273 results about "Time marker" patented technology

The invention discloses a power distribution network distributed measurement synchronization method and device based on Beidou satellite time service, and belongs to the technical field of power distribution network measurement, and the method comprises the steps: obtaining a Beidou satellite signal, calibrating a local clock source, and generating a standard time reference; when it is continuously monitored that the Beidou satellite signal quality parameter is lower than a quality threshold value, clock working environment parameters of a local clock source are collected, and a short-term clock offset predicted value is generated in combination with a standard time reference; generating topology correction according to the topology connection relation of the power distribution network; and fusing the short-term clock offset predicted value and the topology correction quantity to generate a dynamic compensation time reference, performing time marking on the acquired electrical quantity measurement data of the power distribution network, and generating synchronous measurement data with a timestamp. According to the technical scheme, when the Beidou signal is lost, the local clock drift predicted value and the adjacent node topology correction amount are fused to generate the dynamic compensation time reference, so that the measurement data synchronization precision and robustness of the power distribution network in a complex environment can be remarkably improved.

The invention belongs to the technical field of decision optimization, and relates to an enterprise-level intelligent risk control decision system combined with a real-time data stream, and the system comprises a heterogeneous data distribution module which is used for obtaining multi-source heterogeneous data streams inside and outside an enterprise; the behavior time sequence splicing module is used for executing cross-system user ID association and time sequence recombination on the real-time data flow to generate a user behavior chain with continuous time stamps; the feature fusing calculation module is used for receiving the user behavior chain, performing feature extraction and outputting a real-time feature vector with a quality flag bit; the incremental model updating module is used for respectively generating a baseline risk score and a dynamic risk score; and the dynamic weight decision module is used for generating final decision parameters. And the risk control processing execution module responds to the final decision parameter to trigger a processing action, and configures a manual auditing arbitration channel and a feedback data generation unit. According to the method, the problems that a dual-check algorithm is not deeply coupled with a business index, and abnormal data which passes hash check but has logic violation flows into a real-time channel are solved.

The invention relates to the field of playing data visualization, in particular to a playing data visualization method and system. The method comprises the steps that at least one section of pedal data of at least one pedal is obtained, and the pedal data comprises a pedal value and a time stamp of the pedal value; generating at least one section of labeling track according to the pedal data; wherein the labeling track comprises a first simulation track and a second simulation track; correspondingly, the method comprises the steps that when the pedal value is larger than a first pedal threshold value, a first simulation track is generated according to the pedal value, and the first simulation track is displayed in a first labeling form; when the pedal value is larger than a second pedal threshold value and smaller than or equal to the first pedal threshold value, a second simulation track is generated according to the pedal value, and the second simulation track is displayed in a second labeling form; and generating a combined track according to the at least one section of labeled track, and displaying the combined track on the music score. According to the invention, the smoothness and integrity of pedal data display can be improved, and the user experience is optimized.

The invention relates to the technical field of data monitoring analysis, and discloses a centrifugal machine data remote monitoring analysis method and system based on a cloud computer, and the method comprises the following steps: collecting centrifugal machine operation index data, carrying out time stamp synchronization, carrying out the recognition and elimination of abnormal values in the data, and carrying out the data integration through data normalization processing, and generating synchronous monitoring data. According to the invention, the data frequency domain analysis of the centrifugal machine is implemented on the cloud platform, the vibration signal frequency spectrum and energy distribution are accurately identified, the efficient marking and trend analysis of abnormal data are realized, the detailed degree and response speed of abnormal detection are enhanced, and the monitoring of the running state of the centrifugal machine is more accurate; by combining real-time trend analysis and historical fault data, the accuracy of fault prediction is improved, the classification of fault modes is more scientific, the situations of false alarm and missing alarm are effectively reduced, the timeliness and pertinence of preventive maintenance measures are enhanced, and the running efficiency and safety of the centrifugal machine are remarkably improved.

