229 results about "Dynamic database" patented technology

The invention discloses a JDK8-based heterogeneous service large model dynamic adaptation and intelligent scheduling method and system, and belongs to the technical field of artificial intelligence service integration, and the method comprises a unified service module which provides standardized HTTP / WebSocket access for an application layer and shields the difference of multiple platforms at the bottom layer; the dynamic routing module is used for dynamically selecting service nodes based on service quality indexes and supporting weight calculation, fusing recovery and flow dyeing; the service execution module is used for loading a platform adapter through a dual-mode service factory, integrating a tool calling function and realizing protocol conversion and authentication injection; and the configuration management module supports dual-configuration source hot loading of the static file and the dynamic database and provides versioning rollback and consistency verification. According to the method, the problems of multi-platform protocol difference, service rigid expansion, tool calling coupling and the like can be solved, the complexity of multi-platform management is remarkably reduced, and the flexibility and maintainability of the system are improved.

The invention provides an automatic pavement settlement monitoring method and system based on a shield undercrossing airport runway. The dynamic database is constructed by collecting operation parameters such as shield tunneling machine propelling pressure, cutterhead torque and synchronous grouting pressure in real time and combining three-dimensional deformation data obtained through laser scanning. Strain sensing units are arranged in the soil layers to form a layered monitoring network, strain changes of the soil layers of different depths are collected, and spatial correlation is established between the strain changes and the tunneling position. And analyzing a spatial attenuation rule through a dynamic association processing unit, and generating a multi-dimensional feature data set. And establishing a settlement prediction model, fusing the shield dynamic load sequence and the layered strain conduction characteristics, and outputting settlement distribution information. And the system automatically compares the settlement difference value of the adjacent areas with a preset safety threshold value, and generates a graded early warning signal after verification of the three-dimensional deformation data space. According to the technical scheme provided by the invention, real-time three-dimensional prediction and spatial verification type graded early warning of settlement of the airport runway are realized.

The invention discloses a multi-channel meteorological risk early warning information self-adaptive targeted publishing system and method based on low-altitude flight, and solves the problems that existing low-altitude meteorological early warning is low in temporal-spatial resolution, single in risk identification and insufficient in information pertinence. The system integrates air-based, space-based, foundation, social and topographic data, and generates a low-altitude meteorological dynamic database through fusion; micro-scale risks such as wind shear are extracted and graded through an AI model, a digital twin simulation response is constructed in combination with the state of the aircraft, and a risk grid model and coordinates are output; calculating a comprehensive risk index, generating evasion guidance, converting into multi-role early warning information, generating a three-dimensional thermodynamic diagram, and finally adaptively selecting a publishing channel according to user roles, terminals and network states. According to the invention, the accuracy and timeliness of low-altitude flight meteorological risk early warning are improved, and the safety of low-altitude flight is guaranteed.

The invention belongs to the technical field of geological information processing, and discloses a geological mineral exploration data extraction system which comprises the following steps: constructing an air-ground-hole three-in-one acquisition network, and respectively acquiring earth surface mineral spectrum data, seismic longitudinal wave and transverse wave reflection data and rock core main quantity and trace element composition data; processing the collected data to form a five-dimensional data cube containing space coordinates, spectrum parameters, physical property parameters, element parameters and time indexes, performing physical layer attribute extraction on the five-dimensional data cube, performing analysis to obtain a wave impedance value and a lithology category probability array, performing semantic layer attribute extraction on the five-dimensional data cube, and performing semantic layer attribute extraction on the five-dimensional data cube; an alteration type probability array is obtained through analysis, an alteration zoning graph layer is generated, the mineralization potential index and a five-dimensional data cube are fused, a four-dimensional dynamic database is constructed, a mineralization potential prediction graph layer and a drilling priority graph are generated based on the four-dimensional dynamic database, and therefore the decision-making level of ore body drilling deployment is improved.

