78 results about "State of health estimation" patented technology

A wearable platform embodied in a belt or flattened patch-like central body shaped to conform to the abdomen provides physiological monitoring of soldiers during field operations or trauma victims at accident sites and makes health state assessments. The platform includes sensors for heart rate, body motion, respiration rate and intensity, and temperature and further contains a microprocessor and short range transmitter. The respiration sensor uses conductive ink in a novel manner. A small square of the ink is coated on an arched structure so that flexing of the arch either to increase or decrease its radius of curvature modifies the resistance of the structure. This is utilized to set the unstressed resistance of the arch structure and to allow a greater range of resistance values capable of measuring distortions in different deformations of the arch. The respiration sensor supplements the motion information provided by an accelerometer sensor.

Systems and computer-implemented methods are used for analyzing battery information. The battery information may be acquired from both passive data acquisition and active data acquisition. Active data may be used for feature extraction and parameter identification responsive to the input data relative to an electrical equivalent circuit model to develop geometric-based parameters and optimization-based parameters. These parameters can be combined with a decision fusion algorithm to develop internal battery parameters. Analysis processes including particle filter analysis, neural network analysis, and auto regressive moving average analysis can be used to analyze the internal battery parameters and develop battery health metrics. Additional decision fusion algorithms can be used to combine the internal battery parameters and the battery health metrics to develop state-of-health estimations, state-of-charge estimations, remaining-useful-life predictions, and end-of-life predictions for the battery.

Systems, methods and devices which utilize Spread Spectrum Time Domain Reflectometry (SSTDR) techniques to measure degradation of electronic components are provided. Such measurements may be implemented while the components “live” or otherwise functioning within an overall system. In one embodiment, monitoring a power converter in a high power system is accomplished. In this embodiment, degradation of components within the power converter (e.g. metal-oxide-semiconductor field-effect transistors (MOSFETs), capacitors, insulated-gate bipolar transistors (IGBTs), and the like) may be monitored by processing data from reflections of an SSTDR signal to determine changes in impedance, capacitance, or any other changes that may be characteristic of components degrading. For example, an aging MOSFET may experience an increase of drain to source resistance which adds additional resistance to a current path within a power converter. Such a change is able to be analyzed monitored upon processing the reflected test signals.

Disclosed is a body weight managing apparatus comprising: a body weight measuring unit; a bioelectric impedance measuring unit; a body water content evaluation unit; and a health condition evaluation unit. According to the present invention, said body weight measuring unit measures a body weight of a person to be measured, said bioelectric impedance measuring unit applies an alternating current to a body of the person and measures a bioelectric impedance value, said body water content evaluation unit evaluates a body water content based on the bioelectric impedance value measured by said bioelectric impedance measuring unit, and said health condition evaluation unit evaluates a health condition of the person based on the measured body weight and the evaluation result from said body water content evaluation unit.

The invention relates to a health risk assessment and disease early warning information system, and belongs to the technical field of health management. The system comprises an employee health management system and a personal health system; the employee health management system comprises 11 modules such as an employee basic information management module, an employee health data acquisition module,and an employee health questionnaire management module; the personal health system consists of an ordinary user registration sub-module, a personal information management sub-module, a personal health history management sub-module, a daily health monitoring sub-module, a medical sick rest management sub-module, a health questionnaire sub-module, an annual health examination sub-module, a health condition assessment sub-module, a disease risk assessment sub-module, a health promotion management sub-module, and a health consultation forum sub-module. The health risk assessment and disease earlywarning information system forms an integrated network management mode of health management, health risk assessment and health risk intervention control.

Assessing health condition of an animal under study includes receiving heart rate information of the animal under study and performing heart rate variability (HRV) analysis on the received heart rate information for determining autonomic dynamics of the animal under study with respect to a species of which the animal under study is a member, wherein the HRV analysis relates to time domain HRV data and frequency domain HRV data of the received heart rate information that are evaluated with respect to physiological states and corresponding health condition for the time domain HRV data and frequency domain HRV data for the species of the animal under study.

