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 control layer automation device comprises a processor, one or more control layer applications, a database, a wireless interface, a device memory. Each control layer application is configured to perform a discrete set of automation functions. The database comprises a plurality of operator device identifiers and the wireless interface allows the one or more control layer applications to communicate with a plurality of operator devices via the plurality of operator device identifiers. The device memory comprises the one or more control layer applications. The control layer application manager is configured to manage execution of the one or more control layer applications on the processor.

An equipment state monitoring device includes: a feature amount extracting unit to extract a feature amount of operation data in which a state of equipment is measured; an operation pattern determining unit to determine whether an operation pattern of the equipment when the operation data is measured is a learned pattern in which a determination range of a state of the equipment is learned or an unlearned pattern; a feature amount correcting unit to correct the feature amount of the operation data corresponding to the operation pattern determined as the unlearned pattern to correspond to the learned pattern on a basis of a relationship between an operation pattern of the equipment and a feature amount of operation data; and an equipment state determining unit to determine a state of the equipment on a basis of the corrected feature amount and a determination range of a state of the equipment.

In one embodiment, a condition monitoring circuit can include a circuit controller and a node. The node can include a gate controller, a node controller and one or more gates. The node can be configured to detachably couple to a bus of a monitoring system associated with an industrial machine. The circuit controller can be configured to identify an operating parameter associated with the industrial machine. The gate controller can be configured to transfer, via the one or more gates, one or more data packets including data characterizing the operating parameter from the bus in the monitoring system. The one or more gates can be configured to prevent transfer of an outgoing data packet to the bus via the node.

Methods, systems, and non-transitory computer readable storage media are disclosed for generating action recommendations modifying physical emissions sources of an entity based on past and modeled emissions for the entity. Specifically, the disclosed system monitors emissions produced by an entity by determining a number of emissions sources corresponding to an entity and a plurality of emissions values for the emissions sources. Additionally, the disclosed system determines a plurality of constraints corresponding to the entity. The disclosed system also determines goals for the entity including target emissions values. The disclosed system utilizes a modified gradient descent model to iteratively adjust emissions values for the physical emissions sources to obtain the target emissions values according to the constraints. The disclosed system generates action recommendations for modifying the physical emissions sources utilizing the modified gradient descent model and provides the action recommendations for display within a graphical user interface.

A system optimal control technique with accuracy guarantee that enables high-speed calculations is provided. One aspect of the present invention is related to a system optimal control device including a graph converting unit configured to convert, based on an upper bound of an probability of arrival from an initial state to a final state of a stochastic game representing system information, the stochastic game into a flow analysis graph, a path selecting unit configured to select a path having a maximum width among paths from each state node to a final state node in the converted flow analysis graph, a width of each of the paths being defined as a minimum weight of edges forming the path, and a convergence determining unit configured to determine convergence of the upper bound and a lower bound of the probability of arrival of the stochastic game based on information about the selected path.

A crash sensor device may include multiple sensor components positioned along one or more data paths to a communication interface of the crash sensor device. The crash sensor device may include a test control unit. The test control unit may receive a test command from an electronic control unit during operation of a vehicle. The test control unit may perform a test of one or more sensor components, of the multiple sensor components, during operation of the vehicle based on the test command. The test control unit may output a test result to the electronic control unit based on performing the test.

The present application discloses a remote vehicle diagnostic and detection method based on instant messaging communication, an electronic device, and a storage medium. The process is not only faster to obtain car data, but also to obtain more description information based on instant messaging communication, which improves the efficiency of remote vehicle diagnostic and exclusion.

A method of determining the location and size of a crack in a blade includes measuring a time of arrival of a tip of the blade at an angular position in a rotation, using the time of arrival to calculate a displacement of the tip of the blade, and using the displacements to calculate a first vibration condition and a second vibration condition for the blade. The method also includes comparing the first vibration condition and the second vibration condition for the blade to a predetermined baseline first vibration condition and a predetermined baseline second vibration condition for the blade to determine a change in the first vibration condition and a change in the second vibration condition, and using the magnitude of the change in the second vibration condition relative to the change in the first vibration condition to determine the likely location of the crack and using the magnitude of the change in the first vibration condition and the change in the second vibration condition to determine the size of the crack.

An intellectual quality management method is disclosed. A heatmap risk interface is created according to the required data and the parameter configuration which are calculated using a time dependent risk priority number (RPN) equation. An intellectual audit scheduling algorithm is defined via the heatmap risk interface to automatically generate at least one audit plan. An audit program corresponding to the audit plan is performed and a plurality of problem points are selected. Intellectual root cause category recommendation is performed to the questions points. intellectual corrective actions and preventive action recommendations are performed to the problem points according to the intellectual root cause category recommendation to obtain at least one optimum corrective action and at least one preventive action. Corrective actions are performed to each audit unit according to the corrective action to solve the problem points and prevention actions are performed to each audit unit according to the preventive action.