169 results about "Reference device" patented technology

The invention discloses a space-time adaptive power prediction system and method for distributed photovoltaic power generation in a mountainous area, and particularly relates to the technical field of fault prediction and health management. The method is used for solving the problem that the accuracy of power prediction and equipment health state evaluation is influenced by environment characteristic data reconstruction reference drift caused by equipment performance degradation in the prior art. A spatio-temporal data sequence is constructed by acquiring historical data of a photovoltaic unit, a spatio-temporal association network of generated power among equipment is constructed, performance stability of a reference equipment group is evaluated, and when the stability does not meet conditions, a performance attenuation spatio-temporal mode is analyzed to identify common features and personalized features. The propagation path of performance degradation on the space-time correlation network is analyzed based on the characteristics, a critical point is evaluated, reference correction is performed on the environment characteristic data by using the common characteristics and the critical point, and finally, the corrected environment characteristic data is used for executing power generation power prediction and equipment health state evaluation. Therefore, the prediction accuracy and the health management reliability are improved.

The in-vehicle device for receiving time synchronization information transmitted from each of a plurality of reference devices and transmitting the received time synchronization information to another device, includes: a communication unit configured to communicate with the other device; and an information processing unit configured to, if the communication unit receives a frame in which the time synchronization information is stored, store the time synchronization information in a specific queue with priority over other information, wherein the communication unit transmits the time synchronization information stored in the specific queue to the other device.

The invention discloses an air quality sensor self-correction method and system based on time sequence analysis, and the method comprises the steps: continuously collecting measurement values during the normal operation of a sensor to form time sequence data, dividing the time sequence data into continuous time periods, and then calculating the statistical parameters of each time period; by dynamically comparing a current parameter with a historical parameter sequence, the significance change trend of statistical characteristics is intelligently identified, so that whether essential drift occurs or not is judged; and after the drift is confirmed, inquiring a preset correction table according to the trend amplitude and direction to obtain a correction coefficient, and finally adjusting the gain or bias voltage of a sensor output circuit through a digital-to-analog converter to realize autonomous closed-loop correction. According to the method, analysis is carried out only by utilizing historical data of the sensor, external reference equipment or complex model training is not needed, online self-correction which is efficient, low in cost and high in real-time performance is achieved, and the long-term reliability and stability of air quality monitoring data are remarkably improved.

The invention provides a DFT resource configuration prediction method and device, electronic equipment and a storage medium, and belongs to the technical field of electronic design automation, and the method comprises the steps: determining a reference device density based on a process node of a target chip; determining an effective digital logic layout area based on the chip planning area of the target chip and the estimated non-digital logic function region; according to a utilization rate factor corresponding to the physical design constraint of the target chip, correcting the effective digital logic layout area to obtain an available standard cell layout capacity; according to the standard unit layout capacity and the reference device density, generating a time sequence element number prediction interval of the target chip through a logic depth mapping model; and according to the time sequence element number prediction interval, generating testability design DFT architecture configuration parameters of the target chip. The number of chip registers can be quickly and accurately predicted and the DFT architecture configuration parameters can be generated in the early stage of chip design.

The invention belongs to the related technical field of fault diagnosis, and discloses a fault diagnosis sample generation method, application and equipment based on a physical constraint adaptive migration network, and the method comprises the steps: (1) converting original vibration signals of reference equipment and monitoring equipment into a time sequence spectrogram through continuous wavelet transform; (2) processing the time sequence spectrogram by adopting a spectrum feature encoder of the physical constraint adaptive migration network to extract multi-scale spectrum features; wherein a loss function of the physical constraint adaptive migration network comprises content loss, style loss and frequency band energy loss; (3) processing the multi-scale spectrum features by adopting the adaptive style normalization module so as to fuse the fault content features of the reference equipment and the machine style features of the monitoring equipment; and (4) processing the fused features by adopting a feature reconstruction decoder so as to reconstruct and generate a synthetic sample. According to the invention, the problem of insufficient data authenticity and physical consistency is solved.

The invention relates to the technical field of data processing, in particular to an industrial electromagnetic environment multi-dimensional health degree assessment model, which comprises a processor and a memory, and the processor executes a computer program of the memory to implement the following steps: acquiring a multi-dimensional electromagnetic environment data sequence of any equipment in an industrial electromagnetic environment in a current time period, if the abnormal fluctuation time period exists in the current time period, obtaining the abnormal performance degree of each abnormal fluctuation time period according to the data difference of each abnormal fluctuation time period; according to the data fluctuation characteristics of the multi-dimensional electromagnetic environment data sequence and the change trend of the multi-dimensional electromagnetic environment data of each reference device, the interference degree of any device in each abnormal fluctuation time period is obtained; according to the abnormal performance degree of each abnormal fluctuation time period and the interfered degree of any device, the affected degree of any device is obtained, the health degree of the industrial electromagnetic environment is obtained by using the affected degree of each device, and the accuracy of a health degree evaluation result is improved.

