Device and method for detecting faults in machines

Abstract

The invention relates to a method for detecting errors in a machine (1) comprising at least one electric device unit (3) for driving a machine assembly. The frequency spectrum of a measurement variable characterizing the electric power consumption of the drive unit (3) is determined and in an analyzing step, the frequency spectrum evaluates the measurement variable with respect to errors indicating abnormalities.

Description

Device and method for fault detection in machines The invention relates to a method for fault detection in a machine according to the preamble of claim 1 and to a device for fault detection in a machine according to the preamble of claim 13. For predictive maintenance and repair of a machine, it is common practice to detect and analyze mechanical vibrations to identify and locate faults early. Vibration sensors designed to detect these vibrations are installed at defined points on the machine. These sensors detect vibrations, allowing conclusions to be drawn about machine faults and the maintenance required. However, installing vibration sensors on a machine is prone to failure, as the sensors can be easily damaged. Furthermore, installing vibration sensors represents an additional effort and is therefore expensive. Furthermore, it is known in electrically driven devices to detect faults by observing that electrical parameters, particularly those characterizing electrical power consumption, such as the electric current drawn by an electric drive unit, exceed a predetermined limit. The method known from the prior art is based on the fact that, in electric motors, the current flowing through the motor depends on the mechanical load on the motor. Thus, an increasing mechanical load on the electric motor leads to an increase in current, and conversely, a decreasing mechanical load leads to a decrease in current. Therefore, a change in the mechanical load of an electric motor results in a change in the current draw of that motor. The known method for fault detection involves checking the current to see if it exceeds a defined threshold. If the threshold is exceeded, a fault detection signal is output to a monitoring device. A disadvantage of this known method is that while faults in the machine can be detected before a complete machine shutdown, thus potentially preventing unplanned production interruptions, significant mechanical damage has usually already occurred, requiring complex and costly repairs. Based on this, the object of the invention is to provide a device for detecting faults in a machine, by means of which damage can be detected at an early stage and planned machine maintenance can be carried out before complex mechanical damage occurs. The invention is solved starting from the preamble of independent claim 1 by its characterizing features. A device for detecting faults in machines is the subject of dependent claim 13. The invention relates to a method for detecting faults in a machine. The machine comprises at least one electric drive unit by means of which at least one assembly of the machine is driven. According to the method, the frequency spectrum of a measured quantity characterizing the electrical power consumption of the drive unit is first determined. This measured quantity can be any electrical quantity that allows conclusions to be drawn about the power consumption of the electric drive unit. Subsequently, in an analysis step, the frequency spectrum of this measured quantity is evaluated for anomalies indicative of faults. This evaluation can be performed automatically by an analysis unit or by maintenance personnel.The method is advantageous because the spectral analysis of the measured variable characterizing the electrical power consumption of the drive unit allows for the detection of periodic fluctuations in the drive unit's load. This enables, for example, the early detection of periodically occurring collisions between a moving machine element and another machine element, or periodic load peaks in a gearbox. Preferably, the frequency spectrum is compared with a previously recorded reference frequency spectrum. If at least one spectral component of the frequency spectrum deviates from the previously recorded reference frequency spectrum, a fault detection signal is generated. According to one embodiment of the invention, the machine comprises a plurality of drive units, wherein the frequency spectrum of a measured quantity characterizing the electrical power consumption of the drive unit is determined for several or all of these drive units, and in an analysis step, the frequency spectra of these measured quantities are evaluated for anomalies indicating errors. This ensures that several drive units are monitored simultaneously with regard to the vibration behavior of their mechanical load. Preferably, the frequency spectra are compared with a previously recorded reference frequency spectrum, and if at least one spectral component of the respective frequency spectrum deviates from the reference frequency spectrum, an error detection signal is generated.Preferably, a localization signal is also generated, which defines the drive unit where the spectral deviation from the reference frequency spectrum occurred. Depending on the drive unit where a periodic load change occurred, a rough localization of the fault can be performed, i.e., a spatial delimitation of the fault. In particular, the frequency can also be output and / or used to further delimit the