A device for monitoring a digital control unit with regard to functional safety is proposed. The device comprises an interface configured to receive a control signal of the digital control unit for a circuit component. The control signal represents a digital value. Furthermore, the device comprises a timer circuit configured to output an associated timer value in each case for successive points in time. The device furthermore comprises a hash value generator, which is configurable, in response to a change in the digital value, to recalculate a hash value on the basis of the change in the digital value and the timer value at the point in time of the change in the digital value.

A hybrid sensor can be generated by training a machine learning model, such as a neural network, based on a training data set. The training data set can include a first time series of upstream sensor data having forward dependence to a target variable, a second time series of downstream sensor data having backward dependence to the target variable and a time series of measured target variable data associated with the target variable. The target variable has measuring frequency which is lower than the measuring frequencies associated with the upstream sensor data and the downstream sensor data. The hybrid sensor can estimate a value of the target variable at a given time, for example, during which no actual measured target variable value is available.

Monitoring systems for data collection in a vehicle steering system include a vehicle steering system comprising a rack, a pinion, and a steering column; a data acquisition circuit structured to interpret a plurality of detection values, each of the plurality of detection values corresponding to at least one of a plurality of input sensors, each of the plurality of input sensors operationally coupled to the rack, the pinion, or the steering column, and communicatively coupled to the data acquisition circuit; a signal evaluation circuit comprising: a timer circuit structured to generate at least one timing signal; and a phase detection circuit structured to determine a relative phase difference between at least one of the plurality of detection values and the at least one timing signal from the timer circuit; and a response circuit structured to perform at least one operation in response to the relative phase difference.

Methods and systems for sensor fault management are provided. A plurality of potential faults associated with a sensor are obtained. Accommodation approaches are associated with the plurality of potential faults. Severity levels are associated to the plurality of potential faults to produce a hierarchy of potential faults. A fault management tool is generated based on the hierarchy, the fault management tool defining a framework implementable by a controller associated with the sensor for accommodating faulty behaviour of the sensor by following the accommodation approaches of the hierarchy for the plurality of potential faults.

A system for use with an electric machine is provided. The system includes a processor and a memory comprising a set of memory modules, which, when executed by the processor, cause the processor to perform certain operations. The operations include receiving operational data from the electric machine, and generating, based on the operational data, a first set of diagnostic data, by executing a first memory module from the set of memory modules. The operations further include generating, based on the operational data, a second set of diagnostic data, by executing a second memory module from the set of memory modules, the second memory module including a set of parameters associated with a diagnostics model of the electric machine. Furthermore, the operations include effecting, based on the operational data, the first set of diagnostic data, and the second set of diagnostic data, a change in at least one parameter.

A processing abnormality diagnostic device includes an abnormality diagnostic unit that diagnoses whether processing is abnormal using an abnormality threshold by a preset diagnostic model, a success or failure input unit that inputs success or failure of the diagnosis of the abnormality by the abnormality diagnostic unit, a measure determination unit that determines a measure when the diagnosis of the abnormality is input as failure through the success or failure input unit, an abnormality threshold change unit that updates the abnormality threshold, and a learning unit that relearns the diagnostic model using operation information of the machine tool when the diagnosis of the abnormality has failed. The measure determination unit determines which of the abnormality threshold change unit and the learning unit is to be adopted as the measure based on the operation information diagnosed by the diagnostic model when the diagnosis of the abnormality has failed.

A method for monitoring an industrial machine, the method may include selecting a selected reference component for each component out of one or more components of the industrial system; the selecting provides one more selected reference components; wherein each selected reference component is selected out of multiple reference components; wherein for each component the selecting is based on similarities between the component and reference components of the multiple reference components; determining one or more learnt mappings between (i) sensed information related to the one or more components and (ii) predicted failures of the one or more components ; wherein the learning is based, at least in part, on one or more reference mappings between (i) sensed information related to the one or more selected reference components and (ii) predicted failures of the one or more selected reference components; monitoring the one or more components to receive monitoring results; and evaluating the operation of the one or more components based on the monitoring results and the one or more reference mapping.

Systems, methods and an apparatus for data monitoring. A system may include a data acquisition circuit structured to interpret a plurality of detection values, each of the plurality of detection values corresponding to at least one of a plurality of input sensors communicatively coupled to the data acquisition circuit; a data storage circuit structured to store specifications and anticipated state information for a plurality of pump and fan types; an analysis circuit structured to analyze the plurality of detection values relative to specifications and anticipated state information to determine a pump or fan performance parameter; and a response circuit structured to initiate an action in response to the pump or fan performance parameter.

Methods and systems for a data marketplace in a fluid conveyance device includes a self-organizing data marketplace. The self-organizing data marketplace includes at least one data collector and at least one corresponding fluid conveyance device in an industrial environment, wherein the at least one data collector is structured to collect detection values from the fluid conveyance device; a data storage structured to store a data pool comprising at least a portion of the detection values; a data marketplace structured to self-organize the data pool; and a transaction system structured to interpret a user data request, and to selectively provide a portion of the self-organized data pool to a user in response to the user data request.

A method for determining a sensor configuration in a vehicle which includes a plurality of sensors. The method comprises: (i) establishing a preliminary sensor configuration for the vehicle, which sensor configuration includes a first number of real sensors, each of which outputting a real sensor signal, (ii) determining whether at least one of the real sensors can be replaced by a virtual sensor, and (iii) changing the preliminary sensor configuration into a final sensor configuration which includes a second number of real sensors and at least one virtual sensor which has been determined to replace at least one of the real sensors, wherein the second number is smaller than the first number.