The invention relates to the technical field of power equipment state detection, in particular to an ultrahigh-frequency partial discharge online detection system, method and device and a medium, and the system comprises the steps: collecting an initial discharge signal in real time through an ultrahigh-frequency sensor array, and carrying out the preprocessing of the initial discharge signal, so as to obtain an ultrahigh-frequency discharge signal; carrying out peak detection on the ultrahigh-frequency discharge signal, and triggering a high-speed analog-to-digital converter to collect an original waveform when the amplitude exceeds a preset threshold value; performing multi-dimensional feature extraction on the original waveform by using a digital signal processor to obtain multiple groups of dimensional features; identifying and classifying the multiple groups of dimension features based on a random forest algorithm, generating discharge type labels and confidence coefficients, and storing the discharge type labels and the confidence coefficients in a dynamic database; carrying out spatial position calculation on the ultrahigh-frequency discharge signal by adopting a time difference method, and determining a three-dimensional coordinate of a discharge source; the dynamic database and the three-dimensional coordinates of the discharge source are subjected to space-time correlation and multi-dimensional analysis, a defect analysis result is generated, and high-precision online detection of the partial discharge defect of the high-voltage equipment is achieved.

The invention discloses a power grid energy storage capacity demand determination method and system based on multiple time scales, relates to the technical field of power grid energy storage capacity demand calculation, and aims to solve the problem of inaccurate energy storage capacity demand calculation. By generating multiple scenes, quantitatively screening key scenes and incorporating various uncertain factors, energy storage capacity calculation focuses on high-influence scenes, the coping capacity of the scheme to actual risks is enhanced, decision scientificity is improved, ultra-short-term to long-term multi-time scales are divided, core contradictions of all the scales are captured in a targeted mode, limitation of a single scale is avoided, and energy storage capacity calculation efficiency is improved. According to the method, capacity requirements and equipment distribution are integrated, operation rules are defined, visual documents are generated, multi-scale energy storage cooperative operation is achieved, the stability of a power grid is guaranteed, meanwhile, cost is reduced, scheme landing performance and operation efficiency are improved, multi-time-scale power grid state prediction is carried out based on a dynamic database, and historical rules and real-time data are combined, so that the power grid state prediction efficiency is improved. And the prediction coordination is ensured through multi-dimensional verification.

The invention discloses a pupil image recognition and disease change evaluation system based on image recognition, and relates to the technical field of monitoring analysis, and the system comprises the steps: obtaining the identity information and historical pupil data of a patient, and building a pupil dynamic database corresponding to the patient; alternately irradiating the eyes of the patient, and collecting a dynamic image sequence corresponding to a pupil light reflex area of the patient; performing spatial-temporal characteristic analysis on the dynamic image sequence, establishing a pupil diameter dynamic change curve, and generating a light reflection sensitivity index of the pupil of the patient according to the pupil diameter dynamic change curve; constructing a pupil dynamic evaluation model according to the pupil diameter dynamic change curve and the light reflex sensitivity index of the patient pupil, and outputting a pupil grade evaluation result based on the pupil dynamic evaluation model; comprehensive analysis is conducted on pupil grade evaluation results, analysis results are uploaded to an intensive care central system, and a grading early warning mechanism is triggered. The application has the effect of reducing the occurrence of illness state delay.

The invention discloses an engineering safety early warning method and system based on artificial intelligence real-time risk identification, and relates to the technical field of engineering safety, and the method comprises the steps: collecting scattered engineering safety data from each engineering platform in batches, and carrying out the preprocessing of the data, and constructing a dynamic database; according to the engineering safety data collected in batches, an engineering safety knowledge graph is constructed, and different risk levels are preset according to engineering safety standards. According to the method, multi-source engineering safety data are integrated, dynamically changing risk characteristics are analyzed in real time by using an AI risk identification model, the hysteresis of traditional manual inspection and static analysis is overcome, a nonlinear relationship among the risk characteristics is captured by using a random forest model through integrated learning of multiple decision trees, and the risk characteristics are analyzed in real time. And the probability values of high, medium and low risk levels are output in combination with Softmax probability normalization, so that the evaluation precision is remarkably improved, the risk features are positioned, the scientificity of risk traceability is ensured, and data-driven decision support is provided for engineering safety management.