fault. The frequency allows conclusions to be drawn about the periodicity of the load fluctuations, meaning that only those mechanical components that move with this periodicity can be considered as the cause of the fault. In another embodiment, at least one frequency spectrum is continuously or at regular intervals determined. This allows the determined frequency spectrum to be compared with the reference frequency spectrum continuously or after a specific time interval, and any errors that may occur to be detected. Furthermore, the currently determined frequency spectrum can be compared simultaneously with several reference frequency spectra determined in the past, particularly those acquired at different times in the past. This means that the temporal change of the frequency spectrum is determined based on several reference frequency spectra recorded at different times in the past. This allows the progression of an occurring error to be analyzed and the error detection signal to be generated depending on the error's progression. In another embodiment, the reference frequency spectrum is a frequency spectrum recorded when the machine was new. Alternatively, the reference frequency spectrum is a spectrum recorded after a certain operating period following the machine's commissioning. As previously explained, a comparison can also be made with several reference frequency spectra recorded at different times. The reference frequency spectra can be stored in a memory unit that an analysis module can access. Alternatively, the memory unit can also be integrated into the analysis module. In another embodiment, amplitude values ​​of the spectral components of the determined frequency spectrum are compared with threshold values ​​assigned to these spectral components. If at least one threshold value is exceeded, the fault detection signal is generated by the amplitude value assigned to that threshold. For example, a threshold can be defined, and a fault detection signal is only generated when this threshold is exceeded. This threshold can be frequency-dependent, i.e., different threshold values ​​can be defined for different frequencies. In particular, the threshold can be defined as a threshold relative to the reference frequency spectrum, so that a fault detection signal is only generated when a spectral component increases by a certain percentage. This allows a reference frequency spectrum containing several peaks or...If the spectrum exhibits peaks, a threshold curve is assigned to it that is frequency-dependent and adapted to the reference frequency spectrum in such a way that the threshold curve maintains a defined absolute or relative distance to the amplitude values ​​of the reference frequency spectrum. This distance thus defines a tolerance limit, after which the fault detection signal is generated. The threshold or threshold curve can be formed from a multitude of discrete threshold values ​​or from a threshold function (e.g., a polynomial) that defines the threshold curve. In another embodiment, the frequency spectrum of the measured quantity characterizing the electrical power consumption of the drive unit is obtained from the time course of the amplitude of this measured quantity by a transformation into the frequency domain. For example, several discrete amplitude values ​​can be recorded at different times and transformed into the frequency domain using a discrete transformation method to obtain the frequency spectrum. Any transformation method known from the prior art can be used for this transformation, in particular a Fourier transform or a Laplace transform. In another embodiment, the measured quantity characterizing the electrical power consumption of the drive unit is the electric current, i.e., the electric current drawn by the drive unit. The electric current drawn by an electric drive unit depends directly on the mechanical load of this drive unit and is therefore subject to the same fluctuations as the mechanical load of the drive unit. Alternatively, the product of the electric current drawn by the drive unit and the voltage drop across the electric drive unit can also be used as the measured quantity. In a further embodiment, the measured variable characterizing the electrical power consumption of the drive unit is obtained by analyzing a measured variable characterizing the electrical power consumption of the entire machine, by analyzing a measured variable characterizing the electrical power consumption of a group of drive units, and / or by analyzing a measured variable characterizing the electrical power consumption of a single drive unit.Advantageously, the power consumption of each of the machine's drive units is analyzed independently, since when analyzing a measured quantity whose magnitude depends on the power consumption of a group of drive units or on the power consumption of the entire machine, fault analysis becomes more difficult, as it is not possible to assign a detected increase in the amplitude of a spectral component to a specific drive unit and thus to locate the fault. In another embodiment, each drive unit or group of drive units is assigned a control unit. This control unit provides the time course of the measured variable characterizing the electrical power consumption of the drive unit and / or the frequency spectrum of this measured variable. The control unit can, for example, be a drive control unit containing the control electronics of the drive unit and by means of which the control of the electrical drive unit, such