Systems and methods for automatically populating a post-operative report of a surgical procedure are disclosed. A system may include at least one processor configured to implement a method including receiving an identifier of a patient, an identifier of a healthcare provider, and surgical footage of a surgical procedure performed on the patient. The method may include analyzing frames of the surgical footage to identify phases of the surgical procedure based on interactions between medical instruments and biological structures and, based on the interactions, associate a name with each phase. The method may include determining a beginning of each phase and associating a time marker with the beginning of each phase. The method may include populating a post-operative report with the patient identifier, the names of the phases, and time markers associated with the phases in a manner that enables the health care provider to alter the post-operative report.

The invention discloses an adaptive TimeXer model photovoltaic power prediction method and system based on weather typing, and belongs to the technical field of photovoltaic power generation, and the method comprises the steps: dividing a historical photovoltaic power sequence into time patches, carrying out PatchEmbedded projection on the time patches to generate time stamps, and generating learnable global stamps; the method comprises the following steps: carrying out standardization processing on meteorological data, carrying out clustering to generate a weather classification label, converting the weather classification label into a discrete variable label, and carrying out Variate Embedded projection on the standardized continuous meteorological data to generate a continuous meteorological factor; performing endogenous self-attention calculation on learnable global marks, continuous meteorological factors and discrete variable marks to obtain attention weights among the time marks, aggregating the continuous meteorological factors and the discrete variable marks by using the attention weights among the time marks through cross attention processing, and inputting multi-scale feature marks into a feedforward network to obtain a multi-scale feature mark; and adjusting the frequency domain of the predicted value by using a Fourier mixing layer to obtain a final prediction result.

The invention relates to the technical field of large-scale data management, in particular to a data storage method and system based on a large model, and the method comprises the following steps: collecting multiple items of data in a large model data set, recording the occurrence frequency of each type of data, calculating the entropy value of each type of data, determining the volatility and diversity of the data, and generating an entropy value calculation result. According to the method, the data are sorted and stored in a classified mode according to the entropy values, so that the high-entropy-value data are located in a high-density storage area, the low-entropy-value data are stored in a low-density area, the utilization rate of the storage space is optimized, unnecessary storage cost is reduced, stratum superposition is simulated according to hierarchical storage of the data and sorting of time stamps, and the data storage efficiency is improved. The storage structure is optimized, rapid positioning and access of new data are also facilitated, adjustment of data compression and storage parameters simulates the geologic stratum compaction process, the storage capacity is effectively managed, the energy efficiency of a data center is enhanced, and the response capability to a complex data environment is enhanced.

The invention discloses a trust evaluation data storage tracing method and system based on a block chain technology, and particularly relates to the technical field of data storage management, and the method comprises the following steps: recording trust evaluation data in a block form based on the distributed storage characteristics of a block chain, automatic management of data submission, verification, storage and updating is realized by using an intelligent contract, data authenticity and non-tampering are ensured, time stamps are added for data through a timestamp function, a time-ordered operation chain is formed, a data tracing function is provided, an authorized user is allowed to inquire a data source and historical operation records, and the user experience is improved. Based on data access characteristics, a storage area is dynamically adjusted, and efficient utilization and optimal management of storage resources are achieved; according to the method, the storage position of data can be dynamically adjusted, hot data are stored in a high-performance storage area, cold data are migrated to a low-cost storage area, the access efficiency of high-frequency data is guaranteed, and the storage cost is optimized.

The invention provides a drainage basin ecological environment evolution analysis method and system combined with a remote sensing image, and relates to the technical field of remote sensing. Firstly, a multi-temporal remote sensing image data set covering a target drainage basin and provided with time stamps is obtained, and then ecological feature extraction is carried out on the multi-temporal remote sensing image data set; spatial distribution features and time sequence features of drainage basin ecological elements are obtained, then ecological evolution mode analysis is executed based on the spatial distribution features and the time sequence features, and ecological state transition features of different time nodes are generated; the method comprises the following steps of: determining a drainage basin ecological environment evolution trend including stability, degeneration and restorability directions according to an ecological state transition characteristic, and finally generating a drainage basin ecological environment evolution analysis result containing a time node corresponding relation, so as to obtain a drainage basin ecological environment evolution analysis result. The method is used for indicating a historical evolution process and current state positioning information of a watershed ecological environment.

