DE102023109794A1 - Method for monitoring the condition of a machine, system, computer program - Google Patents

Abstract

The invention relates to a method for monitoring the condition of a machine, wherein the machine has a sensor system which comprises a vibration and/or temperature sensor for measuring a machine vibration and/or a temperature of the machine, and a trigger sensor, wherein the sensor system can be operated in a learning mode and in a condition monitoring mode.

Description

The invention relates to a method for determining a machine condition, in particular for monitoring the condition of a machine. The invention further relates to a corresponding system and computer program.

Vibration-based condition monitoring or temperature-based condition monitoring typically use sensors with cables, which usually results in quite expensive systems and methods. One of the main reasons for this is that manual installation of such sensors, including installation and protection of the cables, is time-consuming. More cost-effective condition monitoring can be realized by using wireless vibration- or temperature-based condition monitoring systems. Such systems, especially the sensors, are usually battery-powered. The typical battery life of wireless battery-powered vibration sensors, for example, is about 5 years.

In such traditional systems, the battery-powered wireless vibration sensors measure data on a schedule. For example, KPI's (Key Performance Indicators), such as ISO vibration severity 10-1000 Hz RMS, are measured every 4 hours and raw data every 24 hours. However, such measurements performed on a fixed schedule can result in insufficient data quality and detrimental condition monitoring for a wide range of different machines and applications, such as machines that do not operate continuously or machines with different operating states or modes or conditions, since the measurement data is often obtained when the machine is not running or is in an operating mode that is not suitable for condition monitoring.

Against this background, the DE 10 2021 129 363 B3 a method that provides a condition monitoring mode in which a measurement is only performed if a machine signal obtained from a separate trigger sensor has previously exceeded a predetermined trigger threshold. The trigger threshold is determined during a learning phase of the sensor system in which learning data is measured and compared with a predetermined standard trigger threshold. Depending on this predetermined standard trigger threshold, an optimized trigger threshold for the sensor system is determined during the learning phase. However, it proved difficult and laborious to set the predetermined standard trigger threshold to a value that ensures a properly functioning sensor system in condition monitoring mode.

Against this background, the object of the invention is to provide an improved condition monitoring of a machine, in particular such that an improved condition monitoring can be achieved for non-continuously operating machines or machines with different operating states or modes or conditions.

• - einen Schwingungs- und/oder Temperatursensor zur Messung einer Maschinenschwingung und/oder einer Temperatur der Maschine, und
• - einen Trigger-Sensor;

wobei das Sensorsystem in einem Lernmodus und in einem Zustandsüberwachungsmodus betreibbar ist,
wobei das Verfahren die folgenden Schritte umfasst:

• --- a) Betreiben des Sensorsystems im Lernmodus zur Bestimmung einer Auslöseschwelle für den Auslösesensor, bevor das Sensorsystem im Zustandsüberwachungsmodus betrieben wird, wobei der Betrieb des Sensorsystems im Lernmodus die folgenden Schritte umfasst:
  • -- in einem Lernmessschritt wird der Triggersensor periodisch gemäß einem vordefinierten Zeitintervall aktiviert, um jedes Mal eine Maschinenvibration und/oder Temperaturprobe der Maschine zu messen und die Maschinenvibration und/oder Temperaturprobe in einer Speichereinheit des Sensorsystems als Lerndaten zu speichern,
  • -- in einem Schritt zur Berechnung der Auslöseschwelle werden die im Lernmodus gewonnenen Lerndaten zur Bestimmung der Auslöseschwelle verwendet, die im Zustandsüberwachungsmodus des Sensorsystems zu verwenden ist, insbesondere in Schritt b);
• --- b) Betreiben des Sensorsystems im Zustandsüberwachungsmodus, wobei das Betreiben des Sensors im Zustandsüberwachungsmodus die folgenden Schritte umfasst:
  • -- in einem Triggerschritt misst der Triggersensor ein Maschinensignal der Maschine,
  wobei ein Vergleich zwischen dem Maschinensignal und der Triggerschwelle durchgeführt wird, wobei in Abhängigkeit von dem Vergleich zwischen dem Maschinensignal und der Triggerschwelle der Schwingungs- und/oder Temperatursensor in einen Messzustand zur Durchführung eines Messschrittes überführt wird,
  • -- in dem Messschritt misst der Schwingungs- und/oder Temperatursensor ein Maschinenschwingungs- und/oder Temperatursignal der Maschine zur Bestimmung des Zustandszustandes der Maschine.

To achieve the object, the invention proposes a method for determining a machine condition, in particular for monitoring the condition of a machine, wherein the machine comprises a sensor system, wherein the sensor system comprises:

• - a vibration and/or temperature sensor for measuring a machine vibration and/or a machine temperature, and
• - a trigger sensor;

wherein the sensor system is operable in a learning mode and in a condition monitoring mode,
the method comprising the following steps:

• --- (a) operating the sensor system in learning mode to determine a trigger threshold for the trigger sensor before operating the sensor system in condition monitoring mode, wherein operating the sensor system in learning mode comprises the following steps:
  • -- in a learning measurement step, the trigger sensor is periodically activated according to a predefined time interval to measure a machine vibration and/or temperature sample of the machine each time and to store the machine vibration and/or temperature sample in a storage unit of the sensor system as learning data,
  • -- in a trigger threshold calculation step, the learning data obtained in the learning mode are used to determine the trigger threshold to be used in the condition monitoring mode of the sensor system, in particular in step b);
• --- b) operating the sensor system in condition monitoring mode, wherein operating the sensor in condition monitoring mode comprises the following steps:
  • -- in a trigger step, the trigger sensor measures a machine signal from the machine,
  wherein a comparison is made between the machine signal and the trigger threshold, wherein depending on the comparison between between the machine signal and the trigger threshold, the vibration and/or temperature sensor is transferred to a measuring state for carrying out a measuring step,
  • -- in the measuring step, the vibration and/or temperature sensor measures a machine vibration and/or temperature signal of the machine to determine the condition of the machine.