A method may include receiving, by a first user device from a network node or a second user device, 1) a positioning measurement report including at least one positioning measurement measured by a reference device, and 2) reference positioning-related information to be used for testing and / or validating a machine learning model; determining estimated positioning-related information as outputs of the machine learning model based on at least a portion of the positioning measurement report as inputs to the machine learning model; determining a performance indication of the machine learning model based on the reference positioning-related information and the estimated positioning-related information, wherein the performance indication indicates a performance or accuracy of the machine learning model; and performing, by the first user device, an action based on the performance indication.

The present disclosure relates to a location reference device (LRD) for assisting positioning over sidelink. The LRD comprises a communication interface configured to: receive a location assistance request from a user device or a network element for positioning, wherein the location assistance request indicates a location reference for a positioning of the user device over a sidelink; and transmit a location message over the sidelink, wherein the location message indicates that the LRD is capable of serving as a location reference for the positioning of the user device over sidelink.

Aspects of the disclosure relate to a packaging system, an apparatus (400; 500; 600; 700) for forming a package, an article carrier (90; 190; 390; 490) for packaging one or more articles, a blank (10; 110; 310; 410A-B) for forming the carrier, and to a method of packaging one or more articles. The carrier (90; 190; 390; 490) comprises a main panel (12; 112; 312; 412) having one or more article retention structures (RT1, RT2) for receiving and securing the main panel (12; 112; 312; 412) to a respective article (B). The carrier (90; 190; 390; 490) comprises at least one panel having a peripheral edge, a portion of which provides at least one registration edge shaped to inhibit movement in two orthogonal directions when engaged by a reference device (440; 540; 640; 740) of a packaging apparatus (400; 500; 600; 700).

The embodiment of the invention discloses an equipment information protection method and a related device, which are used for improving the security of hardware equipment information in a complete machine and applied to a baseboard management controller BMC, the BMC comprises a security core isolated from external environment access, and the method comprises the following steps: calling the security core, signing a firmware hash value based on a trusted certificate, and sending the signed firmware hash value to a server; generating a firmware identity certificate, wherein the firmware hash value is obtained by performing hash value calculation on the firmware information of the BMC; acquiring reference equipment information, wherein the reference equipment information is equipment information of the initial hardware equipment; a security core is called, the reference device information is signed based on the firmware identity certificate, a device identity certificate is generated, the device identity certificate is used for extracting the reference device information when the target hash value is not matched with the reference hash value, and the target hash value is obtained by performing hash value calculation on the target device information; the target equipment information is equipment information of the target hardware equipment, and the reference hash value is obtained by performing hash value calculation on the reference equipment information.

The invention discloses an association relationship determination method, equipment and a storage medium. The method comprises the following steps: acquiring a shooting content association degree between every two pieces of equipment in a plurality of pieces of equipment in a preset area; a to-be-determined device is searched from the multiple devices, the correlation degree between the to-be-determined device and the shooting content of a first correlation device meets a first correlation degree requirement, and the first correlation device is a device which has been determined to have a correlation relation with a target interest point in the preset area; and analyzing a first reference device of which the association degree with the shooting content of the to-be-determined device meets a second association degree requirement, so as to determine whether the to-be-determined device and the target interest point have an association relationship or not. In this way, the efficiency and accuracy of association relation determination can be improved.

This invention discloses an intelligent elastic force calibrator, comprising a base with three equally angled horizontal adjustment screws threaded to its upper end. These screws extend through the lower side of the base, and a shock-absorbing base is located at the lower end of each screw. A three-axis fine-tuning platform is mounted on the upper end of the base, positioned at the center of the three horizontal adjustment screws. This intelligent elastic force calibrator can achieve various torque outputs and linear calibration of the elasticity curve sensor. It can also simulate various abnormal sample curves and scan the elasticity curve of a reference device before comparative experiments. This significantly improves product quality and production efficiency in factories, greatly enhances research and development efficiency in scientific research, and, in clinical practice, not only improves equipment accuracy but also significantly reduces training costs, providing clinicians with a solid and reliable standard.

