Abstract: A computer-implemented method, a computer-implemented apparatus, a system and a computer program product for determining an operating state of an industrial production process, includes providing process data, which is associated with the production process, to at least one first trained neural network, wherein the first neural network comprises at least one anomaly identification model and the process data is provided to each at least one anomaly identification model as well as determining, at least partially based on the first trained neural network, whether the process data is assignable to a predefined operating state and providing a first indicator, which is indicative of whether the process data is assignable to an operating state.

Abstract: A control unit, an operating method and a self-monitoring sensor which is fastenable to a measurement object includes a holder projecting radially from the measurement object, wherein at least one sensor element is held in the holder and the sensor element is fixed by a compressive force exerted by an elastic element, where a first detector for detecting the compressive force is arranged in the region of the elastic element to monitor the installation of the self-monitoring sensor, where the self-monitoring sensor is initial provided in an active operating state, where the compressive force acting on the sensor element is detected, where an improper installation state of the self-monitoring sensor is identified if the compressive force detected in the second step falls below an adjustable threshold value, and where a warning about the improper installation state is output to a user and/or a superordinate control unit.

Abstract: An ultrasound flowmeter that comprises at least one ultrasound emitter and at least one ultrasound receiver. The ultrasound emitter is configured to emit an ultrasound burst and the ultrasound receiver is configured to capture the ultrasound burst or the reflection of the ultrasound burst. The ultrasound flowmeter further comprises a control unit that is configured to determine a reception quality parameter based on the captured ultrasound burst or the captured reflection of the ultrasound burst, respectively. The ultrasound flowmeter further comprises a driving means for altering a distance between the ultrasound emitter and the ultrasound receiver. The method for operating the flowmeter comprises determining the at least one reception quality parameter and altering the distance between the ultrasound emitter and the ultrasound receiver until the reception quality parameter reaches an optimized value.

Abstract: A temperature measuring system comprising temperature measuring device, a computer program product suitable for simulating an operating behavior of such a temperature measuring device, and a temperature measuring device for non-invasively measuring a temperature of a medium in a pipe includes a sensor holder and a heat coupling element configured for producing a heat conducting path from a wall of the pipe to a first temperature sensor, wherein the heat coupling element is configured for adjusting the heat conducting path in a layered structure with components composed of different materials where, alternatively or supplementarily, the heat coupling element has an arcuate profile at least sectionally for the purpose of axially reversing the heat conducting path.

Abstract: Method and system for diagnosing messages generated during operation of a technical plant, wherein data sets and a predetermined self-organizing map are used to determine diagnostic statements on the operation of the plant, n-tuples corresponding to the data sets and containing predetermined values for process variables for error-free operation of the plant are stored at nodes of the self-organizing map, after a message has occurred minimum distances between data sets of the current time interval and data sets of the nodes of the self-organizing map are determined, and the corresponding node(s) is/are selected, symptoms are then determined by calculating differences between the data sets of the time intervals and the previously determined node(s), only differences of process variables exceeding a predefined threshold value being taken into account, and where process variables involved in previously determined symptoms are output such that a plant operator is supported in diagnosing a process message.

Abstract: The invention relates to a computer-implemented method for monitoring a prediction system, wherein the prediction system is configured to predict at least one process variable of a machine based on at least one measured value. The method comprising a first step, in which the machine is being run and the at least one measured value is received. The measured value substantially simultaneously fed into the prediction system and an anomaly detection algorithm. In a second step, an anomaly parameter is obtained from the anomaly detection algorithm. In a third step, an unreliable state of the prediction system is detected when the anomaly parameter exceeds a threshold. During a fourth step, a warning is output to at least one of a user or a data interface. The invention also relates to a computer program product that is configured to perform the claimed computer-implemented method and a machine installation on which such a computer program product is run.

