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14 results about "Prognostics" patented technology

Prognostics is an engineering discipline focused on predicting the time at which a system or a component will no longer perform its intended function. This lack of performance is most often a failure beyond which the system can no longer be used to meet desired performance. The predicted time then becomes the remaining useful life (RUL), which is an important concept in decision making for contingency mitigation. Prognostics predicts the future performance of a component by assessing the extent of deviation or degradation of a system from its expected normal operating conditions. The science of prognostics is based on the analysis of failure modes, detection of early signs of wear and aging, and fault conditions. An effective prognostics solution is implemented when there is sound knowledge of the failure mechanisms that are likely to cause the degradations leading to eventual failures in the system. It is therefore necessary to have initial information on the possible failures (including the site, mode, cause and mechanism) in a product. Such knowledge is important to identify the system parameters that are to be monitored. Potential uses for prognostics is in condition-based maintenance. The discipline that links studies of failure mechanisms to system lifecycle management is often referred to as prognostics and health management (PHM), sometimes also system health management (SHM) or—in transportation applications—vehicle health management (VHM) or engine health management (EHM). Technical approaches to building models in prognostics can be categorized broadly into data-driven approaches, model-based approaches, and hybrid approaches.

Deep reinforcement learning for airplane component failure prognostic full cycle automation

The present disclosure provides techniques for deep reinforcement learning to achieve full-cycle automation in airplane component failure prognostics. Flight data is preprocessed to identify parameters representing operational characteristics of an airplane component. A reinforcement learning framework is formulated based on the preprocessed flight, comprising defining a state representation as an input to a policy model, determining an action of sending an alert or not based on the state representation, modeling one or more system behaviors in response to the action using the preprocessed flight data, calculating a reward of the action under the state representation using a predefined reward structure, collecting training data by simulating an airplane component prognostic procedure. The policy model is trained using a learning and optimization algorithm with the training data to increase an expected discounted cumulative reward by choosing an action under the state representation.
Owner:THE BOEING CO

System and method for prognostic-based dynamic task allocation in a multi-agent autonomous system

A system and method for fail-operational mission continuity in a multi-agent autonomous system. Each autonomous agent includes an onboard Prognostic Health Management (PHM) module that monitors health using sensor data. Upon detecting an incipient fault, the PHM module calculates a prognostic Remaining Useful Life (RUL). This RUL is transformed into a quantitative Operational Risk Cost (Ω) and communicated to a multi-agent control system. The control system's dynamic task allocation algorithm uses the Ω values as key inputs in a multi-objective optimization process. This enables the system to proactively and autonomously re-allocate a task from a degrading agent to a healthy agent before a failure occurs. The degrading agent is simultaneously commanded to perform a safe contingency maneuver. This integration of real-time prognostics and multi-agent control creates a resilient, self-healing system capable of completing missions despite hardware degradation.
Owner:MITCHELL RICHARD JOSEPH

Dynamic multi-stage air data probe prognostics health monitoring management

A system for monitoring a vehicle-borne probe includes a first edge device in communication with the probe and configured to sense data related to a characteristic of a heating element of the probe, a coordinator in communication with the first edge device and configured to receive a first data output from the first edge device and to incorporate the first data output into a data package, a cloud infrastructure in communication with the coordinator via a data gateway and configured to analyze the data package to estimate a remaining useful life and predict a failure of the probe, and a ground station in communication with the cloud infrastructure and configured to refine remaining useful life estimation and failure prediction techniques of the system.
Owner:ROSEMOUNT AEROSPACE INC

Substation hard strap state monitoring system based on visual identification

The invention discloses a transformer substation hard pressing plate state monitoring system based on visual identification, belongs to the field of hard pressing plate data analysis and mining, and aims to solve the problems that in the prior art, the efficiency of a monitoring mode is low, and the identification precision cannot be guaranteed. Hard strap image information can be collected in real time through a sensing unit, the state and abnormity of the hard strap can be accurately judged by means of a visual recognition algorithm, the recognition effect is optimized by fusing environmental data, efficient capture of the state and abnormity of the hard strap is achieved, then a Prognomics engine constructs and trains hard strap digital twinborn bodies through a fractional order physical information neural network, and the hard strap digital twinborn bodies are obtained. According to the method, a neural differential equation solver is used for simulating a performance attenuation track under mechanical stress and electric stress, and a potential fault root cause is positioned through an abnormality traceability device based on maximum likelihood estimation, so that precise simulation of performance attenuation of the hard pressing plate and effective tracing of the fault root cause are realized.
Owner:JIANGSU DONGGANG ENERGY INVESTMENT CO LTD

