85 results about "Acquisition time" patented technology

The invention discloses an oil and gas long-distance pipeline automatic control system fault identification method based on deep learning, and the method comprises the following steps: collecting and preprocessing a time sequence, and generating a standardized input sequence; constructing a physical constraint feature set, and generating a physical observable representation; encoding the valve opening instruction time sequence and the pump station frequency instruction time sequence to form a combined input sequence; obtaining Koopman state representation, and generating a linear evolution state sequence; a residual nonlinear compensation structure is introduced to generate residual features, and a comprehensive state sequence is formed; time scale splitting is carried out, and fast, medium-speed and slow time scale feature sequences are decomposed; identifying anomalies and generating a time scale anomaly feature set; leakage energy loss indexes are calculated and fused to form fault mode drift representation; judging the pipeline state, and outputting a fault recognition result. According to the invention, a deep Koopman operator structure is adopted, accurate identification of pipeline faults is realized, and the method has the advantage of high diagnosis reliability.

The invention discloses an early warning method and device for multi-device time sequence data and electronic equipment. The method comprises the steps of determining a time sequence data stream; dividing the time sequence data stream according to the model identifier to obtain a plurality of sub-time sequence data streams, sliding on the sub-time sequence data streams by using the time windows according to a preset step length from the starting timestamps of the sub-time sequence data streams, and determining the time sequence data under the time window which slides each time as a target time sequence data stream; performing timestamp alignment and data filling on time sequence data in the target time sequence data stream to obtain an aligned target time sequence data stream, and predicting a time sequence data predicted value corresponding to the aligned target time sequence data stream in a future time period through a prediction model corresponding to the aligned target time sequence data stream; and determining early warning information corresponding to the target time sequence data stream according to the time sequence data predicted value. The technical problem that the accuracy of an early warning result is affected by data time sequence dislocation caused by inconsistent acquisition time of time sequence data between devices is solved.

The invention discloses a pole piece slitting method, device and equipment and a storage medium, and relates to the technical field of batteries, and the pole piece slitting method comprises the steps that a first signal of the displacement of a slitting assembly in the pole piece slitting equipment in the axial direction of the slitting assembly changing along with the collection moment is obtained, and the axial direction is perpendicular to the pole piece slitting direction of the slitting assembly; based on the first signal, the current state of the slitting assembly is determined; and based on the current state of the slitting assembly, the pole piece slitting equipment is controlled. According to the invention, the first signal that the displacement of the slitting assembly in the axial direction in the pole piece slitting equipment changes along with the collection time can be obtained online in real time, and the current state of the slitting assembly is determined through the signal, so that the pole piece slitting equipment is controlled to be matched with the current state; and the condition that unqualified pole pieces cut by the pole piece cutting equipment flow into the next process can be effectively reduced, so that the performance and the service life of the finally produced battery are improved.

The invention relates to the technical field of power monitoring, in particular to an online monitoring method and system for a power control cabinet. The method comprises the following steps: acquiring a time domain signal, tracking a fundamental wave frequency, adjusting a sampling window, and performing Fourier transform to obtain a harmonic amplitude and a phase; harmonic waves are divided into harmonic wave correlation groups according to association rules, harmonic wave phase consistency coefficients are calculated to weight the total energy in the groups, and weighted harmonic wave energy is obtained; total inter-harmonic energy is calculated, and an inter-harmonic structure factor is obtained based on the spectral entropy. And acquiring a real-time load rate and a change rate, and calculating a synchronous change coefficient and a load factor. And summing the weighted harmonic energy and the corrected inter-harmonic energy to obtain total distortion energy, and obtaining a comprehensive distortion index according to the total distortion energy. According to the scheme, the structured inter-harmonics possibly caused by the early failure of the equipment can be found earlier, and the requirements of early warning and predictive maintenance are met.

