22results about How to "Avoid covering up" patented technology

The application discloses a kind of ball grid array package chip solder ball bubble defect automatic detection method and system, it is related to chip intelligent detection technical field, the method is guided by designing semantic cross-layer fusion framework, realizes multi-scale feature balanced fusion in neck network by introducing feature alignment and redistribution module, strengthens small target details and semantic information using local semantic enhancement module, and the positioning accuracy of bubble is optimized in combination with smooth geometry positioning loss function.The application significantly improves the detection capability of small, fuzzy and occluded bubbles, has strong robustness and generalization, and can be widely used in solder ball bubble, material porosity and surface defect industrial vision detection scene.

The invention discloses a multi-mode signal real-time self-adaptive recognition and extraction method for a complex scene, solves the problem that an existing interference suppression and signal extraction algorithm cannot adapt to gravitational wave measurement requirements, belongs to the technical field of digital signal processing, and adopts a fixed sequence of main carrier clock sideband pseudo code signals to perform signal extraction and separation. According to the sequence, the processing efficiency is optimized, the weak signal is prevented from being covered by the strong signal, and the interference of subsequent processing is remarkably reduced. Compared with parallel or disordered processing in the background technology, the method provided by the invention has the advantages that strong interference components are stripped in sequence, so that rapid convergence in real-time operation is ensured, and the robustness and precision of overall signal extraction are improved.

The application provides a power distribution network fault abnormality monitoring and early warning method based on multi-source operation data fusion, and relates to the technical field of power system distribution network fault monitoring and early warning. The application obtains distribution network equipment operation data, defect abnormality data, equipment abnormality data, heavy overload data, low voltage data and three-phase imbalance data in a marketing system, a production system, a safety monitoring system and a dispatching system, forms multi-source abnormality data, classifies and aggregates the multi-source abnormality data according to line area, abnormality type and collection time, and performs same-source deduplication and cross-source merging to obtain fused abnormality data, analyzes and processes the fused abnormality data, identifies data representing distribution network fault abnormality and generates a fault abnormality event, and then determines a responsible unit and a line area person in charge according to the corresponding relationship between the line area and the person in charge and dispatches them, so that the monitoring and early warning of the distribution network fault abnormality are realized, and the pertinence and accuracy of the monitoring and early warning are improved.

The application discloses an audio coding model construction method, device and equipment. The method includes the following steps: constructing a network structure of an audio coding model adopting a dynamic frame frequency mechanism; learning network parameters of the model from audio training data; dividing a multi-level residual vector quantizer related to acoustic characteristics in the model into multiple quantizer groups; obtaining audio training data of different frequency bands corresponding to different quantizer groups; and adjusting network parameters of the quantizer groups according to the audio training data of the frequency bands corresponding to the quantizer groups. By using this processing method, different frequency band-specific quantization optimization strategies are adopted for acoustic characteristics of different frequency bands in the case of dynamic frame rate, dynamic frame rate and frequency band reconstruction are coordinated, and low-frequency energy of an audio signal is prevented from covering high-frequency details when the dynamic frame rate is low; therefore, the full-band reconstruction quality is effectively ensured to be uniform, and the audio reconstruction quality is improved.

The invention relates to the technical field of traditional Chinese medicine pharmacy, in particular to a preparation method and a fingerprint spectrum method of a maxingshigan pill. The method comprises the following steps: decocting and extracting semen armeniacae amarae for at least two times, and combining the obtained extracting solutions to serve as a liquid-phase component for pelleting; performing low-temperature drying and crushing on the bitter apricot kernel dregs to obtain bitter apricot kernel dreg powder, and mixing the bitter apricot kernel dreg powder with a gallnut extract to obtain bitter apricot kernel functional powder; weighing ephedra, liquorice and gypsum according to the formula ratio, crushing, and mixing with the bitter apricot kernel functional powder to obtain composite powder for pelleting; dividing the semen armeniacae amarae extracting solution into a first liquid phase for nucleation and a second liquid phase for pill growth to form a primary pill core, and gradually growing the primary pill core to form a pill body; and after the pill body reaches a preset particle size, carrying out surface shaping on the pill body, and drying at 60 DEG C for 3 hours to obtain a finished product of the Maxingshigan pill. According to the invention, efficient, stable and high-quality preparation of the maxingshigan pill is realized.

