1445results about How to "Guaranteed smoothness" patented technology

The invention provides a big data platform scheduling task and data collaborative smooth migration method and system, and relates to the technical field of big data, and the method comprises the steps: constructing a digital twin environment of a target system, collecting task operation state data of a source system, extracting task features through a deep neural network, and carrying out the clustering and grouping. And deploying the task group to a digital twin environment, analyzing a task association relationship and a resource competition relationship based on a graph neural network, and generating a task stability score in combination with a task operation index. And constructing a migration risk prediction model to perform quantitative evaluation on the migration risk, and determining a migration priority and an execution sequence according to the quantitative evaluation. And making corresponding resource configuration, data synchronization and fault recovery plans for each task group, carrying out migration drilling in a digital twinning environment, and optimizing a migration scheme by utilizing a reinforcement learning algorithm. The migration risk can be effectively reduced, the smoothness and stability of the migration process are guaranteed, and the migration efficiency is improved.

The invention provides a private domain live broadcast data storage and visitor authentication method and system based on a block chain, and relates to the technical field of data storage and access control, and the method comprises the steps: collecting multi-mode biological characteristic data of a visitor, carrying out the feature extraction and fusion through a deep neural network of a space-time attention mechanism, and carrying out the authentication of the visitor; authenticity verification is carried out in combination with an adversarial generative network, a dynamic identity token is generated, and a hash value of the dynamic identity token is written into the block chain. The method comprises the following steps: performing semantic analysis on live broadcast data flow through a self-adaptive content perception model, constructing a double-layer access control matrix according to a data sensitivity level and a credibility score, performing self-adaptive fragmentation and hierarchical encryption based on federated learning, and then storing. After an access request is subjected to identity verification, an optimal edge node is selected according to access authority and network performance parameters to construct multi-path transmission, and a transmission strategy is generated based on a service quality score and a data sensitivity level. And when the service quality is lower than a threshold value, triggering the smart contract to perform fault migration.

The invention discloses a road traffic signal control system and method, and the method comprises the steps: collecting real-time data through a sensor, a camera and a geomagnetic device, combining historical data with emergency analysis, and predicting a flow mode and a change trend; green light time distribution is dynamically optimized, a fixed timing, inductive and adaptive control strategy is adopted, and traffic light duration and priority adjustment is achieved; through regional cooperation and linkage control, green wave bands and branch intersection red light optimization are set, and peak period traffic signals are intelligently dispatched. A machine learning model is used to predict a flow peak value, environment and accident detection data are combined, a signal lamp period is dynamically adjusted, vehicle waiting time, traffic efficiency, carbon emission and traffic satisfaction are evaluated, and a traffic control strategy is comprehensively optimized. According to the road traffic signal control system and method, the traffic flow in different time periods is predicted by adopting the flow prediction model based on big data analysis and machine learning, and the signal period is adjusted in advance.

The invention relates to the technical field of data desensitization, in particular to an electronic commerce platform information security desensitization scheme analysis system based on artificial intelligence, which comprises a data classification module, an access evaluation module, a dynamic desensitization module and a security audit module. According to the method, the data of the e-commerce platform is intelligently classified and evaluated by adopting an artificial intelligence technology, dynamic desensitization and finer access control of the data are realized, various data access requirements can be dynamically met by evaluating the sensitivity level of the file and the security level of the access request, data processing is performed according to requirements, and the data processing efficiency is improved. The security and privacy of user data are effectively protected, through automation of security audit, the recognition efficiency of abnormal behaviors is improved, the transparency and traceability of overall data management are enhanced, through real-time analysis and response, the risk of data leakage is reduced, and the practical value of data and the fluency of service operation are kept.