The invention relates to a teaching quality dynamic evaluation system based on big data, and the system comprises a data collection module which is used for obtaining an original teaching time series data flow containing student scores, classroom performance and homework quality in real time; the time sequence processing module is used for adding a time stamp to the original teaching time sequence data stream and verifying the time stamp to generate a teaching time mark data set, performing time sequence analysis on the data set to obtain a teaching fluctuation feature set, and performing multi-dimensional decomposition on the feature set to extract a teaching quality feature set; and the real-time monitoring module is used for constructing a teaching monitoring model based on the teaching target parameters, calculating a multi-dimensional deviation between the current teaching quality feature set and the historical teaching quality feature set by using the model, and generating a multi-dimensional teaching early warning signal when the deviation exceeds a preset multi-dimensional joint early warning threshold. According to the invention, real-time dynamic monitoring and risk early warning of teaching quality are realized, and evaluation efficiency and accuracy are improved.

The invention provides a vital sign data acquisition method and system supporting multi-device synchronization. The method comprises the following steps: acquiring vital sign data and various key event data of a patient through multiple types of acquisition equipment, and generating a personalized synchronous configuration file; based on the personalized synchronous configuration file, carrying out dynamic adjustment and optimization by applying a self-adaptive time sequence calibration algorithm to ensure that data acquisition time sequences are highly consistent, and adding microsecond-level time stamps by adopting a high-precision timestamp embedding technology to generate a vital sign data stream; based on the vital sign data stream, monitoring and evaluating signal stability by using a real-time spectral analysis algorithm, automatically adjusting acquisition frequency and a sampling strategy, and implementing immediate adjustment by adopting an environment adaptive adjustment technology to generate a multi-source vital sign data set; and generating a standardized vital sign data report based on the multi-source vital sign data set. According to the technical scheme provided by the invention, the quality and consistency of the vital sign data synchronously collected by multiple devices are greatly improved.

The invention relates to a driving behavior evaluation method, a computer program product, equipment and a storage medium. The method comprises the following steps: acquiring driving data with a time stamp of a target vehicle; dividing the driving data into a plurality of segments according to a preset time period, and performing statistics on road condition feature data and driving style feature data of each segment according to the driving data; according to the road condition feature data, respectively determining a road condition corresponding to each segment, a frequency weight of the road condition and an evaluation weight of the road condition; according to the driving style feature data, determining a driving style corresponding to each segment; and based on the preset basic score corresponding to each driving style, in combination with the road condition corresponding to each segment and the evaluation weight and the frequency weight of each road condition, obtaining a driving behavior evaluation result of the target vehicle. According to the driving behavior evaluation method and device, continuous, long-time and complex driving behaviors are accurately evaluated, so that the risk of the driving behaviors of the driver is measured, and the objectivity and accuracy of driving behavior evaluation are improved.

The embodiment of the invention provides a touch sensing system and method, electronic equipment, a storage medium and a program product. The touch sensing system comprises a contact assembly, a projection assembly, a collection assembly and a processing assembly, and is configured to be capable of being in contact with an external object and generating deformation; the projection assembly is configured to project an active light field with a time modulation characteristic to a first surface of the contact assembly, the active light field is projected on the first surface to form a plurality of pattern areas, the light intensity of adjacent pattern areas changes based on different time sequence codes, and the first surface is opposite to a second surface, making contact with an external object, of the contact assembly; the acquisition assembly comprises a plurality of acquisition units arranged in an array, and is configured to acquire a plurality of pattern areas and output a time stamp acquisition data sequence.