as speed control, is carried out. Furthermore, the invention relates to a device for detecting faults in a machine, wherein the machine comprises at least one electric drive unit for driving a component of the machine. The device includes an analysis module by means of which the frequency spectrum of a measured quantity characterizing the electrical power consumption of the drive unit is determined and evaluated for anomalies indicative of faults. Preferably, the frequency spectrum is compared with a previously recorded reference frequency spectrum. The analysis module is further configured to determine the deviation of at least one spectral component of the frequency spectrum from a previously recorded reference frequency spectrum and to generate a fault detection signal. In a further embodiment, the machine comprises a plurality of drive units, wherein one or more analysis modules are provided. These modules determine the frequency spectrum of a measured quantity characterizing the electrical power consumption of the drive unit for several or all of these drive units and analyze it for anomalies indicating errors. Preferably, the at least one analysis module compares the frequency spectra with a reference frequency spectrum assigned to the respective frequency spectrum. In a further embodiment, the analysis module is configured to generate an error detection signal and / or a localization signal characterizing the respective drive unit if at least one spectral component of the respective frequency spectrum deviates from the reference frequency spectrum. In another embodiment, the analysis module is designed to determine the temporal change of the frequency spectrum based on several reference frequency spectra recorded at different times in the past. In another embodiment, each drive unit or group of drive units is assigned a control unit, wherein the time course of the measured quantity characterizing the electrical power consumption of the drive unit and / or the frequency spectrum of this measured quantity is provided by the control unit. Further developments, advantages, and possible applications of the invention will also become apparent from the following description of exemplary embodiments and from the figures. All described and / or illustrated features, individually or in any combination, are fundamentally the subject matter of the invention, irrespective of their compilation in the claims or their cross-reference. The content of the claims is also incorporated into the description. The invention is explained in more detail below with reference to several exemplary embodiments shown in the figures.The figures show: by way of example, in a schematic block diagram, a machine with a device for detecting faults in a first embodiment; by way of example, in a schematic block diagram, a machine with a device for detecting faults in a second embodiment; by way of example, a reference frequency spectrum of the electric current recorded by the drive unit and associated with the drive unit; by way of example, a recorded frequency spectrum associated with a drive unit with a spectral peak indicating a fault (indicated by an arrow); by way of example, another example of a recorded frequency spectrum associated with a drive unit with a spectral peak indicating a fault (indicated by an arrow). Figure 1 shows a machine, in particular a machine for treating containers, designated by reference numeral 1. The machine 1 comprises several assemblies 2a, 2b, 2c, 2d, 2e, each of which is assigned an electric drive unit 3. The electric drive unit 3 can, in particular, be an electric motor, preferably a servo motor. The drive units 3 are each coupled to a assembly 2a-2e, i.e., each assembly 2a-2e is driven by a drive unit 3. It is understood that other configurations are also encompassed by the invention, for example, that an assembly 2a-2e is coupled to several drive units 3 or that several assemblies 2a-2e are driven by a single drive unit 3.Machine 1 further comprises at least one analysis module 4, or machine 1 has at least one interface via which it can be connected to an analysis module 4. Using the analysis module 4, the frequency spectrum of a measured quantity characterizing the electrical power consumption of a drive unit 3, for example, the electrical current flowing through the drive unit 3, can be determined. This frequency spectrum can be evaluated in an analysis step and analyzed for any errors that may occur. This can be done automatically by the analysis module 4 itself, or the analysis module 4 can have a graphical user interface, such as a display or monitor, with which the frequency spectrum can be displayed. This allows operating or maintenance personnel to evaluate the frequency spectrum and detect any errors by changes in the frequency spectrum. Preferably, the analysis module 4 is configured to compare the frequency spectrum of the measured quantity with a previously recorded reference frequency spectrum. The analysis module 4 determines the deviation of at least one spectral component of the frequency spectrum from a corresponding spectral component of the previously recorded reference frequency spectrum. If the deviation exceeds a defined threshold, the analysis module can generate a fault detection signal. The threshold can be an absolute value, i.e., for example, an amplitude value assigned to a specific frequency. Alternatively, the threshold can be defined as a relative threshold, such that, for example, exceeding the amplitude values ​​of the