340 results about "Complex problems" patented technology

The invention specifically relates to the technical field of natural language processing, and discloses an intelligent interactive customer service system based on an AI large model, which comprises a multi-modal input analysis module, an intention preliminary detection module, a large model semantic understanding module, a dynamic knowledge base association module, a dialogue strategy generation module, a natural language generation module and a service feedback work order module, through deep cooperation of a multi-modal input analysis module and a large model semantic understanding module, entity and attribute information is accurately extracted, context semantic association information is mined, and through the cooperative effect of an intention preliminary detection module, a dynamic knowledge base association module and a dialogue strategy generation module, based on a semantic analysis result output by a large model, a dialogue strategy is generated. According to the method and the system, matching calculation is carried out with the constructed dynamic knowledge base, rich knowledge support is provided for solving complex problems, personalized knowledge content is recommended for different users through the natural language generation module and the service feedback work order module, and the reply matching degree and the complex problem processing capacity are greatly improved.

The invention relates to a multi-agent-based material performance prediction and synthesis system, and the system comprises a multi-agent data enhancement module which is configured to be used for firstly disassembling a complex problem into a plurality of subtasks, and then constructing a fine tuning data set comprising Sub-CoQ question and answer pairs by starting multi-source parallel retrieval; the multi-expert debate module is configured to be used for simulating decision conflicts of different roles in material engineering and generating a direct preference optimization DPO data set through debate; the training and verification module is configured to be used for training and verifying a large model MatMind in the field of materials by utilizing supervised fine tuning SFT and reinforcement learning RLHF based on the fine tuning data set and the DPO data set; and the material performance prediction and synthesis module is configured to be used for realizing intelligent recommendation of a material performance prediction and synthesis process by importing input parameters into the large model MatMind.

The invention discloses a knowledge-based visual question-answering method and device based on big and small model collaboration and a medium, belongs to the technical field of visual question-answering, and solves the problem of how to improve the accuracy of complex questions faced by a visual question-answering technology. In the image description extraction step, an image description and key object label set which is highly associated with a natural language problem is generated, and in the entity enhancement processing step, key entities are extracted and a clarity problem and an entity example which are used for resolving semantic ambiguity are generated. In the candidate answer generation step, a plurality of semantically complementary answers are generated under different reasoning dimensions on the basis of a multi-round generation strategy, optimized candidate answers are screened on the basis of a model built-in scoring mechanism, in the context example retrieval step, examples most related to current input are retrieved, and finally, the candidate answers are obtained. And the large language model receives a unified input prompt formed by splicing output results in the steps, and inference is performed in an autoregression mode to generate answers, so that the accuracy of the visual question-answering technology facing complex questions is effectively improved.

The invention discloses an AI (artificial intelligence) agent construction system based on hybrid retrieval and father-child segmentation, which comprises the following steps of: dividing a subclass knowledge base according to domain knowledge, performing father-child segmentation processing, and constructing a hierarchical semantic network; vectorization embedding and deep semantic reconstruction are carried out on the user question text; retrieving the reconstructed problem by adopting a mixed retrieval algorithm combining sparse retrieval and dense retrieval, and forming a high-score sub-segment set according to a comprehensive score obtained by dynamic weight distribution; mapping the sub-segments to the parent segment through a hierarchical backtracking algorithm, aggregating brother nodes to form an extended candidate set, and generating an associated sub-segment set after duplicate removal and re-retrieval; and finally inputting a large language model to generate a complete answer. According to the method, the problems of context segmentation, low retrieval accuracy and complicated knowledge base maintenance of traditional document segments are solved, the answer coverage and accuracy of an intelligent question-answering system are remarkably improved, and the method is suitable for knowledge question-answering scenes in the complicated technical fields such as intelligent network connection automobiles and the like.

The invention discloses a method for sharing a host based on multiple input devices, and belongs to the technical field of computers, and the method comprises the following steps: after a management user logs in a multi-seat configuration tool, creating second seats with the same number as new input devices according to a Udev rule, and enabling the management user to be a user operating the input device corresponding to a first seat of the host; according to a binding instruction sent by the management user, the second seats and the new input devices are bound one by one, and operation users of the input devices corresponding to the second seats are common users; according to a permission configuration instruction sent by the management user, configuring an application window permission for each common user; and sending the binding relationship between the second seat and the new input device and the application window authority to a window manager, so that the window manager manages the application window according to the binding relationship and the application window authority. According to the invention, the problems of disordered management and complex configuration when multiple users share one host window are solved, and more flexible and efficient equipment management experience is provided for the users.