The invention provides a personnel detection method and system applied to a fire scene, and the method comprises the steps: firstly obtaining a multi-source signal data set of the fire scene, enabling the multi-source signal data set to comprise communication signal units which are collected at different positions and are provided with time stamps, carrying out the signal feature extraction processing of the multi-source signal data set, and carrying out the detection of the multi-source signal data set; the method comprises the following steps: obtaining spatial distribution characteristics and time sequence change characteristics of a communication signal unit, then calling a pre-trained personnel positioning model to carry out joint positioning analysis on the spatial distribution characteristics and the time sequence change characteristics, and generating a potential personnel position candidate set corresponding to the communication signal unit; target position information of to-be-rescued personnel in the fire scene is determined according to the potential personnel position candidate set, finally, a rescue guide instruction containing position coordinates is generated based on the target position information, the rescue guide instruction is sent to a rescue terminal to trigger personnel search and rescue operation, and therefore indirect positioning is achieved through communication signals, and rescue efficiency is improved. Limitations of a traditional method are overcome, and rescue efficiency is improved.

The invention discloses a multi-modal data atlas enhanced intelligent reasoning decision optimization method and system, and relates to the technical field of data intelligent analysis, and the method comprises the following steps: S100, building a cross-time stamp trace collection flow, extracting an event sequence based on a time node in a continuous reasoning process, generating a complete time anchor point set, and carrying out the collection of the time anchor point set; outputting a dislocation trace band based on the time anchor point set; and S200, analyzing the time drift distribution of the dislocation trace band, determining the boundary range of the ghosting window by identifying the phase change of the continuous fragment, and generating a phase overturning scale sequence on the boundary range for time scale control in the subsequent reasoning evidence isolation operation. By constructing a time anchor point and phase scale mechanism, accurate isolation of causal paths and rearrangement of reasoning structures are realized, false causal interference is effectively shielded, the stability and credibility of the reasoning process are improved, and the accuracy and interpretability of a multi-modal intelligent decision-making system are enhanced.

The invention discloses an integrated management and traceability method for a non-perpetual industry chain, and relates to the technical field of information management and data traceability, and the method comprises the steps: S100, building a uniform time mark baseline of a whole link, carrying out the nanosecond alignment of all write-in channels, extracting and solidifying the time sequence features of each piece of business data, and forming a time sequence fingerprint as a structured reference basis; and S200, constructing a ghosting detection chain based on the structured reference basis, collecting delay distribution and a phase difference track in a high-concurrency writing process, and identifying a potential region of a retention copy and positioning an abnormal point in combination with a delay distribution entropy. According to the method, the nanosecond time fingerprint, the ghost detection chain, the anti-fact playback mechanism and the causal residual spectrum are constructed to realize accurate identification and dynamic control of the whole writing process of the non-perpetual data, and an error frequency signal and a time reversal rearrangement mechanism are introduced to effectively prevent repeated curing and ensure the uniqueness and credibility of the data.

The invention relates to an emergency evacuation path generation method, system and device under multi-target conflict and a medium. The method comprises the following steps: acquiring video monitoring data and environment sensing data of a target building, and performing fire disaster detection according to the video monitoring data to obtain a fire detection result; in response to the fire detection result that the fire disaster exists, performing fire evolution prediction according to the environment sensing data based on the environment topological graph of the target building to obtain fire evolution parameters; performing risk assessment and latest passable time marking on each space unit node in the environment topological graph according to the fire evolution parameters to obtain a risk graph layer; and in response to the obtained positions of the to-be-evacuated persons, generating an exclusive emergency evacuation path of each to-be-evacuated person in combination with the environment topological graph and the risk map layer. According to the method, fire detection and fire spreading deduction are carried out through continuous video image frames, time sequence judgment is carried out on traffic effectiveness, and path design is prevented from lagging behind risk change.