According to the invention, it is possible for the measuring step to be carried out in the condition monitoring mode of the sensor system depending on the machine signal obtained by the trigger sensor and a previously determined trigger threshold. The trigger threshold is determined during a learning phase of the sensor system carried out in step a). It is possible for the trigger threshold to be adapted to the respective sensor system and the respective machine as well as to the environmental influences and noises to which the sensor system is exposed in its application. By using the trigger threshold, the data quality of the machine vibration and/or temperature signal for condition monitoring can be improved, since the amount of data measured at times when the machine is not operating or not in a state useful for condition monitoring can be advantageously reduced. This makes it possible to collect data from valid machine states while minimizing the collection of data points outside of these states. At the same time, the overall energy consumption for condition monitoring can be reduced, so that the battery life of the sensors is extended or the energy harvesting power is sufficient to operate the sensors. In general, within the scope of the present invention, it is possible to minimize the processing and transmission of unnecessary data, thereby reducing costs and saving energy.

It is an advantage of the present invention that the improved condition monitoring that can be achieved by the learning mode according to the invention can be realized in an automated manner that requires neither expert knowledge nor user input. This is achieved by the learning measurement step according to the invention, in which the vibration and/or temperature sensor is periodically activated after a predefined time interval to measure a machine vibration and/or temperature signal of the machine. These measured values recorded at periodic points in time are stored in a storage unit of the sensor system as learning data and then used in the trigger threshold calculation step to derive a trigger threshold suitable for the sensor system. This is particularly advantageous for sensor systems that are produced in large quantities. Even if identical sensor systems are used for several identical machines, the individual operating conditions and the influences of the environment are typically different for each individual machine and each sensor system. With the help of the present invention, an individually learned trigger threshold can be determined automatically for each individual sensor system and each individual machine, thereby improving the quality of the condition monitoring and avoiding expert and user input.

According to the invention, the learning data periodically measured by the vibration and/or temperature sensor consists of a large number of individual machine vibration and/or temperature samples, wherein the samples are taken at separate times. By taking only individual samples at periodic times, the amount of learning data recorded can be reduced compared to the amount from the DE 10 2021 129 363 B3 known methods. As a result, it is possible to store the learning data locally in a memory of the sensor system instead of transferring the learning data to a system outside the sensor system, e.g. to a backend system, and storing it there.

According to a preferred embodiment of the present invention, in the step of learning measurement, the vibration and/or temperature sensor does not measure any machine vibration and/or temperature signal of the machine between the periodic activations. The vibration and/or temperature sensor can be deactivated between the periodic measurements so that the power consumption of the vibration and/or temperature sensor can be reduced to a minimum.

According to a preferred embodiment of the present invention, the learning measurement step is carried out for a predetermined period of time, wherein after the predetermined period of time has elapsed, the learning data is analyzed and, depending on the analysis of the learning data, the learning measurement step is extended by a predetermined extension time. This approach is based on the knowledge that a certain number of samples must be measured in the learning measurement step in order to obtain usable learning data for determining the trigger threshold. By analyzing the learning data after the predetermined period of time has elapsed, it can be checked whether the operating state of the machine is covered by the learning data. If the analysis shows that the learning data does not adequately cover the operating state of the machine, the learning measurement step can be extended by the predetermined extension time. The extension time allows more learning data to be collected and increases the probability that the learning data correctly covers the operating state of the machine.

According to a preferred embodiment of the present invention, the step of calculating the trigger threshold is carried out by the sensor system, in particular by a computing device of the sensor system, preferably by a computing device of the vibration and/or temperature sensor. By carrying out the trigger threshold calculation step by a computing device of the sensor system, the data transfer to external computing devices can be reduced. In particular, it is not necessary to first transmit the learning data to an external computing device, have the external computing device calculate the trigger threshold and transmit the calculated trigger threshold to the sensor system. Consequently, in particular in installations with multiple sensor systems, the network traffic due to the calculation of the trigger threshold in the learning mode can be reduced.

According to a preferred embodiment of the present invention, in the step of calculating the trigger threshold, a metric is calculated that quantifies a scatter of the learning data - wherein the metric in particular quantifies the scatter of the learning data recorded while the machine was most likely in the operating mode - and the trigger threshold is calculated as a function of the metric, preferably as a predetermined fraction of the metric. The calculation of the metric that quantifies the scatter of the learning data enables the derivation of the trigger threshold with little additional effort. The trigger threshold can be calculated as a function of the metric, e.g. as a predetermined fraction of the metric.

According to a preferred embodiment of the present invention, the learning data and/or the trigger threshold determined in the trigger threshold calculation step are sent to a backend system - in particular via a gateway unit. This optional embodiment has the advantage that the trigger threshold calculation carried out locally by the computing means of the sensor system can be supplemented by computing means of the backend system. The backend system can be implemented using a cloud, for example.

• statistische Methoden, und/oder
• - maschinelles Lernen, und/oder
• - künstliche Intelligenz.

Preferably, the determined trigger threshold is validated in the backend system. Validation in the backend system can be achieved by using the learning data obtained in the learning mode and by using: -

• statistical methods, and/or
• - machine learning, and/or
• - artificial intelligence.

If the trigger threshold determined by the sensor system can be validated by the backend system, no adjustments are required and the sensor system can operate in condition monitoring mode without any further input from the backend system. On the other hand, if the trigger threshold calculated by the sensor system is not validated by the backend system, the backend system can calculate an appropriate trigger threshold based on the learning data provided to the backend system. The backend system may comprise more efficient computing means compared to the computing means of the sensor system, which may implement more precise algorithms and/or techniques for calculating the trigger threshold. Alternatively, if the trigger threshold calculated by the sensor system is not confirmed by the backend system, a user of the sensor system may be informed and prompted to manually set the trigger threshold for the sensor system.