The invention discloses an axle safety health assessment system and method based on axle coupling analysis, and relates to the field of bridge health monitoring. The axle safety health assessment system comprises an axle coupling analysis subsystem, a bridge health situation assessment system and a traffic safety assessment system, wherein the axle coupling analysis subsystem utilizes actual measurement data of a bridge health monitoring system to correct a bridge finite element model to obtain a bridge benchmark finite element model, and the bridge benchmark finite element model is used for carrying out axle coupling vibration analysis calculation to obtain a theoretical calculating value under an equal condition of the actual measurement data of the bridge health monitoring system; the bridge health situation assessment system compares the actual measurement data with the theoretical calculating value to assess the bridge health situation; the traffic safety assessment system utilizes the theoretical calculating value obtained through the axle coupling vibration analysis calculation and actual measurement bridge vibration data to assess a situation of the traffic safety. The theoretical data and the actual measurement data are combined to realize a purpose that the bridge health and the traffic safety are quantitatively analyzed and assessed, and the reliability of an assessment result is improved.

The invention provides an in-situ detecting method for partial discharge of a damped oscillation wave of a large-length ultrahigh voltage crosslinked cable. According to the method, a damped oscillation wave voltage of which the attenuation period is 300mS is adopted to take the place of a power frequency sine-wave voltage to be used as an excitation voltage for testing the partial discharge in a cable line having potential insulation defects; during a voltage boosting process, the partial discharge testing mode is changed into an electrified detection or distributed monitoring mode that the off-line single end fixation measurement is changed into a mode of measuring along middle joints of the line; for signal pickup, a high frequency pulse current coupling sensor is clamped on a cable metal sleeve outtake line so as to take the place of a coupling capacitor and a detection impeder which are connected with a cable terminal in parallel; for data processing, a PD quantity value is calculated by using a pulse current frequency domain integration method. With the adoption of the method, a technical support for diagnosing the defects of ultrahigh voltage crosslinked cable lines and evaluating the insulation states of the cables is provided, the cable state detection means is further enriched and completed for cable operation and maintenance units, and powerful guarantee for improving the operation reliability of the cable lines is provided.

The invention provides a system and a method for evaluating health conditions based on an internet of things. The method comprises the following steps of: receiving health questionnaire survey information of a user from a medical terminal device; acquiring physical sign data of the user by virtue of a physical sign sensor arranged on the medical terminal device; obtaining a health condition evaluation model from a health evaluation model library according to the health questionnaire survey information and the physical sign data; acquiring geographical position information of the user by virtue of a position sensor arranged on the medical terminal device; matching an environment information platform of an area in which the user is positioned according to the geographical position information, acquiring environment information of the user from the environment information platform, and correcting the health condition evaluation model according to the environment information to obtain a health evaluation report of the user; and adding health improvement suggestions from a doctor into the health evaluation report, and sending the health evaluation report to the medical terminal device. The system and the method provided by the invention can be used for evaluating the health condition of the user in combination with environmental factors of the user, so that the accuracy of an evaluation result is improved.

The invention relates to a vehicle battery state of health (SOH) estimation method based on data driving, and belongs to the technical field of battery management. The method comprises the following steps: selecting a to-be-tested battery, and collecting and arranging technical parameters of the battery; carrying out a cyclic aging experiment of the battery according to the vehicle charging working condition and the constant current or dynamic discharging working condition, and establishing a battery aging database according to the voltage, current, temperature and other information of the battery; extracting health factors of other batteries according to the screened subsets, and estimating SOH estimation verification of the batteries under other different discharge working conditions through the trained regression model; and embedding the trained model into a vehicle battery management system, extracting health factors covered by the subset from the vehicle, and performing SOH estimation. According to the method, the optimal feature subset is selected for model training by using a fusion method, so that the calculation amount can be effectively reduced, the model precision is improved, and reference is provided for actual vehicles.