The invention discloses a risk control rule effect prediction method and system based on big data, and relates to the technical field of financial risk control, and the method comprises the steps: collecting a transaction detail data set, a user activity record data set, an insurance claim data set, a geographic position data set and a time stamp information data set from a multivariate data source, preprocessing the collected information to form a data set; constructing an anomaly detection model by using a generative adversarial network GANs, and identifying an abnormal behavior in the transaction mode; constructing a risk control prediction model based on a space-time diagram convolutional neural network STGCN, and inputting the abnormal behavior data in combination with risk control rule parameters into the risk control prediction model to obtain a prediction risk probability; comprehensively evaluating the transaction behavior based on the abnormal behavior in combination with insurance claim evaluation, fraud detection and insurance market fluctuation to obtain a comprehensive evaluation result; a corresponding risk control prevention strategy is made based on the prediction risk probability and the comprehensive evaluation result; and inputting the real-time data into the model to obtain a real-time risk control prevention strategy, and executing the strategy.

The invention relates to the technical field of airport noise prediction. The airport noise map isoline calculation method and system based on multi-source data fusion are provided, and the method comprises the following steps: carrying out space-time alignment fusion processing on multi-source heterogeneous data to generate a space-time synchronous standardized data set; processing through a track-noise coupling calculation unit to generate a single event noise value containing a meteorological correction factor; performing dynamic gridding accumulation calculation processing on the single event noise value to generate a noise evaluation quantity grid matrix with a time stamp; processing is carried out through a curvature-driven adaptive contour line generation unit, and a fidelity-optimized noise contour map is generated; and selecting a real-time lightweight channel or a distributed batch processing channel for processing based on the calculation mode decision-making unit, and outputting a noise contour map with optimized fidelity, so as to achieve the technical effects of improving noise positioning precision, reducing modeling errors in a dynamic flight environment and improving the fidelity of geographic features of contour lines.

A computer-implemented method for predicting the operating time until a failure state of a system (140), wherein the computer-implemented method comprises: Receiving a plurality of historical image pairs of a system (140), such as image pairs of a failure state of the system (140), by one or more processors (304), wherein each image pair contains an infrared image and a corresponding normal image; Receiving an initial model by the one or more processors (304), which is trained to reconstruct each image pair of the system (140) in a functioning state (120) of the system (140);Generating a similarity coefficient between each historical image pair and a reconstruction of the historical image pair by the first model for the plurality of historical image pairs by the one or more processors (304), wherein the historical image pair contains a timestamp of a capture of the historical image pair; Receiving a second model by the one or more processors (304), which is trained to predict, based on the similarity coefficients and a timestamp of a capture of the plurality of historical image pairs, an operating time until a failure condition of the system (140) occurs;In response to receiving a real-time image pair of the system (140), the one or more processors (304) generate real-time similarity coefficients between the real-time image pair and the real-time image pair reconstructed by the first model, wherein the real-time image pair contains a timestamp of the acquisition of the real-time image pair; and the one or more processors (304) calculate a predicted operating time until the failure state of the system (140) based on a correlation between the similarity coefficients of the real-time image pair and the timestamp of the acquisition of the real-time image pair and a historical image pair from the plurality of historical image pairs with corresponding similarity coefficients and a time delta determined from the timestamp of the acquisition of the real-time image pair and a timestamp of the failure state of the system (140) after the historical image pair with the corresponding similarity coefficients.

The invention discloses an old building reconstruction design method and system based on BIM and real-time monitoring, and relates to the field of old building reconstruction design, and the technical scheme is that the method comprises the steps: constructing a three-dimensional observation environment, carrying out the multi-stage three-dimensional collection of a to-be-reconstructed building, and obtaining observation data with unified coordinates and time stamps; performing stage comparative analysis on the observation data, and performing space matching and data integration under BIM constraint to form three-dimensional time sequence information oriented to each building component; based on the three-dimensional time sequence information, establishing a historical memory model under component identifiers of the BIM model, and extracting a time sequence evolution rule of deviation and defects of each component; and according to a time sequence evolution rule, establishing a transformation evaluation model, comprehensively analyzing the safety, durability and use functions of each component of the building, and generating a transformation design scheme. The method has the beneficial effects that through multi-period three-dimensional acquisition and BIM fusion analysis, the whole-process datamation and intelligent management of old buildings from state monitoring to reconstruction design is realized.

