machine are simulated in a spatially resolved manner using a first thermal simulation model (ST) comprising a plurality of spatially resolved initial functions (FEI, FE2,...) based on the structural data (SD), d) a reduced thermal simulation model (RST) with a smaller number of initial functions (Fl, F2,...) than the first thermal simulation model (ST) is created.) is generated and set in such a way that it essentially reproduces the temperature profiles (TV) specifically at the temperature-critical points (PI, P2), e) the electrical operating data (U, I) are recorded during ongoing operation of the machine, f) on the basis of the structural data (SD) and the electrical operating data (U, I), electrical energy losses (QE) in the machine are continuously simulated in a spatially resolved manner using an electrical simulation model (SE) of the machine, g) on ​​the basis of the structural data (SD) and the simulated electrical energy losses (QE), temperatures (RT1, RT2) at the temperature-critical points (PI, P2) are continuously determined using the reduced thermal simulation model (RST), and h) the determined temperatures (RT1, RT2) are output for temperature monitoring of the machine.

2. Method according to claim 1, characterized in that that an operating current (I) and / or an operating voltage (U) of the machine (M) is quantified by the electrical operating data (I, U).

3. Method according to one of the preceding claims, characterized in that the approach functions (Fl, F2,...) of the reduced thermal simulation model (RST) are selected from the approach functions (FEI, FE2,...) of the first thermal simulation model (ST) and / or are parameterized in such a way that a deviation (D) between the temperature profiles determined by the reduced thermal simulation model (RST) and the temperature profiles determined by the first thermal simulation model (ST) is minimized specifically at the temperature-critical points (Pl, P2).

4. Method according to one of the preceding claims, characterized in that an ambient temperature of the machine and / or an air speed in an environment of the machine is continuously detected by sensors, and in that the temperatures at the temperature-critical points (Pl, P2) are determined as a function of the ambient temperature and / or the air speed.

5. Method according to one of the preceding claims, characterized in that on the basis of the structural data (SD) and mechanical operating data (RPM) of the machine (M), mechanical energy losses (QM) in the machine are simulated in a spatially resolved manner by means of a mechanical simulation model (SM) of the machine, and in that the temperatures at the temperature-critical points (Pl, P2) are determined on the basis of the simulated mechanical energy losses (QM).

6. The method according to claim 5, characterized in that a rotational speed, a torque, a movement speed and / or an exerted force of the machine (M) is quantified by the mechanical operating data (RPM).

7. Method according to one of the preceding claims, characterized in that structural data (SD) on the electrical conductivity and / or the thermal conductivity of the machine elements are modified depending on the determined temperatures (RT1, RT2), and that a simulation of the electrical energy losses (QE) and / or a determination of the temperatures (RT1, RT2) at the temperature-critical points (Pl, P2) is carried out on the basis of the modified structural data.

8. Method according to one of the preceding claims, characterized in that depending on the determined temperatures at the temperature-critical points (Pl, P2) - the machine (M) is turned down, - an indication of optimized operation of the machine (M) is given, - a recommendation for optimised operation of the machine (M) is issued and / or - a cooling device is controlled.

9. Method according to one of the preceding claims, characterized in that a position of a predetermined machine component is determined on the basis of the structural data (SD), that the determined position is used as a temperature-critical point (P1, P2), and that the determined temperature (RT1, RT2) at this position is output as a component-specific temperature value.

10. Machine control (CTL) for operating and monitoring the temperature of an electromechanical machine (M), comprising means for carrying out the steps of a method according to one of the preceding claims.

11. A computer program product comprising instructions which, when executed by a computer, cause the computer to carry out a method according to one of claims 1 to 9.

12. A computer-readable storage medium comprising a computer program product according to claim 11.

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