WO2019077093A1

WO2019077093A1 - Method and system for evaluating an operating state of a watercraft

Info

Publication number: WO2019077093A1
Application number: PCT/EP2018/078676
Authority: WO
Inventors: Bastian Ebeling
Original assignee: Thyssenkrupp Marine Systems Gmbh; Thyssenkrupp Ag
Priority date: 2017-10-20
Filing date: 2018-10-19
Publication date: 2019-04-25
Also published as: DE102017124589A1

Abstract

The invention relates to a method for evaluating an operating state of a watercraft, the method comprising the following steps: providing historic measurement values in a data memory (6) that is coupled with a data processing system (1), wherein for at least a part of the historic measurement values, one historic measurement value each is assigned to an operating state; detecting a current measurement value by means of a measuring device (4); transmitting the current measurement value from the measuring device (4) to the data memory (6); determining, by means of a processor (2) of the data processing system (1), used operating states on the basis of the historic measured values, which are assigned to an operating state; assigning, by means of the processor (2), the current measurement value to one of the used operating states, and evaluating, by means of the processor (2), the current measurement value with reference to the assigned used operating state. The invention further relates to a system for evaluating an operating state of a watercraft.

Description

Method and system for evaluating an operating state of a watercraft

The invention relates to a method and a system for evaluating an operating state of a watercraft, in particular for determining a system state.

It is known to determine measured values of the systems in the case of influencing systems and to calculate the influencing by means of mathematical models. For example, a first motor and a second motor may be arranged close to each other, both of which cause vibrations during operation. In operation, the vibrations of the first motor are affected by the vibrations of the second motor. To monitor the operation of the two motors, the vibrations are measured. The influence of the vibrations of the second motor on the operation of the first motor is eliminated. For this purpose, a valid (and thus costly) modeling of the transmission paths is necessary, which may also change over time and must therefore be adapted.

The document US 2008/0 133 439 A1 discloses a device for monitoring the presence of an anomaly in a machine tool before and during its use, whereby also a failure of the machine tool is to be detected.

US 2017/0 059 332 A1 describes an apparatus and a method for determining a distance to an empty state (DTE) for a motor vehicle. The DTE is the remaining travel distance until a fuel tank or a battery on board the motor vehicle is empty. This remaining distance depends on the distance traveled, operating conditions of the vehicle and environmental conditions. An odometer (odometer) continuously measures the actual distance traveled. The driver is shown a predicted remaining distance as a function of the distance traveled so far and of various parameters. This prediction will from a computing unit on board the vehicle (Cluster Controller System 100) continuously updated. For the update, it is predicted which route will be covered at a certain time. If the actual traveled distance up to this time is smaller than the predicted driving distance, the parameters are adjusted and the retraced route is re-predicted. In one embodiment, the invention is used on board an electric car, and for the prediction of the remaining route, the available battery energy in kWh and the so-called efficiency (fuel efficiency in km / kWh), ie the quotient of distance traveled so far and used battery energy, used.

The object of the invention is to provide an improved technology for monitoring operating states. More particularly, it is an object of the present invention to provide a method and apparatus for automatically monitoring a craft which in many cases automatically detects a system condition other than a desired range without necessarily directly measuring that condition of the system.

This object is achieved by a method having the features specified in claim 1 and claim 1 1 and a system having the features specified in claim 21 and claim 22. Advantageous developments emerge from the subclaims, the following description and the drawings.

In one aspect, a method is provided for automatically monitoring a watercraft. For this purpose, an arrangement is used which comprises a measuring device and a data processing device with a processor and a data memory.

A first phase and a subsequent second phase are performed.

In the first phase, the measuring device measures a large number of first measured values on the vessel. The measuring system continues to measure for every first measured value a first operating state in which this first measured value occurs. In the data memory, a plurality of data records is stored. Each data record includes a first measured value (historical measured value) and the assigned first operating state (historical operating state).

