Methods, systems, and vehicles are provided for controlling an active control system for a vehicle. In one embodiment, a method for controlling an active control system includes determining a health of a first control system, via a first processor of the first control system; determining a health of a second control system, via a second processor of the second control system; selectively controlling the active control system with instructions from the first control system or the second control system, based on the health of the first control system and the second control system; and selectively controlling communications from the first control system and the second control system, based on the health of the first control system and the second control system.

Method and system for performing close-loop analysis to electronic component failures are provided. The system establishes an electronic component fault tree of physics of failure (FTPF), converts the FTPF into a failure locating fault tree, establishes an electronic component fault dictionary with the cause of failure mechanism corresponding to failure characteristics, and performs close-loop analysis to the electronic component according to the fault tree and the fault dictionary. According to the disclosure, it is possible to locate the electronic component fault in the internal physical structure by the failure locating fault tree, to give a clear failure path, to quickly identify the failure mechanism corresponding to the electronic component failure mode by analyzing the failure characteristic vector in the fault dictionary, and to determine the mechanism factors and influencing factors of relevant failure mechanism by the FTPF, thereby achieving fast and accurate locating and diagnosis for the electronic component failure.

A failure-effect validation system includes an effects modeler configured to develop a cumulative effects model for failure modes of the complex system, and by which a model of the complex system is extendible to form an extended complex-system model. The effects modeler is also configured to develop search targets each of which includes logical expressions of notable hazards and other factors that contribute to the cumulative effects, such as crew workload, safety margin and/or physiological effects. A model analysis system is configured to perform an automated analysis using the extended complex-system model and search targets, and in which the automated analysis includes a graph search of possible states of the extended complex-system model to locate search targets. And the effects assessment system is configured to selectively generate a layout of failure analysis data including at least a portion of the extended complex-system model and results of the automated analysis.

A method for realizing a centralized control platform for large fully-mechanized coal mining face equipment is provided. In the method, on the basis of a coal cutter system, a hydraulic support system, a coal mining face transportation system, an emulsion pump station system, a mobile transformer substation system and a video monitoring system of the large fully-mechanized coal mining face equipment, real-time monitoring, centralized coordination control and information communication network are realized by a high-speed embedded computer UNO-3072A, a high-speed data acquisition card PCI-1716, a PowerBuilder front-end development platform, an SQLServer database, a Modbus TCP/IP communication protocol and an industrial Ethernet, thereby realizing centralized control over the large underground fully-mechanized coal mining face equipment. Automated production of fully-mechanized coal mining faces is realized.

A testing platform tests an electrical and mechanical system such as an HVAC unit according to an algorithm that reduces the total testing time of the components of the system, while ensuring the safety of the system during system-wide testing. The platform uses constraints that are checked both before and during the testing to ensure that HVAC operating conditions are acceptable for starting and maintaining component tests. Preferably, the platform uses finite-state machines for each device to organize the component tests, allowing for monitoring of constraints and starting, pausing, and stopping component tests. Preferably, total test execution time is reduced by running component tests in parallel, running component tests based on loads of the components, or combinations of both.

Systems and methods are provided for dynamically grouping data analysis content derived from a plurality of sensors. In one embodiment, a plurality of sensors can be disposed on a plurality of machine trains or one or more components within the plurality of machine trains, each machine train including one or more machines configured to operate in an industrial environment. A communication circuit can be operatively coupled to the plurality of sensors and configured to communicate data measured by the plurality of sensors, and a graphical user interface (GUI) can be configured to generate one or more visualizations of the measured data. A processor can be configured to receive the measured data via the communication circuit, to generate a plurality of measurements based on the measured data, and to operatively control the GUI.

A method for determining the state of health of an industrial process executed by at least one industrial plant comprising an arrangement of entities, and the state of each such entity, includes obtaining values of the entity state variables; providing the values to a model to obtain a prediction of the state of health; determining propagation paths for anomalies between said entities; determining importances of the states of health of the individual entities for the overall state of health of the process; and aggregating the individual states of health of the entities to obtain the overall state of health of the process.

A risk evaluation system includes a storage unit, an operation unit, a calculation unit, a risk evaluation unit and a display unit. The calculation unit calculates first and second factors for use in risk evaluation relating to specific constituent devices on the basis of predetermined information about the specific constituent devices. The risk evaluation unit generates risk evaluation information to be used for displaying a device risk evaluation matrix defined by two axes of the first factor and the second factor and including plot images plotted based on the first and second factors of the specific constituent devices. Further, the risk evaluation unit generates the device risk evaluation information in identifiable displaying mode to allow identification of plot images of specific constituent devices constituting a same process.

Disclosed is a system and method for measuring a health index of a plant in which a condition of a lower level component is reflected. The actual measurement values of lower level components are reflected to the health index such that, when an actual measurement value of a certain component deviates from a normal range, if the deviation is less likely to trip the plant, the actual measurement value of the component has a minimal influence on the health index. The condition of the plant can be more easily and conveniently monitored based on only the health index of the uppermost level layer.

Systems and methods for building a dependency diagnostic model of a complex system are provided. The system may include, but is not limited to, a processor, the processor configured to receive at least one function model corresponding to each assembly of the complex system, at least one health and condition indicator model corresponding to an output of the complex system, a program data dictionary, standard failure modes and propagation rules, determine interdependencies between the plurality of assemblies of the complex system and the output of the complex system based upon the at least one function model, the at least one health and condition indicator model and the program data dictionary, generate the diagnostic model based upon the determined interdependencies between assemblies of the complex system and the output of the complex system, and optimize the generated diagnostic model based upon the standard failure modes and the propagation rules.