Load forecasting method for urban low-voltage distribution network based on PHM

This invention relates to the field of distribution network load forecasting technology. Specifically, it relates to a load forecasting method for urban medium- and low-voltage distribution networks based on PHM (Prognostics and Health Management). It includes the following steps: S1, collecting historical load data of the medium- and low-voltage distribution network, simultaneously acquiring PHM data of the medium- and low-voltage distribution network equipment, performing risk health index analysis based on the PHM data, and obtaining the risk health index of the medium- and low-voltage distribution network. This invention employs a hierarchical load splitting strategy of medium-voltage feeder-transformer area-individual user, combined with a two-dimensional user classification system of electricity consumption characteristics and total electricity load, refining load data to the individual user level. Simultaneously, it dynamically sets the data collection duration through load fluctuation frequency and sets a comprehensive fluctuation range based on the statistical characteristics of the load fluctuation range of users of the same category, achieving refined and personalized load forecasting. Compared with existing single-dimensional classification and fixed-range constraints, this significantly improves the accuracy of load forecasting for different types of users.
Owner:GUANGZHOU JIENENG POWER TECH CO LTD

Contrastive learning based prognostics and health management method

The present application relates to the technical field of fault analysis, and more particularly to a fault prediction and health management method based on contrast learning, comprising: constructing a wind turbine health operation dataset to be input into a space-time contrast encoder to generate a wind turbine health benchmark feature library; comparing and analyzing the health deviation degree of the wind turbine according to the wind turbine operation data, wind turbine location meteorological data and wind turbine health benchmark feature library; analyzing the fault state of the wind turbine according to the health deviation degree analysis result of the wind turbine, wind turbine oil detection data and wind turbine blade inspection image data; importing the health deviation degree comparison analysis result and fault state analysis result of the wind turbine into a wind turbine dynamic scheduling strategy analysis model to generate a wind turbine dynamic scheduling strategy, and dynamically scheduling the operation of the wind turbine in the wind turbine generator set; the load of the high-risk wind turbine can be adaptively adjusted to reduce the fault risk, and the utilization rate of the low-risk wind turbine is improved to meet the total demand, thereby improving the equipment life and grid stability.
Owner:HUBEI NORMAL UNIV

Brake coefficient of friction (μ) estimation for prognostics and health management (PHM) and improved load balance (LB)

A method for controlling brake assemblies of a vehicle is provided. Receiving a deceleration of each wheel assembly of a plurality of wheel assemblies of the vehicle. Comparing the deceleration of each wheel assembly to an average deceleration of the plurality of wheel assemblies. Responsive to one or more of the deceleration of each wheel assembly of one or more wheel assemblies being outside a predetermined range of the average deceleration of the plurality of wheel assemblies, reporting a warning message to a maintenance crew to inspect one or more brake assemblies associated with the one or more wheel assemblies.
Owner:GOODRICH CORP

A method and system for prognostics and health management of end devices of a ventilation system

The application provides a kind of ventilation system end equipment failure prediction and health management method and system, it is related to state monitoring technical field, the method comprises: step 1, the standardized operating data set is as processing object, extracts the key time-frequency features of the mechanical operation of fan and the state of pipeline airflow;Based on the spatial distribution coordinates of three key monitoring nodes and the aerodynamic mechanical impedance characteristics of each node, a three-dimensional space mapping ellipsoid is fitted and constructed;Step 2, the three-dimensional space mapping ellipsoid is adaptively meshed along the main axis direction and the flow-vibration energy transfer numerical simulation is carried out, and the spatial phase coupling correction value is obtained.The application realizes the precise perception of the multi-physical field coupling state of the equipment, the quantitative early warning of the early hidden failure and the closed-loop management of the predictive maintenance.
Owner:ZHONGQING RUI (XIAMEN) ENVIRONMENTAL TECH CO LTD

A PHM system for subway train fault detection

ActiveCN116658596BRealize major oil leakage fault detectionWhether a broken tooth failure occurs?GearboxesGear lubrication/coolingGear wheelIn vehicle
This application discloses a PHM (Prognostics and Health Management) system for subway train fault detection, relating to the field of subway train fault detection technology. It includes an onboard host and gearbox, a dynamic PHM fault diagnosis module, and a static PHM fault diagnosis module. The gearbox contains a gear set. The technical advantages of this application are: by combining the static and dynamic PHM fault diagnosis modules, when the subway train is noisy, the dynamic PHM fault diagnosis module performs gearbox fault detection on the lubricating oil; when the subway train is stationary, the static PHM fault diagnosis module performs a secondary judgment on the previously occurred fault warnings; a liquid level photoelectric sensor provides an upper limit warning for the oil level during oil filling, and through modification, it can also detect major gearbox oil leakage faults; when the train is stationary, a color sensor detects whether the lubricating oil has emulsified; and when the train is moving, a color sensor can also preliminarily detect whether a gear tooth breakage fault has occurred.
Owner:QINGDAO YUNKAI TECHNOLOGY CO LTD