reference frequency spectrum by a defined percentage leads to the generation of a fault detection signal. In the embodiment shown in Figure 1, each drive unit 3 is assigned a control unit 5, which controls the respective drive unit 3. The control units 5 can contain control electronics by means of which the rotational speed, acceleration, and / or angular position of a drive shaft of the drive unit 3 can be controlled. In particular, the drive unit 3 can be a servo drive. The control unit 5 can be configured, in particular, to determine the time course of a measured quantity characterizing the electrical power consumption of the drive unit, for example, the electric current flowing through the electric drive unit 3. The control unit 5 is preferably coupled to the analysis module 4 via a data line 6 for data exchange. The control unit 5 can, for example, transmit time-dependent amphdum measurements of the respective measured quantity to the analysis module 4 via this data line 6. This data transmission can be live or continuous, i.e., the determined time-dependent amphdum measurements are transmitted directly to the analysis module without intermediate storage. Alternatively, the control unit 5 can also include a storage unit in which the determined amphdum measurements are temporarily stored before being transmitted to the analysis module 4.This allows, for example, the transmission of the determined time-dependent amplitude measurements after a definable time interval or upon the occurrence of definable conditions that trigger the transmission (e.g., a specific machine state). According to the embodiment shown in Figure 1, the determined time-dependent amplitude measurements are, for example, each assigned to a drive unit 3; that is, independent time-dependent amplitude measurements of the quantity characterizing the electrical power consumption of the drive unit are determined for each drive unit 3. The analysis module 4 is preferably designed for the spectral analysis of the received measured quantities assigned to the respective drive units 3. In particular, the analysis module 4 can determine a frequency spectrum by transforming the received time-dependent amphduda measurements of the measured quantity into the frequency domain. This spectrum is assigned to the respective drive units 3 and contains information regarding the vibration content of the measured quantity. For example, a drive unit 3 of the machine 1 may experience an increased point load at periodic intervals, leading to a periodically increased power consumption of the respective drive unit 3, i.e., in particular, an increase in the electric current flowing through the drive unit 3. This could, for example, be caused by bearing damage or by a position-dependent collision of a machine element moved by the drive unit 3.These periodic load fluctuations lead to periodic fluctuations in the power consumption of the respective drive unit 3 and thus to periodic fluctuations in the current flowing through the electric drive unit 3. The transformation of the time-dependent measured quantity into the frequency domain therefore results in a peak in the frequency spectrum of this measured quantity, i.e., a spectral peak at a defined frequency that corresponds to the periodicity with which the power fluctuations occur (f = 1 / T, where T is the period of the power fluctuation ([s]) and f is the frequency [Hz]). The transformation of the time signal into the frequency domain can be carried out by any transformation method known from the prior art, in particular by a Fourier transform or a Laplace transform.In the event that the control units provide 5 time-discrete amplitude values ​​of the measured quantity, a discrete transformation procedure, for example a discrete Fourier transform (DFT), can be performed. The analysis module 4 can, in particular, receive the time-dependent measured value separately for each drive unit 3 and thus determine a frequency spectrum for this time-dependent measured value separately for each drive unit 3. If one of the determined frequency spectra has a spectral component that lies above a defined threshold value, the analysis module 4 preferably generates a fault detection signal. Optionally, a localization signal can also be generated, indicating which drive unit 3 caused the generation of the fault detection signal. This makes it possible to locate a fault more quickly. In one embodiment, it is possible to determine the frequency spectrum continuously or quasi-continuously (for example, by introducing delays due to data transmission and frequency spectrum calculation) based on the time course of the measured quantity, and to perform a continuous or quasi-continuous comparison with a reference frequency spectrum. Alternatively, it is possible to determine the frequency spectrum of the measured quantity characterizing the power consumption of the drive unit at regular time intervals, and to perform the comparison with the frequency spectrum at regular time intervals as well. The reference frequency spectrum can, in particular, be a frequency spectrum recorded when the machine was new and stored in a dedicated storage unit. This storage unit can be located within the analysis module 4 or be an external storage unit to which the analysis module 4 is connected and which the analysis module 4 can access to perform the spectral comparison. Alternatively or additionally, this storage unit can contain several reference frequency spectra recorded at different times in the past. For