A centralized management device includes a sensor data acquirer and an acquisition cycle changer. The sensor data acquirer acquires periodically, by communication, from each of one or more outdoor units, sensor data including measurement results of one or more sensors included by the outdoor unit. When a sign of malfunction is detected in any of the outdoor units, the acquisition cycle changer makes a change to shorten an acquisition cycle of the sensor data for the outdoor unit for which the sign of malfunction is detected.

An example rotational joint assembly for a robotic medical system, the rotational joint assembly comprising at least one arm segment and a rotational joint provided at one end of the arm segment. The rotational joint is to allow the arm segment to rotate about a rotational axis. The rotational joint comprising a brake to lock rotation of the arm segment at the rotational joint and an actuator to selectively engage or disengage the brake. The actuator comprising a cam having two stable regions separated by two transition regions, the two stable regions comprising a first stable region corresponding to engagement of the brake and a second stable region corresponding to disengagement of the brake.

A determination device includes: a memory; and a processor coupled to the memory and configured to: obtain sensor data on motion of a device from a plurality of sensors, extract, from the sensor data, data related to an anomaly based on a threshold value used in detecting the anomaly with use of the sensor data, convert the data related to the anomaly into structural data having a graph structure focusing on an analogous relationship between or among the plurality of sensors, and generate a classifier that identifies a cause of the anomaly with use of the structural data.

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 non-transitory computer-readable storage medium stores instructions, which when executed by a processing device of a diagnostic server, cause the processing device to perform certain operations. The operations include receiving, from a processing chamber, (i) measurement values of a combined signal that is based on an injection of an alternating signal wave onto a first output signal of a controller of the processing chamber, and (ii) measurement values of a second output signal of the controller that incorporates feedback from the processing chamber. The operations further include generating, based on the measurement values of the combined signal and the measurement values of the second output signal of the controller, a baseline bode fingerprint pertaining to a state associated with the processing chamber. The operations further include storing, in computer storage, the baseline bode fingerprint to be used in performing diagnostics of the processing chamber.

A decision support system and method for an industrial plant is configured and operates to: obtain a causal graph modeling causal assumptions relating to conditional dependence between variables in the industrial plant; obtain observational data relating to operation of the industrial plant; and perform causal inference using the causal graph and the observational data to estimate at least one causal effect relevant for making decisions when operating the industrial plant.

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.

Techniques monitor machinery for the production or treatment of synthetic fibers. Such techniques involve constant generation and recording of system messages of machine components and control components. Such techniques further involve continuous storage of the system messages as log data in a log memory. Such techniques further involve readout, preprocessing and analysis of the log data with the aid of algorithms based on statistical procedures and machine learning methods in order to identify frequent sequences of system messages and/or an anomaly.

An apparatus for connecting and monitoring processes of a production machine includes a process monitoring device designed to capture sensor data relating to the production machine and process data relating to the production machine, and a connection device designed to capture control data relating to the production machine. The apparatus is designed to change a hardware function of the apparatus based on the sensor data, the process data, and the control data. The process monitoring device may be designed to carry out data processing for the sensor data and the process data, or the connection device may be designed to carry out data processing of the control data. The apparatus may include a field-programmable logic gate array device designed to change the hardware function.

Proposed is a method of diagnosing abnormality of sensorless control of a motor for an air compressor, the method including estimating a speed of a motor in real time when a motor starts determining whether or not a preset condition for activating a function of diagnosing abnormality of sensorless control is satisfied, from a slope of the estimated speed of the motor performing control for decreasing an amount of electric current to be applied to the motor, in a case where the preset condition is satisfied computing an amount of decrease in the slope of the estimated speed of the motor while the amount of the electric current is decreased; and determining whether or not the sensorless control fails, by comparing the amount of the decrease in the slope of the speed of the motor with a preset value for confirming diagnosis of the abnormality of the sensorless control.