The method for monitoring the condition of the hydraulic system for predicting the risk of failure is designed for hydraulic systems, whose components include at least one pump (1) for transporting fluid through the distribution system of the hydraulic system. The hydraulic system simultaneously detects at least one current magnitude of pressure and the current value of speed of the pump (1), whereupon the current speed value is compared with the trend speed value obtained from the statistically processed archived data of speed from the previous operation of the pump (1) and/or with the reference speed value of the pump (1), whereupon the comparison result provides the condition and risk of failure of the hydraulic system.

The embodiments of the present application provide an environmental monitoring system, which is configured to monitor concentrations of air pollutants of process regions in a clean room, and includes: a plurality of process regions in the clean room; a sampling device, configured to collect environmental samples of the process regions; a controlling device, configured to control the sampling device to collect the preset environmental samples of the process regions; and an analyzing device, communicated with the sampling device and configured to analyze the collected environmental samples. The present application facilitates a rapid acquisition of the analysis data of the environmental samples in particular process regions and improves the accuracy of data analysis.

A system includes an industrial automation component configured to receive a first voltage from a voltage source to enable the industrial automation component to perform one or more operations, a mechanical device configured to generate a second voltage, and a display configured to present image data. The display is configured to maintain presentation of the image data in absence of the first voltage received from the voltage source or the second voltage received from the mechanical device. The system also includes processing circuitry configured to use the second voltage generated by the mechanical device to adjust the image data presented by the display when the first voltage is unavailable.

A collector (110) included in a data delivery control apparatus (100) collects data from a PLC (603, 604) and outputs the data to which collection time information indicating collection time is added. A validity determiner (140) determines whether the data is valid based on whether the collection time indicated by the collection time information added to the data is at or later than a starting time indicating a time at which a data sequence as a preset data processing sequence is started. A deliverer (130) delivers the data in accordance with a data sequence setting defining the data sequence in response to validity determination means determining that the data is valid.

A collector (110) included in a data delivery control apparatus (100) collects data from a PLC (603, 604) and outputs the data to which collection time information indicating collection time is added. A validity determiner (140) determines whether the data is valid based on whether the collection time indicated by the collection time information added to the data is at or later than a starting time indicating a time at which a data sequence as a preset data processing sequence is started. A deliverer (130) delivers the data in accordance with a data sequence setting defining the data sequence in response to validity determination means determining that the data is valid.

An apparatus is described herein related to remote monitoring of perishable trade items in environmentally-controlled storage containers. Relevant changes in the container environment are detected through various sensors-based event detectors. A timer serves to trigger a plurality of distinct alert states, comprising pre-alerts and full alerts, following an event-initiated time threshold expiry. A data repository of generic merchandise data is accessed in order to derive suitable timer pre-sets in relation to time thresholds for alert states. An account configuration engine serves to customize the threshold presets to the specific items stored inside the container.

A control device of a technical installation receives in normal operation cyclically measurement variables from sensors, and outputs control variables to actuators. In normal operation, the control device stores the history of at least some of the measurement variables at least for a limited time and monitors the measurement variables for the occurrence of a fault. If a fault occurs, the control device transmits a fault message identifying the fault and the history to a knowledge base. In response to the fault message and the histories, the control device receives a reply from the knowledge base and outputs the reply to an operator. Before the normal operation is performed, the control device receives from the operator specifications which allow the control device to defines the histories. In the event of a fault, the control device determines, in dependence on the specifications, which histories to transmit to the knowledge base.

A computer-implemented method, system, and computer program product are provided. A plurality of maintenance messages (MMSGs) are identified. Each MMSG is associated with at least one shut-off valve. A sensor parameter is identified based on an analysis of sensor parameters associated with the shut-off valves of each MMSG. A threshold value for the sensor parameter is identified as being associated with abnormal operation of the respective shut-off valves. A sensor associated with a first shut-off valve captures values for the sensor parameter during a first and second predefined time period, the first and second predefined time periods associated with an opening and a closing of the first shut-off valve. Upon determining that a difference between the maximum values of the sensor values captured during the first and second predefined time periods exceeds the first threshold value, a determination is made that the first shut-off valve is operating abnormally.

A plant operation data monitoring device comprises: an input section that receives operation data on a plant; and a calculator that includes databases storing the operation data received, and a computing section executing a program. The computing section stores the operation data received in a first database of the databases in time series. The computing section determines from peak values of the operation data stored whether gradients of the operation data are positive or negative, and then stores the gradients in a second database of the databases for positive gradients or in the second database of the databases for negative gradients in time series. The computing section determines threshold values for abnormality determination about the positive and negative gradients, divides the positive gradients and the negative gradients into normal values and abnormal values, and additionally stores the divided gradients in the second database for the positive or negative gradients.

The present subject matter describes a method to detect anomaly in an environment based on AI techniques. The method comprises receiving one or more data representations of one or more objects present in an environment. A first-type of information is captured from a first-area within the one or more data representations. A second-type of information from a second-area different than the first area in the data representations is also captured. A third information is generated from the first information, said third information corresponding to predicted information for the second area using one or more artificial-intelligence models for evaluating the second information. The third information is compared with the second information to determine abnormality with respect to state or operation of one or more objects within the environment.