141 results about "Continuous recording" patented technology

The invention relates to the technical field of unmanned aerial vehicle cooperative tracking, in particular to a multi-unmanned aerial vehicle cooperative tracking method and system based on a complex environment. Comprising the following steps: S1, acquiring image data acquired by each unmanned aerial vehicle and flight position data of each unmanned aerial vehicle, and determining a tracking target, a main tracking unmanned aerial vehicle and an auxiliary unmanned aerial vehicle; s2, establishing an appearance feature library for the tracking target according to the image data; an auxiliary unmanned aerial vehicle checks an environment shielding risk in advance through rasterizing a pre-survey point and simulating a target moving track, when shielding occurs, a stop mechanism is triggered, an auxiliary tracking position is optimized, an optimal position is calculated in combination with a direction weight and a distance threshold value, continuity of a tracking process is ensured, and the tracking efficiency is improved. Meanwhile, when the image feature proportion of the auxiliary unmanned aerial vehicle is higher than that of the main tracking machine, identity replacement is automatically triggered, it is ensured that when the view angle of the main tracking machine is limited, continuous recording of the target can still be kept through the auxiliary unmanned aerial vehicle, and the task reliability in the complex environment is improved.

The invention discloses a monitoring management method and system for an artificial intelligence development platform, particularly relates to the field of computer system monitoring management, and is used for solving the problems of unstable attribution of monitoring fragments and inconsistent alarm interpretation in a switching scene. A training task continuous identifier is generated based on a submission record, a running instance identifier mapping table is established, a monitoring data stream is collected, a monitoring fragment is formed when a switching event arrives, a switching time sequence alignment index and a training semantic continuation index are calculated, and sequence inference is executed to obtain a fragment attribution result. Generating a training task continuous record according to the training task continuous identifier, generating a switching instruction, executing consistency verification on the training task continuous record to form a consistency verification result, triggering a correction instruction to update the mapping table and reconstruct the training task continuous record, and revising a boundary echo window construction rule and a semantic anchor point deduction rule at the same time; and stable unification of monitoring affiliation and explanation caliber is realized.

The invention relates to a rapid detection method for the resonant frequency of a hemispherical harmonic oscillator, belongs to the technical field of inertial measurement, solves the problems of long measurement time and low detection precision in the measurement of the second-order resonant frequency of the hemispherical harmonic oscillator in the prior art, and comprises the following steps: S1, providing a voltage excitation source, and applying a broadband sinc excitation signal to the hemispherical harmonic oscillator; s2, continuously recording the detection data in a set continuous recording time period; s3, performing frequency mixing to obtain data after frequency mixing; step S4, carrying out anti-aliasing filtering and down-sampling on the data after frequency mixing; step S5, carrying out N-point fast Fourier transform on the downsampled data to obtain a frequency spectrum of the detection signal; s6, based on the frequency spectrum of the converted detection signal, determining the frequency corresponding to the peak value of the frequency spectrum, and obtaining the measured second-order resonant frequency of the hemispherical harmonic oscillator; and S7, based on the measured second-order resonant frequency of the hemispherical harmonic oscillator, performing frequency phase loop, amplitude loop closed loop and orthogonal closed loop on the hemispherical harmonic oscillator.

The embodiment of the invention discloses a cooling liquid flow distribution method, device and equipment for a liquid cooling server and a storage medium, and the method comprises the steps: collecting the core temperature and power consumption data of each calculation unit in the server in real time, and continuously recording the temperature time sequence change; based on real-time heating power calculation fused with temperature and power consumption information, the heating power proportion of each unit is determined; further, for the unit with the heating power exceeding the threshold value, a dynamic weight factor is introduced to adjust the corresponding expected flow proportion; a closed-loop controller is adopted to adjust the opening degree of a liquid cooling branch valve, so that the actual flow accurately tracks the expected value; and finally, performing adaptive optimization on the dynamic weight factor according to the temperature change rate to form closed-loop control. Therefore, the method effectively solves the problems of local overheating and flow waste caused by uneven load in a multi-heat-source environment, the heat dissipation energy efficiency is remarkably improved, the system reliability is remarkably improved, and the service life of hardware is remarkably prolonged.