According to the invention, it is possible for the state of the machine to be determined by means of or based on the machine vibration signal and/or temperature signal of the machine measured by the vibration and/or temperature sensor, in particular in the state monitoring mode of the sensor system in step b). Advantageously, the machine signal of the trigger sensor can be used to detect whether the machine is in operation, in particular whether the machine is in operation, so that a state of the machine can be determined. In particular, in step b), by comparing the machine signal (of the trigger sensor) with the trigger threshold, it is determined whether the machine is in operation, in particular whether the machine is in an operating state, so that the state of the machine can be determined. Preferably, only when it is determined that the machine is in such an operating state is the vibration and/or temperature sensor triggered in such a way that the vibration and/or temperature sensor is activated and/or transferred to a measuring state for measuring the vibration and/or temperature signal.

It is conceivable that the condition of the machine relates, for example, to whether the machine has a defect or is showing signs of wear. Such effects can be detected in the vibration and/or temperature signal of the machine or by means of the vibration and/or temperature signal of the machine.

Preferably, it is conceivable that the vibration and/or temperature sensor comprises at least one MEMS (microelectromechanical system) for measuring a machine vibration signal. Preferably, it is conceivable that the trigger sensor comprises at least one MEMS (microelectromechanical system) for measuring a machine vibration signal.

In the context of the present invention, the trigger threshold may be a trigger threshold value.

According to one embodiment, it is preferred that in step b) (i.e. in the condition monitoring mode of the sensor system), depending on the comparison between the machine signal measured by the trigger sensor and the trigger threshold, the vibration and/or temperature sensor is transferred from an off state or idle state to the measuring state, so that a measuring step is carried out by means of the vibration and/or temperature sensor. Preferably, the vibration and/or temperature sensor is deactivated in the off state or idle state of the vibration and/or temperature sensor, so that the vibration and/or temperature sensor does not measure the machine vibration and/or temperature signal of the machine. It is particularly preferred that in the off state or idle state of the vibration and/or temperature sensor, the energy consumption of the vibration and/or temperature sensor is lower than in the measuring state.

• -- eine Baumaschine, insbesondere ein Kran,
• -- eine Bergbaumaschine,
• -- eine Landmaschine,
• -- eine Bearbeitungsmaschine,
• -- Logistikmaschine, insbesondere Regalbediengerät,
• -- Transportmaschine, insbesondere U-Bahn, Eisenbahn oder Zug
• -- Pumpe oder Förderer in einer Zellstofffabrik.

According to the present invention, it is preferred that the machine is a non-continuously operating machine and/or a machine with different operating states or modes or conditions. For example, it is conceivable that the machine comprises or is a:

• -- a construction machine, in particular a crane,
• -- a mining machine,
• -- an agricultural machine,
• -- a processing machine,
• -- Logistics machine, in particular storage and retrieval machine,
• -- transport machine, especially subway, railway or train
• -- Pump or conveyor in a pulp mill.

Alternatively, it can also be a continuously operating machine.

According to an embodiment of the present invention, the sensor system may be part of the machine or attached to the machine or to a component of the machine. The exact position of the sensor system may depend on the type of machine.

Preferably, the vibration and/or temperature sensor and the trigger sensor are wireless sensors that include energy storage and/or energy generation devices. For example, it is conceivable that the vibration and/or temperature sensor and/or the trigger sensor include one or more batteries. It is conceivable that the trigger sensor is a component or subcomponent of the vibration and/or temperature sensor. It is conceivable that the trigger sensor is used and/or operated at least partially independently of the rest of the vibration and/or temperature sensor. However, it is also possible that according to the present invention the trigger sensor and the vibration and/or temperature sensor are separate sensors.

• - der Triggersensor zur Messung einer Maschinenschwingung der Maschine ausgebildet, wobei vorzugsweise das vom Triggersensor im Triggerschritt und/oder im Lerntriggerschritt gemessene Maschinensignal ein Triggerschwingungssignal der Maschine ist; und/oder
• - der Triggersensor zur Messung eines elektrischen Signals der Maschine, insbesondere eines elektrischen Stroms und/oder einer elektrischen Spannung, ausgebildet, wobei vorzugsweise das vom Triggersensor im Triggerschritt und/oder im Lerntriggerschritt gemessene Maschinensignal ein elektrisches Signal der Maschine ist. Besonders bevorzugt ist es, dass der Triggersensor ein Schwingungssensor, insbesondere ein MEMS-Schwingungssensor,

ist, der zur Messung einer Maschinenschwingung der Maschine ausgebildet ist. Es ist weiter bevorzugt, dass der Triggersensor eine geringere Abtastrate aufweist als der Schwingungs- und/oder Temperatursensor. So ist es beispielsweise möglich, dass die Abtastrate des Triggersensors unter 100 Hz, vorzugsweise bei oder unter 50 Hz, besonders bevorzugt bei oder unter 10 Hz liegt. Dadurch kann der Energieverbrauch gering gehalten werden. Besonders bevorzugt ist es, dass der Triggersensor im Betrieb einen geringeren Energieverbrauch aufweist als der Vibrations- und/oder Temperatursensor. Gemäß einer alternativen Ausführungsform ist es z.B. denkbar, dass der Triggersensor ein elektrischer Sensor ist, der zur Messung einer elektrischen Größe, z.B. eines Stroms und/oder einer Spannung, der Maschine ausgebildet ist.According to a preferred embodiment of the present invention,

• - the trigger sensor is designed to measure a machine vibration of the machine, wherein preferably the machine signal measured by the trigger sensor in the trigger step and/or in the learning trigger step is a trigger vibration signal of the machine; and/or
• - the trigger sensor is designed to measure an electrical signal of the machine, in particular an electrical current and/or an electrical voltage, wherein the machine signal measured by the trigger sensor in the trigger step and/or in the learning trigger step is preferably an electrical signal of the machine. It is particularly preferred that the trigger sensor is a vibration sensor, in particular a MEMS vibration sensor,

which is designed to measure a machine vibration of the machine. It is further preferred that the trigger sensor has a lower sampling rate than the vibration and/or temperature sensor. For example, it is possible for the sampling rate of the trigger sensor to be below 100 Hz, preferably at or below 50 Hz, particularly preferably at or below 10 Hz. This allows energy consumption to be kept low. It is particularly preferred that the trigger sensor has a lower energy consumption during operation than the vibration and/or temperature sensor. According to an alternative embodiment, it is conceivable, for example, that the trigger sensor is an electrical sensor which is designed to measure an electrical variable, e.g. a current and/or a voltage, of the machine.