The invention provides a lithium battery hybrid power motorcycle performance improvement control strategy generation method, which comprises the steps that vehicle driving states comprise a sliding state and a braking state, if the current vehicle is in the sliding state, a preset sliding energy recovery mode is activated, and if the current vehicle is in the braking state, a preset braking energy recovery mode is activated; different energy recovery strategies are combined and optimized according to the subdivision result of the energy recovery strategies in the sliding state and the braking state, and the vehicle speed, the battery charging state and the energy recovery potential value parameters are input to obtain a target energy recovery strategy combination scheme; the intention of acceleration, deceleration or constant speed of a driver is judged according to the operation characteristics of an accelerator and a brake, the operation characteristics refer to the force of stepping on an accelerator pedal and a brake pedal, and the driver intention obtained through judgment serves as the basis for dynamic adjustment of the energy recovery strategy.

The invention relates to the technical field of multimedia interaction, in particular to an intelligent interaction control method and system for digital exhibition hall multimedia equipment, and the method comprises the following steps: S1, carrying out the arrangement of a sensor, and carrying out the intelligent sensing and data collection; s2, generating an intelligent interaction strategy; s3, equipment cooperative control and execution; and S4, performing real-time feedback and system optimization. According to the method, user behaviors and environment data are collected in real time through the multi-modal sensor, user requirements are accurately speculated in combination with a deep learning algorithm, the optimal interaction strategy and task priority are generated, individuation and interaction efficiency of user experience are remarkably improved, multi-device cooperation is optimized through distributed task scheduling, and user experience is improved. According to the method, display content and environment parameters are dynamically adjusted, self-optimization of the system is realized by utilizing user feedback, real-time performance, smoothness and reliability of interactive experience of the exhibition hall are ensured, rapid fault response and accurate maintenance demand prediction are realized through anomaly detection and equipment log analysis, and the stability and sustainability of operation of the exhibition hall system are greatly improved.

The invention discloses a holographic display digital human speech recognition enhancement method based on multi-modal interactive learning, and the method comprises the following steps: S1, collecting and preprocessing data, and generating a multi-modal feature matrix; s2, inputting the multi-modal feature matrix into a self-adaptive multi-modal interaction kernel to generate multi-modal interaction features; s3, inputting the multi-modal interaction features into an emotion convolution block to generate semantic-emotion mapping features; s4, inputting the semantic-emotion mapping features into a cross attention generator, and outputting multi-modal fusion features; s5, inputting the multi-modal fusion features into a multi-modal fusion-decomposition two-way network, and generating multi-modal features after decoupling optimization; s6, inputting the multi-modal features into a holographic-speech symbiosis optimization module to generate speech recognition and holographic display data; and S7, performing parameter optimization by applying self-supervised learning and comparative learning strategies to realize self-adaptive adjustment. According to the invention, the enhancement of holographic display digital human speech recognition is realized by using a multi-mode interactive learning method.

The invention relates to the technical field of e-commerce intelligent recommendation, in particular to an e-commerce intelligent recommendation system based on user behavior big data, which comprises a data acquisition and storage unit, a data preprocessing unit, a model construction training unit and a recommendation generation and output unit. The method comprises the steps that data such as user behaviors, equipment, geographic positions and access time are collected and stored in a distributed database, a data preprocessing unit extracts the data, constructs a user behavior sequence and encodes commodity and behavior characteristics, and a model construction training unit obtains user interest vectors by using a long and short-term memory network in combination with an attention mechanism; model parameters are updated with the help of a deep Q network, commodities are screened, sorted and displayed by a recommendation generation and output unit according to interest vectors, meanwhile, a feedback optimization system is collected, recommendation accuracy is improved, user shopping experience is enhanced, and an e-commerce platform is assisted to improve operation efficiency and commodity sales conversion rate.

The invention provides a cross-platform low-code application development system based on a Flutter framework. Comprising a login registration module, a project management module, an interface design module, a state management module, a route management module, a team management module, a help document module, an AI page design module, a development document generation module, a hardware integration module, a code generation module, a multi-user collaborative development module, a communication module, an online simulator module, an AI generation application module and an interface management module. An asset management module, a developer forum module, an application market module and an application packaging module. The communication module supports various communication protocols and secure transmission modes, and ensures that data exchange applied to cross-platform and cross-system environments is secure and reliable. Through component dragging and graphical configuration, the low-code platform automatically analyzes configuration data to generate an App, a development document and a source code. And meanwhile, multi-person collaborative development is supported, so that the development threshold is reduced and the development speed is increased.

