41results about How to "Realize organic integration" patented technology

The invention relates to an unmanned ship supporting multiple underwater execution mechanisms and a cooperative control method of the unmanned ship, and belongs to the field of artificial intelligence and unmanned ships. The system is composed of an unmanned ship, a plurality of underwater execution mechanisms and a cable. The method comprises the following steps: S1, initializing a deep reinforcement learning network; s2, the unmanned ship reaches the operation area to release the underwater execution mechanism; s3, the unmanned ship receives the operation task; s4, the underwater executing mechanism obtains the current state and feeds back the current state to the unmanned ship; s5, rewards of the constraint conditions are constructed; s6, generating an operation task distribution action and issuing the operation task distribution action to an underwater execution mechanism; s7, the underwater execution mechanism obtains a real-time state; s8, constructing a reward of the physical information; s9, generating an execution action and executing the execution action through an execution device; and S10, repeating the steps S3-S9 until all the operation tasks are completed. According to the method, organic fusion of constraint conditions and physical information can be realized, and automatic, optimized and cooperative control of multiple underwater execution mechanisms in an unsupervised complex environment is realized.

The invention discloses a transformer fault identification method, system and device and a medium, and relates to the technical field of transformer fault identification, and the method comprises the steps: collecting an audio signal of a transformer, and extracting a chaotic domain multi-scale parting dimension feature, a time domain zero crossing rate feature and a frequency domain fractional order spectrum entropy feature of the audio signal; constructing a biological heuristic multi-domain neural network model; the biological heuristic multi-domain neural network model comprises a spiking neural network, a bionic convolutional layer and a chaotic neural network; inputting the extracted audio signal features into a biological heuristic multi-domain neural network model, and identifying the fault category of the transformer; according to the method, the accuracy of fault identification is improved, and fault diagnosis can be stably carried out in a complex and changeable operation environment.

The invention provides a forest fire spreading intelligent prediction and active intervention control method and system, and relates to the technical field of forest fire management. The intelligent prediction and active intervention system for forest fire spreading comprises a data acquisition module, a data preprocessing module, an intelligent prediction module, a model optimization and verification module, an active intervention decision module, an intervention strategy optimization module, a real-time monitoring and evaluation module, a user interaction interface module and a communication module. Through a series of core technologies of highly integrating multi-dimensional data acquisition, intelligent data analysis and prediction, automatic intervention control, dynamic optimization adjustment and the like, efficient and accurate prediction of the forest fire spreading trend is realized. The system not only can comprehensively collect multi-dimensional data including meteorological conditions, landforms, vegetation distribution and the like in real time, but also utilizes advanced deep learning and machine learning algorithms to intelligently analyze the data, so that a high-precision forest fire spreading prediction model is constructed.

This utility model relates to a blood pressure monitor, disclosing a multifunctional blood pressure monitor including a main unit and a secondary unit. A cuff is installed at the lower end of the main unit, and a first main control board is installed inside the main unit. The secondary unit contains a second main control board and a battery, which is connected to and powers the second main control board. Electrodes are also installed on the secondary unit and connected to the second main control board. The main unit and the secondary unit are detachably connected. When the secondary unit is mounted on the main unit, the battery is connected to the first main control board via the second main control board. The battery in the secondary unit not only ensures the normal operation of its own ECG and heart sound measurement functions but also, when mounted on the main unit, powers the first main control board of the main unit via the second main control board. This power supply mode solves the problem of separate power supply for the main unit and achieves the organic integration of blood pressure, ECG, and heart sound measurement functions. Users do not need to prepare multiple power supply devices, reducing operating costs.

The invention discloses a nuclear medicine-oriented image intelligent processing system and method, and relates to the technical field of nuclear medicine image processing, and the main scheme is as follows: receiving original image data and patient medical history, age and gender data; extracting feature maps of different levels of the original image by using a convolutional neural network, calculating a mean value and a standard deviation to determine a fusion weight coefficient, and obtaining a fused feature map; analyzing and processing the feature map to obtain an input feature vector, generating a clinical information vector in combination with medical history and other data, fusing the clinical information vector to obtain a comprehensive feature vector, and calculating an output probability vector to perform preliminary focus detection; calculating a lesion judgment index according to the output probability vector, and when a preliminary judgment condition is met, calculating an uncertainty degree value and a dispersion degree value to assist in judging whether a lesion exists or not; and generating a detailed diagnosis report according to a detection result. Multi-source data and an advanced algorithm are integrated, the accuracy and reliability of nuclear medicine image focus detection are improved, and powerful support is provided for disease diagnosis and treatment.