The invention relates to an equipment category determination method and device, a storage medium and electronic equipment, and relates to the technical field of computers.The method comprises the steps that current data information reported by terminal equipment is received, the current data information is analyzed, and a to-be-detected equipment identifier and a reference equipment identifier associated with the terminal equipment are obtained; matching a first historical device identifier corresponding to the reference device identifier in a preset device identifier database to obtain a first identifier matching result, and matching a second historical device identifier corresponding to the to-be-detected device identifier to obtain a second identifier matching result; and according to the first identifier matching result and the second identifier matching result, determining a device category to which the terminal device belongs. According to the invention, the accuracy of the obtained equipment category is improved.

The invention particularly relates to a three-dimensional C arm and optical navigation fused spine screw placement path planning system, and relates to the technical field of intelligent medical treatment and surgical navigation. According to the system, a first coordinate set of coding characteristics in a C-arm image and a second coordinate set of optical navigation tracking are synchronously obtained through a reference device installed on a cone; respectively constructing a spatial topology network based on the image and the navigation coordinate system, and automatically establishing a mapping relation between the image and the navigation coordinate system by using an image matching algorithm to realize fusion registration; the planned path is converted to be stored in a dynamic coordinate system with the device as the reference; during operation, the dynamic coordinate system pose is tracked and solved in real time, and a path is mapped and displayed to guide instrument operation. According to the method, automatic and robust registration without manual marking is realized, and registration failure caused by movement of a patient in an operation is avoided through binding of a path and a dynamic coordinate system.

An aspect of the present disclosure provides a system comprising a sensing device comprising a housing and at least one sensor in sensing communication with an outer environment of the housing. The at least one sensor can be configured to detect a user radiation signal that is reflected or emitted by at least a portion of a body of the subject. The system can further comprise a reference device comprising at least one radiation source configured to output a reference radiation signal. The user radiation signal and the reference radiation signal can be analyzed to determine a physiological feature of the subject.

The application provides a field calibration system for calibrating a laser tracker, and belongs to the technical field of laser measurement. The field calibration system comprises a truss reference device, a plurality of target ball seats and a plurality of connecting rods. Two adjacent target ball seats are fixedly connected by a connecting rod, so that the plurality of target ball seats form a truss structure through the plurality of connecting rods. A target ball is configured to be selectively fixed to any one of the plurality of target ball seats. The laser tracker is configured to measure a plurality of spatial position data of the target ball in a base coordinate system when the target ball is fixed to the plurality of target ball seats. The base coordinate system is established with the base of the laser tracker as the origin. A parameter calibration device is in communication connection with the laser tracker and is configured to determine a measurement distance value between two adjacent target ball seats based on the plurality of spatial position data, and calibrate the laser tracker based on the standard length of the plurality of connecting rods and the plurality of measurement distance values.

One aspect of the present disclosure provides a system including a sensing device including a housing and at least one sensor in sensing communication with an external environment of the housing. The at least one sensor may be configured to detect a user radiation signal reflected or emitted by at least a portion of a body of a subject. The system may also include a reference device including at least one radiation source configured to output a reference radiation signal. The user radiation signal and the reference radiation signal may be analyzed to determine a physiological characteristic of the subject.

This application provides an AI device evaluation method, apparatus, device, and medium based on stepped pressure. The method includes: for each AI device to be evaluated, obtaining at least one type of test load model based on AI device domain requirements and AI device parameters; running the AI ​​device to be evaluated in each test load model; applying multiple levels of fixed stepped pressure to each test load model; when the test load model is stable under each level of fixed stepped pressure; collecting multi-dimensional performance parameters of the AI ​​device to be evaluated; determining cross-vendor multi-dimensional normalized reference values ​​of the test load model based on historical standard parameters of the reference AI device; calculating a comprehensive score for the AI ​​device to be evaluated based on the multi-dimensional performance parameters of each test load model, AI device domain requirements, and cross-vendor multi-dimensional normalized reference values ​​of each test load model; and evaluating the AI ​​device with the highest comprehensive score as the optimal device that meets the AI ​​device domain requirements, thereby improving the accuracy of the evaluation results.

The invention discloses a gas sensor self-calibration calibration method, and relates to the technical field of gas sensors, and the method comprises the steps: S1, carrying out the collection of gas sensors in a gas transmission network, obtaining a data sequence, and constructing a standard time-space comprehensive similarity matrix; s2, calculating the current average sensitivity of the gas sensor based on the standard time-space comprehensive similarity matrix; s3, defining and updating a dynamic self-calibration coefficient based on the current average sensitivity; and S4, establishing a calibration function, and calibrating the drifting gas sensor. According to the invention, closed-loop calibration of the gas sensor network is realized, and no external reference equipment is needed. Spatio-temporal information is fully utilized to automatically screen an optimal reference group, automatically update coefficients and correct drifting in real time, labor cost is remarkably reduced, long-term accuracy of monitoring data is guaranteed, and the problems of response lag and single-point failure risk of a traditional method are solved.