In the second phase, the measuring device on the watercraft measures a second measured value (current measured value) and a second operating state (current operating state) in which this second measured value occurs. The processor determines in the data memory all or at least some of those stored data sets, each comprising a first operating state, wherein this first operating state deviates from the measured second operating state by no more than a predetermined tolerance. The processor compares the first measured values belonging to the determined data records with the measured second measured value. If this comparison satisfies a predetermined trigger criterion, the processor triggers the step that a signal is output.

In one aspect, a method for evaluating an operating condition of a watercraft is disclosed. The method comprises the following steps: provision of historical measured values in a data memory which is coupled to a data processing device, at least for a part of the historical measured values in each case a historical measured value being assigned to an operating state; Detecting, by means of a measuring device, a current measured value; Transmitting the current measured value from the measuring device to the data memory; Determining, by a processor of the data processing device, operating states used based on the historical measurement values associated with an operating state; Allocating, by means of the processor, the current measured value to one of the operating states used and evaluating, by means of the processor, the current measured value with reference to the assigned operating state used. In another aspect, a system for evaluating an operating condition of a watercraft is provided. The system has a data processing device with at least one processor, a data memory and a measuring device. The data memory is coupled to the data processing device. Historical measured values are provided in the data memory, wherein in each case at least for a part of the historical measured values a historical measured value is assigned to an operating state. The measuring device is set up to record a current measured value and to transmit the current measured value to the data memory. The processor is set up to determine operating states used on the basis of the historical measured values assigned to an operating state, to assign the current measured value to one of the operating states used and to evaluate the current measured value with reference to the assigned operating state used.

In this application, "operating state" is understood to mean one of a number of different and possible modes of operation, for example operation at the design limit, load-free operation or any state in between.

By "used operating states", this application is understood to mean a selection of operating states that are actually or predominantly used in the operation of the watercraft A "system state" is a state that the watercraft or a component assumes on its own without a targeted external intervention. A system condition is changed, for example, by wear or aging or cracking.

The current measured value can be assigned to a current operating state.

It can be provided that each historical measured value is assigned to an operating state.

The term "measured value" (historical measured value and / or current measured value) can refer both to a date from an automation and to a data series, for example, a vibration sensor, but the term should also be understood as a multiplicity of measured values during operation of the vessel by a Variety of transducers, data processing information or automation information.

The method allows monitoring of measured values and operating states. Among other things, statements about pending maintenance can be made. Furthermore, an evaluation of the operating states is possible.

The method is based on the assumption that identical operating states lead to identical measured values when the vessel is unchanged. If, for example, a component of the vessel is operated with a certain power, a first measured value is determined for this purpose. As long as the component is unchanged, each time the component is operated at the specified power, a currently determined metric should match historical values stored in the data memory for the first metric. If there is a deviation between the currently measured value and the historical values, this is an indication that the component has changed, for example due to wear.

The situation is similar with the operation of several components. In the simultaneous operation of a first component (eg, a first motor) and a second component (eg, a second motor), the influence of the second component on the first component can be determined without performing calculations. When the first component is operated at a first specific power and the second component is operated at a second specific power, the influence of the second component on the first component is always the same as long as the first component and the second component are unchanged. Thus, if at the first determined power and the second determined power actual measurements are determined that deviate from historical measurements of the first determined power and the second determined power, this is an indication that the first component and / or the second component is a different system state to have. Thanks to the invention, in many cases a system state can be determined without necessarily having to measure this system state directly. According to the above assumption, identical operating states lead to substantially identical measured values given constant system states. Therefore, the second measured value does not differ significantly (not outside the predetermined tolerance) from a stored first measured value that was determined at such a first operating state, which does not deviate significantly from the second operating state. If the second measured value thus deviates from a first measured value, even though the second operating state is substantially equal to the assigned first operating state, then this is an indication of a change in a system state.

The triggered signal preferably comprises a description of the second measured value, a description of the second operating state and optionally a description of the deviating first measured values and / or the substantially identical first operating states.