The invention relates to the technical field of multimode signal coverage, and discloses a multimode-based signal coverage amplification system and method. The system comprises a multi-source signal feature acquisition module, a real-time coverage situation generation module, a coverage deviation evaluation module, a resource scheduling module and a beam optimization execution module. The multi-source signal feature acquisition module acquires a multi-dimensional signal backtracking feature set containing first signal intensity distribution and first channel parameters at historical acquisition moments of a target area in a preset scanning period; a real-time coverage situation generation module obtains a real-time coverage situation map containing second signal intensity distribution and second channel parameters; a coverage deviation evaluation module constructs a coverage deviation matrix accordingly; a resource scheduling module retrieves a matched coverage blind area feature set, and when the dispersion reaches the standard, a resource release coefficient is calculated; and the beam optimization execution module executes coverage enhancement operation on the coverage resources according to the coefficient from the storage starting moment, so that the signal coverage quality and the resource utilization efficiency of the target area are effectively improved.

The invention discloses an intelligent bracelet integrated with photoelectric volume pulse wave detection and a data processing method thereof, and belongs to the field of intelligent bracelets.The intelligent bracelet comprises a host, a display screen is arranged on the upper surface of the host, an acquisition sensor is arranged on the lower surface of the host, and a control knob is arranged in front of the outer surface of the host; through the detachable structure of the watchband, the mounting groove and the inner groove are formed in the left end and the right end of the host and matched with the clamping block, the pinch bar, the spring and the button of the watchband to form a quick dismounting mechanism, the pinch bar can be driven to be separated from the clamping groove of the clamping block by pressing the button, the watchband can be dismounted by hands without tools, and the operation time is shortened to be within 3 seconds; in order to solve the problem that a traditional watchband is tedious to replace and easy to damage, the method comprises the following steps: in a signal preprocessing stage, combining band-pass filtering and adaptive Kalman filtering, and synchronously introducing motion data of an acceleration sensor and a PPG signal signal-to-noise ratio evaluation mechanism, when SNRlt; and the acquisition time is automatically prolonged or a user is prompted to stabilize the hand at 10dB.

The invention provides a sensor acquisition time synchronization method and system based on ZYNQ. A unified clock source is arranged in the FPGA, and it is guaranteed that no accumulated drift exists in the time difference. Hardware triggering is carried out by adopting an IMU signal as a reference, camera triggering at a precise moment is carried out according to the triggering moment in combination with factors such as exposure time and transmission delay of an image, and it is ensured that IMU data transmitted to a memory and a camera image are from the same real moment. Sensor data are calibrated through a software algorithm, and a result is fed back to the sensor trigger signal offset processing module to form a complete calibration loop. And closed-loop feedback is introduced, so that automatic and self-adaptive high-precision synchronization is realized. The IMU signal is used as a camera image acquisition triggering means, so that the image frame frequency and the IMU frequency are in a multiple relationship, and the parameters of the offset processing module can be modified according to the required frame frequency and the existing IMU frequency in the actual operation process to adjust the frame rate.

The invention relates to the technical field of power equipment monitoring, in particular to an intelligent electric energy meter operation state abnormity monitoring management method. Obtaining a fluctuation characteristic value according to local data at any moment in the load data sequence and the corresponding fitting data; filtering according to the fluctuation characteristic value to obtain a smooth load sequence; obtaining different load time periods according to the smooth load sequence, carrying out clustering, and obtaining a power utilization fluctuation value according to fluctuation characteristic values at all moments in a time period cluster; acquiring an acquisition time period according to the time period distribution characteristics of the time period cluster; the relative fluctuation degree is obtained according to the electricity utilization fluctuation values of the user and other users in the collection time period and the distance characteristics of the electric energy meter; and obtaining a frequency adjustment coefficient according to the load data of the user, the temperature sequence and the relative fluctuation degree. The monitoring data of the electric energy meter are adaptively acquired according to the frequency adjustment coefficient, and the monitoring accuracy of potential faults of the electric energy meter is improved while the storage pressure of the monitoring data is reduced.