Abstract: A control unit, an operating method and a self-monitoring sensor which is fastenable to a measurement object includes a holder projecting radially from the measurement object, wherein at least one sensor element is held in the holder and the sensor element is fixed by a compressive force exerted by an elastic element, where a first detector for detecting the compressive force is arranged in the region of the elastic element to monitor the installation of the self-monitoring sensor, where the self-monitoring sensor is initial provided in an active operating state, where the compressive force acting on the sensor element is detected, where an improper installation state of the self-monitoring sensor is identified if the compressive force detected in the second step falls below an adjustable threshold value, and where a warning about the improper installation state is output to a user and/or a superordinate control unit.

Abstract: Method for monitoring operation of a technical object, wherein a) a first orientation of the first acceleration sensor in the form of a position vector is determined, b) the mathematical model for operation of the object is generated and trained, c) the first acceleration sensor is disassembled and a three-axis replacement acceleration sensor is assembled with a new orientation on the object, d) acceleration values are detected, e) respective indicator values are calculated from the temporal course of the detected acceleration values of the replacement acceleration sensor, f) a replacement vector is determined from the indicator values and a differential vector between the replacement vector and the position vector of the first acceleration sensor determined in step b) is determined, and g) the model during operation of the object for the position vector in the orientation of the replacement vector is applied by taking into account the differential vector.

Abstract: A temperature measuring system comprising temperature measuring device, a computer program product suitable for simulating an operating behavior of such a temperature measuring device, and a temperature measuring device for non-invasively measuring a temperature of a medium in a pipe includes a sensor holder and a heat coupling element configured for producing a heat conducting path from a wall of the pipe to a first temperature sensor, wherein the heat coupling element is configured for adjusting the heat conducting path in a layered structure with components composed of different materials where, alternatively or supplementarily, the heat coupling element has an arcuate profile at least sectionally for the purpose of axially reversing the heat conducting path.

Abstract: A method for calibrating a temperature measuring device, a computer program product for simulating an operating behavior of the temperature measuring device and a temperature measuring device for non-invasively measuring a temperature of a medium in a tube, wherein the temperature measuring device includes first and second temperature sensors that are accommodated in a sleeve that has a closure for contacting a wall of the tube.

Abstract: A computer-implemented method for operating a technical device with a model based on artificial intelligence including detecting a first operating parameter of a reference apparatus in a first operating environment and a first permissible operating mode, detecting a second operating parameter of the reference apparatus in a second operating environment and a second permissible operating mode, performing a first Fourier transform for the first sensor signal and a second Fourier transform for the second sensor signal, determining a quotient from the first and second Fourier transforms as a transfer function, generating and training a first model based on artificial intelligence for the reference apparatus in the first operating environment, generating a second model based on artificial intelligence for the technical device in the second operating environment using the first model and applying the transfer function, and operating the technical device with the second model.

Abstract: Method and system for predicting the operation of a technical installation in which a process-engineering process having a process step runs, wherein datasets are acquired and stored in a memory and, during a learning phase, a self-organizing map is learned, symptom threshold values and associated tolerances are ascertained and stored for each neuron per SOM and all permissible temporal profiles of victor neurons are ascertained and stored per process step or batch for all timestamps, where a time starting from which operation of the technical installation should be predicted is determined during an evaluation phase, a victor neuron profile for the overall process step or batch is ascertained using current datasets of a process step via learned victor neuron profiles, and values, stored in neurons of this victor neuron profile, of the process variables are displayed after the previously determined time as a predicted profile.

Abstract: A temperature measurement facility for determining a medium temperature of a medium from first and second temperatures at a location immediately around a surface surrounding the medium includes a first and second sensors for determining the first and second temperatures, and a measured value processor connected to the first and second sensors by a first and second feed lines and which provides, cyclically over time, at a measurement interval the first and second temperatures as the measured value for determining the medium temperature, wherein an evaluator is configured to determine a rate of change, from a difference between the first and second temperatures, and depending on its value configured to provide a quality feature, and is further configured to transmit the quality feature, as an evaluation of a measurement accuracy of the medium temperature, together with the measured value of the medium temperature, to a higher-level system.