The invention relates to the technical field of artificial intelligence and the field of financial science and technology, and discloses a text-to-video method based on deep semantic analysis, which comprises the following steps of: extracting keywords and named entities from a to-be-converted text, analyzing a core theme and a text structure of the text, and performing semantic analysis to generate a semantic analysis result; retrieving matched images, video clips, sound effects and background music according to a semantic analysis result, and performing spatial layout to generate a preliminary visual layout framework; and constructing a video timeline, integrating the layout scheme, the background music and the sound effect to generate a complete video content, and finally outputting the video content as a video file. Keywords, named entities, core topics and text structures in texts are accurately extracted through semantic analysis, images, video clips, sound effects and background music conforming to semantics are intelligently matched, and the problem that a large amount of manual intervention is needed is avoided. An adaptive animation effect is generated through a deep learning model, and dynamic presentation of video content and continuity of a visual effect are ensured.

The embodiment of the invention discloses a database migration method and device for a heterogeneous database and a medium, and relates to the technical field of database migration, the method comprises the steps that database migration demand information is acquired, and the database migration demand information comprises current service information, target migration database information and source database information; automatically migrating the data table structure and the business data according to the database migration demand information, extracting SQL statements based on the source database information, and determining a plurality of original SQL statements of the source database; based on the target migration database information, determining current statement rule information, performing rule matching check on the original SQL statement according to the current statement rule information, determining a plurality of risk SQL statements, and generating a migration compatibility evaluation set; and generating a migration compatibility optimization reference file through the migration compatibility evaluation set, and realizing database migration of the source database and the target migration database based on the migration compatibility optimization reference file.

The invention relates to an automatic driving vehicle obstacle avoidance method and device based on TransFormer-APF-MPC and a medium, and the method comprises the following steps: obtaining pedestrian motion data and interaction scene data in real time, inputting the pedestrian motion data and the interaction scene data into an automatic driving vehicle obstacle avoidance network based on TransFormer-APF-MPC, and outputting an automatic driving vehicle obstacle avoidance scheme; the automatic driving vehicle obstacle avoidance network based on the TransFormer-APF-MPC comprises a TransFormer model and an APF-MPC obstacle avoidance model, the TransFormer model is used for predicting pedestrian trajectories according to input data, the APF-MPC obstacle avoidance model comprises a path planning layer and a trajectory tracking layer, the path planning layer is used for generating an optimal obstacle avoidance path by improving an artificial potential field method, and the trajectory tracking layer is used for tracking the optimal obstacle avoidance path. According to the improved artificial potential field method, the repulsive force between the vehicle and the obstacle and the gravitational force between the vehicle and the target point are calculated according to the improved repulsive force constant function with the adjustment factor introduced; and the trajectory tracking layer is used for calculating a vehicle control instruction through a model prediction control method, so that the vehicle runs along the optimal obstacle avoidance path. Compared with the prior art, the real-time obstacle avoidance planning and control of the vehicle can be better realized.

The invention relates to the technical field of signal processing, in particular to an unmanned aerial vehicle self-noise filtering method and system based on multichannel time-frequency spatial filtering. The method comprises the following steps: acquiring a multi-channel noise-containing sound signal by using a microphone array carried by an unmanned aerial vehicle, and performing short-time Fourier transform to obtain a frequency domain signal; estimating a ratio mask by using a deep neural network, and performing logarithm normalization processing on the frequency domain signal; remodeling the sound signal to match the FFT length of the time-frequency spatial filter, and constructing the time-frequency spatial filter in combination with the multi-channel ratio mask; removing the self-noise of the unmanned aerial vehicle by using the filter and obtaining a target sound signal; and finally, converting the frequency domain signal into a time domain signal through inverse short-time Fourier transform. Through innovative fusion of multi-channel acquisition, deep learning and time-frequency space filtering, the self-noise of the unmanned aerial vehicle in a complex environment is accurately filtered, and the accuracy and efficiency of transformer substation noise monitoring are remarkably improved. Reliable acoustic data are provided for state monitoring of the power equipment, and the method has important engineering application value.