The invention belongs to the technical field of aircraft coating processing, and particularly relates to an aircraft surface automatic spraying method based on a heavy-load robot, which comprises the following steps: carrying out geometric modeling on an aircraft body workpiece; a spray gun tool coordinate system is calibrated, and TCP coordinate optimization calculation is carried out by fusing spray gun 3D model parameters and flame long distance values; constructing a global workpiece coordinate system dynamic database; automatic coverage of a multi-layer U-shaped reciprocating spraying path is achieved through a path planning algorithm; after a fixed spraying distance parameter is set, the spraying software process package generates a robot track, and path simulation is carried out; a robot movement track program is generated by combining parameters of coating types, plasma flame lengths, spraying angles and spraying speeds; and a low-speed transition point is inserted into a track alarm point, and dynamic smooth connection of a spraying path is achieved. The spraying efficiency of the large machine body workpiece is improved, and manual intervention is reduced; and the adaptability is high, and spraying objects of different shapes and sizes can be rapidly dealt with.

The invention relates to a rapid non-contact sensing detection method for a bolt loosening defect of a power transmission line tower, and belongs to the technical field of power system maintenance and monitoring. The method comprises the following steps: constructing a bolt vibration characteristic dynamic database, and detecting the bolt loosening condition by adopting an impact elastic wave principle; recognizing the bolt loosening condition of the power transmission line tower by using an acoustic imaging technology, an infrared imaging technology and an electromagnetic field detection technology; a power transmission line tower bolt looseness early warning model is constructed, and the power transmission line tower bolt looseness condition is obtained by adopting detection data of real-time acoustic imaging, infrared imaging and electromagnetic field detection; and finally, early warning of looseness of the bolt of the power transmission line tower. By combining multiple detection means, the detection efficiency and accuracy of the bolt loosening defect of the power transmission line tower are improved, so that the maintenance cost is reduced, and the reliability and safety of a power transmission system are improved.

Techniques for dynamic database redaction using protected encryption secret material are described. A masking policy is defined that includes a reference to a secret material stored by a secrets manager service. The masking policy further identifies a pseudonymous redaction function that utilizes a cryptographic function requiring such a secret material. The secrets manager service is configured to grant access to the secret material by an entity of the database service that executes queries, such as a leader node of a cluster. For a particular query, the cluster obtains the secret material from the secrets manager service in a secure manner, uses the secret material for applying the cryptographic function to values for redaction purposes, and deletes any copies of secret material thereafter.

The invention relates to a multi-agent search enhancement generation method and system. The method comprises the following steps: analyzing a task instruction through a first agent to generate a search feature set; matching a plurality of corresponding second intelligent agents and performing directional semantic conversion on the original semantic vector to generate a query statement set; screening a plurality of third intelligent agents, and executing query operation through the third intelligent agents to obtain a preliminary retrieval set; inputting the preliminary retrieval set and the retrieval feature set into a fourth agent for verification, and generating an optimized retrieval result; in conclusion, according to the multi-agent search enhancement generation method and system provided by the invention, intelligent analysis, cross-modal semantic conversion, dynamic database partition scheduling and search result optimization verification of task instructions are realized through a multi-agent cooperation mechanism; the method has the effects of improving the retrieval precision and efficiency, enhancing the adaptability to complex query intentions and optimizing the collaborative retrieval capability of the heterogeneous database.

The invention provides an intelligent infusion system and an intelligent liquid control method based on database dynamic feedback regulation and control, and relates to the technical field of medical equipment intelligent control. The system comprises an infusion terminal execution module, a multi-parameter monitoring module, a data transmission module, a central control server module and a dynamic database module; patient information, an infusion scheme, a threshold range and multi-dimensional data of historical records are stored through the dynamic database module, the central control server module calls the data and compares the data with real-time physiological parameters and infusion state parameters collected by the multi-parameter monitoring module for analysis, and the target infusion speed is calculated. Early warning is carried out according to the target infusion speed and the real-time monitoring parameters, accurate monitoring of the regulation and control parameters and the individual condition of the patient is ensured, the infusion speed is always in the optimal range adaptive to the physiological state of the patient, and the infusion adverse reaction caused by parameter errors and exceeding the physiological range is avoided.