The invention relates to the technical field of radio positioning, in particular to a helicopter emergency rescue positioning method and system, and the method comprises the following steps: a ground base station captures an initial positioning signal sent by a helicopter in a rescue area, binds the timestamp of the signal with signal data, and analyzes the correlation between the data and time, thereby obtaining a positioning result; signal time stamp data is generated. According to the method and the device, the signal quality is optimized and the stability and the reliability of the signal in an interference environment are enhanced by utilizing time axis inversion and signal amplitude adjustment, and the loss can be reduced, the transmission effect of the signal can be optimized and the overall receiving efficiency of the signal can be improved in a transmission process through encoding processing and signal inversion; the ground base station uses the signal propagation time difference and the path change data to carry out multiple times of comparison and calculate the position of the helicopter in real time, so that the accuracy and efficiency of rescue positioning are remarkably improved, a target is quickly and accurately positioned in emergency rescue, and the success rate and safety of rescue are improved.

The invention discloses an intelligent low-carbon service model and method based on block chain fusion, particularly relates to the technical field of low-carbon management, and is used for solving the problem that the credible recognition and settlement of carbon behaviors are not clear. According to the method, identity verification, time marking and caliber standardization are carried out on energy consumption and travel multi-source data through a trusted data gateway, a carbon behavior voucher containing a signature and an abstract is generated, minimum disclosure under an index upper chain and an original text chain is adopted, it is ensured that the source and the caliber are verifiable and cannot be tampered, and then merging is carried out through a unified event model; and performing conflict resolution and consistency verification to form a one-event one-key event, attaching a consistency label and a credibility index, performing calculation by a rule base and a scene parameter set, performing intelligent contract accounting, and providing rollback correction by using a unique identifier of the event, enabling the credibility index to participate in integral and right confirmation, performing low-credibility entering and re-verification, and suppressing abnormities. And the fusion accuracy and the auditing efficiency are improved.

The invention discloses a radon measurement method based on time stamp background deduction, and the method comprises the steps: recording an average count value per second and an end moment when the last measurement is finished when the last measurement is finished; otherwise, recording the average count value per second from which the background is not deducted as 0, and taking the ending moment as the starting moment of the measurement; after the measurement is started, recording moments according to seconds, and calculating background counts needing to be deducted at each moment; after the measurement is finished, adding the background counts which need to be deducted and are calculated at each second moment in the measurement to obtain a total background count; subtracting the total background count of the previous step from the total count of the measurement to obtain a deducted total count; dividing the deducted total count by the second number of the measurement time, and multiplying by the calibrated efficiency coefficient of the instrument to obtain the deducted real radon concentration. According to the method, the next measurement is directly carried out under the condition of decay interference in the previous measurement, so that a real result can be restored, the purification waiting time is canceled, and the working efficiency is improved.

A system for accurate geospatial location and time transfer using radio transmissions without satellite signals. A position and timing measurement system uses standard uncorrelated radio broadcast signals, each of which transmits on an assigned frequency from a known position defined in latitude and longitude, and each of which transmits a modulated or unmodulated carrier signal. A reference unit at known fixed position receives the said standard broadcast signals in the vicinity, samples the frequencies and content values of their signals and broadcasts the said measured frequency and content data nearly simultaneously with a time mark representing the time of said measurement and further broadcasts its position in latitude and longitude. A mobile unit at an unknown position to be determined receives the said standard broadcast signals in the vicinity and measures the time of arrival of their broadcast, recording the time of said measurement.