example, one reference frequency spectrum can be the frequency spectrum of a drive unit 3 recorded when the machine was new, and the other reference frequency spectra can be the frequency spectra of this drive unit 3 recorded at specific time intervals or after a specific operating period.This allows the temporal progression of the change in the frequency spectrum over time to be determined, making it easier to detect gradually occurring errors. Figure 2 shows an alternative embodiment of the machine 1, which also has a plurality of drive units 3 that are coupled to the assemblies 2a-2e. Unlike the embodiment shown in Figure 1, each group of drive units 3 is assigned a control unit 5; that is, one control unit 5 controls several drive units 3. The control units 5 can separately acquire a measured quantity characterizing the electrical power consumption of each drive unit 3 in the group of drive units 3, or they can determine a common measured quantity for the entire group of drive units 3, reflecting the summed power consumption of this group of drive units 3.The measured quantity is preferably a time-dependent signal, in particular the amplitude or magnitude of the electric current flowing through the respective drive unit 3 or the group of drive units 3. As already described with reference to Figure 1, the time-dependent measured quantity(ies) is transmitted to the analysis module 4, which is configured to transform the time-dependent measured quantity into the frequency domain. The resulting frequency spectrum can thus be assigned to a group of drive units 3. The functionality of the control units 5 and the analysis module 4 otherwise corresponds to the functionalities described above with reference to Figure 1. Figures 3 to 5 show exemplary frequency spectra 10, 11, 12 of the electric current received by a drive unit 3, where the abscissa represents the respective frequencies [Hz] and the coordinate represents the amplitudes or magnitudes of the current [A].The spectrum shown in Figure 3 is, in particular, a reference frequency spectrum 10, which was recorded, for example, when a machine 1 was new and corresponds, for example, to the frequency spectrum of the electric current flowing through a drive unit 3. The reference frequency spectrum 10 already shows several peaks at different frequencies. Figures 4 and 5 show different frequency spectra 11, 12, which, for example, each reflect the spectral profile of the electric current drawn by a drive unit 3 after a longer operating period of a machine 1. As a comparison of the frequency spectra between Figure 3 and Figure 4 shows, the frequency spectrum 11 shown in Figure 4 exhibits a higher ripple, i.e., several peaks occur at different frequencies.Particularly noticeable is the peak marked with the arrow, which has increased significantly compared to the reference frequency spectrum 10 shown in Figure 3. A threshold curve 7, which specifies threshold values ​​as a function of frequency, can be associated with the reference frequency spectrum 10 from Figure 3. Preferably, the threshold curve 7 is fitted to the reference frequency spectrum 10, i.e., the spectral response of the amplitude of the measured quantity. The threshold curve 7 can be formed by a multitude of frequency-dependent threshold values, i.e., threshold values ​​each assigned to a defined frequency, with the magnitudes of these threshold values ​​being adapted to the amplitude of the spectral component at that defined frequency. For example, the threshold value can be defined by a percentage value indicating by what percentage the threshold value of the spectral component lies above the amplitude of that spectral component.In the event that a spectral component of the spectrum exceeds this spectral threshold curve 7, an error detection signal is generated. By assigning the reference frequency spectrum 10 and the frequency spectra 1 1 , 12 to a defined drive unit 3 or to a group of drive units 3, a localization or a rough localization of the fault can be carried out, since a suddenly occurring or increasing peak in the frequency spectrum 1 1 , 12 indicates an increased power consumption of the drive unit 3 assigned to this frequency spectrum 1 1 , 12, and is thus attributable to a defect in the assembly 2a - 2e coupled to this drive unit 3. Further fault localization can be carried out based on the frequency at which the peak occurs in the frequency spectrum 1 1 , 12. This frequency allows conclusions to be drawn about components within the assembly 2a - 2e that, for example, move at a frequency corresponding to the frequency at which the spectral peak occurs. Figure 5 shows another example of an occurring error, again at the location indicated by the arrow, using a further frequency spectrum 12. As a comparison with the reference frequency spectrum 10 according to Figure 3 shows, a new peak has appeared in the region of approximately 125 Hz, i.e., a peak not present in the reference frequency spectrum 10, which is attributable to an occurring error. If this peak exceeds a defined threshold value or the threshold curve 7, an error detection signal is generated. The invention has been described above using several exemplary embodiments. It is understood that numerous modifications and variations are possible without departing from the underlying inventive concept. Reference symbol list 1 machine 2a - 2e assembly 3 Drive unit 4 Analysis module 5 Control unit 6 data lines 7 Threshold value curve 10 Reference frequency spectrum 1 1 , 12 Frequency spectrum