The invention relates to a marine ranching digital construction method and system based on artificial intelligence, and the method comprises the steps: monitoring plankton in a marine ranching in real time, obtaining a water body image through an image recognition technology, and building a dynamic database, so as to regularly store and update the related data of the plankton. Based on monitoring data, a water quality evaluation model is established, and the correlation among plankton species, density and water quality parameters is analyzed. Factors such as water flow velocity and flow direction are integrated, a flow change model is established, and the influence of water flow on plankton is judged. A primary culture optimization scheme is formulated by simulating the interaction between cultured organisms and planktons, and the culture trend is predicted in real time and the management strategy is adjusted by integrating the water quality evaluation and the output result of the flow change model. According to the scheme, the intelligent management level of the marine ranching is effectively improved, dynamic and scientific management of the culture environment is achieved, powerful support is provided for healthy growth of cultured organisms, and sustainable development of the marine ranching is promoted.

The invention discloses an aircraft control simulation platform construction method, and the method comprises the steps: constructing a terrain multi-dimensional model, fusing a cross-scale meteorological particle system, and dynamically obtaining an environment disturbance factor; a space obstacle dynamic database is generated in combination with millimeter-level space positioning data, and virtual collision detection is carried out; performing eye movement-gesture collaborative decision, and identifying a control instruction with high confidence; the six-degree-of-freedom kinetic equation is coupled with an unreal engine interface in real time, and a high-fidelity instrument is driven to feed back; generating a training defect thermodynamic diagram, triggering an adaptive optimization strategy and iterating platform parameters; the invention provides a solution integrating multi-modal high-precision data acquisition, dynamic environment-physical rule coupling, intelligent decision and closed-loop optimization so as to realize aircraft control simulation training with high immersion degree, high fidelity and high adaptability.

The invention relates to the field of ecological monitoring, in particular to a marine ecological anomaly detection method and system based on multi-source data. Comprising the following steps: acquiring multi-source dynamic data of a target sea area; constructing a dynamic quality evaluation system, inputting multi-source dynamic data, and outputting a quality control report; based on the multi-source dynamic data conforming to the preset quality threshold value, establishing a marine ecological dynamic database in combination with a spatio-temporal indexing mechanism; based on the marine ecological dynamic database, space-time anomaly features are extracted, and candidate anomaly regions are determined; and generating a marine ecology comprehensive abnormal index by adopting the dynamic weight calculation model, outputting a prediction result through a preset abnormal trend prediction model based on the marine ecology comprehensive abnormal index, and generating an early warning measure. Through a distributed crawler and sensor gateway collaborative architecture, comprehensive acquisition of macroscopic data and near-shore real-time data is realized, and high-quality basic data is provided for subsequent detection.

The invention provides a dynamic database connection pool adjustment method and system, and relates to the technical field of computers, and the method comprises the steps: collecting the operation state data of a target dynamic database connection pool in real time, and sending the data to a configuration center; the configuration center determines a connection number adjustment index based on the received operation state data of the connection pool in combination with a connection request of the current target dynamic database connection pool; and based on the connection number adjustment index, the configuration center dynamically updates the maximum connection number of the connection pool, and notifies the connection pool module to update. The operation state data of the target dynamic database connection pool acquired in real time is calculated by using the configuration center in combination with the connection request to obtain the connection number adjustment index, and then the maximum connection number of the connection pool is dynamically updated by using the connection number adjustment index, so that the external service capability of the connection pool is effectively improved, and stable operation of a service system is ensured.