The embodiment of the invention discloses a 4K splicing processor and a 4K splicing display system. The 4K splicing processor comprises a driving circuit used for processing a 4K resolution signal, the driving circuit comprises an FPGA chip U5, TVS array chips U10, U11, U12 and U13 and DP signal line connectors CN9 and CN10; the model of the U5 is Spartan-6, the models of the U10, the U11, the U12 and the U13 are all RClamp0524P, the CN9 is connected with the U5 through the U10 and the U11, and the CN10 is connected with the U5 through the U12 and the U13; the U5 receives the input 4K resolution signal through the CN9 to process the 4K resolution signal and outputs the processed 4K resolution signal through the CN10 to achieve 4K resolution signal looping. According to the 4K splicing processor and the 4K splicing display system, the problem that 4K splicing display system equipment is complex is solved.

The invention discloses an electric power field credible question-answering system based on a knowledge graph and multiple agents, and belongs to the technical field of intelligent power grids. The electric power field credible question-answering system comprises the steps that an existing knowledge base is stored through a vector knowledge base, the knowledge graph and a relational database, and then a multi-agent system is constructed based on a large language model; a complex problem is decomposed into a plurality of sub-problems by adopting a logic form language in real-time dialogue, solving is carried out based on operators such as planning, reasoning and retrieval, symbolization and structuring of a problem solving process are realized, knowledge is aligned and integrated by using a semantic reasoning technology, a semantic relationship between the knowledge is identified and established, and a real-time dialogue result is obtained. And realizing credible questions and answers in a manner of recalling related knowledge. According to the method, the deep fusion of the unstructured text, the structured data and the semantic relationship is realized by constructing the multi-modal knowledge storage system, the knowledge coverage rate and the semantic consistency are remarkably improved, and the understanding and response capabilities of the system to compound problems are improved.

The invention discloses a knowledge graph enhanced reasoning method and a knowledge graph enhanced reasoning system for high-risk field medical decision, which are used for strictly limiting the reasoning of a large language model within a high-quality knowledge graph range, so that the reliability is improved, and factual errors and'model illusion 'are fundamentally eliminated. Through an innovative constraint generation and traceability mechanism, each conclusion can be traced to a direct evidence in the knowledge graph, the interpretability is enhanced, and the complete transparency of the reasoning process is realized. The mixed query driven sub-graph retrieval method can deeply understand the intention of a user, accurately position and extract structured knowledge related to complex problems, improves the retrieval precision, and has a retrieval effect far better than that of traditional keyword or vector retrieval.

The invention belongs to the technical field of unmanned system reliability, and provides an unmanned cluster fault mode analysis and transverse and longitudinal propagation analysis method and system based on a task chain, electronic equipment and a storage medium. The method comprises the steps of model construction, fault mode recognition, severity setting, fault transmission recognition, adjacency matrix construction, network model construction and fault transmission influence analysis. According to the method, the unmanned cluster is subjected to hierarchical division, so that the problem of complex calculation process of a physical model is avoided, and the real-time performance of fault mode analysis is improved; through fault mode identification, severity setting and fault transmission identification, analysis of complex cooperation relation and interaction among individuals is realized, and adaptability of a dynamic change environment is improved. Through adjacency matrix construction, network model construction and fault transmission influence analysis, the analysis of the mutual dependency relationship between different fault modes is improved, and the accuracy of the propagation path is improved.

The invention discloses an operation and maintenance method and system based on an AI large model, and relates to the technical field of artificial intelligence operation and maintenance. The method comprises the following steps: acquiring monitoring data, analyzing the monitoring data, and decomposing the analyzed monitoring data into a plurality of field feature sets; determining a knowledge vector corresponding to each domain feature set; obtaining historical normal operation data of each knowledge vector, calculating a deviation value according to the historical normal operation data, and determining an abnormal symptom vector according to each deviation value; determining potential root cause vectors in the knowledge vectors according to the knowledge vectors and the abnormal symptom vectors; searching all paths, calculating a comprehensive weight value of each path, and taking the path with the highest comprehensive weight value as a root cause reasoning chain of the composite problem; and extracting a processing strategy corresponding to each knowledge vector, and performing optimization according to the logic sequence of the root cause inference chain and the processing strategy to generate a solution. By implementing the technical scheme provided by the invention, the system operation and maintenance efficiency can be improved.

