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143 results about "Maintenance actions" patented technology

Maintenance actions, historically referred to as socio-emotive actions, are those leadership actions taken by one or more members of a group to enhance the social relationships among group members. They tend to increase the overall effectiveness of the group and create a more positive atmosphere of interaction within the group.

Intelligent condition-based engine/equipment management system

Health management of machines, such as gas turbine engines and industrial equipment, offers the potential benefits of efficient operations and reduced cost of ownership. Machine health management goes beyond monitoring operating conditions, it assimilates available information and makes the most favorable decisions to maximize the value of the machine. These decisions are usually related to predicted failure modes and their corresponding failure time, recommended corrective actions, repair / maintenance actions, and planning and scheduling options. Hence machine health management provides a number of functions that are interconnected and cooperative to form a comprehensive health management system. While these interconnected functions may have different names (or terminology) in different industries, an effective health management system should include four primary functions: sensory input processing, fault identification, failure / life prediction, planning and scheduling. These four functions form the foundation of the method of ICEMS (Intelligent Condition-based Engine / Equipment Management System). To facilitate information processing and decision making, these four functions may be repartitioned and regrouped, such as for network based computer software designed for health management of sophisticated machinery.
Owner:INTEL CORP

Direct drive fan system with variable process control

The present invention is directed to a direct-drive fan system and a variable process control system for efficiently managing the operation of fans in a cooling system such a as wet-cooling tower or air-cooled heat exchanger (ACHE), HVAC systems, mechanical towers or chiller systems. The present invention is based on the integration of key features and characteristics such as tower thermal performance, fan speed and airflow, motor torque, fan pitch, fan speed, fan aerodynamic properties, and pump flow. The variable process control system processes feedback signals from multiple locations in order control a high torque, variable speed, permanent magnet motor to drive the fan. Such feedback signals represent certain operating conditions including motor temperature, basin temperature, vibrations, and pump flow rates. Other data processed by the variable process control system in order to control the motor include turbine back pressure set-point, condenser temperature set-point and plant part-load setting. The variable process control system processes this data and the aforesaid feedback signals to optimize the operation of the cooling system in order to prevent disruption of the industrial process and prevent equipment (turbine) failure or trip. The variable process control system alerts the operators for the need to conduct maintenance actions to remedy deficient operating conditions such as condenser fouling. The variable process control system increases cooling for cracking crude and also adjusts the motor RPM, and hence the fan RPM, accordingly during plant part-load conditions in order to save energy.
Owner:PRIME DATUM

A modeling method of hybrid fault early warning model and hybrid fault early warning model

InactiveCN102262690AGuarantee intrinsic safetySpecial data processing applicationsOperabilitySystem failure
The embodiment of the invention provides a modeling method of an early warning model of mixed failures and a modeling system. The modeling method provided by the invention comprises the following steps of: generating a function analyzing module on the basis of HAZOP (Hazard and Operability Analysis) or FMEA (Failure Mode and Effects Analysis); generating a degeneration analyzing module on the basis of FMEA analyzing results and a theory of stochastic processes; generating an accident analyzing module according to state monitoring data and maintenance action information; generating an action analyzing module according to output results of the function analyzing module and the degeneration analyzing module through combining a DBN (Dynamic Bayesian Network) theory; taking the output of the accident analyzing module as an inference evidence and utilizing a DBN inference algorithm to process forward and backward inferences in the same time period to generate an evaluating module for outputting factors and consequences of system failures; taking the output results of the evaluating module and the accident analyzing module as the inference evidence and utilizing the DBN inference algorithm to process forward and backward inferences in the different time periods to generate a predicating module for outputting prospective degeneration tendencies of each member of the system. The model provided by the invention can be used for tracking the failure factors of the system and inferring possible failure consequences and probability.
Owner:CHINA UNIV OF PETROLEUM (BEIJING)

Monitoring System for Power Grid Distributed Power Generation Devices

InactiveUS20110130982A1Restoring power performance of powerReducing false alarmElectric devicesPower measurement by current/voltageData acquisitionData interface
The invention relates to an autonomously working monitoring system (10), a method for monitoring and maintenance of power grid distributed power generation devices (14) and a related computer program product. The system comprises at least one power performance monitoring unit (12) for monitoring, analyzing and storing at least power performance data (70) of at least one power generation device (14);
  • at least one power generation device (14) comprising at least one power generation module (16) for generation of electric power and at least one inverter module (18) for feeding in electric power of said power generation module (16) to a power grid (20);
  • and an external network (22) connecting one or more power generation devices (14) with said power performance monitoring unit (12).
The power generation device (14) further comprises
  • at least one data acquisition module (24) for measuring of power output of each power generation module (16);
  • at least one inverter measuring module (26) for measuring of power output of said inverter (18) to the power grid (20);
  • a data interface module (28) in power line communication with said data acquisition module (24), and in communication with said inverter measuring module (26) and said external network (22) for sending power performance data (70) of said power generation device (14) to said power performance monitoring unit (12) including power generation module ID (66) and inverter ID (68), and/or for autonomously sending a maintenance notice for requesting a maintenance action based on at least a specific power performance pattern.
Owner:IBM CORP

Optimal selective maintenance optimization method and device for multi-stage task multi-state system

ActiveCN103714397AAvoid the risk of overuseEasy to implementForecastingDependabilityComputer science
The invention discloses an optimal selective maintenance optimization method and device for a multi-stage task multi-state system. The method comprises the steps that a component layer performance set, a state transition rate matrix of each component and a multi-stage task sequence in the system are given; according to the state transition rate matrix of each component, probability distribution of the component layer performance set is calculated; according to the component layer performance set and the probability distribution of the component layer performance set, a system layer performance set and probability distribution of the system layer performance set are calculated; according to the performance state of each component, the system layer performance set, the probability distribution of the system layer performance set and the multi-stage task sequence, system reliability is calculated; according to the residual number of replacement components, a maintenance action feasible set is calculated; the system task reliability is taken as an indicator function, and the maintenance action feasible set is taken as constraint conditions; according to the multi-stage task sequence, the performance state of each component and the residual number of the replacement components, a maintenance optimization model is built, and an optimal strategy table is solved.
Owner:TSINGHUA UNIV
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