The invention relates to a low-altitude economic development form analysis method and system based on a high-density city, and the method comprises the steps: obtaining task address information and task type information of each aircraft, and carrying out the path planning in a preset airspace range according to the task address information and the task type information, obtaining flight path information of each aircraft; acquiring real-time traffic flow and airspace condition information in a preset airspace range, and performing real-time optimization adjustment on the flight path information according to the real-time traffic flow and the airspace condition information; monitoring the activities of the aircrafts in the airspace in real time, obtaining the flight information of each aircraft, and judging whether the corresponding aircraft has a flight violation condition or not according to the flight information; the flight task state is tracked and fed back in real time, the aircraft state and the equipment operation condition in the airspace are monitored, equipment alarm is triggered under the abnormal condition, and preset emergency treatment measures are taken. The method has the effect of improving the low-altitude aircraft management and control efficiency.

The invention discloses an LED lamp strip rhythm flickering control method and system, a storage medium and a program product, and the method comprises the steps: calculating a relative entropy value among a high-frequency band, a middle-frequency band and a low-frequency band; establishing an energy flow diagram, and determining a dominant frequency band according to an energy flow topological structure in the energy flow diagram; a phase tracking function is constructed, and hierarchical level division is carried out on the beat mark points; establishing a recursive segmentation window, calculating a spectrum centroid trajectory, and extracting an inflection point sequence; establishing a corresponding relation between the polar coordinate angle and the color parameter of the LED lamp strip and a corresponding relation between the polar radius and the brightness parameter; a spatial propagation mode of the LED lamp strip is designed based on the topological structure of the energy flow diagram, so that the propagation direction of the light effect along the LED lamp strip is kept consistent with the energy flow direction between the frequency bands, and the propagation speed is adjusted according to the energy flow intensity; and generating a driving control sequence of the LED lamp strip according to the gradient function. The emotional progression and tension change of music are captured, and the LED lamp strip is accurately controlled to flicker according to the emotional progression and the tension change.

The utility model discloses a two-shaft mixing pump. The two-shaft mixing pump is characterized by comprising a pump body and two connecting shafts, a roots pump body cavity and a screw pump body cavity which are mutually independent are arranged in the pump body; the pump body is provided with an air inlet, an air outlet and a connecting channel, the roots pump body cavity is communicated with the outside atmosphere through the air inlet, the screw pump body cavity is communicated with the outside atmosphere through the air outlet, and the roots pump body cavity is communicated with the screw pump body cavity through the connecting channel. Two roots rotor parts which are meshed with each other are arranged in a cavity of the roots pump body, and the two roots rotor parts are respectively arranged on the two connecting shafts; and two screw rotor parts which are meshed with each other are arranged in a cavity of the screw pump body, and the two screw rotor parts are respectively mounted on the two connecting shafts. According to the utility model, the occupied space is reduced, the vacuum degree is improved, and the cost is reduced.

The invention relates to a touch all-in-one machine interaction control method and device, computer equipment and a medium, and the method comprises the steps: receiving image data through a preset video stream protocol, and obtaining a corresponding image data stream; acquiring a real-time network bandwidth condition, and then performing adaptive compression processing on the image data stream based on the real-time network bandwidth condition, and dynamically adjusting image transmission parameters; comprehensively analyzing the image data stream by using a deep learning algorithm, extracting operation characteristics of a user, generating an output control instruction based on the operation characteristics, and further controlling and adjusting image display and / or an equipment state; content information is extracted from the image data stream, and content analysis is carried out by adopting a corresponding content analysis strategy according to the content information, so that real-time display and / or storage are / is carried out according to the analyzed content; and obtaining a user interaction behavior, generating a corresponding adjustment feedback instruction based on the user interaction behavior, and performing personalized adjustment on the user interface. The method has the effect of improving the image transmission quality.