In one embodiment, the measuring device first measures the second measured value and the associated second operating state. Subsequently, a test is carried out in which the second measured value is compared with a predetermined desired range. At least when the second measured value is outside the setpoint range, the further steps of the second phase are carried out, ie the current measurement results (second measured value, second operating state) are compared with historical data sets. Thanks to this configuration, the further steps of the second phase are not carried out again after each measurement, which often requires too much computing capacity or too much running time. Rather, the further steps of the second phase, that is to say the comparison of the measurement results with historical data, are only carried out if the second measured value lies outside the desired range. The fact that the second measured value is outside the desired range may be due to an undesired or impermissible system state or else to a permissible, but for example, rarely occurring or extreme operating state. Thanks to the configuration, these two cases are automatically distinguished from each other. The method and system may also be used for facilities other than watercraft, such as land vehicles, aircraft, and industrial plants. Any device that has one or more operating states can be monitored with the technology.

The operating states can be obtained, for example, from an automation system. The operating conditions may be various driving modes such as "half power ahead" or "full power ahead", or a combat station. Each operating state can be provided with a time stamp, for example a UTC time stamp (UTC - Coordinated Universal Time).

Each historical measured value and / or the current measured value may be assigned a time stamp, for example a UTC time stamp. The measured values (historical measured values and the current measured value) can be, for example, a frequency or the frequency spectrum of a vibration, a temperature, a position (eg determined by means of GPS), a water depth, a water temperature, a direction of travel, a speed, an air pressure, an air temperature, a wind speed, on / off information to a component (eg, a pump); An on / off information on flaps and doors, flow rates or oil quality, eg number of particles in the oil, be. Several current measurements of the same size can be determined. It may also be provided to acquire several current measured values of different sizes. The particular operating states used (regularly used operating states) form a so-called cluster (English, see accumulation point) of measured values. Methods of cluster analysis, principal component analysis, artificial intelligence, a self-learning algorithm, methods of evaluating big data, and a combination thereof can be used to determine the operating conditions used. The aforementioned methods can furthermore be used to evaluate the measured values and / or the operating states used. It can be provided that the evaluation comprises a comparison of the current measured value with historical measured values of the assigned operating state used. The evaluation may include a comparison of the current measured value with a predetermined threshold value, wherein a signal is output when the current measured value deviates from the threshold value. The deviation can be an exceeding of the threshold value or an undershooting of the threshold value. It may also be provided a comparison with multiple thresholds. The threshold / thresholds can be determined by an algorithm. The signal may be an optical signal, an audible signal, a tactile signal, an olfactory signal and a combination thereof.

The evaluation may include determining a remaining useful life (also called RUL - remaining useful life). The remaining useful life may relate to the used operating state associated with the current measured value. Alternatively or additionally, a remaining service life for a different operating state can be determined.

It may further be provided that the evaluation comprises determining a change in the operating states used, wherein the change in the operating states used is determined taking into account a frequency of use. If it is determined that only a few selected operating states are actually used by several operating states stored in the automation system, the stored operating states can be adapted to the operating states used.

The evaluation can include the determination of a future use of one or more operating states, such that a threshold is not exceeded or undershot during future use (or several thresholds are not exceeded or undershot). For example, future use may include certain mission requirements and / or take into account required redundancy. The evaluation may include an anomaly detection. The method may include a prediction. An anomaly is a departure from expected behavior. The expectation is the so-called prediction of the method, for example: value remains constant as always. If an anomaly occurs (for example, an oscillation energy increases), it can be evaluated, if necessary by checking details (eg at which frequency / which frequencies is an increase). This can be an indicator of wear. The anomaly detection can be done by comparing table values.

Switching states between two operating states can be detected and evaluated.

Furthermore, it can be provided that a particular sequence used is detected and evaluated by operating states used.