The invention discloses a high-frequency electrotome negative plate impedance detection method and system and a high-frequency electrotome, and the detection method comprises the steps: an impedance detection signal preprocessing step: determining an acquisition time interval of an impedance detection signal according to a current working mode and a corresponding optimal acquisition time interval; only the impedance detection signals in the acquisition time interval are collected; the acquisition time interval is one or more carrier periods in which the signal-to-noise ratio of the impedance detection signal is higher than the average value of the signal-to-noise ratio in a unit modulation period T under the current working mode; and the optimized impedance detection signal is filtered and amplified and then is input into an impedance calculation module to calculate and obtain a real-time impedance value of the negative plate of the high-frequency electrotome. Interference is filtered out by monitoring information such as power and impedance intervals when the high-frequency electrotome works and combining noise waveform characteristics of different working modes.

The invention provides a non-contact life signal processing method in a strong clutter environment, and belongs to the field of data processing.The method comprises the steps that extreme points in a signal data sequence of a user and first and last signal data are recorded as to-be-corrected data; obtaining an amplitude adjustment parameter and a slope adjustment parameter of each piece of to-be-corrected data according to a numerical value difference and an acquisition time difference between each piece of to-be-corrected data and the to-be-corrected data on the left side and the right side of the to-be-corrected data; and combining the numerical value of the to-be-corrected data to obtain a corrected value of the to-be-corrected data, thereby obtaining upper and lower envelope lines. The invention aims to solve the problem that the signal data of a user is processed by an EMD (empirical mode decomposition) algorithm due to the fact that an upper envelope line and a lower envelope line which are obtained through extreme points in a signal data sequence are greatly influenced by noise because the noise in an environment where the user is located has a great influence on the signal data of the user. And the accuracy of the obtained heart rate signal and respiration signal is low.

The invention relates to the technical field of plastic pipe cutting, and provides a multi-angle band saw operation control method and system.The method comprises the steps that vibration data, current data and rotor angles at different collection moments are collected in the plastic pipe cutting process, and the target collection moment is marked; constructing a vibration sequence, a current sequence and a rotor angle sequence at a target acquisition moment; determining a cutting misalignment degree, a cutting misalignment degree sequence and a cutting misalignment degree predicted value sequence at the target acquisition moment, and determining a notch form offset degree at the target acquisition moment according to the difference between the cutting misalignment degree sequence at the target acquisition moment and the cutting misalignment degree predicted value sequence; and an integral gain adjustment value at the target acquisition moment is calculated, and real-time adjustment of operation of the multi-angle band saw for plastic pipe cutting is achieved in combination with the rotor angle at the target acquisition moment. According to the method, the integral gain is adaptively valued, and the cutting track offset is reduced.

The invention discloses a residual current real-time remote protection method based on edge calculation, which relates to the technical field of power failure protection, and comprises the following steps: executing time sorting and differential calculation based on residual current signal data acquired by current sensors deployed on power distribution branches and corresponding acquisition timestamps; generating a residual current signal record containing the time interval value and the amplitude difference value; extracting a signal arrival delay value and a time jitter value of each record according to the residual current signal record and a locally stored model version number, and fitting the two types of data to generate a time drift compensation parameter; performing version consistency comparison based on the time drift compensation parameter and a cloud model version number returned by the cloud interface; according to the method, a synchronous verification and arbitration updating mechanism of the local and cloud residual current anomaly judgment result is constructed in an edge computing environment, so that the consistency of the judgment result can still be kept under the conditions that the network is unstable and the model is frequently updated.