The invention discloses a carbon emission data anomaly detection system and method based on event triggering, and the method comprises the steps: S1, collecting the data of a plurality of sensors, and obtaining a carbon emission database; s2, judging whether the sensor is abnormal or not according to the carbon emission database; if yes, obtaining an abnormal sensor and sending an equipment abnormal signal; if not, skipping to S4; s3, predicting a normal value of the abnormal sensor by using a data filling method, and updating the carbon emission database; s4, obtaining the predicted total carbon emission at the current time by using the carbon emission prediction model, and obtaining the actual total carbon emission from the carbon emission database; s5, whether the difference value between the predicted total carbon emission and the actual total carbon emission is larger than a preset difference value threshold value or not is judged; if yes, sending a standard exceeding signal; and if not, sending a normal signal. The invention relates to the technical field of factory carbon emission detection, and solves the technical problems that the data quality accuracy cannot be guaranteed and the data mining of a carbon emission prediction model is single in the existing method.

The invention provides a document question-answering system and method based on a large model, and relates to the technical field of artificial intelligence, and the system comprises a document segmentation module which is used for segmenting a document uploaded by a user according to a paragraph structure to obtain a plurality of paragraph nodes; and the answer generation module is connected with the document segmentation module and is used for performing similarity matching on a query question proposed by a user and each paragraph node and sending the paragraph node with the highest similarity into a local large language model for processing so as to display answer information associated with the query question to the user. The method has the beneficial effects that the document is segmented according to the paragraph structure, so that the related content is effectively prevented from being split into different paragraph nodes, the context continuity is ensured, and the accuracy of a search result is improved; and the answer information is generated by adopting a local large language model, so that data leakage and privacy risks are avoided, and the data security is enhanced while the user privacy is effectively protected.

The invention relates to the technical field of vehicle engineering and automatic control, in particular to an AMPC control method for a hub motor suspension system of an electric vehicle. The method comprises the following steps: S1, obtaining pavement preview information; s2, inputting road excitation in the information into a prediction model, and outputting dynamic response of the hub motor suspension system; s3, generating a control signal based on an adaptive model prediction control method; and S4, adjusting the dynamic response by using a control signal. By means of the method, the hub motor suspension system can perceive the road condition in advance through the road surface preview information, control signals are generated and hub motor input and suspension parameters are adjusted in combination with the AMPC method, the response speed, stability and comfort of the system are improved, and therefore the control requirements under different road conditions are met.

The present invention relates to the field of tire processing technology, in particular to an environmentally friendly processing device for recycling and utilizing waste tire rubber, comprising a crushing box, a first material guide block is provided at the lower left end of the crushing box, a first belt conveyor is provided on the first material guide block, a crushing assembly is provided inside the crushing box, a screening box is provided at the left end of the first belt conveyor, a disc screen assembly is provided inside the screening box, two support blocks are fixedly provided on the outer wall of the screening box in a symmetrical structure, a reflux block is installed at the lower end of the screening box, the reflux block is in an inclined structure, the lower right end of the reflux block is connected to the upper end of the crushing box, a second material guide block is provided at the lower end of the screening box, and a steel wire processing box is provided at one end of the second material guide block. It is convenient to crush and separate steel wire and rubber in waste tires, ensure the efficient separation of steel wire and rubber, improve the processing efficiency and crushing effect of waste rubber tires, improve the quality of recycled rubber, and provide strong technical support for the recycling and utilization of waste tires.

The invention discloses a portable planting machine for corn cultivation, and relates to the technical field of corn planting.The portable planting machine comprises a main body, sliding grooves are symmetrically formed in the upper portion of the main body, the sliding grooves are slidably connected with a supporting plate, and the upper portion of the supporting plate is fixedly connected with a stirring box used for stirring corn seeds and chemical fertilizer; an oscillating mechanism is arranged on the lower portion of the supporting plate and used for preventing materials in the stirring box from being blocked, a flow guide box is fixedly connected to the lower portion of the stirring box, an intermittent discharging mechanism is arranged on the lower portion of the flow guide box and used for intermittently falling corn seeds, and a planting mechanism is arranged on the lower portion of the main body. The sowing spacing of the seeds can be accurately controlled through the intermittent discharging mechanism, and the situation that the seeds compete for nutrients, moisture and illumination due to the fact that the distance between the seeds is too short is avoided, so that it is guaranteed that each corn seedling can obtain sufficient growth resources.