This invention relates to a gait recognition method and system based on multi-branch collaborative learning and spatiotemporal representation enhancement, comprising: acquiring gait contour map sequences and constructing them into a dataset; constructing a gait recognition model, including a dynamic temporal adaptive module, an enhanced 3D feature extraction network branch module, a global spatiotemporal feature extraction network branch module, a multi-scale spatiotemporal feature extraction network branch module, and a multi-layer adaptive fusion module; the enhanced 3D feature extraction network branch module includes a multi-layer enhanced 3D feature extraction network, the global spatiotemporal feature extraction network branch module includes a multi-layer global spatiotemporal feature extraction network, and the multi-scale spatiotemporal feature extraction network branch module includes a multi-layer multi-scale spatiotemporal feature extraction network; jointly training the gait recognition model using improved triplet loss and cross-entropy loss to obtain a trained gait recognition model; and using the trained gait recognition model to extract identity features to complete gait recognition.

The present application relates to the technical field of aluminum electrolysis, and provides an aluminum electrolysis cell damage inversion method based on a machine learning algorithm, comprising the following steps: obtaining current data of an aluminum electrolysis cell through a fiber-optic current sensor, and obtaining temperature data of the aluminum electrolysis cell; performing discharge area division according to a discharger of the aluminum electrolysis cell; performing area division on the current data and the temperature data, and performing feature extraction on the current data and the temperature data; establishing a physical information forward model based on a neural network, and associating and mapping a damage state vector with current feature data and temperature feature data through the physical information forward model; constructing a cathode joint loss function and an anode joint loss function; respectively performing iterative solution on the cathode joint loss function and the anode joint loss function through an optimization algorithm, outputting an optimal damage state vector, and generating a damage space distribution result of the electrolysis cell. The present application can realize online inversion and spatial distribution visualization of anode and cathode damage states.

The application discloses a traditional Chinese medicine polycystic ovary syndrome data structuring method based on a knowledge graph, and relates to the technical field of medical big data structuring.The application establishes corresponding personal experience diagnosis graphs based on the polycystic ovary syndrome diagnosis records of various traditional Chinese medicine experts, aligns the contents of the personal experience diagnosis graphs, and then generates multiple consensus knowledge areas and differential knowledge areas, obtains a multi-modal heterogeneous knowledge graph, and establishes a symptom ontology tree corresponding to the polycystic ovary syndrome, and then acquires real-time medical record condition data of a patient, extracts conditional nodes from the real-time medical record condition data, matches the conditional nodes with symptom nodes in the symptom ontology tree, extracts a feature symptom mapping sub-tree from the symptom ontology tree according to a matching result, matches the feature symptom mapping sub-tree with the multi-modal heterogeneous knowledge graph, and then outputs a consensus diagnosis scheme according to a matching result.

The application provides a live conference real-time subtitle generation method and system fused with AI, relates to the field of real-time subtitle generation, and comprises the following steps: collecting an audio stream and dividing the audio stream into segments, assigning a sound source identifier to each audio subsegment after sound source separation and identification; performing speech recognition on the identified audio and associating the sound source to generate identified text; correcting text ambiguity by using a context knowledge base containing a subject word table and historical text; cutting the text according to an audio energy envelope to form a subtitle unit; calculating a subtitle display time, assigning a vertical offset to subtitles with overlapping time but different sound sources to realize spatial separation; adjusting the subtitle display coordinates in combination with a disabled area determined by a video frame foreground, and rendering and outputting. The method realizes clear distinction and accurate presentation of multi-speaker subtitles, and improves the readability and user experience of conference live subtitles.

This invention relates to the field of NLP technology and discloses a plug-in function testing method for a pre-trained power system model based on NLP. The method includes: receiving a technical supervision query question and performing vector encoding and retrieval to obtain an initial retrieval result set; obtaining reference text with standard citation annotations through weighted sorting and concatenating it with multi-level prompt word templates to obtain domain-structured prompt words; performing a bundle search using a large technical supervision domain model fine-tuned with LoRA low-rank adaptation to generate candidate answer texts; and conducting quality assessments including citation integrity detection, logical consistency detection, and entity illusion detection to obtain a qualified technical supervision standard answer. This method solves the technical problems of low standard retrieval accuracy, poor answer accuracy, lack of citation tracing, and insufficient domain customization capabilities in existing technologies, providing a complete technical solution for intelligent applications in the field of power technical supervision.