The application discloses a method, device and equipment for identifying a movement time point of a surface electromyogram signal and a medium. The method comprises the following steps: acquiring a to-be-detected force platform signal corresponding to a to-be-detected surface electromyogram signal; wherein the acquisition time points of the to-be-detected surface electromyogram signal and the to-be-detected force platform signal are synchronous; determining a positive slope cumulative function according to the to-be-detected force platform signal, and performing first-order derivation on the positive slope cumulative function to obtain a positive slope change rate function; determining a movement time point of a movement event corresponding to the to-be-detected surface electromyogram signal according to the positive slope change rate function and a movement change rate threshold; wherein the independent variable and the dependent variable of the positive slope cumulative function are the acquisition time point of the to-be-detected force platform signal and the cumulative positive slope respectively, and the movement time point is a starting time point or an ending time point. The embodiment of the application solves the problem that the traditional identification method is susceptible to noise interference of the surface electromyogram signal, and improves the identification accuracy of the movement time point.

The invention relates to the technical field of power plant auxiliary equipment, in particular to a power plant auxiliary equipment vibration fault diagnosis method and system based on deep learning. Comprises: establishing a fault database of power plant auxiliary equipment; setting a fault diagnosis model and a plurality of equipment points based on the fault database, and acquiring a monitoring data packet of each monitoring point according to a preset acquisition time node; judging whether an early warning instruction is generated or not according to all the monitoring data packets and the fault diagnosis model; the method comprises the following steps of: performing structural analysis on the power plant auxiliary equipment, setting a plurality of equipment points, constructing an abnormal signal set of each equipment point by utilizing a deep learning technology, setting a corresponding processing sub-model and a global diagnosis model according to the abnormal signal set, and analyzing a time sequence association relationship among characteristic sub-signals in a single abnormal signal set to obtain a diagnosis result of the abnormal signal set. And the corresponding processing sub-model is constructed, so that the processing efficiency of the monitoring data of each equipment point and the screening efficiency of the fault signal are improved, and the fault diagnosis efficiency of the power plant auxiliary equipment is improved.

The invention relates to the technical field of electronic device detection and intelligent repair, in particular to a Russian circuit board failure analysis method. N types of synchronous scanning are carried out on the plating layer of the tested circuit board, and acquisition timestamps and space coordinates are marked; aligning the scanning images in various forms according to the acquisition timestamps and the space coordinates to obtain a multi-modal data set; key material characteristic parameters of the Russian circuit board are extracted as priori knowledge; the method comprises the following steps: constructing an N-channel Transform encoder, and designing different encoder structures for each channel; constructing a failure feature library, and determining circuit board failure modes and key features corresponding to each failure mode; performing similarity calculation on the multi-modal data set, the priori knowledge and the failure feature library by using an N-channel Transform encoder; after Softmax normalization, the confidence of each failure mode is output, and a 32-dimensional confidence vector is formed; and judging the main failure mode of the current coating according to the maximum value in the confidence vector.

The embodiment of the invention provides a vehicle end data processing method and device, electronic equipment and a storage medium, and the method comprises the steps: analyzing vehicle end structural data, and obtaining a plurality of collection signal frames of each collection signal, and the collection time and collection value of each collection signal frame; according to each acquisition time of each acquisition signal frame in each acquisition signal, comparing two acquisition values of any two adjacent acquisition signal frames of each acquisition signal, and generating analysis data of each acquisition signal frame of each acquisition signal; and obtaining an analysis data packet of the vehicle end structured data according to the analysis data of each acquisition signal frame of each acquisition signal. Therefore, the invention provides an efficient data compression processing scheme, the data transmission quantity and the transmission time consumption of the vehicle end structured data in the transmission process can be reduced, and the data storage space is reduced.

The present application relates to a kind of suspension bridge pin joint type sling rotation angle measurement method, comprising the following steps: S1, selecting the two places of sling of suspension bridge around lower pin shaft rotation site are carried out transverse marking and longitudinal marking;S2, the marked part of rotation site is videoed and frame is extracted, and the image sequence after frame extraction is obtained;S3, the image gray scale of image sequence after frame extraction is carried out using self-defined single channel method;S4, after the pre-processing of gray-scale image, all straight lines of image are identified using Hough transform, and the long straight line located at the edge of transverse marking and longitudinal marking is extracted;S5, the angle between long straight line respectively located at the edge of transverse marking and longitudinal marking is calculated, and the angle value of sling around pin shaft rotation with time variation in acquisition time period is obtained.The method proposed in the present application can realize the measurement of sling around pin shaft rotation angle, and provide reliable data basis for sling rotation law and related damage mechanism research.