The invention discloses a wind power blade unmanned aerial vehicle inspection method and device, and belongs to the technical field of wind driven generators, and the wind power blade unmanned aerial vehicle inspection method comprises the steps: carrying out the unmanned aerial vehicle inspection of the front surface of a wind power blade to form first inspection information, and carrying out the unmanned aerial vehicle inspection of the back surface of the wind power blade to form second inspection information, the first inspection information comprises a first track point data set and a blade front image set, and the second inspection information comprises a second track point data set and a blade back image set; according to the first inspection information and the second inspection information, in combination with a wind power blade defect judgment condition, obtaining a wind power blade unmanned aerial vehicle inspection result; according to the wind power blade unmanned aerial vehicle inspection result, whether an unmanned aerial vehicle re-inspection mode is started is judged, if yes, the unmanned aerial vehicle re-inspection mode is started, and the wind power blade unmanned aerial vehicle inspection result is updated; and if not, the re-inspection mode is not started. The method can reduce the influence on the wind power plant operation and power generation efficiency, and improves the accuracy of the wind power blade unmanned aerial vehicle inspection result.

The utility model discloses an indexable wave-shaped edge turning blade which comprises a blade body with a center hole in the geometric center, a cutting unit is arranged on the upper surface of the blade body, and the cutting unit comprises an arc edge located at the vertex angle of the blade body and a main cutting edge connected with the two ends of the arc edge. Chip flutes are formed in the main cutting edge in the direction extending towards the center hole, and every two adjacent chip flutes located at the vertex angle are symmetrically separated through an isolation belt; the main cutting edge includes a wave-shaped cutting edge, the wave shape of which is shaped in an axial direction. Through the design of the wave-shaped cutting edges, the chip flutes and the isolation belts, the cutting force is effectively reduced, the chip treatment is improved, the quality of the machined surface is remarkably improved, and the service life of the cutter is remarkably prolonged.

The invention belongs to the technical field of microbial fermentation, and particularly relates to pseudomonas aeruginosa and application thereof. According to the specific technical scheme, the pseudomonas aeruginosa HY-8 is preserved in the Guangdong Microbial Culture Collection Center on October 24, 2024, and the preservation number of the pseudomonas aeruginosa HY-8 is GDMCC (China General Microbiological Culture Collection Center) NO: 65339. The invention provides a strain of pseudomonas aeruginosa which can tolerate high-concentration ethanol and can produce rhamnolipid at high yield. The pseudomonas aeruginosa is used for producing the rhamnolipid through fermentation, and ethanol is added in the fermentation process, so that the problem that a large amount of foam is generated in the fermentation process can be effectively solved, the normal growth of the pseudomonas aeruginosa cannot be influenced, and the continuity and stability of the rhamnolipid produced through fermentation can be ensured, thereby greatly improving the yield of the rhamnolipid produced through fermentation.

The embodiment of the invention relates to the technical field of computers, and discloses an NPC animation effect implementation method and device, a medium and a product. The method comprises the steps of determining a current LOD level of an NPC according to a current distance between the NPC and a player character; determining a target animation scheme according to the current LOD level; the target animation scheme is a CPU animation scheme or a GPU animation scheme; according to the target animation scheme, realizing an animation effect of the NPC; wherein when the current distance is changed and the current LOD level is changed, the target animation scheme can be dynamically switched between the CPU animation scheme and the GPU animation scheme, and the method and the device can be at least used for solving the technical problem that in the related technology, simultaneous presentation of a large number of NPCs and a high-quality presentation effect cannot be achieved.