A method of monitoring a condition prevailing inside a piping system with respect to an impairment due to accretion, abrasion or corrosion caused by fluid(s) flowing through the piping system is disclosed, comprising the steps of: installing at least two measurement devices susceptible to an impairment and configured to measure variables indicative of the impairment; wherein the measured variables include at least two variables exhibiting a different dependency on the impairment; continuously recording data including time series of measured values of the variables measured; based on training data included in the data determining a dynamic reference behavior of the variables corresponding to time dependent distributions of values of the variables to be expected of the measured values when the measurement devices are unimpaired; repeatedly determining a deviation between a monitored behavior of the measured values of the variables and the reference behavior.

The invention relates to an inventory data synchronization and consistency verification system supporting network disconnection fault tolerance, and discloses an inventory data synchronization and consistency verification system which realizes continuous recording of inventory operation during a network disconnection period through network state detection and local cache, performs batch transmission after network recovery through a synchronous uploading and verification mechanism, and ensures data integrity. According to the inventory data synchronization and consistency verification system supporting network disconnection fault tolerance, data conflicts are automatically solved through a conflict detection and strategy processing module, a difference report is generated through consistency verification, and secondary synchronization is executed, so that safe synchronization and final consistency guarantee of inventory data are achieved, and it is ensured that the service process is continuous and stable. The system is characterized by comprising a network state detection module, a local cache module, a transaction log management module, a synchronous uploading module, a conflict detection module, a conflict resolution strategy module, a consistency verification module and an abnormity alarm and manual intervention interface module.

The invention discloses an early-stage intelligent monitoring system for citrus reiculata Blanco canopy diseases and insect pests based on multispectral imaging, and belongs to the technical field of agricultural information. The system comprises a multispectral imaging module, a three-dimensional point cloud acquisition module, a data fusion module, a time sequence data analysis module, an intelligent identification module and a monitoring result output module. The method comprises the following steps: synchronously acquiring a multispectral image and laser radar point cloud data of a citrus reiculata tree canopy, and generating a point cloud model through spatial registration fusion; continuously recording model data of a plurality of time points, and extracting a time sequence feature vector; identifying disease and pest types and severity by using a deep learning model; and outputting a result to the user terminal. According to the invention, the problem that large-range and high-precision early monitoring of diseases and insect pests of citrus reiculata canopies is difficult to realize in the prior art is solved, early discovery, precise positioning and trend early warning of the diseases and insect pests are realized through air-space-ground integrated data fusion and intelligent analysis, and the intelligent level of orchard management and the disease and insect pest control efficiency are effectively improved.

The invention relates to the technical field of environmental monitoring, in particular to a measurement data acquisition method based on ecological detection platform construction, which comprises the following steps: monitoring surface change based on remote sensing and patrol data, identifying ground feature features and dividing sections, analyzing image resolution fluctuation and marking low-efficiency nodes, and optimizing monitoring point location and resource allocation. And scheduling the acquisition equipment to complement the measurement data, generating monitoring output and synchronously labeling the control table. According to the method, the surface change is identified by combining the remote sensing image and patrol data, the dynamic sensing capability of ground feature distribution is improved, node efficiency sorting is realized through path and equipment state analysis, patrol coverage balance is guaranteed, high-frequency data supplementary collection is performed on key areas by using spatial positioning and a layer tool, and the continuous recording capability of the ground feature change is enhanced; and a period monitoring result is integrated to identify a missing section and mark abnormity, so that linkage of data synchronous correction and mark switching is realized, and the real-time tracking and abnormity response capability of ecological changes is improved.

The invention relates to the technical field of electronic contract signing, in particular to an electronic contract signing method and system for video recording willingness authentication, and the method comprises the steps: associating a contract with signing party information through generating a unique task identifier, automatically triggering video recording in a signing link, and completing identity verification in advance; then multi-dimensional information including biological characteristics, willingness statement audio and a signing operation process is synchronously collected in the continuous recording process, finally, characteristic values of a recorded file and a contract file are calculated respectively, and the characteristic values, digital signatures and task identifiers are fused and stored in a tamper-proof mode. The real-time and strong association binding of the video evidence and the electronic contract on the data level is realized, the traceability, tampering prevention, completeness and credibility of the whole signing process are ensured, and the technical problems that in the prior art, the audio-visual evidence and the electronic contract are mutually independent, loose in association and easy to tamper, and a complete evidence chain with judicial proving power is difficult to form are effectively solved.