The application relates to the technical field of liquid crystal display panel detection, and discloses a liquid crystal display panel visual detection system and method, which comprises the following steps: S1, acquiring real-time image information of a liquid crystal display panel and production parameters of a production line; S2, performing multi-dimensional analysis according to the real-time image information to acquire multi-dimensional evaluation indexes; and S3, establishing a panel qualification judgment model according to the production parameters, inputting the multi-dimensional evaluation indexes into the panel qualification judgment model, and obtaining a detection result. According to the multi-dimensional analysis of the liquid crystal display panel based on the real-time image information, the panel qualification judgment model is established according to the production parameters of the production line, the quality of the liquid crystal display panel is judged through the panel qualification judgment model and the multi-dimensional evaluation indexes, the 'apparent quality' and 'process health degree' of the panel can be comprehensively reflected, the misjudgment caused by single-dimensional information can be avoided, the organic fusion of multi-source heterogeneous information is realized, and the robustness of decision-making is improved.

The invention belongs to the field of rural property trading, particularly relates to a rural property trading platform, and aims to solve the problems that information related to existing rural property trading is stored in different systems or platforms in a scattered manner, so that data management and integration are difficult, data acquisition and analysis complexity is increased, and the cost is low. In order to solve the problems that rural resource assets, right confirmation data, economic contracts and transaction data are difficult to organically integrate, and comprehensive analysis and decision support cannot be performed on a unified platform, the invention provides the following scheme: the system comprises an information registration module, the information registration module is connected with a publishing module, the publishing module is connected with an auditing module, and the auditing module is connected with a cloud server. According to the system, rural resource assets, right confirmation data, economic contracts and transaction data can be organically fused, so that organic fusion of dynamic data and static data is realized, and the efficiency and transparency of rural property right transaction are improved.

A license plate lamp suitable for an electric vehicle comprises an upper cover, a lower cover matched with the upper cover and a license plate lamp body, the license plate lamp body is arranged in a closed space formed by the upper cover and the lower cover, and an electric vehicle fixing connector connected with the electric vehicle is arranged at the tail end of the upper cover. A license plate lamp transparent cover and a projection lamp transparent cover are arranged on the lower cover, and the included angle between the projection lamp transparent cover and the projection lamp transparent cover in the clockwise direction is an obtuse angle. The independent projection lamp is introduced into a traditional license plate lamp structure, the license plate lamp transparent cover and the projection lamp transparent cover are arranged on the lower cover in a matched mode, and the clockwise included angle between the license plate lamp transparent cover and the projection lamp transparent cover is the obtuse angle, so that light rays of the license plate lamp directly face a license plate area, light rays of the projection lamp are projected to the ground, and LOGO or pattern display can be formed. According to the structure, one lamp body has two functions, the requirements for traffic compliance and appearance individuation are both considered, the whole vehicle design sense is improved, and organic integration of the functions is achieved through the included angle design and the lamp body integration mode.

The application provides a proppant migration state prediction method and system based on images, and relates to the technical field of oil and gas development.The method comprises the following steps: processing and predicting a real-time image sequence currently collected by using a prediction neural network model to obtain current placement form prediction data of the proppant in a complex fracture; obtaining a regulation instruction based on the current placement form prediction data, and sending the regulation instruction to a field fracturing construction control unit to close-loop control the proppant migration process.The application realizes accurate prediction and closed-loop control of the proppant migration state through downhole image collection, preprocessing, segmentation correction, multi-source data fusion modeling and real-time prediction and regulation.

The invention provides a Web unauthorized vulnerability detection system based on a large model, which comprises a crawler module used for simulating form elements and clickable webpage buttons to crawl comprehensive business URL (Uniform Resource Locator) interface information, the vulnerability verification module is used for carrying out vulnerability detection on a business URL interface by utilizing double accounts with different user identity information to obtain a vulnerability unauthorized interface and an unauthorized vulnerability interface, and is used for generating a report based on the unauthorized vulnerability interface and the vulnerability unauthorized interface, a large model technology is introduced, and the vulnerability verification efficiency is improved while the capability of a single step point is improved. And organic fusion of three steps of crawler crawling, vulnerability verification and report generation is also realized.