According to the PCIe Switch system and the PCIe switch, a PCIe hardware IP is used as a bottom layer, and a basic PCIe interface function for physical layer and link layer management is provided; and identifying and configuring all connected devices to construct a device address routing mapping table through a Soft Switch IP mounted on the PCIe hardware IP, and determining a specific target of data transmission based on the constructed mapping table so as to route the data to a specific position of the corresponding device. According to the invention, flexible equipment enumeration can be carried out by selecting a pure hardware mode or a software and hardware combined mode according to actual requirements, so that the data can be correctly and efficiently transmitted to the target endpoint from the source equipment, and the complex problems of address resolution and routing management are solved. Compared with the prior art, the method can replace the existing PCIe Switch IP of a manufacturer, provides higher flexibility and expansibility, obtains better balance in the aspect of cost control, and is suitable for various applications needing large-scale PCIe equipment connection, virtualization and high-speed data exchange.

The invention discloses a signal enhancement method and device in an industrial plant area, and relates to the field of wireless communication, and the method comprises the steps: firstly, obtaining complete channel state information, and guaranteeing that all decisions are based on real channel characteristics instead of theoretical assumptions; and secondly, if the complete channel state information does not meet the target QoS demand quantization parameter, maximizing a receiving signal to interference plus noise ratio and meeting the target QoS demand are taken as optimization targets, an optimization result is obtained based on channel field intensity distribution information of a preset digital twin model, and finally, the optimization result is controlled and executed to form closed-loop feedback. According to the method, optimization is carried out based on channel field intensity distribution information of a unit space in a digital twin model, and a complex problem needing to be solved by a high-dimensional iterative solution algorithm in related technologies is converted into table lookup and interpolation operation based on space coordinates, so that the calculation complexity is remarkably reduced, the time for obtaining an optimization result is greatly shortened, and the calculation efficiency is improved. Therefore, the time when the terminal is in a poor-quality signal state is greatly reduced.

The embodiment of the invention discloses a multi-modal mixed retrieval enhanced question and answer method and device, belongs to the technical field of artificial intelligence, and is used for improving the accuracy of answering complex questions. Comprising the steps of obtaining an original document of a target knowledge field, performing segmentation processing on the original document to obtain a plurality of knowledge slices, and respectively constructing a graph database and a vector database based on the knowledge slices; obtaining a query statement of a user, retrieving entities of knowledge slices in the graph database based on the entity of the query statement to obtain a first knowledge slice list, retrieving content vectors of the knowledge slices in the vector database based on the query vector to obtain a second knowledge slice list, and retrieving content vectors of the knowledge slices in the vector database based on the knowledge query vector to obtain a second knowledge slice list; retrieving knowledge enhancement vectors of knowledge slices in the vector database to obtain a third knowledge slice list; and fusing the first knowledge slice list, the second knowledge slice list and the third knowledge slice list to obtain a target knowledge slice, and determining a target answer according to the target knowledge slice.

The invention provides a cross-platform visual database execution plan analysis method and device and a medium, and belongs to the technical field of data storage. The database execution plan analysis method comprises the steps that a cross-platform support tool is used, standard SQL grammar is called, and an execution plan of each database in multiple databases is extracted; using a unified database execution plan conversion algorithm to convert the execution plan of each database into a unified intermediate representation format to obtain a standardized execution plan; displaying the standardized execution plan by using a graphical interface; analyzing potential performance problems of the execution plan according to the key analysis indexes of the execution plan, and generating optimization suggestions for the potential performance problems in combination with statistical information of the database table. The method can solve the problems that in the prior art, a unified interface and a display mode are adopted between tools, cross-platform use is complex, and display is complex.

The invention provides a DIKWP semantic modeling method. Complex problems of an enterprise are converted into a five-layer linkage semantic map. The method comprises the following steps: 1, cleaning multi-source heterogeneous data to form nodes by a data layer; (2) information layer construction domain ontology clarification concepts and constraints; (3) the knowledge layer aligns with the knowledge base to infer and complement the relationship to generate a knowledge graph; (4) the wisdom layer outputs scheme elements, benefits and risks based on decision rules; and (5) modeling each intention layer refining strategic target constraint layer. Full-link semantic mapping from data to intention is achieved, consistency and accuracy of problem definition are improved, cross-department implicit causality is mined, it is ensured that a scheme is accurately aligned with a strategic target, an interpretable semantic basis is provided for automatic scheme generation, scene simulation and optimization decision, and the method has remarkable commercial application value.