To prevent degradation of service to users by analyzing reading errors of an absolute positioning system that detects absolute positions.SOLUTION: An elevator system includes an APS tape on which absolute position information is continuously set corresponding to the position of the car in the direction of movement within the elevator shaft, an APS sensor installed on the car and equipped with two cameras that read absolute position information corresponding to the car's position, and an information processing device that processes the absolute position information read by the APS sensor. The two cameras are positioned so that the reading positions of the absolute position information are separated by an offset distance in the direction of movement. The information processing device includes a recording processing unit that records error information including the error position when a reading error occurs in each of the two cameras, and a compilation processing unit that compiles compilation data that associates the error position with the number of errors based on the recorded error information.SELECTED DRAWING: Figure 8

The invention discloses a multispectral remote sensing disaster monitoring and early warning system using deep learning, and the system comprises a spectral data collection and preprocessing module which is used for continuously recording image data in different time periods based on surface reflection information to obtain an original data set, preprocessing the original data set to obtain a clear image data set; the mode recognition module is used for carrying out mode classification on the clear image data set to obtain a potential disaster related feature combination; the disaster risk assessment module is used for performing time sequence analysis on the potential disaster related feature combination to obtain a probability assessment value associated with the disaster risk; the disaster risk early warning module is used for constructing a quantitative index system associated with the disaster risk based on the probability evaluation value and determining an early warning reference standard based on the constructed quantitative index system associated with the disaster risk; and the closed-loop monitoring module is used for continuously monitoring the multispectral data acquired in real time based on an early warning reference standard to generate early warning information containing risk levels and outputting the early warning information.

A robotic insurance platform is disclosed that transforms an autonomous service robot into a tamper-resistant “digital witness” capable of supplying legally probative evidence without human intervention. The robot is equipped with surround video cameras, a spatial microphone array, an on-board processor, a cryptographically isolated secure enclave, a wireless communication module, and a rolling-buffer memory that retains encrypted audio-video data for a configurable period such as forty days. A companion mobile application enables an insured user to register, perform know-your-customer identity verification, and pair the robot with an insurance policy stored on a cloud server that hosts an claim-decision engine and policy database. Following explicit verbal consent from the user, the robot records continuously while performing ordinary tasks. When an incident is detected—either by on-board heuristics or by a user-initiated claim request—the processor extracts a time window surrounding the event, computes a cryptographic hash of the clip inside the secure enclave, and commits that hash as an immutable anchor to a permissioned or public blockchain ledger. Only after blockchain confirmation is the encrypted clip transmitted to the insurance server, where the claim-decision engine verifies integrity, applies machine-learning analytics to determine causation, and issues a coverage determination. Approved claims trigger repair dispatch, replacement shipment, or direct monetary reimbursement, while unclaimed data exceeding the retention interval are securely erased. The platform delivers objective, bias-free evidence, virtually eliminates false claims, and reduces end-to-end settlement time from weeks to minutes, thereby lowering operational costs for insurers and increasing transparency for policyholders.

To allow results of measuring physical fitness of students to be continuously recorded in an educational institution.SOLUTION: A computer executes: acquiring student identification information identifying a student; generating authentication information to be associated with class information of a class that the student belongs to; acquiring the student identification information and the authentication information from a student terminal of the student; associating the class information with the student identification information, based on the student identification information and the authentication information acquired from the student terminal; acquiring, from the student terminal, measurement information obtained by associating the student identification information with results of measuring physical fitness; and updating history information indicating a history of results of measuring physical fitness of the student for multple grades and associated with the student identification information, based on the measurement information and the class information corresponding to the student identification information.SELECTED DRAWING: Figure 1

A memory management method for continuously recording digital content and a circuit system operating the method are provided. The circuit system includes a control circuit, a memory, and a storage device. The memory has a buffer that is defined as a pre-buffer or a main buffer based on a current recording mode. In the method, the circuit system loads continuously-received data and sequentially saves the data in the buffer that is defined as the pre-buffer in a first-in-first-out manner before a start-record instruction is received. After the start-record instruction is received, the data buffered in the pre-buffer is combined with the data that is continuously recorded to the main buffer. This file is then written to the storage device until a stop-record instruction is received.

