A system for detecting and evaluating environmental quantities and events is formed by a detection and evaluation device and a mobile phone, connected through a wireless connection. The device is enclosed in a containment casing housing a support carrying a plurality of inertial sensors and environmental sensors. A processing unit is coupled to the inertial sensors and to the environmental sensors. A wireless connection unit, is coupled to the processing unit and a wired connection port, is coupled to the processing unit. A programming connector is coupled to the processing unit and is configured to couple to an external programming unit to receive programming instructions of the processing unit. A storage structure is coupled to the processing unit and a power-supply unit supplied power in the detection and evaluation device. The mobile phone stores an application, which enables a basicuse mode, an expert use mode, and an advanced use mode.

A testing system computer device for dynamically updating a test plan of an apparatus includes at least one processor in communication with at least one memory device. The testing system computer device is configured to store a plurality of historical data and generate a simulation model of the apparatus based in part on the historical data. The simulation model includes a plurality of inputs and a plurality of outputs of the apparatus. The testing system computer device is also configured to determine a plurality of tests to perform on the apparatus based on the simulation model and the plurality of historical data. The testing system computer device is further configured to receive a plurality of desirability ratings from a user, rank the plurality of tests to perform based on the plurality of desirability ratings, and present the ranked plurality of tests to the user.

An information retrieval system (1) for use with a control system (10) in a plant having processes and/or pieces of equipment, the control system (10) connected with at least one input component and/or at least one output component for monitoring and controlling the processes and the pieces of equipment, the control system enabled to produce state indications (12) from the input and output components indicating potential fault in one or more of: at least one input and/or output component; at least one process; at least one piece of equipment; a part of the control system (10); or, a part of the plant.

A diagnostic system for identifying vehicle sensors impaired by a foreign substance. The system includes a plurality of vehicle sensors configured to facilitate navigation of a vehicle in an environment. A gear shift detection sensor is configured to detect a gear position of the vehicle. A control module is configured to identify which of the plurality of vehicle sensors is impaired by a foreign substance; and identify for an operator of the vehicle which of the plurality of vehicle sensors is impaired due to the foreign substance based on the gear position of the vehicle.

The present invention provides a processing apparatus (10) including a first determination unit (11) that determines whether a target apparatus is normal or abnormal on the basis of detection data of a first sensor, and a second determination unit (12) that, in a case where the determination of normal or abnormal is impossible based on the detection data of the first sensor, starts a second sensor and determines whether the target apparatus is normal or abnormal on the basis of detection data of the second sensor.

Suitability of an operational state of a steam-using equipment is accurately estimated to allow for early detection of a sign of abnormality in the steam-using equipment. A steam-using facility monitoring system composed of a steam-using equipment includes a control state detector that detects a state of a steam controller provided in a steam pipe accompanying the steam-using equipment, and an operational state estimating means having a signal input unit that inputs a detection signal from the control state detector and an operational state estimation unit that estimates the operational state of the steam-using equipment based on one inputted detection signal or a preset particular combination of detection signals.

An evaluation system includes an acquisition module that acquires a safety program, an instruction extraction module that extracts an instruction directed to processing for causing a target device to operate with safety maintained, a signal extraction module that extracts an input signal and an output signal related to the instruction, a setting module that displays the extracted input signal and the extracted output signal in association with each other, and receives a setting of an expected output value for the displayed output signal, the expected output value being a value for causing the target device to operate with safety maintained, and an evaluation module that changes a value of the extracted input signal and determines whether a value of the output signal calculated by an operation in accordance with the safety program, in response to change of the value of the input signal, is identical to the expected output value.

Systems and methods are disclosed for detecting and classifying faults in a networked system. An offline training offline storage and training function can store network data and periodically train machine learning models for identifying faults. Machine learning models can include separate detection and classification models. These machine learning models can be periodically provided to an online anomaly detection function and an online anomaly classification function for detecting and classifying anomalies in real time.

One embodiment can provide a system for detecting faults in a machine. During operation, the system can obtain a dynamic signal associated with the machine, apply one or more signal-processing techniques to the dynamic signal to obtain frequency, amplitude, and/or time-frequency information associated with the dynamic signal, extract motion-insensitive features from the obtained frequency, amplitude, and/or time-frequency information associated with the dynamic signal, and determine whether a fault occurs in the machine based on the extracted features.

Advanced analytics refers to theories, technologies, tools, and processes that enable an in-depth understanding and discovery of actionable insights in big data, wherein conventional systems and methods may be prone to errors leading to inaccuracies. Embodiments of the present disclosure provide systems and methods for performing data analytics in an IoT platform wherein input data pertaining to problem type, solution associated thereof, sensory information corresponding to sensors deployed in the platform, knowledge of domain expert(s) specific to input data are depicted in graphical knowledge representations, wherein relationships between (i) sensors and associated attributes and (ii) the domain knowledge across the plurality of graphical knowledge representations are determined wherein Machine Learning (ML) models are then applied to the determined relationship for optimizing ML models wherein problem statement, root cause, from one knowledge to another are translated using translation technique(s) to determine root cause analysis and interpretable root cause information.