A platform for updating one or more properties of one or more digital twins including receiving a request for one or more digital twins; retrieving the one or more digital twins required to fulfill the request from a digital twin datastore; retrieving one or more dynamic models corresponding to one or more properties that are depicted in the one or more digital twins indicated by the request; selecting data sources from a set of available data sources based on the one or more inputs of the one or more dynamic models; obtaining data from selected data sources; determining one or more outputs using the retrieved data as one or more inputs to the one or more dynamic models; and updating the one or more properties of the one or more digital twins based on the one or more outputs of the one or more dynamic models.

A fault prediction system based on sensor data on a numerical control machine tool and a method therefor. The fault prediction system includes a plurality of sensors for collecting numerical control machine tool operation state data serving as multi-channel data, wherein an output end of a sensor is connected to an input end of a multi-channel sensor interface circuit, and an output end of the multi-channel sensor interface circuit is connected to a controller. The plurality of sensors can be multi-path temperature sensors, multi-path vibration sensors or multi-path noise sensors. The defects in the prior art of there being no model for researching a cross correlation of multi-channel data, collected by a plurality of sensors, of an operation state of a numerical control machine tool, and a device fault subspace of the multi-channel data being unable to be obtained are effectively prevented.

A method for event-oriented transmission of measured process values includes receiving the measured process values via an automation device of a control system of a process plant; automatically performing sensitization or desensitization of a measurement range of the measured process values on the automation device where, during sensitization or desensitization and depending on an undershoot of a minimal transmission rate of the measured process values from a measurement device to the automation device or an overshoot of a maximum transmission rate of the measured process values from the measurement device to the automation device, the measurement range is automatically decreased during sensitization and increased during desensitization by the automation device via a heuristic method, and transmitting the measured process values, on an event-oriented basis, to the operator station server of the control system of the process plant, where an event represents a predetermined change to the measured process values.

Described techniques provide direct measurement of shaft torque in control valve assemblies. The measured torque can be utilized to analyze the performance or health of the control valve. The described techniques utilize a direct measurement of shaft torque, providing a more accurate and precise measurement than an indirect or proxy measurement.

Fault tolerance for an automation controller for a machine is provided. A first portion of phases of the automation controller may be processed with fail operational protection, in which a failure of one of the computers used for the first portion still permits full operational functionality in the machine. The remaining portion of the phases are processed with fail degraded protection, in which a failure of a computer used for the remaining portion permits continued operation but with one or more constraints, as compared to the fail operational portions.

An irregularity detection apparatus (100) converts a multi-valued-signal value of each of one or more multi-valued-signals at each time point into a binary-signal-value group. The irregularity detection apparatus calculates a forecast-signal-value group at a subject time point by computing a forecast model with use of, as input, a past-signal-value group which is a collection of a binary-signal value of each of one or more binary signals at each past time point and the binary-signal-value group of each of the one or more multi-valued signals at each past time point. The irregularity detection apparatus compares with the forecast-signal-value group, a collection of the binary-signal value of each of the one or more binary signals at the subject time point and the binary-signal-value group of each of the one or more multi-valued signals at the subject time point, and determines a state of a subject system (220) at the subject time point.

Methods and systems for data collection in an environment including pumps and fans are disclosed. A monitoring system may include a data collector communicatively coupled to a plurality of input channels, wherein the input channels are communicatively coupled to sensors measuring operational parameters of a pump or fan. A data storage may store one or more frequencies related to an operation of the pump or fan, and a data acquisition circuit may interpret a plurality of detection values from the collected data. A frequency evaluation circuit may detect a signal on one of the input channels at a frequency higher than the one or more frequencies at which the pump or fan operates.

An abnormality detection apparatus is provided, comprising a target data generation unit configured to generate, based on operation-related data resulting from an operation of a movable apparatus, a plurality of target data that are temporally separated, and a detection processing execution unit configured to execute change detection processing on the plurality of target data. An abnormality detection method that is executed by a computer for detecting an abnormality in a movable apparatus is provided, the method comprising generating, based on operation-related data resulting from an operation of the movable apparatus, a plurality of target data that are temporally separated, and executing change detection processing on the plurality of target data.

A method for derivation of a machine signature includes receiving sensor information from a primary sensor, where the primary sensor is positioned to receive information from a portion of an industrial operation, and receiving sensor information from one or more secondary sensors. The secondary sensors are arranged to provide additional information about the industrial operation indicative of current operating conditions of the industrial operation. The method includes using the sensor information from the secondary sensors and machine learning to determine if the portion of the industrial operation is operating in a normal condition and, in response to determining that the portion of the industrial operation is operating normally, using sensor information from the primary sensor during the normal operating condition to derive a primary sensor signature for the sensor information from the primary sensor.

An industrial analytic system includes a device interface component. The device interface component is configured to collect data from a plurality of analytic appliances and transfer the data to an analytic component. Each of the plurality of analytic appliances is configured to collect data from a respective set of devices of a plurality of sets of devices. The plurality of sets of devices perform a plurality of operations in one or more industrial systems.