Prognostics in hydraulic transmission system using e-machine drive

A device for determining fluid degradation includes a memory and processing circuitry configured to cause the device to generate first calibration data of an e-machine at a first time, generate second calibration data of the e-machine at a second time subsequent to the first time, and determine that the fluid is degraded in response to a difference between the first calibration data and the second calibration data being greater than or equal to a degradation threshold.
Owner:DEERE & CO

Systems and methods for integrated diagnostics and prognostics of a multicomponent dynamic system

A vehicle that can perform component-level diagnostics of its various systems, is disclosed. The vehicle includes processors, memory, a communication interface, and one or more sensors. The vehicle may receive vibration data related to a multicomponent dynamic system from the one or more sensors. The vehicle may also determine that a set of operating conditions associated with the multicomponent dynamic system is satisfied and determine health indication data for the multicomponent dynamic system. Based on the health indication data for the multicomponent dynamic system the vehicle can determine that the system is exhibiting unexpected behavior. Further, the vehicle may also determine that a second set of operating conditions associated with a component of the multicomponent dynamic system are satisfied and determine second health indication data for the component. Based on second health indication data, the vehicle may determine that the component is contributing to the unexpected behavior of the system.
Owner:FORD GLOBAL TECH LLC

Data efficient tool for predicting failures under dynamic operating conditions

Lack of data, among other technical issues, can make it difficult or impossible to properly predict the degradation over time of various physical components or equipment. A failure prognostics system includes a degradation evolution model and a parametric model. The system can obtain the one or more physical quantities of a physical system, and train the parametric model with the one or more physical quantities of the physical system. The system can calibrate the degradation evolution model with one or more calibration parameters that are output from the parametric model. Furthermore, the system can generate a degradation output from the degradation evolution model that predicts a degradation of the physical system over time. In some cases, based on the degradation output, the system triggers an action to replace or repair a portion of the physical system.
Owner:SIEMENS AG +1

Ring main unit live detection system and control method fusing infrared sensing and phm diagnosis

PendingCN122171906AEffectively distinguish abnormal temperature risesAvoid misdiagnosis of faultsRadiation pyrometryElectrical testingComputational physicsFault avoidance
This invention relates to the field of ring main unit (RMU) testing technology, specifically to a live-line testing system and control method for RMUs integrating infrared sensing and PHM (Prognostics and Health Management) diagnostics. It includes: a RMU topology modeling unit; a multi-source synchronous acquisition unit; a dynamic attention PHM diagnostic unit with a built-in dynamic attention mechanism adapted to the RMU's power operation scenarios; and a fault location output unit. This invention integrates a Fourier steady-state heat conduction model into the dynamic attention mechanism, quantifying the heat conduction attenuation coefficient between nodes. This effectively distinguishes between temperature changes caused by internal heat conduction effects within the RMU and abnormal temperature rises caused by the fault source itself, avoiding misdiagnosis. Simultaneously, it dynamically adjusts the weight allocation of infrared temperature features and electrical features based on the real-time operating conditions of the RMU, adapting to the fault feature analysis needs under different operating scenarios such as high load and low load, thus improving the accuracy and scenario adaptability of fault diagnosis in live-line testing scenarios of distribution network RMUs.
Owner:B&C ELECTRIC CHINA CO LTD

Simulation method and system of airplane fault prediction and health management PHM architecture

The invention discloses a simulation method and system of an aircraft fault prediction and health management (PHM) architecture. The method comprises the following steps: dividing an aircraft system into a data acquisition layer, a signal processing layer, a state monitoring layer, a health assessment layer, a prediction layer and a decision support layer according to a PHM system architecture; a simulation model of each layer is constructed in sequence, and sensor data acquisition and noise addition, data noise reduction and conversion, abnormal state judgment based on threshold detection, health assessment and fault probability calculation based on Bayesian reasoning, residual service life prediction based on a degradation trend and maintenance decision generation based on comprehensive cost optimization are simulated respectively. The invention provides a hierarchical and standardized system-level simulation solution, which can perform dynamic and executable verification and optimization on the overall architecture design, each layer of algorithm logic and interaction performance of the PHM system before physical prototype manufacturing, and effectively solves the problems of disjunction of design and verification, tight model coupling and poor reusability in the prior art. And the development cost and risk are obviously reduced.
Owner:NORTHWESTERN POLYTECHNICAL UNIV