When determining the operating states used, the current measured value can be evaluated. Clusters of the measured values can be determined in order to determine the operating states used. An accumulation point of a set is clearly a point that has an above-average number of points of the set in its vicinity. Each accumulation point can correspond to a used operating state. In one embodiment, each first data record is determined whose first operating state deviates from the measured second operating state by no more than the tolerance. In another embodiment, a first data set is only determined if the deviation of the operating states lies within the tolerance and, in addition, a predetermined selection criterion is fulfilled. This embodiment prevents a signal from being emitted too frequently. According to this embodiment, a signal is not output if the measured second measured value deviates only from a few stored first measured values. A deviant first Measured value can occur, for example, when the first measured value was measured during a rapid transition from one operating state to another operating state and therefore occurs only rarely. In one embodiment, it is predicted in which range of values a measured value measured by the measuring device will lie at a measuring time lying in the future. For this prediction, a time series is used which consists of stored first measured values and the measured second measured value. This prediction can be used to predict a remaining useful life. In one embodiment of this embodiment, based on the stored first operating states, it is estimated how often in the future which operating state will be set, and this estimate is used for the prediction of the range of values. The disclosed embodiments of the method may be provided according to the system and vice versa.

Below, the inventive method is explained in more detail with reference to an embodiment shown in the drawings. Hereby show:

Fig. 1 is a block diagram of a system;

Fig. 2 is a flow chart for an embodiment of the method;

Fig. 3 shows another embodiment of the method. 1 shows a block diagram of a system for evaluating an operating state of a watercraft. The system has a data processing device 1 which has a processor 2 and a memory 3. The data processing device 1 can be designed as a personal computer, server, laptop, tablet or smartphone. Furthermore, the system comprises a measuring device 4 with a measuring sensor 5. The measuring device 4 is configured to detect a measured value for a measured variable by means of the measuring sensor 5. The data processing device 1 and the measuring device 4 are provided with a Data memory 6, for example, a database, data-coupled. The data processing device 1 can also be coupled with the measuring device 4 in terms of data technology. A flowchart of a method is shown in FIG. Measured values are provided in the database 6 (step 10).

At least for a part of the historical measured values, a historical measured value is assigned to an operating state. Each historical measured value can also be assigned to an operating state. The assignment is also stored in the database. By means of the measuring device 4, a current measured value is detected (step 20). The current measured value is transmitted from the measuring device 4 to the data memory 6 (step 30). By means of the processor 2 of the data processing device 1, the operating states used are determined (step 40). Here, both the historical measured values that are assigned to an operating state and the current measured value can be taken into account. The current measured value is assigned to one of the operating states used (step 50). Finally, the current measured value is evaluated with reference to the assigned operating state used (step 60).

Another embodiment is shown in FIG.

An automation system 101 comprises data concerning various information, for example operating states, operating data and / or switching states. The automation system 101 may serve the user or personnel to assist the operation of the watercraft. An operating state may in this case be, for example, the following: "full load machine." The operating data may relate to various parameters of the watercraft engine, for example one or more internal combustion engines, for example a temperature at a bearing of the engine "and" off ". The information, in particular the operating states, are provided with a time stamp (eg a UTC time stamp) (step 102) and exported to a database 103.

In addition, a current measured value is acquired in a data collection (step 104). The current measured value can be converted into digital data by means of an analog-to-digital converter. The current measurement is assigned a timestamp (e.g., a UTC timestamp) (step 105). The current measured value is stored together with the time stamp in the database 103. Several current measured values can also be recorded and transmitted. This first phase can also be called data acquisition.

In a phase designated as data processing, accumulation points are determined for the data aggregate from historical measured values and the current measured value or values (step 106). This step is also called clustering. Each accumulation point corresponds to an actually used operating state (also called a cluster). The operating states used may be driving modes or a combat station or situation 107. The measured values are subjected to spectral analysis (step 108), for example by means of a fast Fourier transformation. If, for example, an aggregate of the watercraft, for example a turbocompressor, is active, for example at a speed of 18,000 rpm (= 300 rpm), then this rotational frequency can be discernible in the frequency spectrum which is for another (for example adjacent arranged), in which case a proportion with a frequency of 18,000 rpm with an amplitude of height x is measurable. If the turbo-compressor is not active, its rotation has no influence, the proportion of the ascertained amplitude at the frequency 18,000 rpm would be much less or not at all.