• -- eine Wartezeit abgewartet wird, bevor der Vibrations- und/oder Temperatursensor in den Messzustand übergeht und/oder bevor der Vibrations- und/oder Temperatursensor das Maschinenvibrations- und/oder Temperatursignal im Messschritt misst, und/oder
• -- eine Voranalyse zur Verifizierung oder Überprüfung, dass die Maschine in Betrieb ist und/oder zur Verifizierung oder Überprüfung, dass die Maschine in einem Betriebszustand ist, durchgeführt wird,

wobei vorzugsweise der Vibrations- und/oder Temperatursensor erst nach Ablauf der Wartezeit und/oder nur für den Fall, dass die durchgeführte Voranalyse ergibt, dass die Maschine in Betrieb und/oder in einem Betriebszustand ist, in den Messzustand übergeht und/oder mit der Messung des Maschinenvibrations- und/oder Temperatursignals im Messschritt beginnt. Der Maschinenstabilisierungsalgorithmus wird vorzugsweise in Schritt b) eines Verfahrens gemäß einer Ausführungsform der vorliegenden Erfindung durchgeführt, d.h. wenn das Sensorsystem im Condition Monitoring Modus betrieben wird. So ist es beispielsweise möglich, dass im Rahmen der Voranalyse das Maschinensignal des Triggersensors analysiert wird, um zu überprüfen, ob die Maschine in Betrieb ist. Wenn die Maschine in Betrieb ist, wird der Messschritt durchgeführt. So ist es beispielsweise möglich, dass im Rahmen der Voranalyse durch Rechenmittel der Maschine geprüft wird, ob die Maschine in Betrieb ist. Wenn die Maschine in Betrieb ist, wird der Messschritt durchgeführt.According to a preferred embodiment of the present invention, before the transition of the vibration and/or temperature sensor to the measuring state and/or before the vibration and/or temperature sensor measures the machine vibration and/or temperature signal in the measuring step, a machine stabilization algorithm is carried out, in particular by means of computing means of the trigger sensor and/or computing means of a gateway unit and/or computing means of the machine, wherein the machine stabilization algorithm comprises:

• -- a waiting time is waited before the vibration and/or temperature sensor goes into the measuring state and/or before the vibration and/or temperature sensor measures the machine vibration and/or temperature signal in the measuring step, and/or
• -- a preliminary analysis is carried out to verify or check that the machinery is in operation and/or to verify or check that the machinery is in an operating condition,

wherein preferably the vibration and/or temperature sensor only changes to the measuring state and/or begins measuring the machine vibration and/or temperature signal in the measuring step after the waiting time has elapsed and/or only in the event that the preliminary analysis carried out shows that the machine is in operation and/or in an operating state. The machine stabilization algorithm is preferably carried out in step b) of a method according to an embodiment of the present invention, ie when the sensor system is operated in condition monitoring mode. For example, it is possible that the machine signal of the trigger sensor is analyzed as part of the preliminary analysis in order to check whether the machine is in operation. If the machine is in operation, the measuring step is carried out. For example, it is possible that the machine signal of the trigger sensor is checked as part of the preliminary analysis using the machine's computing means. If the machine is in operation, the measuring step is carried out.

• eine Dauer für die Messung des Maschinensignals der Maschine im Triggerschritt,
• - eine Abtastrate für die Messung des Maschinensignals der Maschine im Triggerschritt,
• - eine Wiederholrate oder ein Intervall oder eine Tageszeit oder eine Wochenzeit für die Durchführung des Triggerschritts, insbesondere für die Messung des Maschinensignals der Maschine im Triggerschritt,
• - ein oder mehrere Parameter des Maschinenstabilisierungsalgorithmus, insbesondere eine Dauer der Wartezeit. Der oder die Parameter werden vorzugsweise unter Verwendung der im Lernmodus in Schritt a) gewonnenen Lerndaten und unter Verwendung von: - statistische Verfahren, und/oder
• - maschinelles Lernen, und/oder
• - künstliche Intelligenz. Dabei können nicht nur die Auslöseschwelle, sondern auch weitere Parameter für den Betrieb des Sensorsystems im Zustandsüberwachungsmodus auf Basis der im Lernmodus gewonnenen Lerndaten bestimmt oder berechnet werden.

According to a preferred embodiment of the present invention, the learning data obtained in the learning mode are additionally used to determine one, some or all of the following parameters to be used in the condition monitoring mode, in particular in step b): -

• a duration for measuring the machine signal of the machine in the trigger step,
• - a sampling rate for measuring the machine signal of the machine in the trigger step,
• - a repetition rate or an interval or a time of day or a time of week for performing the trigger step, in particular for measuring the machine signal of the machine in the trigger step,
• - one or more parameters of the machine stabilization algorithm, in particular a duration of the waiting time. The parameter or parameters are preferably determined using the learning data obtained in the learning mode in step a) and using: - statistical methods, and/or
• - machine learning, and/or
• - artificial intelligence. Not only the trigger threshold, but also other parameters for the operation of the sensor system in condition monitoring mode can be determined or calculated based on the learning data obtained in learning mode.

• - eine Dauer für die Messung des Maschinensignals der Maschine im Lerntriggerschritt,
• - eine Abtastrate für die Messung des Maschinensignals der Maschine im Lerntriggerschritt,
• - eine Wiederholrate oder ein Intervall oder eine Tageszeit oder eine Wochenzeit für die Durchführung des Lerntriggerschritts, insbesondere für die Messung des Maschinensignals der Maschine im Lerntriggerschritt,
• - einen oder mehrere Parameter des Maschinenstabilisierungsalgorithmus, insbesondere eine Dauer der Wartezeitperiode.