This invention provides a high-sensitivity satellite navigation signal acquisition method. It utilizes an improved acquisition algorithm based on FFT coefficient compensation and block code Doppler compensation to acquire satellite navigation signals, obtaining the acquisition result. This invention effectively reduces the impact of Doppler frequency offset during long coherent acquisition times through coefficient-compensated FFT operations and the block code Doppler compensation algorithm. When calculating the FFT spectrum, only the spectral lines at specified positions need to be calculated, effectively shortening the calculation time, improving acquisition efficiency, and achieving high-sensitivity acquisition of weak signals.

The invention provides a coal quality detection system, method and equipment based on near-infrared coupling TRLIBS and a medium, and the system comprises a transmission module which is used for conveying a coal sample and inputting an operation state signal to a synchronous control module; the TRLIBS detection module is used for exciting a coal sample to generate plasma, collecting a time-resolved laser-induced breakdown spectrum of element characteristics and inputting the time-resolved laser-induced breakdown spectrum into the data processing module; the near-infrared detection module is used for acquiring a near-infrared absorption spectrum of a molecular functional group of the coal sample and inputting the near-infrared absorption spectrum into the data processing module; the synchronous control module is used for receiving the running state signal of the transmission module, sending an asynchronous delay control synchronous trigger signal and controlling an acquisition time sequence; and the data processing module is used for receiving, fusing and processing the TRLIBS spectrum and the near-infrared absorption spectrum, and outputting a coal quality parameter detection result, so that the problems of incomplete parameter coverage, poor multi-module synchronization performance and low detection precision of the coal quality online detection device are solved.

The invention discloses a real-time audio and video end-to-end delay statistical method based on two-way time synchronization, and particularly relates to the technical field of real-time audio and video communication and network performance measurement, which comprises the following steps: S1, time synchronization: a plug flow client and a pull flow client respectively calculate clock skew with an SFU server through two-way message exchange; the method comprises the following steps: S1, a flow pushing end converts an acquisition timestamp and deviation into SFU reference time, and the SFU reference time and stage time consumption metadata are embedded into SEI information to be sent along with a video stream, S3, an SFU server forwards the video stream containing the SEI information, and S4, delay calculation and decomposition: a flow pulling end analyzes the SEI information, calculates total end-to-end delay in combination with the deviation of the flow pulling end, and decomposes the time consumption of each stage. Through high-precision time synchronization and time data losslessly carried by SEI information, non-intrusive, automatic, full-link-covered and decomposable end-to-end delay accurate statistics is realized, and the bottleneck problems that a traditional method is high in invasiveness, low in precision and incapable of positioning are effectively solved.

This invention claims protection for a MEMS gyroscope installation error calibration method based on a large-range autocollimator, comprising the following steps: Step 1, designing an autocollimator with an angle measurement range of ±9° using the reflection angle sensitivity modulation mechanism of a non-standard corner cone mirror (HCCCR); Step 2, establishing an evaluation benchmark for three-axis MEMS gyroscope measurement data by orthogonally combining two large-range autocollimators; Step 3, establishing a common data acquisition serial port between the autocollimator camera and the IMU host computer, and achieving dimensional unification and time synchronization between the autocollimator and MEMS gyroscope output readings by integrating the MEMS gyroscope angular rate measurement readings with time; Step 4, calibrating the MEMS gyroscope installation error coefficient using a traditional precision angular rate output turntable and conducting a comparative experiment. The experiment shows that the relative deviation of the IMU output after compensation by the two calibration methods is less than 0.3%.