The invention discloses a method and a system for positioning and transmitting continuous recording data of a broadband measuring device. The method comprises the steps that a master station queries measuring point data from a local time sequence database according to a continuous recording data query request of a user client, if the measuring point data is not obtained, a broadband measuring device is determined according to the query request, the broadband measuring device is accessed according to the query request, the broadband measuring device reads a Comtrade configuration file, and the Comtrade configuration file is sent to the user client; acquiring measuring point information, time information and sampling rate information in the query request, wherein the time information takes second as a unit; the broadband measuring device locates the positions of the continuous recording data of a plurality of measuring points in a Comtrade data file according to the measuring point information, and extracts the continuous recording data corresponding to the time information based on the time information and the sampling rate information; the broadband measuring device organizes and compresses extracted continuous recording data, packages the continuous recording data into messages according to a predefined data format, sends the messages to the master station through a reliable transmission protocol, transmits the messages to a user client through the master station, and stores the messages in a local time sequence database of the master station.

To improve, without time and effort, color reproducibility in an image formed on a coloring material undercoat layer.SOLUTION: An image processing control device 20 comprises: an acquisition unit (control unit 21) that acquires undercoat layer information that is information on an undercoat layer formed with a coloring material on a substrate (continuous recording medium P); and the control unit 21 that, when the undercoat layer information acquired by the acquisition unit indicates forming the undercoat layer, generates correction data on the basis of RIP image data that is image data of a print job subjected to RIP processing, and performs color adjustment of the image formed on the undercoat layer by applying the correction data.SELECTED DRAWING: Figure 5

The invention relates to the technical field of environment monitoring, in particular to an internet-of-things-based breeding environment monitoring system for pond turtles, and the system comprises a turtle movement trajectory tracking module which is used for collecting real-time images of an incubator, comparing pixel differences among continuous image frames to carry out background subtraction, and recognizing a moving foreground target. According to the method, the pixel differences between image frames are continuously compared, the geometric center point of the moving target is calculated, continuous recording of the moving tracks of the water tortoise individuals in the cultivation box is achieved, the moving area is gridded, the occurrence probability is calculated by counting the frequency that coordinates fall into all units, an objective data basis is provided for environment optimization, and the method is suitable for large-scale popularization and application. Meanwhile, multiple groups of temperature sensors are arranged at key positions such as a spawning area and a drying platform, multiple paths of environment sensing redundant numerical values are obtained, the state range is predicted according to a water body thermal inertia model, multiple paths of readings are updated and calibrated, deviation data are effectively recognized and eliminated, and the reliability of environment monitoring data and the fault tolerance of the system are improved.

A method for training a computer-based machine learning model to assess a characteristics-of-interest in embryos such as viability, sex or genetic superiority / inferiority by processing video of each of a plurality of embryos and wherein a subset of the embryos each embodies the characteristic-of-interest. The method includes obtaining (taking or otherwise procuring) a plurality of training videos, each video being of a target embryo and each video having a real-time frame speed (specifically not time-lapse frame speed) over a continuous recording duration of ten minutes or less. Each video includes image data representing micro-movement of the target embryo. The image data is processed thereby generating a computer-based machine learning model for assessing the characteristic-of-interest in future embryos from image data of those embryos.

The utility model discloses a robinia pseudoacacia volumetric water content and environmental factor acquisition device. The device comprises an adjustable mounting rod; the environment factor acquisition part is arranged on the adjustable mounting rod and is used for acquiring environment factor data in real time; the plurality of robinia pseudoacacia data acquisition parts are used for respectively acquiring robinia pseudoacacia trunk data of the plurality of robinia pseudoacacia; and the electric appliance mechanism is arranged on the adjustable mounting rod, is electrically connected with the environment factor acquisition part and the robinia pseudoacacia data acquisition part, and is used for controlling the environment factor acquisition part and the robinia pseudoacacia data acquisition part to work and sending the acquired environment factor data and robinia pseudoacacia trunk data to an external monitoring terminal for processing and analysis. According to the utility model, the environmental factor data is acquired in real time through the environmental factor acquisition part, and the robinia pseudoacacia trunk data is acquired in real time through the robinia pseudoacacia data acquisition part and is sent to the external monitoring terminal for processing and analysis, so that the relationship between the volume water content of the robinia pseudoacacia and the environmental factors can be obtained; and real-time monitoring and continuous recording can be realized while the efficiency is high.

The invention belongs to the technical field of data storage, and particularly relates to a video data storage method and device, a computer program product and terminal equipment. The method comprises the following steps: under the condition that a target video data file meets a continuous recording condition, determining a continuous recording position based on a video index file; the target video data file is a video data file which stores video data recently, and the video index file stores an effective data length of the target video data file; based on the continuous recording position, determining a target continuous recording information storage data packet in the target video data file; the target continuous recording information storage data packet stores continuous recording reference time of the target video data file; and storing each piece of to-be-stored video data based on the continuous recording position and the continuous recording reference time stored in the target continuous recording information storage data packet.