A fuzzy probability comprehensive judgment-based battery state-of-health estimation method belongs to the technical field of lithium iron phosphate battery estimation and aims to solve the problems that the state-of-health of a single battery cannot be ensured by a traditional health estimation technology to cause that the lifetime of a battery pack is remarkably reduced. The fuzzy probability comprehensive judgment-based battery state-of-health estimation method comprises the steps of obtaining estimation data by charge-discharge experiment on a battery to be estimated; obtaining a relation between a state-of-charge (SOC) value and a voltage during the charge-discharge process of the battery; performing normalization on voltage values of the battery under different SOCs, and then taking the voltage values as a state-of-health judgment object of each single battery; calculating an index weight forming an evaluation index coefficient, and determining the state-of-health of each single battery according to a maximum probability principle; and determining the state-of-health of the lithium iron phosphate battery pack by fuzzy comprehensive judgment according to a maximum membership principle. By health estimation on the grouped battery pack, the initialization performance of the battery pack can be greatly improved.

The invention provides a human body pulse information collecting device, comprising an automatic pulse wave collecting module and a pulse wave characteristic vector generating and analysis processing module, wherein the automatic pulse wave collecting module is used for collecting a pulse wave signal of a human body and transmitting the collected pulse wave signal to the pulse wave characteristic vector generating and analysis processing module; and data including characteristic points are extracted from the pulse wave signal by using the pulse wave characteristic vector generating and analysis processing module so as to generate a characteristic vector used for describing a pulse wave. The invention also provides a human body health status monitoring device, comprising the human body pulse information collecting device; and the human body health status monitoring device also comprises a health status evaluating and suggestion generating module, wherein the characteristic vector used for describing the pulse wave and generated by the human body pulse information collecting device is transmitted to the health status evaluating and suggestion generating module; the received characteristic vector and the stored characteristic vector are compared by using the health status evaluating and suggestion generating module; and the health status of the human body is judged according to a comparison result.

The invention discloses a large-scale bridge structure health monitoring method based on three-dimensional modeling simulation. The method comprises the following steps: installing a sensor and a collected central station on a bridge; carrying out real time measuring point monitoring to the bridge; transmitting monitoring data to an information control chamber and storing in a server database; establishing a three-dimensional model of the bridge on a GIS platform so as to simulate and display a bridge structure, the each measuring point and real time monitoring information; carrying out a health status assessment to the bridge structure by combining the real time monitoring information and according to a preset assessment standard; carrying out simulation displaying of an assessment result and simulating the health status of the bridge structure; positioning the sensor and the collected central station on the bridge; adjusting an acquisition parameter of the sensor and the collected central station; real-timely feeding back and controlling operations of the on-site sensor and the collected central station. By using the method of the invention, three-dimensional space display of the sensor and acquisition equipment can be performed. Acquisition and control of hardware equipment can be realized through accurate positioning and the current health status of bridge can be simulated and displayed.

Systems and computer-implemented methods are used for analyzing battery information. The battery information may be acquired from both passive data acquisition and active data acquisition. Active data may be used for feature extraction and parameter identification responsive to the input data relative to an electrical equivalent circuit model to develop geometric-based parameters and optimization-based parameters. These parameters can be combined with a decision fusion algorithm to develop internal battery parameters. Analysis processes including particle filter analysis, neural network analysis, and auto regressive moving average analysis can be used to analyze the internal battery parameters and develop battery health metrics. Additional decision fusion algorithms can be used to combine the internal battery parameters and the battery health metrics to develop state-of-health estimations, state-of-charge estimations, remaining-useful-life predictions, and end-of-life predictions for the battery.

The invention discloses an acousto-optic combined detection method and system for partial discharging of a high-voltage cable. On the basis of fusion of ultrasonic and ultraviolet sensing type non-electrical detection technologies, a partial discharge detection mode of non-fixed high-voltage cable inspection in a complex and strong electromagnetic interference environment is performed by using low-cost portable ultrasonic and ultraviolet sensors to realize synchronous and efficient collection of ultraviolet light and ultrasonic signals of partial discharge of the high-voltage cable; and then multi-analytical-domain partial-distribution information mining and fusion processing of ultrasonic and ultraviolet light pulses is performed, so that the partial discharge detection information is enriched substantially. Partial discharge information that can not be provided by the single technology is provided; the accurate identification and determination of the partial discharge type, cable fault diagnosis, and health status assessment are performed; and real-time storage and analysis of two paths of partial discharge information as well as display and alarm interaction and the like on the main control module are realized.

