A method and apparatus are provided for sensor fault prediction. A time-sequence of output values is received from a sensor. A plurality of features are extracted from the received values. A model is applied to the features to obtain a health score for the sensor. The trend of the health score over time is calculated to detect degrading performance of the sensor, and a time at which the sensor will become faulty is predicted.

The information processing device includes a matching unit 32A and a display control unit 33A. The matching unit 32A is configured to match a database 21A, which associates first detection data indicative of a past state of maintenance target equipment 3 with first maintenance information relating to maintenance of the maintenance target equipment 3 in the past state, with second detection data indicative of a current state of the maintenance target equipment 3. The display control unit 33A is configured to display, based on a result of the matching by the matching unit 32A, second maintenance information relating to maintenance in accordance with the current state of the maintenance target equipment 3 on a display unit 45A.

A diagnosis device stores a model used for diagnosing the condition of an industrial machine in a storage unit, acquires data related to the condition of the industrial machine, and based on the acquired data, determines the condition of the industrial machine by using the model stored in the storage unit. Then, in response to detecting that a component of the industrial machine has been replaced based on the acquired data and the data related to the determined condition of the industrial machine, the diagnosis device adapts the model stored in the storage unit to the condition of the industrial machine whose component has been replaced.

Various embodiments described herein relate to management of industrial process optimization related to batch operations. In this regard, an optimization request to optimize an industrial process that produces an industrial process product is received. In response to the optimization request, product spent characteristics for one or more blending components of a batch operation subprocess are determined. Also in response to the optimization request, demand data for one or more feed products associated with the one or more blending components is updated based on the product spent characteristics and inventory data indicative of an inventory level for the one or more feed products. Furthermore, a control signal configured based on the demand data is transmitted to a controller configured for optimization associated with the industrial process that produces the industrial process product.

A phasor measurement unit (PMU) of the present disclosure measures phasor, i.e., magnitude and phase angle of voltage and current, and related data from a specific location on the electrical gird synchronized to a common time source. The time-synchronized phasor is called a synchrophasor. In a system of the present disclosure, a plurality of PMUs transmit the synchrophasors and related data to a phasor data concentrator (PDC), which aggregates and time-aligns the data for real time and post analysis. The PMU of the present disclosure further functions as a power quality meter determining at least one of symmetrical components' phasor, frequency, rate of change of frequency, high-speed digital inputs, analog fundamental power and/or displacement power factor.

An industrial shock absorber system may include at least one sensor that is configured to measure an operating parameter of the industrial shock absorber during operation of the shock. The system may be configured to determine Time-Through-Stroke (TTS) and/or Rod Return Time (RRT) utilizing data from the sensor or sensors. The system may be configured to utilize machine learning to detect and/or predict a failure of the industrial shock absorber.

The independent claims of this patent signify a concise description of embodiments. An automatic process for determining and/or predicting the original root-cause(s) of a violation is proposed using two major enhancements on top of the current VC-Static solution. First, an information repository is created by mining various Static checker components' analysis information, and second, an analysis framework is created which systematically prunes the above-mentioned information repository to find the actual root cause(s) of the violation. This Abstract is not intended to limit the scope of the claims.

The present invention discloses a safety devices adapted to prevent workers from going into hazardous environment, such as underground using the faulty safety device. As a safety device, typically embodied as a cap lamp, must be charged prior to each use, the device is adapted to detect when the device is removed from the charger. The device starts to blink continuously when disconnected from the charger. An automated test procedure is completed on the device. The user may also complete a manual portion of the test procedure to make the device usable. When the test procedure is completed successfully, the lamp stops blinking. If the test procedure is not successful, the lamp continues blinking to effectively prevent user from using a faulty device.

The present disclosure relates to a recloser control that monitors compliance of a standard for distributed energy resources (DERs). For example, a method includes obtaining power system measurements between a microgrid and an area electronic power system (EPS). The method includes determining a rate of change of power (RoCoP) based on the power system measurements. The method includes determining that a DER exceeded a threshold of the area EPS based at least in part on the RoCoP. The method includes sending a signal indicating that the DER has violated the threshold.

A system configuration information management device includes a storage device configured to store therein control system identification information, component identification information, and version information in association with one another. The control system identification information identifies a control system. The component identification information identifies each of a plurality of components composing the control system. The version information indicates a version of an element of each of the components having at least hardware.