The invention discloses a dynamic tool selection system and method based on multi-stage training, and belongs to the field of natural language processing. The method comprises the following steps: acquiring a labeling data set in a specific vertical field through a high-confidence training sample construction module, preprocessing the labeling data set to obtain different types of complex problem sets, generating a positive sample tool and a negative sample tool for each complex problem, and performing reasoning to obtain a high-quality training sample set; a progressive training module is used for multi-stage training of a model, and the model comprises a supervised fine-tuning training stage, a comparative learning stage and a reinforcement learning stage; and performing multi-dimensional evaluation on the trained model by taking the accuracy rate, the recall rate and the F1 score as evaluation indexes through a multi-dimensional evaluation module. Through the synergistic effect of the modules, the question answering ability of the model in the vertical field is effectively improved, particularly, a remarkable breakthrough is made in the aspect of tool selection accuracy, and a reliable technical scheme is provided for application of an intelligent question answering system in the professional field.

The invention discloses a question data reply method and device, electronic equipment and a computer program product. The method comprises the steps of obtaining to-be-replied question data; expanding the to-be-replied question data by adopting a pre-trained operation and maintenance intention recognition model to obtain target question data; a pre-trained first preset model is adopted to perform thinking chain analysis on the target problem data to obtain target thinking chain data, and the target thinking chain data at least comprises a plurality of first subtasks arranged according to a thinking logic sequence; determining a target reply sub-data set based on a plurality of reply sub-data queried by the target thinking chain data; and arranging the multiple pieces of reply sub-data in the target reply sub-data set to obtain target reply data of the to-be-replied question data. The technical problem that in the prior art, the reply accuracy of complex questions is poor is solved.

The invention relates to a fractured rock thixotropic fluid seepage diffusion path characterization method, and belongs to the technical field of geotechnical engineering. The method comprises the following steps: constructing a fractured rock mass network geometric model based on geological exploration data; constructing a fluid seepage constitutive equation according to the thixotropic fluid characteristic parameters; grid division is carried out based on the constructed fractured rock mass network model, a one-dimensional fluid seepage channel is assembled, and dimension reduction solving of a complex problem is achieved; fluid pressure and fluid seepage velocity parameters are obtained through iterative solution, and a fluid characteristic parameter change rule is updated in real time; and generating and outputting a fluid seepage diffusion behavior tracking result under a set working condition based on the simulation state quantity. Compared with the prior art, the method has the advantages that the complex fluid diffusion rule caused by the thixotropic fluid viscosity time-varying characteristic can be accurately described, the method is suitable for accurate characterization of the grouting diffusion path in geological engineering, and a scientific basis is provided for optimizing construction parameters.

The invention discloses a construction method of a single-cell multi-omics data analysis system based on a containerization technology, and the construction method of the single-cell multi-omics data analysis system based on the containerization technology comprises the following steps: constructing a single-cell multi-omics analysis modular toolkit; a production mirror image is constructed on the high-performance cluster through a Single container engine, and deployment of a production environment is completed; a single-cell multi-omics automatic analysis platform is built through a snakemake process engine; and a JupyterLab interactive analysis platform for exploratory analysis of the single-cell multi-omics data is constructed. According to the single-cell multi-omics data analysis system construction method based on the containerization technology, the data acquisition link in the analysis process is accelerated, an automatic working process is formed to solve the problem of complex process, and the actual requirements of multiple users on a high-performance computing cluster for scientific exploration and analysis of single-cell data are met.

The embodiment of the invention discloses a business execution method based on a large model, and the method comprises the steps: taking data inputted into the large model as initial data, reversely determining a final step which needs to be executed to obtain an output target, forwardly determining an inference boundary condition which can be deduced by the initial data, and according to the inference boundary condition and the final step, carrying out the business execution according to the inference boundary condition and the final step. And constructing a reasoning process to obtain an output result, and executing a service according to the output result. According to the method, a global solution direction is determined through independent reverse planning, blindness and local traps caused by only forward reasoning are avoided, better robustness and adaptability are embodied in a complex problem scene through butt joint of forward derivation verification and reverse planning, computing resources can be saved, and meaningless search overhead is reduced.

