Abstract: Various embodiments of the teachings herein include an insulation system. An example includes a polymer blend in the form of a solid two-dimensional insulation material, a material for wire insulation by means of extrusion and/or an injection-molded and/or compression-molded article. The blend is resistant to partial discharges and at least partly replaces any mica content in the insulation system. The blend comprises at least three blend partners including at least one copolymer based on polyetherimide and siloxane blended with at least two high-temperature thermoplastics. At least of one the high-temperature thermoplastics is in semicrystalline form, such that spherulites are detectable in the polymer blend.

Abstract: A method for configuring a measurement application system is provided, the method comprising providing to a configuration device a system description data structure that defines, for one or more measurement application devices that are present in the measurement application system, properties, and constraints, and dependencies of properties, receiving for at least one of the properties a user input comprising a value to be set for the respective property, evaluating at least one of the constraints or dependencies based on the at least one value received via the user input, updating, if according to the evaluation the at least one of the constraints or dependencies are fulfilled, at the configuration device the system description data structure according to the at least one value received via the user input, and updating a configuration of the one or more measurement application devices according to the updated system description data structure.

Abstract: A method for generating comparison pairs and distributing them to individual comparison requests for experiment participants for subjective individual ratings of pair comparisons. The method includes: providing a data set comprising sensory samples; identifying potentially promising comparison samples for each sample based on a metric, wherein the metric is based on a relationship between a possible estimation of the rating by experiment participants and at least one quantitative characteristic of the sample; distributing a predetermined number of overall comparisons to the potentially promising comparison pairs; generating the comparison requests for experiment participants by assigning the comparison pairs to the comparison requests, taking into account the following conditions to the effect that each sample is not provided more frequently than once in a comparison request, each sample is equally often provided for predetermined subgroups of the entirety of all experiment participants.

Abstract: A method for adjusting a noise generated by a device. The method includes: ascertaining, for each device feature, a dependence of a contribution of the device feature to a noise evaluation characteristic number on the value of the device feature by training an EBM with combinations of values for the device features and, for each of the combinations, an associated value of the noise evaluation characteristic number, each of a plurality of decision trees of the EBM ascertaining a contribution to the noise evaluation characteristic number for a device that has the value for the device feature; ascertaining values of the device features for a device of which the noise is to be adjusted; ascertaining changes for one or more of the device features to the values of the device features for improving the noise evaluation characteristic number; and adjusting the device according to the ascertained changes.

Abstract: The present disclosure provides a method for operating a measurement system comprising at least one measurement application device, the method comprising receiving a sequence of control commands provided in the measurement system, automatically optimizing the recorded sequence of control commands for improving execution speed of the sequence of control commands in the measurement system, and controlling the measurement system based on the optimized sequence of control commands. Further, the present disclosure provides a respective measurement system controller, and a respective measurement system.

Abstract: The present disclosure provides a method for operating a measurement system that comprises at least one measurement application device and at least one device under test, the method comprising centrally configuring the measurement system for a test measurement, centrally verifying the correct setup of the measurement system, and performing the test measurement with the measurement system. In addition, the present disclosure provides a respective central test control unit and a respective measurement system.

Abstract: The invention relates to a method for removing a rotor (100) of a generator (4) in a turbine plant (1) in which the generator (4) is driven by at least one turbine (7), in particular a gas turbine or steam turbine, in which the turbine (7) is opened and the rotor (39) of the turbine (7) is removed, and only then is the rotor of the generator (4) pulled out of the generator (4) so that it is located in the lower housing half of the turbine (7).

Abstract: Machine learning is used to classify a pleasantness of a sound emitted from a device. A plurality of pleasantness ratings from human jurors are received, each pleasantness rating corresponding to a respective one of a plurality of sounds emitted by one or more devices. Differences between each pleasantness rating and each of the other pleasantness ratings is determined via pairwise comparisons. These differences are converted into binary values based on which pleasantness rating is higher or lower in each comparison. Measurable sound qualities are received associated with the sounds. Second differences between each of the measurable sound qualities and every other of the plurality of measured sound qualities is determined in pairwise fashion. A classification model is trained to classify sound pleasantness by comparing the binary values with the second differences.

Abstract: Machine learning is used to predict a pleasantness of a sound emitted from a device. A plurality of pleasantness ratings from human jurors are received, each pleasantness rating corresponding to a respective one of a plurality of sounds emitted by one or more devices. A microphone system detects a plurality of measurable sound qualities (e.g., loudness, tonality, sharpness, etc.) of these rated sounds. A regression prediction model is trained based on the jury pleasantness ratings and the corresponding measurable sound qualities. Then, the microphone system detects measurable sound qualities of an unrated sound that has not been rated by the jury. The trained regression prediction model is executed on the measurable sound quality of the unrated sound to yield a predicted pleasantness of the unrated sound.