The operating conditions used and the results of the analysis are stored in the database 103.

Then the current operating state is determined. It is determined to which used operating state the current measured value (or the current measured values) belongs. The current measured value is assigned to the used operating state (cluster) (step 109). A learned cluster of historical data may be the basis for assigning a current state. Here, a confidence level can be provided, as well as a value for a cluster and, bordering on it, does not match one (or all other) clusters. For example, you can work with the silhouette value ("Silhouette clustering").

Furthermore, characteristic values are determined (step 1 10) and stored in the database. The characteristic values are, for example: acceleration a, velocity v, position s effective, peak height, peak position, maximum acceleration, RMS acceleration, vibration energy and radius of a motion ellipse. This phase is called state detection.

Measured values are measured values. Characteristic values are derived from one or more measured values. Characteristic values are, for example, energy values that were detected during a vibration measurement. Another possible characteristic value is the mean amplitude over for a frequency range, for example from 100 to 300 Hz, or the amplitude at 1 .000 Hz. It is determined how well the current operating state coincides with the assigned operating state used (step 1 1 1 ). In this step, exceptions can be treated, such as a switch from a first operating state to a second operating state or the use of a previously not considered operating state. The current measured value is compared with limit values (step 1 12) which may be specified by a manufacturer. This phase is also called health assessment. For example, the silhouettes value from the "Silhouette clustering" is usable.

Furthermore, it is determined how a common change (eg wear) per used operating state is (step 1 13). As vibration amplitudes increase, this indicates less round-going (machine) components. Wear can be as that Growth of amplitudes are understood. The more the amplitude increases, the greater the wear - the bearing can beat stronger.

The usual change (e.g., wear) per operating state used is combined with the frequency of use of the operating state (e.g., a driving profile). If, for example, it was determined from the history that 100 hours in a cluster "c" means an increase in amplitude of 1% (or even absolute), that is a statement. In cluster "d" it is for example only 1 per thousand. In this way, it can then be determined when, with further wear = increase in the amplitude, a limit value has been reached. If it is determined that there are deviations from a predetermined limit value, a signal is output (step 1 14).

It can also be determined a remaining useful life. For example, it can be determined how long cluster "c" can be used until the limit is reached. This phase can be called forecasting.

In a phase referred to as consultation generation, future usage is planned taking into account constraints 15 (e.g., mission requirements and / or required redundancy) (step 16). For example, in the case of a mission of the vessel, it may be required to cover 1, 000 nm (nautical miles). This could happen through 100 hours of operation in cluster "c" or through 150 hours in cluster "d". Since, as exemplified above, in cluster "d" the wear may be lower, now cluster "d" might now be the better choice, unless the demand to be at the target 50 hours faster requires a different decision. The mission may alternatively request to be back within 120 hours at the latest. Then 60 hours drive in cluster "c" and 60 hours drive in cluster "d" would be the recommendation.

This takes into account that no deviations from the limit value should occur or should be minimized. The exemplary minimization may affect other aggregates of the craft. Here it can be provided to minimize the wear (or exceed as few limits). Based on the analysis, a monitoring frequency, for example a frequency of the measured value acquisition, can be adapted (step 1 17). The frequency can be increased or decreased. For example, if a change in a measured value starts to get stronger, for example, because deviations of successive measured values exceed a threshold value, it can be checked more frequently.

It is also conceivable to evaluate, compare and use the data obtained in this way across vehicles (see Fleet Optimization). For example, if two units of vessels of different vitality, for example, different expected or projected remaining useful lives, are available, it may be provided that, for example, only one unit is still able to complete the mission (without maintenance in between). Another answer could be that both units would be able to - and then, for example, the less capable or vital can be used, for example, the unit that needs to undergo a (next) maintenance earlier, the supposedly better Keep the unit available for heavier duty.