The application provides a preparation method of fluorinated chitosan-based nanocarrier PTX-FP@FCS-NPs, which comprises the following steps: synthesizing fluorinated chitosan, dissolving Tween 80 and the fluorinated chitosan in an acetic acid aqueous solution, stirring to obtain a mixed solution, adding 5, 10, 15, 20-tetrakis(3, 5-bis(trifluoromethyl)phenyl) porphyrin and paclitaxel into the mixed solution after dissolving, stirring and centrifuging, taking the precipitate, and washing the precipitate with distilled water to obtain the fluorinated chitosan-based nanocarrier PTX-FP@FCS-NPs. 19 The nanocarrier has the characteristics of F MRI / FLI bimodal imaging, pH / laser dual-response drug release, and efficient co-loading of paclitaxel and porphyrin, and under the stimulation of laser, the nanocarrier effectively inhibits tumor growth through multi-mechanism synergistic effect and has good biological safety.

The application discloses an embryo in-vitro culture and in-situ monitoring system and method, and belongs to the field of online monitoring of embryo in-vitro culture. The system comprises: a high-precision microscope, which is a table type fixed structure and is provided with a stage; a culture unit, which is based on the structural design of the stage and is arranged on the stage, is used for accommodating embryos and providing a culture environment required by in-vitro development of the embryos; a thermostat, which seals the related part of the microscope containing the stage and provides a stable temperature environment for the culture unit; and a control unit, which is connected with the culture unit, is used for providing a multi-channel perfusion culture pipeline and driving and can perform time-periodic perfusion culture. The application wraps the microscope by the thermostat and adopts cascade closed-loop temperature control to provide a stable temperature and humidity environment; realizes fine shear force stimulation through time-periodic perfusion; realizes in-situ high-resolution imaging through adaptation of the high-precision microscope, does not need to transfer embryos, and significantly improves imaging quality and experimental efficiency.

The application relates to the technical field of data processing, and discloses a soil profile database-based organic carbon density prediction method and system. The method comprises the following steps: collecting soil profile data, obtaining soil attribute parameters and environmental parameters of each depth layer, and obtaining a profile data set; dividing samples into different groups according to pH values and texture parameters to obtain a classification matrix; training a bulk density prediction model in each group, interpolating the missing values of the bulk density, and obtaining complete bulk density data; establishing a transfer function, substituting the organic carbon content, the bulk density value and the layer thickness, and calculating the organic carbon density of each depth layer; and weighting and accumulating the organic carbon density of each depth layer according to the layer thickness to obtain the profile organic carbon storage. The application solves the problems that, in the prior art, a global unified model leads to low bulk density prediction accuracy, and the heterogeneity of soil types and the depth effect are not considered, resulting in inaccurate organic carbon density estimation.

This invention discloses an esterase-responsive nanogel-modified bioprosthetic valve, its preparation method, and its application, belonging to the field of bioprosthetic valve technology. This invention solves the problem of balancing the anti-infective properties, biocompatibility, and high surface modification rate of bioprosthetic valves. The invention uses ester-containing methacrylates and antibiotic drugs as raw materials to synthesize esterase-responsive monomers, then synthesizes esterase-responsive nanogels, and then attaches them to the surface of the bioprosthetic valve. Under pathological conditions with high esterase concentrations, the ester bonds decompose, releasing the antibiotic drugs in situ, thereby treating bacterial infections, reducing inflammatory cell infiltration, and improving the anti-infective and anti-inflammatory properties of the bioprosthetic valve. Furthermore, the nanogel contains a large number of hydrophilic groups, forming a hydration layer on the bioprosthetic valve surface, effectively reducing the risk of thrombosis and coagulation, and resisting bacterial adhesion. The prepared bioprosthetic valve exhibits excellent anti-infective, anticoagulant, anti-calcification capabilities and stability.

The invention relates to the technical field of data processing, and discloses a breast cancer risk assessment and intervention method based on a multivariate coupling model, which comprises the following steps: quantifying the interaction between environmental parameters such as temperature, humidity and air pressure and human energy metabolism, and quantifying the interaction between food cold and heat attributes, kinetic energy consumption and midnight-noon ebb-flow rhythm; real-time prediction and hierarchical management and intervention of deterioration risks are realized by quantifying a dynamic balance relationship between blood pressure energy and breathing energy, adopting a synergistic effect of a classical prescription, an acupuncture therapy, guide movement and the like according to a principle and adopting a machine learning algorithm. According to the invention, a multi-dimensional correlation and regulation coupling model of environment, psychology and physiology is established, and breast cancer disease prediction and tumor prognosis evaluation are realized.