This utility model relates to a multi-protocol compatible data communication and acquisition device, including a main control unit, at least one pluggable interface unit, and a non-volatile memory. Each interface unit is equipped with an in-situ detector and an onboard identification information memory. The in-situ detector is electrically connected to the main control unit via a freeze control line and a recovery confirmation line, and the onboard identification information memory is electrically connected to the main control unit. The non-volatile memory is an FRAM or NVRAM, connected in parallel with a supercapacitor to complete continuous recording during insertion / removal or power failure. The main control unit is electrically connected to the non-volatile memory and establishes corresponding data channels with each interface unit. When an interface unit is inserted / removed or disconnected, the in-situ detector triggers the main control unit to freeze the corresponding data channel via the freeze control line. During the freeze period, the main control unit writes continuous records (including segment numbers and water level lines) into the non-volatile memory and confirms them via the recovery confirmation line after unfreezing.

The present invention discloses a method for using machine learning to statistically calculate the arcing position and duration of a low-clutter antenna. The method relates to the field of magnetic confinement fusion. During operation of a magnetic confinement fusion device, a visible camera is used to observe the bright spots produced by arcing, continuously recording the changing process of the arcing state of the low-clutter antenna. A large number of different arcing states are identified and classified, and a corresponding database is established. The database is used as input in a deep convolutional neural network analysis program, which statistically learns and classifies the different arcing states. The results of manual and program identification of the arcing states are compared, and the accuracy of the program calculations is verified while calibrating. Based on the program identification results, the machine learning-based DBSCAN algorithm is further used to normalize and cluster the classified images of the different arcing states, and the duration of different arcing positions on the low-clutter antenna is calculated. The present invention can achieve real-time identification of arcing states for low-clutter antennas and simultaneously calculate their arcing positions and durations.

Data processing system for the automated processing and analysis of large data sets in scalable network systems, comprehensive a plurality of processing units distributed from one another, a data acquisition unit for the continuous recording and pre-structuring of incoming data, a control unit for assigning data processing tasks to the processing units, as well as a storage unit for storing raw data and processing results, characterized by the fact that A hardware-implemented preprocessing unit is provided which segments and classifies incoming data structures based on defined structure and integrity parameters and only releases data for analysis that meets predefined processing conditions, whereby the processing units execute parallel analysis processes and the results are merged in a consistent state space.

The invention discloses a continuous recording method and device and electronic equipment. The method comprises the steps that a low-power-consumption power domain of the system is configured to control the system to enter a sleep mode, a microphone of the low-power-consumption power domain continuously collects audio data, a continuous recording controller of the low-power-consumption power domain carries out abnormal sound detection on the audio data to obtain a detection result, and if the detection result is that abnormal sound is detected, the system is awakened. According to the invention, the low-power-consumption power domain is used for continuous recording, after the system enters the dormant state, the low-power-consumption power domain still keeps working, and abnormal sound detection can be carried out on the audio data collected by continuous recording, so that continuous recording is realized in a low-power-consumption mode, and the requirement of long-time use of battery products is met.

The invention provides a gear hobbing machine automatic production line monitoring method and system based on artificial intelligence, and the method comprises the steps: firstly receiving a dynamic data sequence which is transmitted by a gear hobbing machine automatic production line in real time and continuously records a working state, namely, a gear hobbing machine operation state flow; and dynamic association modeling is carried out through an artificial intelligence model, and a structured feature set representing association relationships among the operation states, namely, a gear hobbing machine operation state association map, is generated. And tracing a cause chain of abnormal operation based on the operation state association map, and constructing a regulation and control scheme combination aiming at each link according to the cause chain, namely a gear hobbing machine operation regulation and control strategy set. And finally, converting the regulation and control strategy set into a standardized instruction, and sending the standardized instruction to a production line control terminal. According to the invention, real-time, accurate and intelligent monitoring of the automatic production line of the gear hobbing machine is realized, the operation stability and production efficiency of the production line are effectively improved, and the fault occurrence rate is reduced.