The application discloses a high-sensitivity fast acquisition method and system in a star-ground dynamic environment, and the method comprises the following steps: S1, a transmitting end transmits a communication signal conforming to a target communication frequency, and a receiving end receives the communication signal; S2, a plurality of local signals with different frequency points are generated in a frequency search interval through a local parallel digital control oscillator (NCO) group, and FFT-IFFT acquisition determination is performed on the communication signal; S3, if the acquisition determination fails, the frequency search interval is adjusted, and the step S2 is performed again; if the acquisition determination fails in two adjacent frequency search intervals, sideband interval estimation is performed on the two adjacent frequency search intervals, and FFT-IFFT acquisition determination is performed according to the sideband interval estimation result; the step is repeated until the acquisition determination succeeds. Under the conditions that the detection probability is more than 99%, the minimum carrier-to-noise ratio is 34.66 dB, and the minimum signal-to-noise ratio is 16 dB, the receiver sensitivity of-130 dBm can be realized, the total Doppler frequency offset acquisition range can reach 140 kHz, and the acquisition time can be as low as 0.8 seconds.

This invention provides a network signal strength value processing system, method, apparatus, and storage medium. The system includes an emergency call module and communication unit, a vehicle-mounted unit, and a processing terminal. The emergency call module and communication unit collect log information associated with the vehicle's driving route and send the log information to the vehicle-mounted unit. The log information includes geographical location information, signal strength value information, connection status information, network status information, and a collection timestamp. The vehicle-mounted unit receives and stores the log information. The processing terminal performs text parsing of the log information, associates the geographical location information with the signal strength value information, connection status information, and network status information based on the collection timestamp, displays the driving route and one or more of the signal strength value, connection status, and network status on a map, and displays the filtered signal strength. This invention intuitively optimizes signal display and recording.

This invention provides a sensor acquisition time synchronization method and system based on ZYNQ. A unified clock source is set in the FPGA to ensure that time differences do not accumulate and drift. Hardware triggering is performed using an IMU signal as a reference. Based on the trigger time combined with factors such as image exposure time and transmission delay, precise camera triggering is achieved, ensuring that the IMU data transmitted to memory and the camera image originate from the same real-time point. Sensor data is calibrated using a software algorithm, and the result is fed back to the sensor trigger signal offset processing module, forming a complete calibration loop. The introduction of closed-loop feedback achieves automated and adaptive high-precision synchronization. Because an IMU signal is used as the trigger for camera image acquisition, the image frame rate is a multiple of the IMU frequency. During actual operation, the offset processing module parameters can be modified to adjust the frame rate according to the required frame rate and the existing IMU frequency.

The invention discloses a high-real-time multi-camera external trigger synchronous acquisition system, which comprises a multi-camera acquisition unit, a trigger detection unit, a synchronous acquisition control unit and a cache management unit, and is characterized in that a time reference management unit is used for acquiring acquisition time information corresponding to image frames acquired by at least two cameras; and taking the occurrence time of the synchronous acquisition trigger event as a unified time reference. The method has the beneficial effects that the processing path of the trigger signal sinks from an unpredictable software application layer to a hardware / driving layer, so that the disturbance of the scheduling of an operating system on the trigger real-time performance is eliminated, and the acquisition starting time deviation among multiple cameras is stably controlled at the microsecond magnitude; and the harsh requirements of high-real-time application scenes such as automatic driving and high-speed industrial detection are met.

The application provides a method and device for improving sound source positioning accuracy of a binaural hearing aid, which is applied to the binaural hearing aid, and the method comprises the following steps: acquiring a first frequency signal and a second frequency signal, and recording intensity information and respective acquisition time stamps of the first frequency signal and the second frequency signal, wherein the first frequency signal and the second frequency signal are the same specific frequency signal with different acquisition positions; if the acquisition time stamp of the first frequency signal is synchronous or earlier than that of the second frequency signal, when the binaural hearing aid is affected by a head shadow effect, the intensity information difference between the first frequency signal and the second frequency signal and the time difference of the acquisition time stamps are calculated, the analog distance of the specific frequency signal affected by the head shadow effect on a propagation path is deduced, the intensity information of the analog frequency signal and the analog acquisition time stamp are calculated through the difference of sound wave propagation speeds in different media, and available frequency information can be generated.