The present disclosure provides a DFT resource configuration prediction method and device, electronic equipment and storage medium, belonging to the technical field of electronic design automation. The method comprises the following steps: determining a reference device density based on a process node of a target chip; determining an effective digital logic layout area based on a chip planning area of the target chip and a predicted non-digital logic function area; correcting the effective digital logic layout area according to a utilization factor corresponding to a physical design constraint of the target chip to obtain an available standard cell layout capacity; generating a timing element quantity prediction interval of the target chip through a logic depth mapping model according to the standard cell layout capacity and the reference device density; and generating a design for test (DFT) architecture configuration parameter of the target chip according to the timing element quantity prediction interval. The chip register quantity can be quickly and accurately predicted and the DFT architecture configuration parameter can be generated at an early stage of chip design.

The present disclosure relates to an air conditioner control method, device, electronic equipment, air conditioner, medium and product. The method comprises: obtaining target air conditioner sensing information, the target air conditioner sensing information representing a state of a target object perceived by a target air conditioner; obtaining reference device sensing information, the reference device sensing information representing a state of the target object perceived by a reference device; determining an actual state of the target object according to the target air conditioner sensing information and the reference device sensing information; and controlling the target air conditioner according to the actual state of the target object. The actual state of the target object is determined by comprehensively combining the target air conditioner sensing information and the reference device sensing information, and through the collaborative fusion of multi-source sensing information, the limitations of single device sensing can be avoided, the accuracy of determining the state of the target object is improved, and thus the operation of the target air conditioner can be more in line with actual needs, improving user experience while saving energy and reducing consumption.

The application discloses a device management method and an electronic device, and the method comprises the following steps: in response to a position matching trigger event, obtaining a to-be-matched position fingerprint of a target device; the to-be-matched position fingerprint comprises wireless ranging information between the target device and a plurality of reference devices; matching the to-be-matched position fingerprint with position fingerprints of a plurality of preset installation positions respectively, and determining a target installation position corresponding to the target device; wherein the position fingerprint is used for identifying the position of the corresponding preset installation position in a physical space; and when a preset configuration inheritance condition is met, associating configuration information associated with the target installation position with the target device. The technical scheme can realize automatic matching and configuration inheritance of the device and the installation position without additional hardware and manual intervention, reduces operation and maintenance cost, and improves matching accuracy and system self-recovery capability.

Aspects presented herein may enable a UE to improve (e.g., reduce) convergence time for visually assisted positioning by enabling the UE to use images embedded with location information. In one aspect, a UE receives a list of visual features and a location of each visual feature in the list of visual features from a reference device, a server, or a map. The UE identifies, via at least one camera, at least one visual feature in an area, where the at least one visual feature is included in the visual feature list, where the area is within a threshold distance of the UE. The UE estimates a location of the UE based on the identified at least one visual feature in the region and the location corresponding to the at least one visual feature.

This application provides a storage service fault analysis method, apparatus, electronic device, and medium, belonging to the field of artificial intelligence technology, and applicable to the financial and medical fields. The method includes: acquiring fault information and a device topology diagram of the storage device; locating associated devices connected to the storage device based on the device topology diagram; performing device relationship analysis on the storage device and associated devices to obtain target device relationship data; performing similarity retrieval in a preset device relationship database based on the target device relationship data to obtain reference device relationship data; associating the reference device relationship data with reference fault causes; acquiring the reference fault causes associated with the reference device relationship data; and performing fault analysis using a pre-trained language model based on the reference fault causes and fault information. This application embodiment can improve the accuracy of storage service fault analysis.

This disclosure provides a method for controlling a sensing device including a controllable component and associating with at least one associated client and a reference device, the reference device being a gateway of a local area network to which the sensing device is connected. The method includes: obtaining a first client list of the at least one associated client and a second client list of clients that are currently connected to the same local area network as the sensing device by connecting with the reference device; comparing the first client list with the second client list to determine a comparison result which indicates a matching client that is connected to the local area network as the sensing device; determining at least one state control strategy based on the comparison result; and controlling a state of the sensing device by controlling the controllable component based on the at least one state control strategy.

A reference devices system (720) for generating and managing calibration data for sensors used to obtain weather information is provided. The reference devices system (720) includes a plurality of reference devices, wherein a reference device (110) of the plurality of reference devices is configured to be calibrated against a weather station (115) and to serve as a calibration reference for a community device (130).