This invention discloses an experimental device for simulating the flow law and dynamic liquid carrying capacity of a high-yield water-gas well, comprising a gas supply component, a gas-liquid mixing device, a wellbore simulation unit, a data acquisition and visualization unit, a pressure controller, a liquid supply unit, and a gas-liquid processing unit. The data acquisition and visualization unit includes a wire mesh sensor, a flow / pressure measurement device group, a high-speed camera, and a data terminal. The visualized tubing is mounted on a sliding rail-type variable angle multiphase pipe flow simulation device. The data terminal is connected to the wire mesh sensor, the flow / pressure measurement device group, and the high-speed camera. This invention can simulate wellbore flow under laboratory conditions with different visualized tubing angles, different pipe diameters, different gas-liquid flow rates, and different outlet pressure constraints, and has the function of synchronous acquisition and continuous recording of pressure, flow rate, liquid holdup, and high-speed images.

A system and method using a therapeutic electromechanical device to externally control movement for recognizing the tongue movements, vocalizations, and throat vibrations of a patient and converting them into words. The device can be activated by electromyography (EMG), electroencephalography (EEG), or through mechanical and / or optical methods. The force, speed of movement, limit of movement, duration of movement, and frequency of movement can be adjustable / programable / configurable. The device can be coupled with stimulatory and / or detection sensors and / or electrodes. The device can be used for performing mechanical movements with adjustable force and speed / duration of movement to remediate physical impairments. The system can continuously record the movement of the patient's tongue, vocalizations, and throat vibrations and extract small video segments. Each video segment can be analyzed by AI software or other configured software to match the specific tongue movements, vocalizations, and throat vibrations with a pre-learned reference word. Multiple recordings can be performed. The software / configured system can then translate the signals into speech.

The present disclosure relates to a method for predictive monitoring of the measurement accuracy of a measurement device for a medium variable and a measurement variable. The medium is located in a container of a facility that operates independently of the measured value and whose operation includes recurring specific operation phases during which the characteristics of the measured values measured are distinguishable from the measured values measured during other time periods, and when the facility is operating correctly and the measurement device meets the specified measurement accuracy, the characteristics conform to reference characteristics. The method includes: continuously recording data including the measured values during the operation of the facility; determining, based on training data included in the data, a classification method that identifies a data set measured during a specific operation phase; performing the classification method and determining, based on the identified data set, a time series of a conformity indicator indicating the degree of conformity of at least one property indicating the characteristics of the measured values with a reference property of the reference characteristics; determining, based on the time series at least once, the remaining time until the degree of conformity drops below a predetermined minimum degree of conformity; and providing an output notifying the remaining time.

The invention discloses an intelligent medical supply management and control method, and belongs to the field of intelligent medical treatment, and the method comprises the following steps: S1, storing medical supplies, building a unique binding relation between a two-dimensional code of each medical supply and an article name, a warehouse positioning serial number, a bar code positioning lamp number and a validity period, and writing the unique binding relation into a management and control database; s2, an operator initiates a search request, calls a target medical supply warehouse positioning sequence number and a bar code positioning lamp number from the management and control database, and displays the numbers; s3, generating a lamp control instruction according to the warehouse positioning serial number and the lamp number, and enabling the target bar code positioning lamp to emit light in a preset color and flicker rhythm; s4, an operator completes positioning according to the light, and the taking-out number is input and confirmed at the mobile terminal; s5, updating the inventory based on the access data and continuously recording; s6, calculating the number of remaining use days to generate validity period state data; and S7, jointly analyzing the inventory and validity period data to generate a prompt, and updating light and background display. The method has the beneficial effects that the searching efficiency and the inventory and validity period management precision are improved.

The invention provides a shipborne marine gravimeter quasi-static test evaluation method and device, belongs to the technical field of marine geophysical measurement, adopts a dual correction mechanism to reconstruct the structural composition of a data processing function module, and specifically adopts a technical means of synchronously collecting GNSS elevation change data to realize accurate measurement. The GNSS positioning system is rigidly connected with the gravimeter to continuously record elevation change data of the ship; calculating a gravity correction value caused by elevation change; the earth tide correction value and the elevation change correction value are deducted from gravity observation data at the same time, the accurate residual observation quantity is obtained, the technical inertia that in the prior art, only earth tide correction is considered, but the elevation change influence is ignored is broken, the GNSS system is ingeniously used for recording the ship elevation change condition, and a dual correction mechanism is adopted; the problem that the evaluation result is inaccurate due to the fact that the ship fluctuates along with the tide level in a wharf mooring test is solved, and then the technical effect of accurately evaluating the performance of the gravimeter in the quasi-static environment is achieved.