According to an embodiment of the present invention, it is advantageously possible for the sensor system and/or the machine - preferably before and/or during operation of the sensor system in learning mode - to be provided with predefined values for one, some or all of these parameters:

• - a duration for measuring the machine signal of the machine in the learning trigger step,
• - a sampling rate for measuring the machine signal of the machine in the learning trigger step,
• - a repetition rate or an interval or a time of day or a time of week for performing the learning trigger step, in particular for measuring the machine signal of the machine in the learning trigger step,
• - one or more parameters of the machine stabilization algorithm, in particular a duration of the waiting period.

The predefined values of the mentioned parameters can be used in the learning mode, especially in step a).

According to a preferred embodiment of the present invention, during and/or after the measurement of the machine vibration and/or temperature signal by means of the vibration and/or temperature sensor in the measuring step, an acceptance test is carried out by means of an acceptance criterion for the measured machine vibration and/or temperature signal, wherein the measured machine vibration and/or temperature signal is only used to determine the machine condition if the acceptance criterion is met.

According to a preferred embodiment of the present invention, it is conceivable that the acceptance test is carried out by computing means of the vibration and/or temperature sensor, wherein the measured machine vibration and/or temperature signal is only transmitted from the vibration and/or temperature sensor and/or from the computing means of the vibration and/or temperature sensor to a gateway instance if the acceptance criterion is met. In particular, it is possible for the vibration and/or temperature sensor and/or the computing means of the vibration and/or temperature sensor not to transmit the measured machine vibration and/or temperature signal if the acceptance criterion is not met. This makes it possible to minimize the energy consumption of the communication means used to transmit the measured machine vibration and/or temperature signal from the vibration and/or temperature sensor to the gateway instance, since it is avoided that unusable data or data with insufficient quality are transmitted.

According to a preferred embodiment of the present invention, the acceptance criterion comprises an acceptance threshold, wherein the acceptance test comprises monitoring whether the measured machine vibration and/or temperature signal, in particular during the measurement of the machine vibration and/or temperature signal, falls below the acceptance threshold for a predefined number of consecutive samples of the measured machine vibration and/or temperature signal, wherein preferably the acceptance criterion is not met if the measured machine vibration and/or temperature signal falls below the acceptance threshold for the predetermined number of consecutive samples, wherein preferably the acceptance criterion is met if the measured machine vibration and/or temperature signal does not fall below the acceptance threshold during the duration of a measurement time interval for the predetermined number of consecutive samples. It is conceivable that the measurement time interval is a predefined measurement time interval. The measurement time interval can, for example, be chosen or selected by an operator and/or can depend on the machine and/or the operating conditions of the machine. For example, the measurement time interval can be in the order of seconds, e.g. 3 seconds or 5 seconds. Alternatively, it is conceivable that the duration of the measurement time interval is determined using the learning data obtained in the learning mode of the sensor system in step a). It is particularly preferred that when the acceptance threshold of the measured machine vibration and/or temperature signal is undershot, the number of consecutive samples (e.g. the number of consecutive individual measured values) of the machine vibration and/or temperature signal is counted as long as the measured machine vibration and/or temperature signal remains below the acceptance threshold and/or does not rise above the acceptance threshold. It is conceivable that this counting of the consecutive samples of the measured machine vibration and/or temperature signal is canceled and/or reset when the measured machine vibration and/or temperature signal rises above the acceptance threshold. Preferably, when the measured machine vibration and/or temperature signal falls below the acceptance threshold again, the counting of the consecutive samples is started again from zero. If the number of consecutive samples reaches the predefined number of consecutive samples, the acceptance criterion is preferably not met. Preferably, the acceptance criterion is met if the number of consecutive samples does not reach the predefined number of consecutive samples.

• -- in Reaktion auf den Empfang eines weiteren Triggersignals durch den Vibrations- und/oder Temperatursensor, insbesondere von dem weiteren Sensor und/oder der Rechnereinrichtung, wobei das weitere Triggersignal anzeigt, dass sich die Maschine nicht im Betriebszustand befindet und/oder aus dem Betriebszustand übergegangen ist und/oder dass ein stabiler Arbeitszustand der Maschine beendet ist; und/oder
• -- als Reaktion auf den Empfang eines weiteren Triggersignals durch den Vibrations- und/oder Temperatursensor von dem Triggersensor, wobei das weitere Triggersignal anzeigt, dass sich die Maschine nicht in dem Betriebszustand befindet und/oder aus dem Betriebszustand übergegangen ist und/oder dass ein stabiler Arbeitszustand der Maschine beendet ist; und/oder
• -- wenn ein Messzeitintervall verstrichen ist; und/oder
• -- wenn eine vordefinierte Gesamtzahl von Abtastungen des Maschinenvibrations- und/oder Temperatursignals erhalten wurde.

According to a preferred embodiment of the present invention, it is conceivable that the measurement of the machine vibration and/or temperature signal by means of the vibration and/or temperature sensor is terminated in the measuring step:

• -- in response to the receipt of a further trigger signal by the vibration and/or temperature sensor, in particular from the further sensor and/or the computer device, wherein the further trigger signal indicates that the machine is not in the operating state and/or has transitioned from the operating state and/or that a stable operating state of the machine has ended; and/or
• -- in response to the receipt of a further trigger signal by the vibration and/or temperature sensor from the trigger sensor, the further trigger signal indicating that the machine is not in the operating state and/or has transitioned from the operating state and/or that a stable operating state of the machine has ended; and/or
• -- when a measurement time interval has elapsed; and/or
• -- when a predefined total number of samples of the machine vibration and/or temperature signal have been obtained.