The features disclosed in the above description, the claims and the drawings may be important both individually and in any combination for the realization of the various embodiments.

reference numeral

1 data processing device

2 processor

3 memory

4 measuring device

5 measuring sensor

6 data memory

10 Providing Historical Readings

20 Acquire a Current Reading

30 Transfer the current reading

40 Determining the operating states used

50 Assigning the current measured value to a used operating state

60 Evaluating the current measured value

101 automation system

102 Associate a timestamp with information

103 database

104 Acquire a Current Reading

105 Associate a timestamp to the current metric

106 Determining the operating states used (clustering)

107 operating states

108 Spectral analysis

Claims

claims

1 . Method for automatically monitoring a watercraft

using an arrangement that

- A measuring device (4) and

- A data processing device (1) with a processor (2) and a

Comprises data memory (6),

wherein, in a first phase of the method, the steps are carried out such that - the measuring device (4) on the watercraft a plurality of first

Measured values and for each first measured value in each case a first operating state in which this first measured value occurs, measures and

- In the data memory (6) a plurality of data sets is stored, each record comprises a first measured value and the associated first operating state, wherein in a temporally subsequent second phase of the method, the steps are performed

the measuring device (4) on the watercraft measures a second measured value and a second operating state in which this second measured value occurs,

- The processor (2) in the data memory (6) all or at least some

those stored records determined, each having a first

Include operating conditions that deviate from the measured second operating state by no more than a predetermined tolerance,

- The processor (2) the stored first measured values of the determined

Compare records with the measured second reading and

- The processor (2), when this comparison meets a predetermined triggering criterion, the output of a signal triggers.

2. The method according to claim 1,

characterized in that Each of the first and second modes of operation is each a value of a magnitude that correlates to a required electrical or mechanical or hydraulic power given to a component of the craft, and each first and second measurements is a measured value of magnitude associated with a vehicle correlates to the following sizes:

- a service which actually delivers this component at the respective required service,

a frequency or a frequency spectrum of a vibration of a component of this component,

a temperature of this component,

a proportion of a substance in a fluid, in particular an oil, which dispenses the component.

3. The method according to any one of the preceding claims,

characterized in that

the vessel comprises an influencing and an influencing component,

wherein the influencing component at least temporarily exerts a physical effect on the affected component,

wherein the operating conditions are measured at the influencing component and

wherein the measurements are effected by the affected component.

4. The method according to any one of the preceding claims,

characterized in that

additionally, in the first phase, the respective time at which a first measured value was measured,

as a time stamp of the respective data record together with the first measured value and the assigned first operating state in the data memory (6)

is stored and

the processor (2) determines in the determination of the data records those data sets whose first operating states - deviate from the measured second state of use by no more than the tolerance, and

- additionally satisfy a predetermined selection criterion, wherein a record meets the selection criterion when its first operating state has occurred at least for a predetermined minimum period of time.

5. The method according to claim 4,

characterized in that

the comparison satisfies the predetermined trigger criterion when

the measured second measured value deviates from a predefined minimum number of determined first measured values by more than one tolerance, or

the measured second measured value deviates from a predetermined minimum proportion of the determined first measured values in the totality of the stored first measured values by more than one tolerance, or

- the measured second measured value deviates from an average of the determined first measured values by more than one tolerance.

6. The method according to any one of the preceding claims,

characterized in that

the processor (2) in the second phase after the measurement of the second measured value and the second operating state

- Compares the second measured value with a predetermined target range and

- At least when the second measured value is outside the target range, the further steps of the second phase is performed.

7. The method according to any one of the preceding claims,

characterized in that

additionally, in the first phase, the respective time at which a first measured value is measured,

is stored as a time stamp of the respective data record together with the first measured value and the associated first operating state in the data memory (6) and In addition, in the second phase, the steps are performed such that the time at which the second measured value is measured is determined, the processor (2) at least when the comparison between the measured second measured value and the determined first measured values is a predetermined triggering time. Met criterion,

using the time stamps and first measured values belonging to the determined data records as well as the second measured value and the determined one

Time a series of measurements is generated and

- predicts, using the generated time series, a range of values in which the measured value measured by the measuring device (4) will lie at a measuring point in the future.