This invention provides a fully automatic sock inspection and sorting machine, including a frame. A sock-supporting rotating assembly is mounted on the frame to open the heel of the sock and rotate it 360° horizontally. A detection component is mounted on the side of the sock-supporting rotating assembly. The detection component includes a detection module for acquiring image information of the sock heel at a first height and a first tilt angle, and at a second height and a second tilt angle, for defect detection. This invention utilizes the sock-supporting rotating assembly to open the heel of the sock, while the detection component can adjust its height and tilt angle, thereby achieving defect detection of both the sock leg and the heel, further improving detection accuracy. Furthermore, by dividing the sock into upper and lower parts for inspection, the influence of sock length on the detection results is reduced.

The application discloses an unmanned aerial vehicle (UAV) measurement system for highway subgrade bearing capacity, and particularly relates to the technical field of highway engineering detection, which generates an initial measurement path and a measurement point layout scheme through task planning, drives the UAV to complete measurement data and spatial position acquisition, aligns and analyzes the measurement data with a reference pavement model, divides sub-road sections along the direction of the subgrade, further generates structure deformation and measurement reliability evaluation factors for each sub-road section, then determines the distribution density of the measurement points, and adjusts the initial measurement path accordingly to form a measurement path planning that matches the state characteristics of different sub-road sections of the subgrade. The application improves the coverage integrity through path planning and measurement point layout, depicts the differences between the subgrades through segmented analysis, realizes targeted measurement by determining the density of the measurement points and adjusting the path, improves the accuracy of bearing capacity evaluation, reduces redundant operations, improves the efficiency and reliability, and supports the optimization of the level of engineering application and decision-making ability.

This invention discloses a gas pipeline leak detection method based on the random forest algorithm, relating to the field of gas leak detection. The invention first collects and preprocesses monitoring data from combustible gas sensors in the gas pipeline, then extracts features from the preprocessed data and assigns classification labels based on actual leak conditions, constructing a gas pipeline leak detection dataset. Using this dataset as training samples, a model is trained based on the random forest algorithm to obtain a gas pipeline leak detection classification model. Finally, real-time monitoring data from each combustible gas sensor during gas pipeline operation is input into the trained classification model, and the pipeline leak status is determined based on the model's output. This invention, through standardized data preprocessing, feature engineering, model training, and parameter optimization processes, can achieve accurate identification and early warning of gas pipeline leak status, effectively improving the accuracy and efficiency of leak detection.

This invention discloses an in-vehicle selective noise reduction method based on sound field reconstruction, relating to the field of in-vehicle safety warning technology. The method includes: collaboratively collecting in-vehicle acoustic and vibration data through sensors; separating the acoustic and vibration data using a blind source separation algorithm to obtain a voiceprint feature tensor; inputting the voiceprint feature tensor into a convolutional neural network for voiceprint recognition, outputting a safety sound category and a safety sound hazard level; generating adaptive noise reduction parameters based on vehicle speed and safety sound category; assigning the final adaptive noise reduction parameters to seats in different regions; and issuing a physical vibration warning based on the safety sound hazard level to complete the in-vehicle selective noise reduction. This invention significantly improves the detection and recognition accuracy of critical safety sounds in road noise environments; it balances noise suppression and active safety assurance, effectively enhancing the vehicle's perception and response capabilities to emergency sound sources while improving passenger comfort.

The application discloses a kind of engineering cost auditing method and system based on multi-source data fusion.Belongs to the field of engineering cost auditing, the present application obtains the engineering quantity list of the engineering to be audited, construction site space-time image and construction log text data, input model trained by multi-modal data, generates cost declaration and physical live characteristic vector, then calculates correlation score and extracts empirical segment features, and with cost declaration features fusion generates semantic fusion feature matrix;Finally, identify sub-item engineering category, calculate its Mahalanobis distance with process feature prototype vector, if exceed threshold value, then determine abnormal, generate the audit result containing abnormal cost item and construction period lack of empirical information.The present application effectively solves the problem that existing technology cannot accurately and efficiently audit engineering cost.

The invention discloses a nonmetal pipeline detection positioning device, method and system, and the positioning device integrates a sound generation device, a sound pickup, a main controller and the like through a detection box body, and an operator can carry one detection box body to carry out the detection work of a nonmetal pipeline. The sound generating device and the sound pick-up are used in cooperation, the position of the non-metal pipeline can be accurately determined by emitting the sound with the specific frequency and receiving the echo generated after the sound is transmitted in the non-metal pipeline, and the mode based on sound transmission is not limited by the non-conductive and non-magnetic characteristics of the non-metal pipeline; and the problem of non-metal pipeline detection can be effectively solved. The display device is installed on the detection box body and can display the position information of the nonmetal pipeline in real time. The main controller accurately analyzes and processes sound signals sent by the sound generating device and echo signals received by the sound pick-up, specific signals related to the non-metal pipeline are extracted, and the detection accuracy is improved.