The invention belongs to the field of battery management and provides a battery stat of charge estimation method and a battery state of health estimation method. With the battery state of charge estimation method and the battery state of health estimation method of the invention adopted, an open-circuit method, an ampere-hour method and a Kalman method can be used in a combined manner through objective and accurate judgment according to the actual physical state of a battery, so that the strengths of each of the methods can be drawn, and therefore, estimation accuracy and reliability can be improved. The state of charge estimation method comprises the following steps that: the working state, stable state, working state conversion mode and working characteristic region of a battery are periodically detected; an SOCocv is obtained through the open-circuit method according to the working state and stable state of the battery; an SOCqc is obtained through the ampere-hour method according to the working state, stable state and working characteristic region of the battery; an SOCklm is obtained through the Kalman method according to the working state and stable state of the battery; and weighted calculation is performed on the SOCocv, SOCqc, and SOCklm, so that a final SOC is obtained. With the battery state of charge estimation method and the battery state of health estimation method adopted, the problems of low precision and low reliability of an existing method which are caused by the failure of the existing method to perform collaborative estimation according to the current and past actual states of a battery can be solved.

Methods and systems for tracking aging effect on battery impedance are provided. A first voltage associated with a first state of a battery, a second voltage associated with a second state of the battery, and an impedance of the battery are determined. A battery impedance table that is used for calculating a state of charge of the battery is updated using the determined impedance. Methods and systems for tracking state of health of a battery are also provided. Partial charge cycles of a received battery are counted between a first charge event and a second charge event of the battery. State of health data of the batter is tracked, and a new state of health estimation is calculated based on the state of health data if the counted partial charge cycles of the battery has a count value that has a predetermined relationship with a predetermined count threshold.

The invention provides a health risk early-warning system and method based on the Internet of things. The health risk early-warning method comprises the steps of receiving health questionnaire survey information of a user from medical terminal equipment; acquiring physical sign data of the user through a physical sign sensor; acquiring a health condition assessment model from a health assessment model library according to the health questionnaire survey information and the physical sign data; matching an environment information platform of an area where the user is located according to geographical location information of the user, acquiring environment information of the user, correcting the health condition assessment model according to the environment information to acquire a health assessment report; parsing the health risk grade of the user from the health assessment report; when the health risk grade exceeds a preset grade, performing early-warning marking on the health risk grade, and adding health improvement suggests of a doctor to the health assessment report; and sending the health assessment report to the medical terminal equipment. The health risk early-warning system and method consider environment factors in which the user is located in health condition assessment, the accuracy of an assessment result is improved, and early-warning is provided timely.

A method for state of health estimation and misalignment correction in a vehicle lane management system. Two lane sensing systems onboard a vehicle provide lane information to a lane management system, where one of the lane sensing systems may be a dedicated forward-viewing lane sensing system, and the other may use images from a surround-view camera system. The lane information is stored in a fixed-length, moving-window circular data buffer. A correlation coefficient is recursively computed from the lane information from the two lane sensing systems and used to calculate a state of health of the lane management system. A linear regression relationship is also computed between the data from the two lane sensing systems, and the scale factor and offset value are applied to the lane information from the second lane sensing system before a fusion calculation is performed on the lane information from the two lane sensing systems.

The invention relates to a lithium ion battery state of health estimation method. The method includes the following steps that: discharging voltage, discharging current, and discharging time data during the charging and discharging of a lithium ion battery which are performed under a certain working system before and after the aging of the lithium ion battery are obtained; discharging voltage, discharging current, and discharging time data during identical state of charge intervals are intercepted from the data which are obtained in the first step; the state of health indication factor expression of the lithium ion battery is defined; the value of Vlower limit in the third step is obtained; and an HI value in the formula is obtained, and the state of health of the battery is obtained. According to the lithium ion battery state of health estimation method of the invention, the state of health of the lithium ion battery is estimated according to the apparent data (discharging voltage, discharging current, and discharging time data) which can be measured in real time during the work of the battery. The lithium ion battery state of health estimation method of the invention has he advantages of easiness in parameter acquisition, high applicability and real-time application. The lithium ion battery state of health estimation method can be easy to embed a battery management system toestimate the state of health of a battery. The lithium ion battery state of health estimation method can assist in greatly eliminating the defects of existing test systems or test equipment, and is very practical.