Abstract: A system includes a processor, wherein the processor is programmed to receive sound information and vibrational information from a device in a first environment, generate a training data set utilizing at least the vibrational information and a sound perception score associated with the corresponding sound of the vibrational information, wherein the training data set is fed into an un-trained machine learning model, in response to meeting a convergence threshold of the un-trained machine learning model, outputting a trained machine learning model, receive real-time vibrational information from the device in a second environment, and based on the real-time vibrational information as an input to the trained machine learning model, output a real-time sound perception score indicating characteristics associated with sound emitted from the device.

Abstract: A system includes a processor in communication with one or more sensors. The processor is programmed to receiving, from the one or more sensors, vibrational information and sound information associated with the vibrational information from a test device, generating a training data set utilizing at least the vibrational data and the sound information associated with the vibrational data, wherein the training data set is sent to a machine learning model configured to output sound predictions, receiving real-time vibrational data from a run-time device running an actuator or electric dive emitting the real-time vibrational data, and based on the machine learning model and the real-time vibrational data, output a sound prediction indicating a purported sound emitted from the run-time device.

Abstract: A method includes, in response to at least one convergence criterion not being met: receiving a labeled dataset that includes a plurality of labeled samples; receiving an unlabeled dataset that includes a plurality of unlabeled samples; identifying a plurality of labeled-unlabeled sample pairs; applying a data augmentation transformation to each labeled sample and each corresponding unlabeled sample; computing, for each least one labeled-unlabeled sample pair, latent representation spaces using the machine learning model; generating, using the machine learning model, a label prediction for each unlabeled sample for each labeled-unlabeled sample pair; computing a loss function for each labeled-unlabeled sample pair of the plurality of labeled-unlabeled sample pairs based on respective latency representation spaces and respective label predictions; applying an optimization function to each respective loss function; and updating a weight value for each labeled-unlabeled sample pair of the plurality of labeled-un

Abstract: A method includes receiving a labeled dataset that includes a plurality of labeled samples and initially training the machine learning model using the labeled dataset. The method also includes receiving an unlabeled dataset that includes a plurality of unlabeled samples. The method also includes computing latent representation spaces for each respective sample of the plurality of labeled samples and each respective sample of the plurality of the unlabeled samples. The method also includes generating a k-nearest neighbor similarity graph based on the latent representation spaces, generating a combined similarity graph by augmenting the k-nearest neighbor similarity graph using an expert-derived similarity graph, and propagating, using the combined similarity graph, labels to each respective sample of the plurality of unlabeled samples.

Abstract: A burner module according to the invention comprises at least three or four or five or six or seven or eight functional walls which delimit at least one first functional space and form a module body, wherein the module body has at least three or four or five or six or six or seven gas passage openings and at least two of these gas passage openings are connected to one another communicatively via the first functional space, and wherein at least one nozzle device having a fuel gas opening is formed in an upper wall of the burner module, which fuel gas opening is connected communicatively to the first functional space via a gas channel. The burner module is produced in an additive manner.

Abstract: A method of customized setting at least one measurement device, comprises the steps of setting an intended measurement setup on the at least one measurement device manually via a user interface, recording, via a command recorder, at least one remote control command assigned to the manual setting of the intended measurement setup, converting the at least one remote control command recorded into specific instructions, and generating a standalone executable code at least based on the specific instructions obtained from the remote control command recorded. Further, a measurement system is provided.

Abstract: The present invention relates to an enhanced control of a measurement device displaying a signal waveform of a measurement signal. For this purpose, the waveform of the measurement signal is displayed on a touch-screen. The touch-screen receives multi-digit touch gestures comprising at least two touch gestures. The touch gestures of the multi-digit touch gesture are analyzed in order to determine simultaneously an operation and a range of the measurement signal on which the determined operation has to be applied. In this way, the control of the measurement device can be simplified.

Abstract: A burner module according to the invention comprises at least three or four or five or six or seven or eight functional walls which delimit at least one first functional space and form a module body, wherein the module body has at least three or four or five or six or six or seven gas passage openings and at least two of these gas passage openings are connected to one another communicatively via the first functional space, and wherein at least one nozzle device having a fuel gas opening is formed in an upper wall of the burner module, which fuel gas opening is connected communicatively to the first functional space via a gas channel. The burner module is produced in an additive manner.

Abstract: The invention relates to a user interface control device, comprising display; an input key that can be pressed by a user, and a processor configured to register a starting time and a duration of a key press on the input key, wherein the processor is configured to assign a first function to the input key if the duration of the key press is shorter or equal to a threshold time value, and wherein the processor is configured assign a second function to the input key if the duration of the key press exceeds the threshold time value, wherein the display is configured to display a graphical element, which indicates a duration of the key press at least until the threshold time value is reached.

Abstract: A frame trigger recreation method is provided. Said frame trigger recreation method comprises the steps of generating a periodic trigger on the basis of a receiver clock with at least one period adjustment and at least one offset based on a difference between the receiver clock and a transmitter clock.

Abstract: A frame trigger recreation method is provided. Said frame trigger recreation method comprises the steps of generating a periodic trigger on the basis of a receiver clock with at least one period adjustment and at least one offset based on a difference between the receiver clock and a transmitter clock.