The utility model discloses a highway dam type roadbed structure with a graded water drainage and storage function, and aims to overcome the defects of low water storage efficiency and blockage of a drainage system in the prior art. The structure comprises a roadbed body, and a roadbed cushion layer is laid at the bottom of the roadbed body; the upstream face of the roadbed body is of a slope-shaped structure and is provided with slope protection measures; a drainage square culvert and a water control gate are arranged in the roadbed body. Through the innovative dam type roadbed structure design, the graded water drainage and storage system, the low-cost construction and maintenance scheme, the eco-friendly design and the optimized construction process, the functionality, stability and ecological benefits of the highway dam type roadbed in the loess gully area are remarkably improved, and meanwhile the construction and maintenance cost is reduced.

The present application belongs to the field of early warning technology, and particularly relates to a mine multi-system collaborative early warning method and system based on three-dimensional GIS digital twinning. The method comprises: obtaining time series monitoring data of multiple monitoring systems for standardization, and mapping to a three-dimensional GIS model to construct a space-time data matrix; calculating a prior risk weight based on fault and ventilation information to generate a spatial risk weight matrix; constructing an objective function containing a data fidelity term and a mixed sparsity constraint term, calculating the norm ratio after solving, adjusting the sparsity component weight when the threshold value is exceeded, and applying a negative correlation penalty factor to the energy maximum overlap group; using the risk weight reciprocal to weight the constraint term, and using the alternating direction multiplier method to obtain a sparse solution matrix, and comparing the multi-level early warning threshold and triggering the early warning in the model. The scheme of the present application can improve the accuracy of mine multi-source monitoring data processing and the reliability of safety early warning, and enhance the accuracy and intuitiveness of mine disaster collaborative prevention and control.

The application discloses a kind of intelligent electric screwdriver compliance compensation and driving pose collaborative topology optimization method, constructs intelligent electric screwdriver rigid-flexible coupling dynamics model, the coupling relationship between rigid driving movement, compliance deformation and external contact reaction force is characterized;Further establish the multi-objective collaborative topology optimization model with topological optimization material density variable and driving pose variable as joint optimization variable;Again based on adaptive element optimization framework with element controller is solved by adaptive collaborative optimization, obtains optimal structure topological configuration, optimal driving pose reference, optimal time-varying stiffness matrix and optimal time-varying damping matrix;Finally, the optimal solution above is injected into the collaborative control law containing compliance deformation direct feedback item, executes closed-loop compliance compensation and pose collaborative control.The application realizes the synchronous optimal matching and adaptive regulation and control of intelligent electric screwdriver structure topology, driving pose and compliance characteristics, significantly improves pose accuracy, torque control stability and compliance compensation response performance.

The invention provides an oil and gas intelligent pipe network digital conversion method and device and a storage medium, and relates to the technical field of digital information transmission. The method comprises the following steps: dividing a pipe network into a physical level, an energy level and an information level, constructing a digital model group, obtaining multiple pieces of equipment facility data from the physical level, converting the equipment facility data into corresponding energy flows through a physical-to-energy flow model, converting the energy flows into information flows of the information level through an energy-to-information flow model, and establishing a digital model group; and performing optimization decision analysis on the information flow through the information flow model, outputting a control instruction, converting the control instruction into a physical control quantity through the information flow physical control quantity model, and feeding back the physical control quantity to equipment corresponding to the physical hierarchy. According to the invention, the physical entity and the information space of the oil and gas intelligent pipe network and the energy space for implementing the full-service process of the intelligent pipe network are interacted and controlled in a digital information manner by using the digital model group, so that the informatization management capability of the oil and gas intelligent pipe network is improved.

The application provides a kind of based on knowledge graph and RAG collaborative enhancement's guest station user query response method and device, first to user query is classified, for real-time data query class and response level determination class respectively call real-time data interface by big model answer or pass through response level determination model output response level;For knowledge question and answer class and emergency scheme generation class, then parallel execution based on RAG's semantic retrieval and based on knowledge graph's subgraph retrieval, the target text block, knowledge subgraph and real-time data retrieved are fused into structured context, and input based on ReAct framework's multi-round iteration reasoning agent, finally generate the specific question and answer result or structured emergency disposal scheme.The application realizes the organic fusion of static preplan knowledge, domain knowledge graph and real-time dynamic data, improves the factual accuracy, logical coherence and scene adaptability of emergency scheme generation, reduces the noise interference and logical breakage risk caused by single retrieval enhancement generation.

