563 results about "Predictive maintenance" patented technology

A system for condition monitoring and fault diagnosis includes a data collection function that acquires time histories of selected variables for one or more of the components, a pre-processing function that calculates specified characteristics of the time histories, an analysis function for evaluating the characteristics to produce one or more hypotheses of a condition of the one or more components, and a reasoning function for determining the condition of the one or more components from the one or more hypotheses.

A “Constrained Predictive Interface” uses predictive constraints to improve accuracy in user interfaces such as soft keyboards, pen interfaces, multi-touch interfaces, 3D gesture interfaces, EMG based interfaces, etc. In various embodiments, the Constrained Predictive Interface allows users to take any desired action at any time by taking into account a likelihood of possible user actions in different contexts to determine intended user actions. For example, to enable a virtual keyboard interface, various embodiments of the Constrained Predictive Interface provide key “sweet spots” as predictive constraints that allow the user to select particular keys regardless of any probability associated with the selected or neighboring keys. In further embodiments, the Constrained Predictive Interface provides hit target resizing via various piecewise constant touch models in combination with various predictive constraints. In general, hit target resizing provides dynamic real-time virtual resizing of one or more particular keys based on various probabilistic criteria.

A display system in which subsequent failures of plant equipment and plant systems are predicted to occur and in which the probability of failure before a specified date and the probability of failure after a specified date is determined and displayed and in which the calendar date is determined and displayed when the desired probability that the equipment not fail prior to the calendar date is specified. The system includes an Equipment Failure And Degradation Module that determines the remaining equipment / system life; a Probability-of-Failure Predictor Module that determines the probability of the equipment / system failing prior to a specified date and the probability of the equipment / system failing after a specified date; and a Date-of-Failure Predictor Module that determines the calendar date that corresponds to a specified probability that equipment not fail prior to the date.

A system for condition monitoring and fault diagnosis includes a data collection function that acquires time histories of selected variables for one or more of the components, a pre-processing function that calculates specified characteristics of the time histories, an analysis function for evaluating the characteristics to produce one or more hypotheses of a condition of the one or more components, and a reasoning function for determining the condition of the one or more components from the one or more hypotheses.

A method and system for maintaining an item of equipment supports the provision of predictive maintenance in a manner which eliminates or reduces downtime of the equipment. The method includes tracking performance data on the equipment or a particular component of the equipment. At least one required maintenance activity is predicted based upon the performance data with respect to a defined performance standard. Performance of the required maintenance activity is scheduled at a defined respective time based upon the prediction.

A system and method of operating a storage system is provided. The storage system includes a tape cartridge having a magnetic tape medium and a tape drive for reading and writing data to the magnetic tape medium of the tape cartridge. Performance data associated with specific operating loci (e.g., bands, directions, tracks, segments, etc.) of the tape drive and tape medium are collected, analyzed, and stored, allowing for analysis and detection of trends over time. In one example, tape usage events are monitored and when they cross a threshold the system may remove particular tapes in a preventative maintenance approach to reduce system outage. Performance data is collected and analyzed with a portion of the performance data being saved to emulated medium auxiliary memory (EMAM) on the magnetic tape, and a portion of the of the performance data saved in non-volatile storage in the drive.

A method for predictive maintenance of a machine includes collecting feature data for the machine which includes a plurality of feature vectors. At least some of the feature vectors are standardized to facilitate compatibility between different vectors. At least some of the standardized feature vectors are transformed into corresponding two-dimensional feature vectors. At least some of the two-dimensional feature vectors are clustered together based on operating modes of the machine. Similar steps are performed on additional feature data collected from the machine. Recently gathered two-dimensional feature vectors are compared to previously clustered feature vectors to provide predictive maintenance information for the machine.

A method of building a model for predicting failure of a machine, including parsing (41) daily machine event logs of one or more machines to extract data for a plurality of features, parsing (42) service notifications for the one or more machine to extract failure information data, creating (43) bags from the daily machine event log data and failure information data for multiple instance learning by grouping daily event log data into the bags based on a predetermined predictive interval, labeling each bag with a with a known failure as positive, and bags without known failures as negative, where a bag is a set of feature vectors and an associated label, where each feature vector is an n-tuple of features, transforming (44) the multiple instance learning bags into a standard classification task form, selecting (45) a subset of features from the plurality of features, and training (46) a failure prediction model using the selected subset of features.