Abstract: Method and system for diagnosing messages generated during operation of a technical plant, wherein data sets and a predetermined self-organizing map are used to determine diagnostic statements on the operation of the plant, n-tuples corresponding to the data sets and containing predetermined values for process variables for error-free operation of the plant are stored at nodes of the self-organizing map, after a message has occurred minimum distances between data sets of the current time interval and data sets of the nodes of the self-organizing map are determined, and the corresponding node(s) is/are selected, symptoms are then determined by calculating differences between the data sets of the time intervals and the previously determined node(s), only differences of process variables exceeding a predefined threshold value being taken into account, and where process variables involved in previously determined symptoms are output such that a plant operator is supported in diagnosing a process message.

Abstract: A method and system for analyzing the cause of faults in a process engineering installation, wherein engineering information of the engineering installation, where the information contains information about the engineering installation components as well as their interconnection in the engineering installation, is provided in digital form in order to use the engineering information to create an inference model in the form of a probabilistic physical model of the engineering installation with probability distributions and prior variables, where measurement data from the engineering installation are used to perform Bayesian inference of fault probabilities during a diagnosis mode of the inference model.

Abstract: Method for monitoring operation of a technical object, wherein a) a first orientation of the first acceleration sensor in the form of a position vector is determined, b) the mathematical model for operation of the object is generated and trained, c) the first acceleration sensor is disassembled and a three-axle replacement acceleration sensor is assembled with a new orientation on the object, d) acceleration values are detected, e) respective indicator values are calculated from the temporal course of the detected acceleration values of the replacement acceleration sensor, f) a replacement vector is determined from the indicator values and a differential vector between the replacement vector and the position vector of the first acceleration sensor determined in step b) is determined, and g) the model during operation of the object for the position vector in the orientation of the replacement vector is applied by taking into account the differential vector.

Abstract: A diagnostic device for monitoring the operation of a technical plant with an automation system, wherein the diagnostic device includes a data memory in which at least one data set characterizing the operation of the plant with values of process variables can be stored, and an evaluation device, where the diagnostic device is characterized in that the evaluation device is configured to determine a diagnostic statement about the operation of the technical plant based on the data set and at least one self-organizing map and based on a program for controlling a sequence during the operation of the technical plant with repeatedly traversed step sequences via a Dynamic Time Warping method.

Abstract: A diagnosis method, a diagnosis system, a process-engineering plant and a training method for the diagnosis system, wherein course over time of plant data, which at least partially characterizes the plant status, is provided and a plant status is classified with the aid of a plurality of models based on the course over time of the plant data, where each model of the plurality of models differs with respect to a time window from which the plant data are based, a confidence is allocated to each classification that result from the at least two models, and where diagnosis information based on the classifications of the plant status and the confidences allocated thereto is output.

Abstract: A diagnostic device and diagnostic method for monitoring operation of a technical system with an automation system, wherein values of process variables, which were previously automatically determined as relevant to a diagnosis by analyzing a program for a sequential function chart, are determined when each step of the cycle to be checked is executed and evaluated based on at least one predetermined self-organizing map acquired based on fault-free cycles during a system operation with repeatedly run step sequences such that automatic preselection of the process variables is which are relevant to the diagnosis is performed such that misdiagnoses can advantageously and largely be avoided and the reliability of the diagnostic statement can be increased.

Abstract: A method for automatically determining a parameterization of an evaluation method via a computer includes generating a comparison data set and storing reference data in the generated comparison data set, stipulating a parameterization with which identification of particular partial data items of reference data items stored in the comparison data set is influenceable via the evaluation method, such that a relative number of partial data items identified during the evaluation in relation to all the reference data items stored in the generated comparison data set is quantitatively smaller than a predetermined threshold value, preferably smaller than 10%, preferably smaller than 5%, particularly preferably smaller than 1%, and providing the determined parameterization for performing the evaluation method to identify particular partial data items of the data set of the industrial plant.