The invention relates to the technical field of computer data processing, and discloses an immigrant archive multi-dimensional information integration and intelligent query method, which comprises the following steps: collecting and standardizing multi-source heterogeneous immigrant archive data to generate to-be-processed data; based on the to-be-processed data, constructing an initial event knowledge graph containing element nodes, event nodes and relationships; performing causal relationship discovery and correction on the initial event knowledge graph, and performing mining, confidence updating and logic completion on the causal relationship between events by fusing data statistical analysis and a business process normal form learned from historical data to generate a time sequence causal graph; and receiving a natural language query request of a user, and executing query and reasoning on the time sequence causal atlas. According to the method, the business process logic hidden behind the data can be revealed, intelligent questions and answers for complex problems such as event reasons and influences are supported, and the intelligent level of query and the interpretability of results are improved.

The invention discloses an RAG question and answer self-optimization method based on spatio-temporal knowledge graph reasoning, which comprises the following steps: 1) acquiring a data source, processing the data source, and constructing a domain knowledge graph; 2) obtaining a user question text, and performing multi-hop logical reasoning and semantic association analysis on the user question text by using a graph neural network based on the space-time knowledge graph to generate a structured reasoning path; 3) collecting explicit feedback and implicit feedback of a user, and generating an optimization signal; and 4) automatically updating the domain knowledge graph and / or adjusting parameters of the graph neural network according to the optimization signal. According to the method, knowledge boundaries can be dynamically expanded, manual annotation is reduced, the multi-hop reasoning capability of complex problems is improved, and synchronous optimization of system response speed and accuracy is realized.

The invention provides a question and answer model training method and device, electronic equipment and a storage medium. The method comprises the steps that multiple pieces of training data are acquired; in the process of training the question and answer model according to the sample question, performing repeated fragment identification on a reasoning process generated by performing multiple sampling on the sample question to determine a repeated penalty value of a repeated fragment, and performing reward value calculation on an answer generated by performing sampling on the sample question; performing fusion based on the repeated penalty value and the reward value to form a reward signal, performing normalization processing on the reward signal to obtain a dominant value of current sampling, and introducing the dominant value of the current sampling into a grouping strategy optimization algorithm to construct a loss function; and updating model parameters through gradient back propagation to inhibit repeated thinking behaviors of the question and answer model in the reasoning process, and continuing to perform iterative training on the updated question and answer model. More attention is paid to'effective thinking 'in the training process, and the ability of the question and answer model to solve complex problems is improved.

The invention provides a consultation answering method, electronic equipment and a program product. The method comprises the following steps: receiving a consultation question input by a user; processing the consultation question based on a preset knowledge base through a large model to generate a consultation answer; calculating the confidence of the consultation answer, and if the confidence is greater than or equal to a first preset threshold, replying the consultation answer to the user; if the confidence coefficient is smaller than the first preset threshold value, generating a corresponding processing suggestion reply to the user through the large model according to the consultation question, historical dialogue data between the user and the large model and a knowledge base; new knowledge entries are generated based on consultation questions, consultation answers and real-time data obtained from an external interface through a large model so as to update a knowledge base, complex questions can be processed in time, the content of the knowledge base can be dynamically optimized, the consultation accuracy and timeliness can be ensured, and therefore the workload of staying personnel is relieved.

The invention provides a knowledge graph construction method and device, a question answering method and device, equipment, a medium and a program product, and relates to the technical field of intelligent question answering, the knowledge graph construction method comprises the following steps: cutting an original text into a plurality of text blocks with coherent contents to determine nodes in a knowledge graph; determining edges in the knowledge graph and initial weights of the edges according to a cross reference relationship between contents of the text blocks and / or similarity between themes; based on the relation type to which the edge belongs, adjusting the initial weight to determine the target weight of the edge; and constructing the knowledge graph based on the node, the edge and the target weight. According to the embodiment of the invention, through modular analysis of papers and dynamic perception of the association relationship, multi-level knowledge node and implicit topic association are fused, the logic relationship between modules is accurately quantified, and the constructed knowledge path can effectively capture the logic consistency and cross-document reference transitivity in the document, so that the reliability of the document is improved. And the multi-hop reasoning capability in a complex problem is obviously enhanced.

The invention discloses a reinforcement learning system and method fusing multi-source deep retrieval and reasoning ability, and belongs to the technical field of artificial intelligence. The system comprises a large-model-driven reasoning agent which works in cooperation with a multi-source toolkit integrating local retrieval and network retrieval, and a large-model-driven reasoning agent which works in cooperation with the multi-source toolkit integrating local retrieval and network retrieval. Through a reinforcement learning framework designed by the invention, when the intelligent agent is trained to solve a complex problem, not only can the time of information retrieval be autonomously decided, but also which retrieval tool including a local knowledge base or network search can be intelligently selected and called, and a retrieval result is seamlessly fused into a multi-step reasoning chain. According to the method, the accuracy, timeliness and reliability of an artificial intelligence model in tasks such as question answering and reasoning are effectively improved, and the problems of knowledge illusion and static property of an existing large model are solved.