The mobile ad hoc network includes a plurality of wireless mobile nodes and a plurality of wireless communication links connecting the nodes together. A method for operating the network includes discovering and using routes in the network, predicting route failure in the network, and performing route maintenance in the network based upon the predicted route failure.

The present invention relates to a system for automatically adjusting a vehicle feature of a vehicle, where the system includes a first sensor, an onboard computer, a camera, a mirror, a controller; an actuator; and an algorithm. The algorithm instructs the onboard computer in steps for adjusting one or more vehicle features. The first sensor and the controller are in electronic communication with the onboard computer and the controller is in electronic communication with one or more actuators that connect to and adjust the various vehicle features. The onboard computer includes or accesses a database that correlates users, features, and vehicle feature settings. Such vehicle features include seat position and camera viewing angle.

Provided is a servovalve system for regulating fluid flowing within a fluid circuit. The servovalve system comprises a housing, a spool slidably disposed within the housing, a stepper motor operatively connected to the spool, and a controller and a position sensor electronically connected to the stepper motor. The controller generates driver signals representative of a desired amount of stepper motor rotation in order to cause the stepper motor to effectuate spool motion relative to the housing. The position sensor senses an actual amount of stepper motor rotation and generates a quantity of position signals representative thereof. The controller determines a signal ratio of the quantity of the position signals to the quantity of the driver signals and generates a diagnostic signal when the signal ratio reaches a threshold value representative of a predetermined level of mechanical resistance of spool motion relative to the housing.

According to the present invention, the most challenging issues in this work have been to find systematic ways of enabling maintenance engineers to decide an adequate time for the replacement of vacuum pumps on the basis of their current performance assessment result. Further, the comparison of the currently evaluated diagnostics analysis results and the initial (or reference) data set is shown to enable maintenance engineers to decide the replacement of the considered vacuum pump according to the evaluated pump performance indicators. This quantitative diagnostic analysis result is expected not only to enable maintenance engineers to decide an adequate time for the replacement of vacuum pumps on the basis of their current performance assessment results but also to improve the reliability and confidence of the predictive maintenance of low vacuum pumps.

A method and system for predictive maintenance of electronic equipment on board an aircraft (1). To produce a prognosis, the following are provided: a step (48) of modeling the equipment (3) with a model (53) for damage by an external aggression; a step (49) of simulating the damage up to failure; a learning step (64); a step (65) of classifying calculated and normalized values; and a fusion step (61) giving the real prognosis of the time to maintenance in units of time. The invention applies in particular to a rotary wing aircraft (1), e.g. a helicopter drone.

A system and method for telemetrically collecting on-road vehicle diagnostic data. In one embodiment, the method includes collecting vehicle diagnostic data from service shops, on-road vehicles and warranty records, aggregating the collected data and extracting knowledge therefrom. The extracted knowledge can be used to enhance algorithms on-board vehicles or at service centers so as to better identify vehicle faults and provide enhanced diagnostics and prognostics. The enhanced algorithms can then be used to provide predictive maintenance suggestions, provide trouble shooting assistance or provide vehicle design improvements.

A supply chain transaction network. The network includes a customer agent server hosting a collection of intelligent customer agents for interfacing with and extracting information from one or more of a condition monitoring system, a computer maintenance management system and a procurement system and a distributor agent server hosting a collection of intelligent distributor agents for interfacing and communicating with one or more of a supply chain planning system, an inventory management system, a logistic management system, an order management system, an intelligent order fulfillment system, and an equipment knowledge base. An agent network manager and broker routes messages between the distributor agent server and the customer agent server to effect a movement of items within the supply chain.