The present invention discloses a high-precision fusion positioning method for Wi-Fi RTT / RSS / map of a smart phone, comprising the following steps: S1, using BP neural network to construct an RTT ranging error compensation model; designing the optimal Wi-Fi AP layout strategy, maximizing the positioning performance of a limited number of APs, and using weighted adaptive least squares method to obtain RTT ranging positioning results; S2, through the Wi-Fi signal path loss model, constructing an artificial Wi-Fi RSS / RTT fingerprint database based on indoor grid map data and Wi-Fi base station location, introducing K-Means clustering analysis algorithm, and using weighted K nearest neighbors to carry out fingerprint positioning; S3, using particle filtering to fuse the two positioning results; introducing map data to carry out "point constraints" and "line constraints" to obtain fusion positioning results. The present invention can improve the stability and accuracy of Wi-Fi FTM ranging positioning.

A method for fault cross-system propagation analysis based on performance model, the first step: multi-domain system performance model construction; based on Modelica, the construction, integration and verification of each domain system model are completed; the second step: fault mode and influence analysis; the typical fault mode of components in each domain system and the fault influence relationship between components are identified, and the fault propagation path is determined; the third step: fault propagation analysis based on directed graph; the edge betweenness of each directed edge is calculated and taken as the fault propagation characteristic parameter on the structure level; the fourth step: fault cross-system propagation analysis based on performance model; based on the function failure logic table, the performance influence simulation between multi-domain components is carried out, the performance influence degree of the fault source component on the affected component is analyzed, and the performance characteristic parameter describing the components between each domain is obtained; the fifth step: fault cross-system propagation strength evaluation; the fault propagation structure characteristic parameter and the performance characteristic parameter are normalized and fused, a fault cross-system propagation strength model is constructed, and the key propagation path is identified.

This invention discloses a deep learning-based simulation method for scheduling electronic atomization production lines, comprising: S1, collecting and preprocessing historical production data from the electronic atomization production line to construct a standardized dataset; S2, constructing and training an electronic atomization production line scheduling model using a multi-dimensional spatiotemporal collaborative Transformer network; S3, inputting real-time production line status information into the trained electronic atomization production line scheduling model and evaluating production line operation indicators to generate an optimized set of candidate scheduling strategies; S4, constructing a multi-objective simulation environment for the electronic atomization production line and simulating the execution of the optimized set of candidate scheduling strategies; S5, using an improved multi-objective ant colony optimization algorithm to select the optimal scheduling strategy; S6, applying the optimal scheduling strategy to the actual production line and collecting feedback information in real time; S7, continuously iteratively optimizing the scheduling model based on the feedback data. This invention improves production line operating efficiency, resource utilization, and scheduling response capabilities.

The invention discloses an intelligent diagnosis method for sedimentation diseases of a drainage pipeline, and the method comprises the steps: collecting data through a full-scale test, and carrying out the dimension raising of a one-dimensional overflowing characteristic index into two-dimensional image data with space information through a data processing module based on a Grubm angle and a field. And constructing a data set containing pipeline siltation information. And constructing a convolutional neural network module through the convolutional layer and the pooling layer to extract spatial information in the image. And extracting time characteristics of the one-dimensional data by utilizing a gating circulation unit. A self-adaptive moment estimation optimizer is adopted to train a drainage pipeline siltation disease intelligent diagnosis model, and hyper-parameters are automatically optimized through a self-adaptive variation particle swarm optimization algorithm in the training process. The optimized hyper-parameters are used for training a drainage pipeline siltation disease intelligent diagnosis model, and a diagnosis method capable of intelligently predicting whether the pipeline is silted or not and the siltation degree of the pipeline is provided. The working efficiency of water pipeline siltation inspection can be improved, and the requirements of modern city management are met.

The present invention discloses an automated control method for the production of tension bands, which belongs to the field of cutting control, and includes: setting a bidirectional cutting device for cutting the tension band, which is set on a double-line conveyor belt; obtaining the production parameter information of the preset tension band, extracting the first cutting length and the second cutting length, and if the two cutting lengths are not the same, obtaining the first conveying parameter and the second conveying parameter; inputting the first conveying parameter and the first cutting length, the second conveying parameter and the second cutting length into a cutting automatic control model, obtaining the first cutting parameter and the second cutting parameter; and performing cutting control according to the first cutting parameter and the second cutting parameter. The present invention solves the technical problems that the existing tension band cutting device has low cutting efficiency, unstable cutting accuracy, and is difficult to meet the requirements of efficient and precise cutting production, and achieves the technical effect of improving cutting efficiency through a bidirectional cutting device, ensuring the stability of cutting accuracy, and realizing efficient and precise cutting production.