The invention discloses a hospital examination and inspection result sharing method based on big data, and relates to the technical field of hospital examination and inspection result sharing. Examination data and inspection data are respectively stored in independent databases, and the two types of data are intelligently linked by using a unique identity label of a patient and a time stamp; the format, the time sequence and the semantic information are accurately matched to form a continuous and visual comprehensive disease course record; introducing a deep learning model, carrying out natural language processing on an unstructured text in the inspection data, and automatically converting an image description and a diagnosis report into structured data and a predefined semantic tag; according to the method, the workload of manual structuring is reduced, distributed storage, dynamic updating and multi-dimensional index query modules are constructed based on a big data analysis platform, real-time retrieval and joint query are conducted on comprehensive disease course data records, meanwhile, an early warning report is generated through an anomaly detection algorithm, and a basis is provided for clinical decision making.

Trajectory Determination Device The invention relates to a trajectory determination device arranged to receive signaling events from a mobile or wireless telephone network, each comprising a mobile communication device identifier, a time marker, and a signaling identifier associated with a location and a location radius, and to return trajectory data comprising trajectory segments, each segment comprising two time markers forming boundary markers derived from the time markers of the signaling events, each segment being associated with a movement or stop type label. Fig. 1

The application discloses a construction quality data management and scheduling system based on PCTC roll-on / roll-off ship deck flatness, which comprises a data access unit, an association construction unit, a state analysis unit and a management and scheduling unit. The data access unit is used for uniformly marking and format-converting deck flatness measurement data, construction process parameters and segmented space position information of each working procedure, forming structured precision data with time markers and space coordinates and storing the structured precision data into a precision database. The association construction unit is used for associating and mapping the structured precision data based on segmented assembly relationships and construction sequences, and constructing a precision association data set. The state analysis unit is used for associating and analyzing flatness deviation and grading based on segmented closing sequences and vehicle deck interlayer relationships, and generating quality evaluation indexes. The management and scheduling unit is used for generating working procedure scheduling schemes, resource allocation schemes and quality management and control decisions based on the quality evaluation indexes and construction resource constraint conditions, and realizing dynamic optimization and quality tracing of the construction process, so as to improve deck flatness control level and construction management efficiency.

The application relates to the field of oral medicine diagnosis and discloses an AI-enhanced real-time occlusion detection system based on intraoral images, which comprises a multi-source intraoral image acquisition module, which is used for acquiring dynamic oral image data through a high-definition oral endoscope, recording the three-dimensional structure of a tooth surface in combination with a laser scanning device, and collecting the force distribution of an occlusion contact point through a pressure sensor array; the multi-source intraoral image acquisition module comprises a time stamp synchronization unit, which performs multi-source synchronization on the oral image frame sequence and the occlusion force distribution data by using a unified time mark; through the multi-source intraoral image acquisition module, the synchronous acquisition of dynamic images, three-dimensional structure data and occlusion force distribution is realized, and the time sequence consistency of the data is ensured through the time stamp mark. Compared with the acquisition mode of a traditional single data source, multi-source acquisition can comprehensively record the dynamic characteristics in the occlusion process, provide rich and accurate input for subsequent AI analysis, and avoid data omission or acquisition deviation.

The invention discloses a three-spot welding dynamic imaging stabilization detection method based on motion compensation modeling, and relates to the technical field of photovoltaic energy monitoring, and the method comprises the following steps: obtaining an acoustic vibration signal, a picture time marking signal and a jig lifting displacement signal of the whole jacking process of a compressor shell, carrying out the time synchronization and feature fusion of the obtained signals, and carrying out the feature fusion of the obtained signals; and generating a resonance distribution band for constructing a dynamic reference model for subsequent time sequence analysis. According to the invention, through multi-source signal synchronous modeling and light machine closed-loop regulation and control, millisecond-level consistency of a jacking action and an imaging process is realized. Exposure and vibration phases are accurately controlled through staggered anchor points, a drift sketch, a baseline ring and an alignment key, pixel drift and brightness fluctuation are remarkably reduced, the detection false alarm rate and the detection omission rate are reduced by 73% and 67% respectively, and high precision and high stability of three-spot welding dynamic detection are achieved.