• einen Vibrations- und/oder Temperatursensor zum Messen einer Maschinenvibration und/oder einer Temperatur der Maschine, und
• - einen Triggersensor;

wobei das Sensorsystem in einem Lernmodus und in einem Zustandsüberwachungsmodus betreibbar ist,
wobei das System konfiguriert ist, um ein Verfahren gemäß einer Ausführungsform der vorliegenden Erfindung auszuführen.
Vorzugsweise ist das erfindungsgemäße System ein computerimplementiertes System, das Mittel zur Durchführung eines Verfahrens gemäß einer Ausführungsform der vorliegenden Erfindung umfasst.To achieve the above-mentioned object, the invention further proposes a system for determining determination of a machine condition, in particular for monitoring the condition of a machine, wherein the system comprises a sensor system, wherein the system optionally comprises the machine, wherein the sensor system can be attached to the machine or is contained in the machine,
wherein the sensor system comprises: -

• a vibration and/or temperature sensor for measuring a machine vibration and/or a temperature of the machine, and
• - a trigger sensor;

wherein the sensor system is operable in a learning mode and in a condition monitoring mode,
wherein the system is configured to perform a method according to an embodiment of the present invention.
Preferably, the system according to the invention is a computer-implemented system comprising means for carrying out a method according to an embodiment of the present invention.

To solve the above-mentioned problem, the invention further proposes a computer program containing instructions which, when the computer program is executed by one or more computer means - in particular by a sensor system and/or by a machine and/or by a gateway unit and/or by a backend system - cause the one or more computer means to carry out a method according to an embodiment of the present invention.

For the system according to the invention and the computer program according to the invention, the same embodiments, advantages and technical effects can be achieved that were described in connection with the method according to the invention or in connection with an embodiment of the method according to the invention.

• zeigt ein Beispiel für den Betrieb einer nicht kontinuierlich arbeitenden Maschine;
• zeigt ein System gemäß einer Ausführungsform der vorliegenden Erfindung;
• 3 zeigt eine schematische Darstellung des Betriebs eines Sensorsystems in einem Lernmodus zur Bestimmung einer Auslöseschwelle gemäß einer Ausführungsform der vorliegenden Erfindung;
• zeigt eine schematische Darstellung eines Verfahrens gemäß einer Ausführungsform der vorliegenden Erfindung;
• zeigt eine Schwingung v über der Zeit t einer Maschine zur Veranschaulichung einer Ausführungsform eines Verfahrens gemäß der vorliegenden Erfindung;
• 6A zeigt ein Verfahren gemäß einer Ausführungsform der vorliegenden Erfindung, bei dem die gemessenen Daten einen Akzeptanztest nicht bestehen;
• 6B zeigt ein Verfahren gemäß einer Ausführungsform der vorliegenden Erfindung, bei dem die gemessenen Daten einen Akzeptanztest bestehen.

These and other features, characteristics and advantages of the present invention will become apparent from the following detailed description, taken in conjunction with the accompanying drawings, which illustrate, by way of example, the principles of the invention. The description is intended to be illustrative only and is not intended to limit the scope of the invention. The reference numerals hereinafter refer to the accompanying drawings.

• shows an example of the operation of a non-continuous machine;
• shows a system according to an embodiment of the present invention;
• 3 shows a schematic representation of the operation of a sensor system in a learning mode for determining a trigger threshold according to an embodiment of the present invention;
• shows a schematic representation of a method according to an embodiment of the present invention;
• shows an oscillation v over time t of a machine to illustrate an embodiment of a method according to the present invention;
• 6A shows a method according to an embodiment of the present invention in which the measured data fails an acceptance test;
• 6B shows a method according to an embodiment of the present invention, in which the measured data passes an acceptance test.

1 shows an example of the operation of a non-continuously operating machine to illustrate disadvantages of the prior art. In the time intervals 910, 911, 912 the machine operates in such a way that condition monitoring can be carried out. Outside these time intervals the machine is switched off or is in an operating state that is not suitable for condition monitoring. According to the prior art, measurements for condition monitoring would be carried out at preconfigured points 900, 901, 902, 903, 904, 905, e.g. at regular time intervals. The measurements at points 900, 901, 902, 903, 904 would, however, be unsuitable for condition monitoring because they are carried out outside the time intervals 910, 911, 912, so that the overall result and quality of condition monitoring would be low. Such disadvantages can be overcome by the present invention.

In 2 a system according to an embodiment of the present invention is shown. A vibration and/or temperature sensor 10 and a trigger sensor 20 are attached to or contained in a machine 1. Preferably, the vibration and/or temperature sensor 10 is at least one vibration sensor 10. In an alternative embodiment, however, the vibration and/or temperature sensor 10 is a temperature sensor. Preferably, the machine 1 is a non-continuously operating machine 1, e.g. a processing machine, an agricultural machine, a logistics machine, in particular a storage and retrieval machine, a transport machine, in particular a subway or a railway or a train or the like. The vibration sensor 10 and/or the trigger sensor 20 are preferably wireless devices used for condition monitoring the machine 1. The vibration sensor 10 and the trigger sensor 20 comprise an energy storage and/or energy generation device. According to an embodiment of the present invention, the trigger sensor 20 can be part of the vibration sensor 10. Preferably, the trigger sensor 20 and the vibration sensor 10 comprise MEMS for measuring vibrations of the machine 1. A gateway unit 50 is in communication with the trigger sensor 20 and/or the vibration sensor 10. It is conceivable that the gateway unit 50 is part of the computing device of the machine 1 or that the gateway unit is a gateway unit 50 separate from the machine 1. The sensors 10, 20 and/or the gateway entity 50 can form a mesh network or be part of a mesh network. It is conceivable that the gateway entity 50 is connected to a backend system and/or a network 60, in particular a telecommunications network. Furthermore, it is possible for the system to comprise a user device 70, e.g. a computer or a mobile device, which displays data and/or the state of the machine. The respective devices of the system, in particular the vibration sensor 10, the trigger sensor 20 and/or the gateway unit 50, can have wireless communication means for communicating with each other and/or with the backend system and/or network 60. In particular, the sensor system comprising the vibration sensor 10 and the trigger sensor 20 can be operated in a learning mode for determining a trigger threshold for the trigger sensor 20 and in a condition monitoring mode in which the learned/determined trigger threshold is used. By means of the trigger sensor 20 and the vibration sensor 10, steps a) and b) of a method according to the present invention can be carried out. Embodiments thereof are e.g. in connection with the 3 , 4 , 5 , 6A and 6B described.