The invention discloses a data synchronous acquisition device and system based on multi-channel synchronous triggering and a control method, and the device comprises a receiver module which is used for receiving a radio frequency signal, generating a reference triggering signal and outputting corresponding time information; the trigger configuration module is used for generating configuration information output of synchronous trigger signals of the multiple channels; the multi-channel synchronous trigger signal generation module is used for generating synchronous trigger signals of a plurality of channels according to the configuration information of the synchronous trigger signal of each channel by taking the reference trigger signal as a reference, and outputting the state information of the synchronous trigger signal of each channel and the corresponding time information; and the acquisition time correction module is used for correcting the time of the sensor data according to the synchronous trigger signal state and time of each channel, so that the time of the sensor data is synchronized. According to the invention, data acquisition synchronization of multi-channel synchronous triggering can be accurately realized, and correct matching of sensor data of each channel can be ensured.

This invention discloses a method and apparatus for acquiring medium- and long-code satellite navigation signals. The invention includes acquiring incident intermediate frequency (IF) signals from multiple down-converted satellites and constructing a satellite real matrix based on these signals; performing eigenvalue decomposition on the satellite real matrix using orthogonal trigonometric decomposition to determine the signal noise subspace; determining a Doppler frequency shift estimate based on the signal noise subspace and a preset signal frequency vector; determining a pseudocode phase offset using the extended replication overlap method, the Doppler frequency shift estimate, and a preset local pseudocode; and generating a target satellite navigation IF signal using the pseudocode phase offset and the Doppler frequency shift estimate. This invention solves the technical problem of excessively long acquisition time in existing medium- and long-code satellite navigation signal acquisition technologies.

The invention provides an AIS (Automatic Identification System) and video associated positioning method, which comprises the following steps of: receiving a ship broadcast signal in real time by using AIS receiving equipment, and analyzing to obtain identity information, geographic position data and a corresponding generation timestamp of a ship; the method comprises the following steps: acquiring real-time video stream data through camera equipment in a monitoring sea area, identifying a ship target in the video stream data, and determining a pixel coordinate position of the ship target in a video picture and a corresponding acquisition timestamp; converting the geographic position data of the ship into a theoretical projection position in a visual field range of the corresponding camera equipment based on the parameters of the camera equipment by adopting a coordinate conversion algorithm; the Euclidean distance between the theoretical projection position and the pixel coordinate position of the ship target in the video picture is calculated, and the time synchronization error between the generation timestamp and the collection timestamp is calculated; and if the Euclidean distance is smaller than a preset association threshold value and the time synchronization error is within a preset tolerance range, determining that matching succeeds, and establishing an association relationship between the ship identity information and the ship target.

The invention discloses a road surface damage detection method based on a tire noise signal, which comprises the following steps: S1, in a driving process, recording the tire noise signal and corresponding GPS positioning data in real time, and synchronously recording an acquisition timestamp; s2, the collected audio signals are preprocessed through a Python environment, and noise reduction processing is carried out on the audio signals through an HPSS algorithm in a Nussl library; s3, using a Librosa library to segment the de-noised audio signal into segments with a preset length; s4, inputting the segmented audio segments into the trained damage detection model to identify the type of the road surface damage and determine the time point of the damage; and S5, determining the position of the damage according to the time point of the damage in combination with the GPS positioning data. According to the method, the noise signals generated when the tires make contact with the road surface are collected and analyzed, the machine learning algorithm is combined, the road surface damage type is recognized and positioned, a new technical path is provided for road maintenance and maintenance decision making, and the method has important practical value.