The invention belongs to the technical field of data processing, and discloses a multi-source heterogeneous data fused remote sensing map dynamic database construction method and system, and the method comprises the steps: firstly obtaining multi-source heterogeneous remote sensing data of a target area, extracting remote sensing time sequence data of a land parcel after preprocessing, and obtaining a remote sensing time sequence; constructing a time sequence semantic track containing a key semantic feature time sequence for each land parcel; identifying a semantic evolution trend by using a semantic drift detection model, and generating an abandoned suspicious score; the static factors, the dynamic factors and the prior knowledge of the land parcels are fused, a structure causal graph is constructed by means of a causal discovery algorithm, and abandoned causal credibility is reasoned based on a graph neural network model; and automatically generating abandoned land labels for the land parcels of which the double scores exceed the threshold value, and finally writing the land parcel information into a dynamic database. And the problems of construction lag and information incompleteness of the dynamic database are solved.

The invention discloses a power grid line fault knowledge base construction method and a power grid line fault prediction method. The power grid line fault knowledge base construction method comprises the steps of collecting power grid operation data and meteorological data, and constructing a dynamic database of power grid line faults; designing association rule evaluation indexes of the power grid line faults; constructing a dual-mode dynamic tree DDT-tree, updating the dynamic database to obtain incremental data, and updating the dual-mode dynamic tree DDT-tree; and based on the association rule evaluation index, updating the association rule, and further constructing a fault knowledge base of the power grid line. The power grid line fault prediction method is based on a fault knowledge base of a power grid line, and comprises the following steps: obtaining power grid operation data and meteorological prediction data, preprocessing the data to obtain input data to be detected, and inputting the input data to be detected into a trained fault prediction network to obtain a prediction result; and performing matching judgment on the prediction result in combination with a fault knowledge base to obtain a power grid fault prediction result. The accuracy of power grid fault prediction can be improved.

The invention relates to the technical field of intelligent warehousing, in particular to a double-extension-position stereoscopic warehouse scheduling method and system and a computer readable storage medium, and provides a double-extension-position stereoscopic warehouse scheduling method which comprises the steps that a to-be-executed task dynamic database is generated according to real-time to-be-executed tasks of a double-extension-position stereoscopic warehouse; establishing a storage location-task dynamic mapping relation based on a preset three-dimensional model of the double-extension-location stereoscopic warehouse and a to-be-executed task dynamic database; obtaining an initial path plan based on the storage location-task dynamic mapping relation; calculating a task conflict index according to the equipment parameters of the double-extension-position stereoscopic warehouse and the to-be-executed task dynamic database; and adjusting the initial path plan based on the task conflict index to obtain a scheduling scheme. According to the double-extension-position stereoscopic warehouse scheduling method, the technical problem of efficiency loss caused by insufficient dynamic scheduling capability of a double-extension-position stereoscopic warehouse scheduling system in related technologies is solved.

The invention relates to the field of high-frequency communication comprehensive detection of a pressure feedback type composite actuator, in particular to a high-frequency communication control detection method for the pressure feedback type composite actuator, which comprises the following steps: acquiring high-frequency communication control real-time data of the pressure feedback type composite actuator; establishing a signal flow dynamic database of the pressure feedback type composite actuator by using the high-frequency communication control real-time data; according to the signal flow dynamic database, multi-stage screening analysis processing is carried out to obtain a high-frequency communication control detection result of the pressure feedback type composite actuator, when any comparison abnormity exists, alarm processing is carried out, meanwhile, the abnormity is rechecked subsequently, and effective safety guarantee is made for the process safety of the stamping process.

The invention relates to the field of automatic control, in particular to a method, system and terminal for controlling hierarchical starting and stopping of environment control equipment, which comprises the following steps of: matching an environment temperature value from a preset dynamic database according to an internal temperature value and an external temperature value; according to the exceeding condition between the environment temperature value and a preset reference temperature value, it is determined that the internal temperature value and the external temperature value continue to be obtained or the exceeding time is obtained; judging whether the exceeding time exceeds preset reference time or not; if not, preset environment control equipment is controlled to carry out temperature adjustment at preset adjustment power; if yes, a preset environment control device is started, and the environment temperature value is updated; matching a future temperature value from a preset temperature database according to the updated environment temperature value; and matching equipment on-off control information from the dynamic database according to the future temperature value, and controlling graded on-off of the environment control equipment according to the equipment on-off control information. The method has the effects of improving the working efficiency and dynamically saving the energy consumption.