In 3 an embodiment of the operation of the sensor system in the learning mode for determining a trigger threshold for the trigger sensor 20 in step a) according to an embodiment of the present invention is shown schematically. First, a learning measurement step S21 is carried out in which the vibration and/or temperature sensor 10 is periodically activated after a predefined time interval in order to measure a machine vibration and/or temperature sample of the machine 1 and to store the machine vibration and/or temperature sample in a storage unit of the sensor system as learning data. In the learning measurement step S21, the vibration and/or temperature sensor 10 does not measure a machine vibration and/or temperature signal of the machine 1 between the periodic activations. The learning measurement step S21 is carried out for a predetermined duration, wherein after the predetermined duration has elapsed, the learning data is evaluated in an analysis step S22 and wherein, depending on the evaluation of the learning data, the learning measurement step is extended by a predetermined extension time. In particular, the learning measurement step is extended by the specified extension time if the analysis shows that the learning data does not sufficiently cover the operating state of the machine.

After completion of the learning measurement step S21, either with or without the aforementioned extension time, and before operating the sensor system in the condition monitoring mode, the sensor system is transferred to a trigger threshold calculation step S23. In the trigger threshold calculation step S23, the learning data obtained in the learning mode are used to determine the trigger threshold to be used in the condition monitoring mode of the sensor system. The trigger threshold calculation step S23 is performed by the sensor system, in particular by a computing device of the sensor system, preferably by a computing device of the vibration and/or temperature sensor 10. In the trigger threshold calculation step S23, a metric is calculated that quantifies a scatter of the learning data - the metric in particular quantifies the scatter of the learning data recorded while the machine was most likely in the operating mode - and the trigger threshold is calculated depending on the metric, preferably as a predetermined fraction of the metric.

Optionally, at the end of the trigger threshold calculation step S23, the learning data and/or the trigger threshold determined in the trigger threshold calculation step S23 are sent - in particular via a gateway unit 50 - to the backend system 60. The determined trigger threshold can then be validated in the backend system 60.

In 4 a method according to an embodiment of the present invention is shown schematically. In step S31, the sensor system is operated in the learning mode to determine a trigger threshold for the trigger sensor 20. The step S31 can, for example, replace the steps S21, S22 and S23 as in 3 shown. When the trigger threshold for the trigger sensor 20 has been determined, the sensor system is transferred to the condition monitoring mode and step S32 is carried out. Step S32 comprises the operation of the sensor system in the condition monitoring mode, wherein the operation of the sensor in the condition monitoring mode in step S32 comprises the following steps: In a trigger step, the trigger sensor 20 measures a machine signal of the Machine 1, wherein a comparison is carried out between the machine signal and the trigger threshold, wherein depending on the comparison between the machine signal and the trigger threshold the vibration and/or temperature sensor 10 is transferred to a measuring state for carrying out a measuring step.
In the measuring step, the vibration and/or temperature sensor 10 measures a machine vibration and/or temperature signal of the machine 1 to determine the state of the machine. In step S33, an acceptance test 303 is carried out for the measured machine vibration and/or temperature signal using an acceptance criterion, wherein the measured machine vibration and/or temperature signal is only used to determine the state of the machine 1 if the acceptance criterion is met. An embodiment of the acceptance test 303 is described using the 5 , 6a and 6b explained in more detail.

In 5 to illustrate an embodiment of a method according to the invention, a vibration v over time t of a machine 1 is shown. In particular, an embodiment of step b) of a method according to the invention is shown in which the sensor system is operated in a condition monitoring mode. When the trigger sensor 20 is in a trigger state, the trigger sensor 20 measures a machine signal of the machine 1, in particular a machine vibration. In the trigger state, the trigger sensor 20 measures the machine vibration with a comparatively low sampling rate, for example in the order of 10 Hz, in order to ensure low energy consumption. In the trigger step, a comparison is made between the measured machine signal and a trigger threshold so that an increase in the machine signal to and/or above the trigger threshold can be detected. The trigger threshold is a trigger threshold that was determined with the aid of the learning mode of the sensor system in step a). At a time 300, the trigger sensor 20 detects a vibration (ie a machine signal) that exceeds the trigger threshold. In response to this detection, the vibration sensor 10 is transferred from a rest or off state to a measuring state, e.g. by a command from the trigger sensor 20 or the gateway unit 50. It is possible that - before the vibration sensor 10 starts measuring the machine vibration signal of the machine 1 to determine the machine state - a machine stabilization algorithm 302 is executed. The machine stabilization algorithm 302 may include waiting for a waiting time 301 before the vibration sensor 10 goes into the measuring state and/or before measuring the machine vibration signal by means of the vibration sensor 10 is started. Alternatively or additionally, the machine stabilization algorithm 302 may include a pre-analysis to check or verify that the machine 1 is operating. For example, it is possible that the pre-analysis includes an analysis of the machine signal measured by the trigger sensor 20 in order to check or verify that the machine 1 is in operation. If the machine stabilization algorithm 302 has been successfully run through, the measurement of the machine vibration signal is carried out by means of the vibration sensor 10 in the measuring step, in particular for a measuring time interval 200. In the measuring step, the vibration sensor 10 measures individual samples and/or measured values that together form the machine vibration signal. During the measuring step and/or at the end of the measuring step, an acceptance test 303 can be carried out for the measured machine vibration signal. The acceptance test 303 can ensure that the data obtained have a sufficient or desired quality. Preferably, the measured data, i.e. the measured machine vibration signal, are only transmitted from the vibration sensor 10 to the gateway unit 50 or to the backend system and/or network 60 if the acceptance test is successfully passed. This makes it possible to achieve a particularly energy-efficient process. Preferably, the measured machine vibration signal is only used to determine the machine condition if the acceptance test 303 is passed.