The invention discloses a CNC machine tool with an anti-jamming servo tailstock, and relates to the technical field of machine tool equipment.The CNC machine tool comprises a workbench, a machine tool body is arranged at the upper end of the workbench, a spindle box is arranged at the upper end of the machine tool body, a chuck is arranged on one side of the spindle box, a fixing plate is arranged in the machine tool body, and a first servo motor is arranged on one side of the machine tool body; the output end of the first servo motor penetrates through the lathe bed and is provided with a lead screw, two supporting guide rods are symmetrically arranged between the fixing plate and the inner surface of one side of the lathe bed, a moving block is arranged on the outer surface of the lead screw, a tailstock sliding saddle is arranged at the upper end of the moving block, and a mounting table is arranged at the upper end of the tailstock sliding saddle. According to the CNC machine tool with the anti-jamming servo tailstock, the rear center can be stably driven to transversely move, impurities on the surfaces of the lead screw and the supporting guide rod can be efficiently cleaned and automatically lubricated during use, the jamming condition is prevented, and meanwhile, the center base body and the rear center can be conveniently disassembled, assembled and replaced.

The invention provides a geological exploration sampling method and sampling equipment based on vibration drilling and obstacle recognition, and belongs to the technical field of geological exploration. The geological exploration sampling method comprises the following steps: 1, starting drilling; 2, switching a vibration mode; 3, obstacle recognition; 4, grouting assistance; and 5, recovering drilling and completing sampling. According to the geological exploration sampling method, the adaptability to complex stratums can be improved by switching the rotary drilling mode and the vibration drilling mode, a multi-sensor module is adopted in the obstacle recognition step, and pressure, sound waves and vibration signals are collected in real time, so that the obstacle type is accurately judged, and a basis is provided for subsequent drilling mode adjustment. In the grouting assisting step, grouting equipment is adopted to inject grout into an obstacle area from grouting micropores in the front end of a drill bit through a grouting channel so as to effectively weaken an obstacle structure. By means of the method, efficient drilling and sampling operation under the complex stratum condition can be achieved, the drilling tool jamming risk is reduced, adaptability is high, and efficiency is high.

The invention discloses novel cement pipe pouring forming equipment, and relates to the technical field of pouring equipment, the novel cement pipe pouring forming equipment comprises a supporting seat and a reinforcement cage body, a pouring inner mold and a pouring outer mold are arranged at the top of the supporting seat, the reinforcement cage body is placed between the pouring inner mold and the pouring outer mold, and a control assembly is arranged on the supporting seat. According to the novel pouring forming equipment for the cement pipe, periodic knocking treatment is conducted on the inner wall of the pouring inner mold through the knocking rods, high-frequency vibration is generated, the vibration effect in concrete is remarkably improved through the vibration, and therefore the concrete is fully compacted, bubbles in the concrete are effectively eliminated, and the concrete quality is improved. The reinforcement cage has important significance for improving the strength and durability of the cement pipe, the central position of the reinforcement cage body between the pouring inner mold and the pouring outer mold is ensured through an accurate adjusting and positioning mechanism, the reinforcement cage is prevented from moving in the pouring process, and the construction efficiency is improved. And the problem of non-uniform stress distribution caused by the fact that the position of the reinforcement cage deviates from the center is also avoided.

The invention belongs to the technical field of electronic information and communication, and discloses a self-adaptive signal transmission path optimization system of a chip, which comprises a data acquisition module used for acquiring monitoring video data, chip internal parameter data and chip transmission environment data; the data processing module is used for preprocessing the acquired monitoring video data, chip internal parameter data and chip transmission environment data to obtain a video feature data set, a chip internal parameter feature data set and a chip transmission environment feature data set; analyzing the influence of the chip transmission environment feature data set on the video feature data set and the chip internal parameter feature data set to obtain a transmission influence feature data set; the transmission error analysis module is used for training and obtaining a transmission error prediction model according to the transmission influence feature data set, and obtaining errors generated in the chip internal transmission process of the monitoring video signals based on the transmission error prediction model; the reliability of signal transmission is improved, and the chip resource allocation is more efficient.