A system and method of operating a storage system is provided. The storage system includes a tape cartridge having a magnetic tape medium and a tape drive for reading and writing data to the magnetic tape medium of the tape cartridge. Performance data associated with specific operating loci (e.g., bands, directions, tracks, segments, etc.) of the tape drive and tape medium are collected, analyzed, and stored, allowing for analysis and detection of trends over time. In one example, tape usage events are monitored and when they cross a threshold the system may remove particular tapes in a preventative maintenance approach to reduce system outage. Performance data is collected and analyzed with a portion of the performance data being saved to emulated medium auxiliary memory (EMAM) on the magnetic tape, and a portion of the of the performance data saved in non-volatile storage in the drive.

A predictive maintenance system for wind parks, the wind park comprising a group of wind turbines (Ai), a communications network (RS) and a supervision and control system (ST) The predictive maintenance system comprises a monitoring and processing equipment (SMP) connected to the control system (PLC) of the wind turbine (Ai), such that the monitoring and processing equipment sends alarms through the control system of the wind turbine to the supervision and control system. The invention also refers to a monitoring and processing equipment (SMP) for wind turbines.

A method for requesting one or more machines to be maintained includes monitoring the machine or machines and detecting when a failure of at least one machine occurs. The method further includes executing a computer program on an electronic terminal associated with the failed machine. The method further includes entering data relating to the condition of the failed machine into the computer program via the electronic terminal and transmitting the data to a database server, thereby initiating a process to alter the condition of the failed machine. In one embodiment of the method, the database server compiles historical data relating to the condition of the one or more machines. The historical information may be used in a predictive maintenance environment to further minimize downtime.

According to the present invention, the most challenging issues in this work have been to find systematic ways of enabling maintenance engineers to decide an adequate time for the replacement of vacuum pumps on the basis of their current performance assessment result. Further, the comparison of the currently evaluated diagnostics analysis results and the initial (or reference) data set is shown to enable maintenance engineers to decide the replacement of the considered vacuum pump according to the evaluated pump performance indicators. This quantitative diagnostic analysis result is expected not only to enable maintenance engineers to decide an adequate time for the replacement of vacuum pumps on the basis of their current performance assessment results but also to improve the reliability and confidence of the predictive maintenance of low vacuum pumps.

Predictive maintenance systems and methods are described. A method includes measuring environmental conditions using a plurality of sensors within the IED, processing the environmental measurements to determine long-term exposure factors representing historical operating conditions of the IED, applying a reliability model to the long-term exposure factors, determining a numerical measure of IED life based on the long-term exposure factors and the reliability model, comparing the numerical measure of IED life to preselected boundary values, and signaling if the numerical measure of IED life is outside of the preselected boundary values.

The invention discloses an intelligent manufacturing plant virtual debugging and virtual monitoring method and system based on digital twinning. In the method, real-time cooperation between a digitalmodel of a product and a field device is realized through an intelligent manufacturing plant platform based on digital twinning. A product manufacturer / product user can grasp the use state of the product in real time on a product digital model of a control center and perform remote monitoring and fault diagnosis on the product / equipment, thereby realizing predictive maintenance and avoiding unplanned downtime of the equipment, and meanwhile the operation data of the product are fed back into the product digital model to help the manufacturing enterprise to continually optimize and improve theproducts and to provide basic data for the intelligent manufacturing at the same time.

A method and system for maintaining an item of equipment supports the provision of predictive maintenance in a manner which eliminates or reduces downtime of the equipment. The method includes tracking performance data on the equipment or a particular component of the equipment. At least one required maintenance activity is predicted based upon the performance data with respect to a defined performance standard. Performance of the required maintenance activity is scheduled at a defined respective time based upon the prediction.

The invention relates to a fault diagnosis method for trunked industrial robots based on outliers mining, belonging to the filed of fault diagnosis of electromechanical equipment. The method comprises the following steps of: firstly collecting data of original operating state of the trunked industrial robots and carrying out preprocessing operation of classifying and the like; then using a cluster analysis method to carry out analysis by taking a plurality of robots as a group, so as to lead a plurality of equipment to carry out classification according to operational state; based on clustering, utilizing an outliers mining method to calculate outlier factors of each industrial robot and then obtaining outlier degree thereof; separating outliers according to outlier degree and further determining that whether individual industrial robot represented by the outlier occurs fault or not; and judging the specific parts of faults of the robots according to the types of abnormal operation parameters and obtaining fault diagnosis results. By utilizing the fault diagnosis results, the method can implement targeted and predictive maintenance, thus avoiding the occurrence of faults of equipment, improving the reliability of equipment and guaranteeing reliable operation of trunked operational robots.