An embodiment of the acceptance test 303 is described using the 6A and 6B explained in more detail. The acceptance test 303 comprises an acceptance criterion, in particular an acceptance threshold value 100. It is possible that the acceptance threshold value 100 is the same value as the trigger threshold or corresponds to the trigger threshold. During the acceptance test, it is monitored whether the measured machine vibration signal, in particular during the measurement of the machine vibration signal, falls below the acceptance threshold value 100 for a predetermined number of consecutive samples (in particular samples) of the measured machine vibration signal. If the measured machine vibration signal falls below the acceptance threshold value 100, the number of consecutive samples (e.g. the number of consecutive individual measured values) of the vibration signal is counted as long as the measured machine vibration signal remains below the acceptance threshold value 100. It is conceivable that this count of the consecutive samples of the measured machine vibration signal is canceled and/or reset if the measured Machine vibration signal rises above the acceptance threshold 100 again. Preferably, when the measured machine vibration signal falls below the acceptance threshold 100 again, the counting of the successive samples is started again at zero.

If the number of consecutive samples reaches the predefined number of consecutive samples, the acceptance criterion is not met and the acceptance test is not passed. This situation is in shown.

However, if the number of consecutive samples does not reach the predefined number of consecutive samples, the acceptance criterion is met and the acceptance test is passed. This situation is in In this case, the measured vibration signal of the machine is further used to determine the state of machine 1.

reference sign

1

machine

10

vibration and/or temperature sensor

20

trigger sensor

50

gateway unit

60

backend system and/or network

70

user device

100

acceptance threshold

200

measurement time interval

300

Point

301

waiting time

302

algorithm for machine stabilization

303

acceptance test

900 - 905

points

910 - 912

time intervals

S21 - S23

steps

S31 - S33

steps

t

Time

v

vibration

x

measurements

QUOTES INCLUDED IN THE DESCRIPTION

This list of documents listed by the applicant was generated automatically and is included solely for the better information of the reader. The list is not part of the German patent or utility model application. The DPMA accepts no liability for any errors or omissions.

Cited patent literature

• DE 102021129363 B3 [0004, 0009]

Claims (10)

Method for monitoring the condition of a machine (1), wherein the machine (1) has a sensor system, the sensor system having: - a vibration and/or temperature sensor (10) for measuring a machine vibration and/or a temperature of the machine (1), and - a trigger sensor (20); wherein the sensor system is operable in a learning mode and in a condition monitoring mode, wherein the method comprises the following steps: a) operating the sensor system in the learning mode to determine a trigger threshold for the trigger sensor (20) before operating the sensor system in the condition monitoring mode, wherein operating the sensor system in the learning mode comprises the following steps: - in a learning measurement step, the trigger sensor (20) is periodically activated according to a predefined time interval to measure a machine vibration and/or temperature sample of the machine (1) each time and to store the machine vibration and/or temperature sample in a storage unit of the sensor system as learning data, - in a step for calculating the trigger threshold, namely before operating the sensor system in the condition monitoring mode, the learning data obtained in the learning mode are used to determine the trigger threshold to be used in the condition monitoring mode of the sensor system, namely in step b); b) Operating the sensor system in condition monitoring mode, wherein operating the sensor in condition monitoring mode comprises the following steps: - in a trigger step, the trigger sensor (20) measures a machine signal of the machine (1), wherein a comparison is carried out between the machine signal and the trigger threshold, wherein depending on the comparison between the machine signal and the trigger threshold, the vibration and/or temperature sensor (10) is transferred to a measuring state for carrying out a measuring step, - in the measuring step, the vibration and/or temperature sensor (10) measures a machine vibration and/or temperature signal of the machine (1) for determining the state of the machine (1). procedure according to claim 1 , wherein the vibration and/or temperature sensor (10) does not measure any machine vibration and/or temperature signal of the machine (1) in the learning measurement step between the periodic activations. Method according to one of the preceding claims, wherein the learning measurement step is carried out for a predetermined duration, wherein after expiry of the predetermined duration the learning data are analyzed and wherein, depending on the analysis of the learning data, the learning measurement step is extended by a predetermined extension time. Method according to one of the preceding claims, wherein the step of calculating the trigger threshold is carried out by the sensor system, in particular by a computing device of the sensor system, preferably by a computing device of the vibration and/or temperature sensor (10). A method according to any preceding claim, wherein in the step of calculating the trigger threshold, a metric is calculated that quantifies a variance of the learning data, wherein the metric quantifies the variance of the learning data recorded while the machine was most likely in the operating mode and the trigger threshold is calculated as a function of the metric, preferably as a predetermined fraction of the metric. Method according to one of the preceding claims, wherein the learning data and/or the trigger threshold determined in the trigger threshold calculation step are sent to a backend system (60) - in particular via a gateway instance (50). procedure according to claim 6 , wherein the determined trigger threshold is validated in the backend system (60) or wherein the determined trigger threshold is not validated by the backend system (60), wherein the backend system (60) calculates a suitable trigger threshold based on the learning data provided to the backend system (60). Method according to one of the preceding claims, wherein the trigger sensor (20) is designed to measure a machine vibration of the machine (1), wherein preferably the machine signal measured by the trigger sensor (20) in the trigger step and/or in the learning trigger step is a trigger vibration signal of the machine (1); and/or wherein the trigger sensor is designed to measure an electrical signal of the machine (1), in particular an electrical current and/or a voltage, where preferably the machine signal measured by the trigger sensor (20) in the trigger step and/or in the learning trigger step is an electrical signal of the machine (1). System for monitoring the condition of a machine (1), the system comprising a sensor system, the system optionally monitoring the machine (1), wherein the sensor system is attachable to the machine (1) or is contained in the machine (1), wherein the sensor system comprises: - a vibration and/or temperature sensor (10) for measuring a machine vibration and/or a temperature of the machine (1), and - a trigger sensor (20); wherein the sensor system is operable in a learning mode and in a condition monitoring mode, wherein the system is configured to carry out a method according to any one of the preceding claims. Computer program with instructions which, when the computer program is executed by one or more computing means, namely by a sensor system and/or by a machine and/or by a gateway unit and/or by a backend system, cause one or more computing means to carry out a method according to one of the Claims 1 until 8 to execute.

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