8. The method according to claim 7,

characterized in that

the processor (2)

determined by evaluation of the stored first operating states,

which temporal proportion the periods in which the vessel is operated in the measured second operating state have a total of the total useful life of the vessel, and

- the calculated time share for the prediction of the value range

used.

9. The method according to claim 7 or claim 8,

characterized in that

the processor (2)

using the generated time series and the predicted value range, predicts a remaining useful life of a DUT that effects the measured values of the time series and the predicted value range.

10.A method according to one of the preceding claims,

characterized in that the first phase is carried out before commissioning or during a port stay of the vessel, and

the second phase is carried out after commissioning or during use of the watercraft.

1 1. Method for evaluating an operating state of a vessel, comprising the following steps:

- Providing historical measured values in a data memory (6), which is coupled to a data processing device (1), wherein at least for a part of the historical measured values in each case a historical measured value

Operating status is assigned;

- Detecting, by means of a measuring device (4), a current measured value;

- Transferring the current measured value from the measuring device (4) to the data memory (6);

Determining, by means of a processor (2) of the data processing device, operating states used on the basis of the historical measured values which are respectively assigned to an operating state;

Assigning, by means of the processor (2), the current measured value to one of the operating states used and

- Evaluate, by means of the processor (2), the current measured value with reference to the assigned operating state used.

12. The method according to claim 1 1,

characterized in that

Evaluating a comparison of the current reading with historical

Measured values of the assigned operating state used.

13. The method of claim 1 1 or claim 12,

characterized in that

the evaluation comprises a comparison of the current measured value with a predetermined threshold value, wherein a signal is emitted when the current measured value deviates from the threshold value.

14. The method according to any one of claims 1 1 to 13,

characterized in that

evaluating comprises determining a remaining useful life.

15. The method according to any one of claims 1 1 to 14,

characterized in that

the evaluating comprises determining a change in the operating states used, wherein the change in the operating states used is determined taking into account a frequency of use.

16. The method according to any one of claims 1 1 to 15,

characterized in that

evaluating comprises determining a future use of one or more operating states, such that a threshold is not exceeded or undershot during future use.

17. The method according to any one of claims 1 1 to 16,

characterized in that

the evaluation includes an anomaly detection.

18. The method according to any one of claims 1 1 to 17,

characterized in that

the evaluation comprises a prediction.

19. The method according to any one of claims 1 1 to 18,

characterized in that

when determining the operating conditions used, the current measured value is evaluated.

20. The method according to any one of claims 1 1 to 19,

characterized in that Accumulation points of the measured values are determined in order to determine the operating states used.

21. System for automatically monitoring a watercraft,

being the system

- A measuring device (4) and

- A data processing device (1) with a processor (2) and a

Comprises data memory (6),

wherein the measuring device (4) is designed to measure a measured value on the watercraft and an operating state in which this measured value occurs,

wherein a plurality of data records are stored in the data memory (6), each data record each comprising a first measured value and the associated first operating status,

wherein the processor (2) is configured, after a measurement of a second measured value as well as a second operating state in which this second measured value occurs,

- in the data memory (6) all or at least some of those

stored records, each a first

the stored first measured values of the ascertained data sets with the

to compare measured second measured value and

- if this comparison satisfies a given triggering criterion,

Trigger a signal output.

22. A system for evaluating an operating condition of a watercraft, comprising:

a data processing device (1) having at least one processor (2), a data memory (6) which is coupled to the data processing device (1), wherein historical measured values are provided in the data memory (6), wherein in each case a historical measured value is assigned to an operating state for at least some of the historical measured values, and

a measuring device (4) which is set up to record a current measured value and to transmit the current measured value to the data memory (6), wherein the processor (2) is set up,

determine operating states used on the basis of the historical measured values which are assigned to an operating state,

- assign the current measured value to one of the operating states used, and

- evaluate the current measured value with reference to the assigned operating state used.