The power battery thermal runaway risk early warning method, device, equipment and storage medium extract a plurality of continuous charging segments from original charging data, and then organize them into a two-dimensional time sequence structure including intra-period and inter-period two dimensions, which can simultaneously carry single charging time sequence details and multi-period state evolution law, breaking through the limitations of single charging period analysis. Then, the low-frequency trend and high-frequency abnormal component are decomposed by two-dimensional discrete wavelet transform to realize explicit decoupling of degradation trend and abnormal disturbance, avoid early abnormalities being covered, and finally output early warning results by a thermal runaway risk identification model based on a plurality of groups of frequency band subbands corresponding to each feature channel. Early hidden signs can be captured from multiple time scales, effectively improving early warning lead time and recognition accuracy, and reducing the risk of misjudgment caused by working condition fluctuations.

This invention relates to the fields of fragrance and flavor analysis and artificial intelligence technology, and discloses a method for rapid analysis of the key aroma components of iris essential oil using artificial intelligence. The method acquires gas chromatography-mass spectrometry (GC-MS) data of iris essential oil, constructs compound feature vectors using an aroma knowledge base, calculates the overall aroma contribution value using an artificial intelligence fusion model, and stratifies the core components, auxiliary components, and modifying components. Simultaneously, it outputs recommended proportion ranges for aroma reconstruction. This method can be used for key aroma identification, aroma reconstruction, and fragrance design assistance in natural essential oils.

This application relates to the technical field of fire safety assessment, and discloses a multi-dimensional dynamic assessment method for building fire safety based on the Internet of Things (IoT). Addressing the shortcomings of traditional assessment methods, which rely on manual inspections, cannot capture dynamic risks, and have limited dimensions, this application continuously collects event stream data generated by fire IoT sensors. It extracts characteristic indicators from these data across three dimensions: the operational status of fire protection facilities, maintenance compliance, and the standardization of fire safety management. Dimensional assessment values ​​are calculated for each dimension, followed by safety baseline constraint judgment, weighted aggregation, and correction of the building's inherent risk coefficient. The resulting comprehensive assessment value and differentiated rectification strategies are then dynamically updated according to a preset cycle. This method can automatically identify silent fault detectors, track the degradation trend of linkage links, and accurately determine the physical state of control valves through cross-subsystem verification. Simultaneously, it avoids masking weak points with a single comprehensive score, thereby achieving continuous, multi-dimensional, and quantitative assessment of fire safety.

The invention relates to an application of allicin in food preservation, belongs to the technical field of food preservation, and discloses a pH response type microcapsule for applying allicin to food preservation, and the microcapsule has a core-shell structure; wherein the inner core comprises allicin; the shell layer is a pH-sensitive polymer shell layer and is configured to be stable when the pH value is lower than 6.0, and the shell layer starts to dissolve and release allicin of the inner core when the pH value is higher than 6.0; a key and measurable chemical signal-surface pH value increase in the decay process of perishable food is used as a triggering condition, limited preservatives are intensively used for inhibiting the most serious decay period, the preservation efficiency is maximized, the situation that excessive allicin covers and interferes with the food flavor in the initial preservation period is avoided, the allicin is only released when necessary, and the food flavor is not influenced. And the sensory acceptance is better.

The present application relates to the technical field of dissolved oxygen monitoring, and specifically relates to a complex water body dissolved oxygen differential monitoring method. Current water area data corresponding to each initial sub-water area in a target water area is obtained, and the current water area data includes current hydrological data, current meteorological data, and current water quality data. Based on the current water area data corresponding to each initial sub-water area, the current target dissolved oxygen corresponding to each initial sub-water area is determined. According to the current target dissolved oxygen corresponding to each initial sub-water area, the preset measures corresponding to each initial sub-water area are determined. The real state of dissolved oxygen in different sub-water areas can be accurately reflected, and the sub-water area level fine calculation of dissolved oxygen is realized. Based on the actual dissolved oxygen state of the initial sub-water area, the differential preset measures are accurately matched, the precise control of "one area one strategy" is realized, and the over-intervention or insufficient intervention caused by undifferentiated control is avoided, and the occurrence of ecological risks such as low dissolved oxygen is effectively prevented.