The embodiment of the invention provides a reservoir capacity dynamic monitoring method and system based on an unmanned aerial vehicle, and the method comprises the steps: obtaining a reservoir surface feature data set through the unmanned aerial vehicle, determining the boundary of a water area, scanning the bottom of the reservoir, obtaining the underwater terrain elevation and sediment distribution data, and constructing a three-dimensional terrain model; and determining terrain and deposit change data based on the three-dimensional terrain model dynamic change data of the continuous time sequence. Sedimentation space distribution characteristics are obtained through change rate analysis, and the sediment transportation amount and the sedimentation and deposition space rule are determined in combination with the water flow speed. Key driving factors are screened through correlation analysis, a sedimentation high-risk area is determined according to the key driving factors, and the change of sediments in the area is monitored, so that the change of the reservoir capacity is mastered. The reservoir siltation can be accurately and dynamically monitored, the high-risk area and the change mode are defined, the dynamic database is constructed to update the capacity change in real time, and important technical support is provided for reservoir management and flood control and disaster reduction.

The invention discloses a site-level CCUS dynamic source-sink matching optimization method for an oil field enterprise, relates to the technical field of large-scale deployment of carbon capture, utilization and storage of the oil field enterprise, and particularly relates to the site-level CCUS dynamic source-sink matching optimization method for the oil field enterprise. Comprising the following steps: integrating a carbon source end full life cycle technical economy evaluation system and a storage target area'geology-potential-economy 'three-dimensional grading model to form a dynamic database; on the basis of the dynamic database, a mixed integer linear programming model fusing source sink dynamic priority coefficients is constructed, three scenes of cost minimization, oil displacement income maximization and carbon sink subsidy excitation are set, and a constraint system is coupled; according to the method, carbon source technology economic evaluation and storage target area three-dimensional grading are fused, the specific injection-production cycle, policy incentive and pipe network constraint of an oil field are converted into time-varying weight coefficients, traditional static optimization limitation is broken through, and site-level source-sink dynamic accurate matching is achieved.

The invention discloses a photovoltaic roof health monitoring integrated system for a railway station. The system comprises an information collection system which collects photovoltaic roof BIM three-dimensional model information and GIS model data and performs three-dimensional visual display; the equipment management system is used for monitoring states of various monitoring equipment and recording operation data; the early warning management system is used for analyzing the dynamic database set threshold value and the grade early warning abnormal data; the management and maintenance system automatically generates an inspection task according to a period and records an execution condition; and the reporting system is used for summarizing information, generating various reports and supporting export. The system solves the problems of multi-dimensional data integration, intelligent fault prediction and early warning, data transmission processing real-time performance, unified management and the like, improves the operation and maintenance efficiency and management cost, has flexibility and expansibility, adapts to different photovoltaic roof requirements, effectively makes up for the defects in the prior art, and provides comprehensive guarantee for railway station photovoltaic roof health monitoring.

The invention discloses a time-sharing coal blending combustion method, device and equipment for a coal-fired power plant and a storage medium, and relates to the technical field of coal blending control, and the method comprises the following steps: establishing a dynamic database containing coal reserves and coal quality parameters of the coal-fired power plant, and updating coal characteristic data in real time; dividing the whole day into a plurality of time periods according to a power grid dispatching instruction and historical load data, and setting a reference load range for each time period; and by taking the fire coal characteristic data and the reference load range as constraint conditions and taking the maximum fire coal profit as a target function, generating a fire coal blending combustion scheme of the coal mill in each time period. According to the method, coal quality parameters and inventory data are integrated in real time by constructing a dynamic database, time periods are intelligently divided and a load reference is set in combination with a power grid dispatching instruction, and a coal blending combustion scheme of each time period is generated by using a mathematical optimization algorithm; the problems of poor coal quality fluctuation adaptation, lagging load adjustment, high fuel cost, difficulty in emission control and the like of a traditional artificial experience method are effectively solved.