The invention discloses a composite machine tool digital twinning monitoring system, which relates to the technical field of digital twinning. The composite machine tool digital twinning monitoring system creates a digital twinning monitoring system through using a machine tool information module, realizes multi-platform, multi-data and multi-interface communication based on an OPCUA transmissioninterface, and constructs a man-machine interaction module; a multi-field data acquisition module acquires multi-source heterogeneous data in real time by adopting different types of sensors, processes the acquired data based on an information fusion technology to form twin data, and forwards the twin data to a modeling calculation module; the modeling calculation module is used for forming a digital twinning body of a compound machine tool through driving of the twin data in combination with rules such as constraint, prediction and decision; and a personalized decision module monitors and manages entity machine tool equipment in real time by reconstructing and optimizing a machine tool monitoring twinning model in real time. According to the composite machine tool digital twinning monitoring system, the monitoring process of the operation of the compound machine tool is simplified, the monitoring precision of the machine tool system is improved, and the active predictive maintenance of the operation of the compound machine tool is realized.

A method for assessing health status of a processing chamber is provided. The method includes executing a recipe. The method also includes receiving processing data from a set of sensors during execution of the recipe. The method further includes analyzing the processing data utilizing a set of multi-variate predictive models. The method yet also includes generating a set of component wear data values. The method yet further includes comparing the set of component wear data values against a set of useful life threshold ranges. The method moreover includes generating a warning if the set of component wear data values is outside of the set of useful life threshold ranges.

A method for detecting vibration signatures in a reversible drive is disclosed. The method includes the steps of acquiring digital data representative of vibrations in the reversible drive and identifying and grouping together portions of data in a plurality of groups. The identified portions of data relate to a particular direction of travel of the reversible drive and the plurality of groups relate to travel in different directions of the reversible drive. The method can include the further step of processing at least one of the groups of data using signal processing techniques. A system and computer program product for practicing the method for detecting vibration signatures in a reversible drive are also disclosed.

A method and system for maintaining an item of equipment supports the provision of predictive maintenance in a manner which eliminates or reduces downtime of the equipment. The method includes tracking performance data on the equipment or a particular component of the equipment. At least one required maintenance activity is predicted based upon the performance data with respect to a defined performance standard. Performance of the required maintenance activity is scheduled at a defined respective time based upon the prediction.

A data collector having a digital signal processing circuit that receives a digitized vibration signal, and performs processing steps to isolate high frequency pulses in the digitized vibration signal and quantify energy content of those pulses by detecting a peak negative value of the digitized peak-to-peak amplitude of the received vibration signal, and then using this peak negative value to compute a maximum peak-to-peak value of the received vibration signal. Periodically, the maximum peak-to-peak value and peak negative value are reduced in magnitude by a decay factor, such that the peak negative value and maximum peak-to-peak value decay over time. The decay factors used in computing the maximum peak-to-peak value and peak negative value are determined by the digital signal processing circuit and may be readily changed. As a consequence, high frequency processing performed by the digital signal processing circuit may be readily adapted to the particular frequency characteristics of the machine being analyzed for predictive maintenance, without modification of the analog circuitry of the data collector. The resulting maximum peak-to-peak value comprises a peak-detected digital output signal that may be stored and / or displayed to a user as a reflection of the high frequency content of the vibration signal, or frequency transformed for storage and / or display to a user.

A method and system for automated corrective and predictive maintenance is described herein. In one embodiment, a failure notification associated with a tool is received, wherein the failure notification indicates one or more failure events for the tool. Maintenance data associated with the tool is obtained, wherein the maintenance data includes one or more maintenance events for the tool. An optimal schedule is created for the tool by merging the failure notification and the maintenance data.