The invention provides a data processing method and device based on clinical test data, in the application, a prior probability and a historical likelihood of a symptom corresponding to target clinical test data can be determined through a historical clinical database, the prior probability reflects a basic epidemic rate of an indication in a population, and the historical likelihood of the symptom corresponding to the target clinical test data can be determined through the historical clinical database. According to the historical likelihood, association rules between symptoms and indications are mined from historical cases, the association rules and the indications are dynamically updated through a Bayesian formula, an inference chain conforming to clinical logic is formed, then, a complex multi-feature joint probability estimation problem is converted into product calculation of single-feature statistics through conditional independent assumption, and a probability estimation result is obtained. The problem of calculation feasibility under high-dimensional data is solved, probabilistic output provides a quantitative basis for auxiliary determination of indications, a data-driven statistical rule is converted into a clinically understandable auxiliary support tool, and objectivity, consistency and scientificity of diagnosis decisions are effectively improved.

The invention relates to the technical field of intelligent sports products, and discloses an electronic and electrical architecture, a function backup method, a seat adjusting method and a vehicle. Edge nodes are connected with first sensing and interaction components in the same distribution area, and a power distribution and data transmission module is connected with a first edge node corresponding to the same power distribution and communication area; ordered association of components according to areas, power distribution and communication is realized, the complexity and length of wiring harnesses in the whole equipment are greatly reduced, and the cost is saved. And the power distribution and data transmission module is simultaneously connected with the central computing platform and the power supply part, so that data interaction between the central computing platform and the sensing and interaction part can be completed by relying on the edge nodes, and power supply distribution can be realized. The problems of disordered component connection and complex data transmission path in a traditional architecture are avoided, data interaction is more efficient, power distribution is more accurate, a foundation is laid for subsequent software reuse, and the cost of repeated development of different AI sports equipment architectures is reduced.

The invention discloses an electric power field multi-step intelligent reasoning question answering system and method based on problem decomposition and self-adaptive iteration mixed retrieval, and aims to solve the problems that existing electric power question answering is complex, problem reasoning is not coherent, multi-step knowledge association is weak, retrieval noise is large, and electric power safety regulations are prone to being violated. The method comprises the following steps: S1, constructing a'question-thinking chain-answer 'fine tuning data set in the power field, and performing fine tuning on a Qwen3-32B model; s2, disassembling the complex problem of the user into an ordered sub-problem sequence; s3, dynamically judging a retrieval demand based on an electric power professional vocabulary library, and generating an intermediate answer by adopting sparse and dense fused mixed retrieval; and S4, verifying the candidate answer through the electric power safety regulation hard logic constraint library, and triggering negative feedback regeneration if the candidate answer is illegal until a safety compliance answer is output. According to the method, the accuracy, traceability and safety compliance of complex fault diagnosis and operation guidance questions and answers are improved through'adaptive iterative hybrid retrieval + safety regulation hard constraint 'closed loop.

A mining drilling system, wherein an active drill rod (10) comprises a limiting section (104) and an anti-rotation section (103), a chuck (14) is provided at one end of a main shaft (15), a front end cover (13) is provided at one end of the chuck (14), the chuck (14) clamps on the limiting section (104), the front end cover (13) is slidably connected to the anti-rotation section (103), the front end cover (13) drives the active drill rod (10) to rotate, and a staged hydraulic system controls the clamping pressure of the chuck (14) on the limiting section (104); a front clamping device (2) comprises a front support plate (203) and a rear support plate (205) arranged spaced part, a through hole is formed in each of the front support plate (203) and the rear support plate (205), and is provided with an opening having a width greater than or equal to the diameter of a large drilling tool; a swing body (22) is provided in the front support plate (203) and the rear support plate (205) and can swing outside the front support plate (203) and the rear support plate (205); a tilt sensor (947) and a tilt sensing plate (948) in a positioning system determine whether a rotary arm (96) of a main manipulator (9) drives a gripper (97) to flip towards a frame (3); and a level sensor (962) and a level sensing block (961) determine whether the main manipulator (9) is in a set tilt angle position. The problem of complex operations in the construction of existing drilling equipment is solved.