The invention discloses an aircraft oxygen load distribution method based on a dynamic database, and relates to the field of aviation system engineering and control engineering, and the method comprises the steps: building a digital twin model through simulation software, obtaining the current state of aircraft oxygen, presetting the oxygen demands at different flight stages, and obtaining a digital twin model; performing multi-physics field coupling optimization on the digital twin model through an optimization algorithm, feeding back an optimized result to a dynamic database to obtain an oxygen distribution scheme, training an oxygen demand model by utilizing a federated learning technology, predicting oxygen demand in a future flight stage, and designing and deploying a self-repairing mechanism according to a prediction result; according to the method, the oxygen consumption condition is monitored in real time through the dynamic reconstruction algorithm, and the oxygen distribution scheme is intervened and optimized when it is detected that the oxygen distribution scheme is not matched with the oxygen consumption condition, so that the requirements of emergencies are met, and the error-tolerant rate and the reliability are greatly improved.

The invention discloses a vehicle maintenance package intelligent identification and material customization recommendation system, and the system comprises a data input module which is used for receiving vehicle model information and driving kilometers; the data processing and checking module checks and confirms the vehicle information through a built-in vehicle database and an optical character recognition (OCR) technology; the real-time updating and compatibility optimizing module is used for establishing a cloud dynamic database and is in butt joint with data interfaces of global main automobile manufacturers to realize real-time synchronization of automobile model data and maintenance standards; and the personalized algorithm module is used for constructing a user behavior model based on the historical maintenance record, the vehicle use frequency and the driving environment and providing personalized maintenance suggestions. According to the invention, through the measures of improving a data processing and verification mechanism, real-time updating and compatibility optimization, personalized algorithm optimization, cost-benefit intelligent analysis, enhancement of transparency and user trust, optimization of user experience and education, enhancement of data security and privacy protection, etc. The intelligent maintenance recommendation system which is more accurate, efficient, personalized and safe is provided, comprehensive maintenance services are provided for vehicle owners, the vehicle maintenance efficiency is improved, and the service life of vehicles is prolonged.

The invention discloses a self-adaptive control method and system for a mining drilling machine. The method comprises the steps that state parameter data in the drilling process of the drilling machine are collected in real time through a multi-source sensor; quickly matching the acquired data with a pre-constructed dynamic database, generating an initial control parameter, and inputting the initial control parameter into an optimization model to generate a self-adaptive control strategy; performing closed-loop control on a drilling machine executing mechanism according to the self-adaptive control strategy; and monitoring and evaluating the drilling performance index of the drilling machine in real time, and feeding back an evaluation result to the optimization model to realize online iterative optimization. Through three technical means of dynamic database construction, layered double closed-loop control and multi-parameter coupling optimization, adaptive sensing, intelligent decision making and accurate execution of the drilling machine under complex geological conditions are realized, the drilling efficiency is remarkably improved, the energy consumption is reduced, the operation safety is enhanced, and the engineering application value is extremely high.

The invention relates to the technical field of boiler operation management, in particular to a boiler soot blowing steam consumption multi-dimensional data analysis system which comprises a dynamic database construction module, a steam consumption calculation model construction module, an evaluation module and an optimization strategy generation module. The dynamic database construction module is used for cooperatively acquiring the ash scale thickness value of the heating surface partition of the boiler through an infrared thermal imager and a sound wave thickness measuring device, and realizing structured time sequence data fusion in combination with steam parameters and working condition parameters; the steam consumption calculation model building module is used for building a multi-dimensional consumption data set based on space, time and energy efficiency dimensions; the evaluation module outputs a unit ash scale removal steam consumption value, an invalid steam injection proportion value and a regional energy efficiency deviation coefficient value; the optimization strategy generation module generates a soot blowing pressure gradient adjustment strategy and a steam saturation temperature compensation strategy through index correlation analysis, fine evaluation and control optimization of soot blowing energy efficiency can be achieved, and the boiler operation efficiency and the steam utilization rate are improved.