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.

An abnormality diagnosis system configured to diagnose an abnormality of an electric drive system mounted on a mobile body to drive a motor for moving the mobile body, includes: an information acquisition unit configured to acquire a motor output information which is information related to an output state of the motor; an output state determination unit configured to determine whether the output state of the motor is in a low output state that does not contribute to a movement of the mobile body by using the motor output information; and a diagnosis execution unit configured to diagnose an abnormality of the electric drive system when it is determined that the motor is in the low output state.

A system and method for enabling access to information included in a safety requirement specification (SRS) for a process plant, the process plant controlled by a process control system including displaying, in a user interface, a cause and effect matrix (CEM) having a set of elements including a set of causes and a set of effects, wherein each of the set of causes represents a condition within the process plant and each of the set of effects represents an effect to be performed within the process plant, and wherein at least some of the set of causes and the set of effects are related as cause-effect pairs whereby the corresponding effect activates in response to an occurrence of the corresponding condition. The system and method further including receiving, via the user interface, a selection of an element of the set of elements, and, in response to receiving the selection: (i) accessing, from the SRS, a set of information associated with the element of the set of elements, and (ii) displaying the set of information in the user interface.

Disclosed is a method of analyzing a programmable logic controller (PLC) logic to detect whether an anomaly that deviates from a standard pattern occurs in a repeated cycle. After modeling and patterning an operation pattern of automation equipment and processes with a graph, an anomaly detecting model capable of detecting whether a pattern is abnormal may be constructed as a graph AutoEncoder model. By detecting the change in the process pattern, it is possible to early detect the anomaly of the equipment and processes.

One or more ring closures of a fault tree are provided. For each one of the one or more ring closures: at least one respective edge the respective ring closure is replaced in the fault tree by a respective variable to obtain a placeholder fault tree and a normalized representation of the placeholder fault tree is determined.

This failure tree generation device includes: a causal relationship storage unit that stores information indicating a linkage of the causal relationship of defects of respective component parts constituting subjects to be analyzed in a manner such that the information is associated with the connection relationship of the respective component parts; a system-level failure tree generation unit that generates, for each of the component parts and on the basis of component part constitution information indicating the constitution of component parts to be analyzed and component part connection information indicating the connection relationship of the respective component parts, first element information which is information indicating disturbance having occurred in information transfer between the respective component parts and which indicates the relationship between each of the component parts and a phenomenon having occurred on the component part, and generates, on the basis of the respective items of first element information, system level failure tree information indicating the causal relationship of defects of the component parts; and an equipment/component part level failure tree generation unit that searches for the causal relationship storage unit on the basis of the component part constitution information and the component part connection information, that generates two or more items of second element information indicating information relating to a plurality of events connecting to any one first element and indicating the relationship between the respective component parts and phenomena having occurred on the respective component parts, and that generates, on the basis of the respective items of the second element information, equipment/component part level failure tree information indicating the causal relationship of defects of the component parts, by way of a hierarchical structure.

Provided is a method for analyzing and designing a physical system architecture of a safety-critical system, wherein a physical system analysis model representing the physical system architecture of the safety-critical system is modified incrementally until calculated failure rates of failure modes of the physical system analysis model are less or equal to failure rates of corresponding failure modes of a functional system analysis model representing a functional system architecture of the safety-critical system.

Systems and methods for diagnosing an engine or an aircraft are described herein. Flight data of at least one of the engine and the aircraft is obtained. A graph-based representation modeling a mathematical relationship between parameters of at least one of the engine and the aircraft is obtained. The graph-based representation has a plurality of permutations. Output data for the plurality of permutations is generated based on the flight data. The output data for the plurality of permutations is compared and a fault is detected based on a discrepancy in the output data. A signal indicative of the fault is outputted in response to detecting the fault.

A life prediction system for industrial mechanical power transmission equipment is provided. The system includes a life prediction computing device, the life prediction computing device including at least one processor in communication with at least one memory device, and the at least one processor programmed to receive data of a gearbox measured by one or more sensors, predict remaining useful lifetime of the gearbox based on the received data by using a machine learning model, and output the predicted life of the gearbox.

A method for using sensor data and operational data of an industrial process to identify problems includes gathering sensor data from one or more sensors sensing conditions on equipment of an industrial process, receiving command information about operational commands issued to the equipment of the industrial process, and for each sensor of the one or more sensors, comparing the sensor data with signature information for the sensor. The signature information for the sensor is relevant for operational commands issued to the equipment. The method includes determining if the sensor data of a sensor of the one or more sensors exceeds the signature information corresponding to the sensor, locating a problem with a piece of equipment of the industrial process monitored by the sensor of the one or more sensors based on the sensor data exceeding the signature information for the sensor and issuing an alert reporting the problem.