This invention provides a data analysis-based method and system for compliant registration and identification of tenants in rental properties, relating to the field of data processing technology. The method includes: mapping each behavioral record in each property identifier to a tenant occupancy marker at each time point; constructing a tenant occupancy continuity relationship between adjacent time points; identifying whether each person is stably residing in the rental property, obtaining an occupancy disturbance value; identifying and separating the portion of a person's continuous trajectory belonging to the registered tenant identifier; splicing together the temporally adjacent portions of different people's continuous trajectories with the same tenant identifier; identifying the duration of each person's presence in the rental property, obtaining an occupancy duration value; and filtering out trajectories from unregistered occupancy trajectories where both the occupancy duration value and the occupancy disturbance value meet a preset stability value, thus obtaining differential tenant trajectories. This invention can accurately identify the actual residents of rental properties, avoiding identification errors caused by delayed or incomplete registration information.

This invention discloses an anti-pinch control method for electric seats, specifically relating to the field of automotive seat anti-pinch control technology. The method determines the coupling relationship between the current direction of motion and the direction of gravity; based on this coupling relationship, it acquires real-time load data in the current direction of motion and historical load data in the corresponding reverse direction of motion, and determines the asymmetric characteristics of the attitude load in the opposite direction; it constructs forward and reverse load change trajectories and extracts load continuity features, directional offset features, and local abrupt change features; based on the coupling relationship, the asymmetric characteristics of the attitude load in the opposite direction, the load continuity features, the directional offset features, and the local abrupt change features, it determines whether the current load change belongs to an attitude-gravity coupled load change or an abnormal clamping load change, and executes corresponding control. This invention can distinguish between gravity load offset caused by attitude changes and abnormal clamping load changes, improving the accuracy of anti-pinch control under complex attitude conditions.

The present application relates to the technical field of biomass gas utilization, and particularly relates to a biomass gas coupling unit optimization control method and system based on digital twinning, the method comprising: obtaining operation data of a biomass gas coupling gas turbine unit after entering a stable operation interval in a historical operation process, obtaining an original data set, based on the operation data, screening the collected original data set, eliminating data interference in start-stop and load mutation stages, forming an effective operation data set, based on the effective operation data set, constructing effective response training data, forming a training data set, and training a gas supply flow machine learning model. The present application selects only operation data of the gas turbine unit after entering the stable operation interval, and introduces a synchronous collection mechanism of the speed maintaining state and the output power, so that the formed data set can truly reflect actual response characteristics of the gas turbine to the gas quality and the gas supply capacity under the continuous stable working condition.

This invention relates to the field of computer technology and discloses a personnel allocation decision-making method, system, electronic device, and storage medium based on working hour data. The method includes acquiring working hour data, classifying and structuring it, and performing multi-dimensional statistical analysis on the classified working hour data to generate a working hour distribution map; calculating the maximum number of personnel at full capacity based on the total annual working hour demand and the standard working hours available per person per year; acquiring data on the difference between actual working hours and statutory standard working hours, as well as unused leave, and calculating the equivalent personnel shortage based on an overtime compensation model; establishing a resource balance model that includes constraints such as shift work, skill level matching, time period distribution, and management redundancy, calculating the resource balance coefficient, and correcting the maximum number of personnel at full capacity to obtain an executable personnel allocation base; and determining the personnel allocation plan by combining the equivalent personnel shortage, the personnel allocation base, and future working hour demand. This invention can improve the executability of personnel allocation decisions.

The application discloses a zero-carbon park inter-energy fusion-oriented charging load and industrial load collaborative optimization method, relates to the technical field of energy internet and power system optimization control, acquires park multi-source data, constructs a double-network model of a traffic network and a power distribution network, and takes a charging station as a shared node; a site side and a power grid side risk field is inferred based on a space-time graph neural network; an inter-energy consistency checker IEC is constructed to generate a zero setting gate matrix to form a feasible candidate set; a multi-objective mixed integer programming collaborative scheduling model is solved under the constraint of the feasible candidate set, a bilateral trigger type safety valve slack variable is introduced to generate a bottleneck evidence bag; a key bottleneck object set is determined based on a constraint shadow price distribution and a zero setting ratio distribution, an expansion candidate set is generated, an evidence chain expansion planning model is constructed to obtain an expansion scheme, a feasible region improvement constraint judgment is executed, and rewriting is performed into rolling optimization.

The application discloses a kind of soil microplastic detection method, device, equipment and medium, comprising: obtaining several soil samples in target area, and determine the soil parameters of soil sample;According to the soil parameters, the target area is divided, and first area and second area are obtained;The soil sample of first area is pretreated, and microplastic sample is obtained;The microplastic sample is analyzed, and the microplastic parameter corresponding to the microplastic sample is obtained;According to the microplastic parameter, determine the migration risk;According to the migration risk and the area of first area, determine the detection interval period of the soil microplastic of target area.The application belongs to the field of microplastic detection.The application can accurately determine the microplastic detection period.