[Solution] This use service identification device 50 comprises: an analysis item acquisition unit 51 that acquires an analysis item including a correspondence relationship between a page URL of at least one page in a site to be analyzed and a cookie issued in the at least one page, a web storage to be set, or an external communication URL of external communication to be generated; a use service identification unit 52 that compares the analysis item to a service database 60 and identifies a service corresponding to the cookie, the web storage, or the external communication URL included in the analysis item as a use service used in the at least one page; and a use service registration unit 53 that registers the site URL and the use service in association with each other. The service database registers data in which each of the cookie, the web storage, and the external communication URL is associated with the service. This configuration makes it possible to acquire a cookie, web storage, or external communication URL for each site to be analyzed that was analyzed by an analysis device 10, identify the corresponding use service, and register the identified use service in the use service database 70.

A time synchronization subdevice includes a periodic data receiver that receives periodic data transmitted periodically from a time synchronization reference device, an acquirer that acquires first priority information indicating a first priority assigned to the time synchronization reference device, a first priority transmitter that transmits the first priority information to another time synchronization subdevice, a second priority information transmitter that transmits, when the periodic data is interrupted, transmission information indicating a second priority assigned to the time synchronization subdevice, a second priority information receiver that receives reception information indicating a second priority assigned to a device different from the time synchronization subdevice, and a distributor that distributes, when the periodic data is interrupted and the second priority indicated with the transmission information is higher than the second priority indicated with the reception information, time measured by a clocking unit as new shared time to the another time synchronization subdevice.

Vehicle motion control device, with: an information reference device that obtains information regarding situations ahead of its own vehicle (100) as advance situation information; and an electronic control unit (90) that controls the acceleration of the vehicle (100), the deceleration of the vehicle (100) and the steering of the vehicle (100), wherein the electronic control unit (90) is configured to: when (i) a request is made to execute a follower motion control, and (ii) the electronic control unit (90) determines that another vehicle (101) is ahead of the own vehicle (100), based on the advance situation information, execute (i) an initial target acceleration setting process of the follower motion control to set an initial target acceleration of the own vehicle (100) required to maintain an intermediate vehicle distance between the own vehicle (100) and the other vehicle (101) at a target distance, and (ii) an initial follower acceleration / deceleration process of the follower motion control to control a drive torque to be applied to the own vehicle (100) to accelerate or decelerate the own vehicle (100) to control an acceleration of the own vehicle (100) to the initial target acceleration; when (i) the following motion control is requested to execute, and (ii) the electronic control unit (90) determines that the other vehicle (101) is not ahead of the own vehicle (100), based on the advance situation information, execute (i) a second target acceleration setting process of the following motion control to set a second target acceleration of the own vehicle (100) based on a movement speed of the own vehicle (100) and a target movement speed, and (ii) a second following acceleration / deceleration process of the following motion control to control the drive torque to accelerate or decelerate the own vehicle (100) to control the acceleration of the own vehicle (100) to the second target acceleration; if (i) the electronic control unit (90) performs the second subsequent acceleration / deceleration process to control the acceleration of the own vehicle (100) to the second target acceleration, which is greater than zero, and (ii) the acceleration of the own vehicle (100) is less than a predetermined threshold, increasing the second target acceleration; and If the electronic control unit (90) determines that a stationary object (50) which is potentially touching the own vehicle (100) is present in front of the own vehicle (100), based on the advance situation information, execute a steering evasive control to steer the own vehicle (100) in order to cause the own vehicle (100) to pass the stationary object (50), thereby avoiding the own vehicle (100) touching the stationary object (50), characterized in that the electronic control unit (90) is configured to: Stopping the second subsequent acceleration / deceleration process when the electronic control unit (90) initiates an execution of the steering evasive control while the electronic control unit (90) is executing the second subsequent acceleration / deceleration process; and Limiting the second target acceleration so that the second target acceleration is less than or equal to a predetermined acceleration when the electronic control unit (90) completes an execution of the steering avoidance control.

Embodiments described herein generally relate to analyzing a signal generated by a device under test (DUT). In particular, the signal generated by the DUT may be compared to a reference signal to determine pass / fail results for the DUT. For example, a method may include: storing, on a computing device, a reference signal from a reference device; receiving a test signal from a device under test (DUT); synchronizing the reference signal and the test signal based on a time-synchronization buffer of each signal; after the synchronization, comparing the test signal and the reference signal to determine a pass or fail result for the DUT; and generating a notification indicating the pass or fail result for the DUT.