The invention discloses a multi-parameter integration real-time normally-running condition prediction method for a high voltage power supply of a radar transmitter. The method comprises the following steps of: monitoring input voltage, current, output voltage, and current signals of the high voltage power supply in real time and on line, calculating to acquire four parameter values, namely the output voltage, output resistance, output ripples, and power supply efficiency in real time, and constructing a four-dimensional vector which is used as a fault characteristic vector of the high voltage power supply; performing phase-space reconstruction of four parameters by a genetic algorithm and a least square support vector machine algorithm according to historical time series data of the four parameters, namely the output voltage, output resistance, the output ripples, and the power supply efficiency; obtaining four parameter values at certain moment in future and the corresponding fault characteristic vector by a multivariate time series locality predication integration method; and finally after the fault characteristic vector of the high voltage power supply at certain moment in the future is normalized, and calculating to obtain the Euclidean distance between the normalized fault characteristic vector and the standard fault characteristic vector, wherein the Euclidean distance is used for estimating the running state of the high voltage power supply. By the method, the state of the high voltage power supply of the radar transmitter can be monitored in real time, and the fault of the high voltage power supply can be predicted, and accurate and real-time information is provided for estimation of the running state and the on-condition maintenance of the high voltage power supply of the radar transmitter.

The invention discloses a bridge inspection and monitoring integrated health condition evaluation system and a use method thereof, belongs to the field of building bridges, and adopts the technical scheme that the bridge inspection and monitoring integrated health condition evaluation system comprises a health monitoring system and an on-site inspection part which are combined for use, and the health monitoring system comprises a data management system, a component rating system and a damage evaluation system; the data management system is used for managing detection data of the sensor systemand a preset database; the component rating system is used for rating importance, danger degree and vulnerability of the bridge components; the damage assessment system is used for assessing the damage assessment state; the on-site inspection portion includes conventional inspection, detailed inspection, and special inspection to evaluate a damage state of the component. The invention also discloses a use method of the system. The system has the advantages that the engineering decisions can be scientifically guided, effective maintenance, repair and reinforcement work can be carried out on thebridge, and the service life of the bridge is prolonged. The method is suitable for the bridge structure detection and monitoring.

The invention discloses a lithium ion power battery state-of-health estimation method based on machine learning. The method is used for estimating the state-of-charge (SOC) and the state-of-health ofa power battery in real time. Parameter identification is performed on an equivalent circuit model by establishing the equivalent circuit model of the lithium ion battery, and then a Uoc-SOC model isestablished, and the SOC is estimated. Training is carried out by using a large amount of offline data to obtain a neural network model which takes Uoc-SOC model parameters as input and takes the maximum available capacity as output. The method further has the following steps: performing curve fitting on Uoc and the SOC at the same moment to obtain to-be-identified parameters in the model, inputting the to-be-identified parameters into the neural network model obtained by training to obtain the maximum available capacity, returning the obtained Uoc-SOC model parameters and the maximum available capacity to the SOC estimation step, and updating the parameters of a state equation and an observation equation. According to the lithium ion battery state-of-health estimation method provided by the invention, online estimation is carried out for the battery health state, parameter updating is carried out on SOC estimation, and the estimation precision is improved.

The invention provides an online battery state of health estimation method and a battery management device capable of estimating the battery state of health. The remaining service life of the batterycan be calculated according to the energy exchange times, and the SOH of the battery can be simply and effectively estimated by taking a relation curve of the internal resistance and the SOH of the battery as an auxiliary means, and the requirement of the SOH estimation accuracy of the battery can be fully met; meanwhile, the battery does not need to be subjected to long-time standing, and the state of health can be estimated; and the time consumption is short, the real-time performance is high, the implementation is easy, and the method can be expanded to estimation of the service life of a battery pack and even an energy storage system.