Claims

Patent claims 1. Method for detecting faults in a machine (1) comprising at least one electrical drive unit (3) for driving an assembly (2a - 2e) of the machine (1), characterized in that the frequency spectrum of a measured quantity characterizing the electrical power consumption of the drive unit (3) is determined and that in an analysis step the frequency spectrum of the measured quantity is evaluated with regard to anomalies indicating faults.

2. Method according to claim 1, characterized in that the frequency spectrum (1 1 , 12) is compared with a reference frequency spectrum (10) and that if at least one spectral component of the frequency spectrum (1 1 , 12) deviates from the reference frequency spectrum (10), an error detection signal is generated.

3. A method according to claim 1, characterized in that the machine (1) comprises a plurality of drive units (3), that for several or all of these drive units (3) the frequency spectrum (1, 1, 12) of a measured quantity characterizing the electrical power consumption of the drive unit (3) is determined, and that in an analysis step the frequency spectra of the measured quantities are evaluated with regard to anomalies indicating errors.

4. A method according to claim 3, characterized in that the frequency spectra (1, 1, 12) are each compared with a reference frequency spectrum (10) and that if at least one spectral component of the respective frequency spectrum (1, 1, 12) deviates from the reference frequency spectrum (10), an error detection signal and / or a localization signal characterizing the respective drive unit (3) is generated.

5. Method according to claim 1 or 2, characterized in that the at least one frequency spectrum (1 1 , 12) is determined continuously or at regular time intervals.

6. Method according to one of claims 2, 4 or 5, characterized in that the reference frequency spectrum (10) is a frequency spectrum recorded when the machine is new.

7. Method according to one of the preceding claims, characterized in that amplitude values ​​of the spectral components of the determined frequency spectrum (1 1 , 12) are compared with threshold values ​​assigned to these spectral components and that, if at least one threshold value is exceeded, the error detection signal is generated by the amplitude value assigned to this threshold value.

8. Method according to one of the preceding claims, characterized in that the frequency spectrum (1 1 , 12) of the measured quantity characterizing the electrical power consumption of the drive unit (3) is derived from the temporal The amplitude profile of this measured quantity is obtained by transforming it into the frequency domain.

9. Method according to one of the preceding claims, characterized in that the temporal change of the frequency spectrum (1 1 , 12) is determined based on several reference frequency spectra recorded in the past at different times.

10. Method according to one of the preceding claims, characterized in that the measured quantity characterizing the electrical power consumption of the drive unit (3) is the electric current. 1 1 . Method according to one of the preceding claims, characterized in that the measured variable characterizing the electrical power consumption of the drive unit (3) is obtained by analyzing a measured variable characterizing the electrical power consumption of the entire machine (1 ), by analyzing a measured variable characterizing the electrical power consumption of a group of drive units (3) and / or by analyzing a measured variable characterizing the electrical power consumption of a single drive unit (3).

12. Method according to one of the preceding claims, characterized in that a control unit (5) is assigned to each drive unit (3) or a group of drive units (3) and the time course of the measured quantity characterizing the electrical power consumption of the drive unit and / or the frequency spectrum of this measured quantity is provided by the control unit (5).

13. Device for detecting faults in a machine (1) comprising at least one electrical drive unit (3) for driving an assembly (2a-2e) of the machine (1), characterized in that an analysis module (4) is provided by means of which the frequency spectrum (1 1 , 12) of a measured quantity characterizing the electrical power consumption of the drive unit (3) is determined and evaluated with regard to anomalies indicating faults.

14. Device according to claim 13, characterized in that the frequency spectrum is compared with a reference frequency spectrum (10), wherein the Analysis module (4) for determining the deviation of at least one spectral component of the frequency spectrum (11, 12) from the reference frequency spectrum (10) and for generating a fault detection signal.

15. Device according to claim 13, characterized in that the machine (1) comprises a plurality of drive units (3), and that one or more analysis modules (4) are provided, by means of which the frequency spectrum of a measured quantity characterizing the electrical power consumption of the drive unit (3) is determined for several or all of these drive units (3) and evaluated with regard to anomalies indicating faults.

16. Device according to claim 15, characterized in that the frequency spectra (1 1 , 12) are compared with a reference frequency spectrum (10) by the at least one analysis module (4). 1 / . Device according to claim 16, characterized in that the analysis module (4) is configured to generate a fault detection signal and / or a localization signal characterizing the respective drive unit (3) when at least one spectral component of the respective frequency spectrum (1 1 , 12) deviates from the reference frequency spectrum (10).

18. Device according to one of claims 13 to 17, characterized in that the analysis module (4) for determining the temporal change of the frequency spectrum (1 1 , 12) is designed based on several reference frequency spectra (10) recorded in the past at different times.

19. Device according to one of claims 13 to 18, characterized in that each drive unit (3) or a group of drive units (3) has a is assigned to the control unit (5) and the time course of the measured quantity characterizing the electrical power consumption of the drive unit (3) and / or the frequency spectrum (1 1 , 12) of this measured quantity is provided by the control unit (5).