A redundant control system includes a plurality of channels each including a processing system configured to execute a control application for a controlled system. The redundant control system also includes a switchover artificial intelligence control operable to evaluate a state of the channels of the redundant control system, monitor a plurality of input/output data and communication data of the channels, and apply a fault model to determine one or more component faults and system faults of the channels based on the state, the input/output data, and the communication data. The switchover artificial intelligence control is further operable to command a switchover of a control function from one of the channels having a lower health status to one of the channels having a higher health status based on the component faults and system faults of the channels.

According to one or more embodiments of the disclosure, a device in a network obtains parameters for entropy testing of industrial equipment that controls a physical process. Entropy is added to commands sent to the industrial equipment during the entropy testing. The device receives packets that were generated during the entropy testing of the industrial equipment and include sensor data regarding the physical process. The device determines whether the sensor data is inconsistent by analyzing the sensor data using a machine learning model that models the physical process. The device initiates a corrective measure, when the sensor data is determined to be inconsistent.

Methods for monitoring engine health of an aircraft having a first engine and a second engine are provided. In one example, the method includes obtaining a first turbine gas temperature of the first engine and a second engine turbine gas temperature of the second engine from a first flight. The first turbine gas temperature and the second turbine gas temperature are related to each other to define a first value. The first value is compared to a data set for monitoring the engine health.

A system for analyzing cause of product defect, including: a distributed storage device configured to store production data generated by a factory device; an analysis device including one or more processors configured to perform: acquiring a production record from the production data; the production record includes information of processing devices used during production procedures for producing the products and information of defects occurring, where each product is processed by multiple processing devices, and each processing device participates in only the production procedures of a portion of the products; determining a correlation weight of the processing device to be analyzed corresponding to a defect to be analyzed according to the production record, and determining a correlation between the processing device to be analyzed and the defect to be analyzed according to the correlation weight; a display device configured to display an analysis result of the analysis device.

An abnormality is diagnosed in a control system including a plurality of controllers adopting a redundant configuration, a diagnosing apparatus that diagnoses a control system. The control system includes a plurality of controllers adopting a redundant configuration; and an interface apparatus that outputs control output data, which is based on a plurality of redundant pieces of control data received from the plurality of controllers, to a device under control. The diagnosing apparatus includes a statistical information acquiring section that acquires statistical information including adoption/non-adoption of the control data from each of the plurality of controllers in the interface apparatus; and a diagnosing section that diagnoses the control system based on the statistical information.

A method for calculating a remaining useful life of an apparatus comprises the following steps. Time-series of previous runs and a current run of the apparatus are provided containing data of sensors configured to monitor parameters of the apparatus. An error occurs when a parameter breaches a threshold. Cumulative counts of errors occurring during a run are calculated. A linearly decreasing remaining useful life is calculated for previous runs. Breakdowns of the apparatus are mapped in an error space. Each dimension of the error space refers to one type of an error. The breakdown points are mapped at coordinates which represent cumulative error counts at the time of the breakdowns. A test point representing cumulative error counts of the current run is mapped. At least two nearest breakdown points to the test point are identified. The remaining useful life of the apparatus is calculated based on the nearest breakdown points.

A diagnostic device (10) includes an acquirer (101) and a diagnoser (140). The acquirer (101) acquires a plurality of input signals including a target signal to be diagnosed for abnormality. The diagnoser (140) diagnoses, using a first index value relating to the target signal and a second index value relating to the plurality of input signals based on a correlation between the plurality of input signals, whether an abnormality occurs. The first index value indicates a degree of similarity of a waveform of the target signal to a predetermined reference waveform. The second index value is a value that is based on comparison between the target signal and a predetermined pattern and is calculated from values of the plurality of input signals.

A working machine comprising: a control unit configured to cause the working machine to perform work in a first work mode in which work is performed without collecting diagnostic data; an acceptance unit configured to accept a diagnosis instruction; and a switching unit configured to switch from the first work mode to a second work mode in which work is performed while collecting the diagnostic data, in a case where the diagnosis instruction is accepted by the acceptance unit, wherein the control unit causes the working machine to perform work in the second work mode in a case where the switching unit switches to the second work mode.

Systems, methods, and non-transitory computer-readable media can be configured to perform receiving a notification of a maintenance event associated with a resource. The method includes retrieving historic maintenance data in relation to the resource with which the fault is associated, the maintenance information originating from a time period preceding the time of the maintenance event. The method includes identifying at least a portion of the retrieved historic maintenance data as being indicative of the maintenance event. The method also includes causing the portion of the retrieved historic maintenance data identified as being indicative of the maintenance event to be stored as a precursor signal of the maintenance event. The method also includes causing future maintenance data received from a plurality of resources related to the resource with which the maintenance event is associated to be monitored to predict a future occurrence of the maintenance event in the plurality of resources.

A flight control computer (FCC) has an index calculation component (ICC) configured to compare a reasonableness of at least a first value of a variable and a second value of the variable. A method of operating a flight control computer (FCC) includes providing an index calculation component (ICC) configured to compare a reasonableness of at least a first value of a variable and a second value of the variable.