Systems, methods and devices which utilize Spread Spectrum Time Domain Reflectometry (SSTDR) techniques to measure degradation of electronic components are provided. Such measurements may be implemented while the components “live” or otherwise functioning within an overall system. In one embodiment, monitoring a power converter in a high power system is accomplished. In this embodiment, degradation of components within the power converter (e.g. metal-oxide-semiconductor field-effect transistors (MOSFETs), capacitors, insulated-gate bipolar transistors (IGBTs), and the like) may be monitored by processing data from reflections of an SSTDR signal to determine changes in impedance, capacitance, or any other changes that may be characteristic of components degrading. For example, an aging MOSFET may experience an increase of drain to source resistance which adds additional resistance to a current path within a power converter. Such a change is able to be analyzed monitored upon processing the reflected test signals.

The present invention provides system of active uniform and base station for sensing an aspect of the wearers environment or physiology. Active uniform (1) is comprised of uniform (3), electronic sensors (40) for sensing an aspect of the wearer's environment or of the wearer's physiology and an active tag (10). The system of active uniform (1) and base station (2) is used to collect data from wearers of the at least one item of active uniform which allows an assessment of the health of the wearer where said health assessment is subsequently used to enhance the survivability of the wearer. The active tag contains various components that allow it to communicate with the base station (2) including (i) sensor interface (80) for interfacing electronic sensors (40) to the active tag, (ii) a microcontroller (70), (iii) a data store (60) including flash memory, (iv) radio frequency interface (110), (v) at least one tag antenna (120) and (vi) a battery (100) and power management unit (90). The sensors (40) and active tag (10) are adapted to be retained on or in the item of uniform (3) such that the active uniform (1) is able to be washed without removing the electronic sensors (40) or the active tag (10). Base station (2) comprises base station antenna (20), base station transceiver (320) and data processing apparatus (340) connected to the base station transceiver, which is adapted to receive and store data transmitted by the active tag of the active uniform, including at least, sensor and identification data.

The invention relates to power distribution network evaluation based on improved principal component-analytic hierarchy process, and relates to a power distribution network state evaluation method, which realizes accurate evaluation of the comprehensive state of a power distribution network. The method comprises: screening indexes by adopting an improved principal component analysis method, and then establishing a power distribution network state evaluation index system by adopting an improved analytic hierarchy process; secondly, carrying out unification and dimensionless processing on the indexes; and then calculating a weight by using a Delphi method to obtain a health condition assessment function of the power distribution network area, and assessing the health condition of the power distribution network area according to the assessment function value. The problem of serious index subjectivity caused by a traditional method is solved, reasonable and objective multi-level model building of all indexes in the power distribution network is guaranteed, correlation of all the indexes in power distribution network state evaluation can be analyzed, redundancy of the indexes is reduced, and efficiency and analysis precision during power distribution network evaluation are greatly improved.

A method for determining a state of health of a rechargeable battery includes: determining a change in charge within an upper border and a lower border of a charging state window, the change in charge being determined by summing up current values measured within the charging state window; determining an actual state of health by scaling the change in charge with the width of the charging state window and dividing by an initial charging capacity of the battery; and determining an average state of health by calculating a sliding average of the actual state of health with at least one previous determined state of health.

The present invention provides a highway network pavement technology health condition assessment method. The method comprises the steps: surveying the operation age limits of all the roads with the same grade and the same pavement structure in an area and the pavement technology state parameters of each kilometer; establishing a mathematical relationship model of the pavement operation age limits and the technology state parameters, obtaining the regression equation and curve of the pavement technology state parameters, and calculating the technology state decaying values year by year and the regression pavement technology state average decaying lane mileage; performing statistics of the technology state decaying lane mileage of each kilometer and performing accumulation of the technology state decaying lane mileage of each kilometer, and obtaining the current pavement technology state decaying lane mileage; and assessing the highway network technology state health degree through comparison of the sizes of the average value and a measured value so as to provide basis for the area highway maintenance planning and decision. The highway network pavement technology health condition assessment method can predict the future usage condition of the pavement, and the predication data can be used for providing reference for the mid-long term maintenance and the planning of the pavement.

A battery system may include a battery that in operation couples to an electrical system, and a battery control module that in operation electrically couples to the battery. The battery control modulemay read battery data, estimate a state of charge of the battery based at least in part on the battery data, and estimate a state of charge error of the battery based on magnitudes of state of chargeerror sources. Additionally, the battery control module may update a state of health estimation of the battery when the state of charge error of the battery exceeds a predetermined threshold.