186 results about "Self repair" patented technology

The invention discloses an intelligent management system and method for knowledge graph quality evaluation and self-repairing, belongs to the technical field of knowledge graphs, and aims to solve the problems that in traditional knowledge graph management, manual auditing efficiency is low, an effective automatic repairing means is lacked, and data complexity and real-time changes are difficult to deal with. The system firstly collects multi-source heterogeneous data in a target field, cleans the data through a deep learning noise recognition model, extracts entities and relationships by using a natural language processing technology, and adds metadata to convert the entities and relationships into graph structure data; then, a graph framework is defined based on the ontology, entity semantic alignment is achieved in combination with a graph neural network, and a knowledge graph is constructed by complementing implicit relations with the help of a pre-training language model. Then, the quality of the atlas is quantitatively evaluated through a four-layer quality evaluation system, meanwhile, a repair scheme is generated based on vulnerability feature extraction, knowledge base matching and decision fusion, and intelligent self-repair is achieved; the map can be monitored in real time and evaluated regularly, a repair strategy and a knowledge base are optimized through reinforcement learning, it is ensured that the map is kept accurate and time-efficient for a long time, and the practical value is improved.

The invention relates to a power equipment self-repairing surge protection system based on artificial intelligence, and the system is characterized in that a surge detection module is connected between a live wire and a protection ground wire of power equipment, collects voltage and current data, and transmits the data to an artificial intelligence analysis unit; and the artificial intelligence analysis unit extracts the surge characteristic parameters, generates protection strategy parameters through a deep neural network, and controls the trigger thresholds of all levels of protection devices in the programmable protection circuit. The programmable protection circuit comprises a gas discharge tube capable of adjusting trigger voltage, a metal oxide varistor and a transient voltage suppressor diode, and is used for discharging surges with different energies step by step. The resettable fuse cuts off the circuit when the temperature exceeds a threshold value and recovers conduction after the temperature is reduced. And the controller receives and applies the protection strategy parameter output by the artificial intelligence analysis unit, and dynamically adjusts the trigger threshold value of the protection device, so that the response and protection performance of the system to the surge is improved, and the self-repairing and stable operation of the power equipment are realized.

The invention relates to the technical field of wireless sensor networks, and discloses an automatic maintenance method for wireless sensor network nodes in a mine laneway, which comprises the following steps: S1, network topology structure design: establishing a wireless sensor network consisting of sensing nodes, relay nodes and gateway nodes, the sensing nodes being distributed in the mine laneway, the relay nodes being distributed in the mine laneway, and the gateway nodes being distributed in the mine laneway; the data acquisition node is used for acquiring environment data, the relay node is used for multi-hop transmission of the data, and the gateway node is used for communicating with a ground monitoring system; s2, a fault detection mechanism: integrating a fault detection module in each node; s3, a self-repairing mechanism: when the node detects a fault, automatically triggering the self-repairing mechanism; s4, performing fault early warning and reporting; and S5, energy consumption management and optimization: the system integrates an energy consumption management module in the node. Through the integrated fault detection module and the self-repairing mechanism, the system can automatically identify and try to repair the fault when the fault occurs, so that the downtime of the system is reduced, and the continuous and stable operation of the network is ensured.

The invention belongs to the technical field of building materials, and particularly relates to self-healing high-toughness concrete and a preparation method thereof, in particular to a method for realizing self-healing of the high-toughness concrete by utilizing an excessive precursor alkali-activated gel system, and self-repairing of the cracked concrete is realized by excessively preparing a precursor of a gel material. The toughness of the concrete is enhanced in combination with hybrid fibers, so that the novel self-healing concrete which is low in cost and integrates control and repair is realized. When the amount of the polymer precursor is 900 parts, the tensile strength of the concrete can reach 8.9 MPa or above, the compressive strength can reach 100 MPa or above, the self-healing rate of the concrete in 28 days can reach 98%, and the mass loss rate after 50 freezing and thawing cycles is only 0.66%.

The invention provides a self-adaptive safety self-healing system based on artificial intelligence, and aims to improve the safety protection capability and the self-repairing capability of an information system. The system comprises a client Agent module, a secure transmission module, a data analysis and anomaly detection module, a self-healing strategy management module, an execution module and a monitoring display module. The client Agent module collects data such as system logs, network flow and resource use, and predicts resource changes through a long short-term memory (LSTM) network model. And the secure transmission module adopts a TLS protocol and a block chain technology to ensure the integrity and security of the data. And the data analysis and anomaly detection module identifies threat behaviors through an Isolation Forest algorithm and a deep learning technology, and automatically generates a security event report. And the self-healing strategy management module generates a self-adaptive repair scheme based on an AI analysis result, and the system realizes efficient anomaly detection and self-healing repair through intelligent analysis and self-adaptive adjustment, and is suitable for dynamic security protection in a complex network environment.

The invention discloses a preparation method of modified self-extinguishing insulating oil with flame-retardant and self-repairing functions. Wherein the insulating liquid is mixed oil of mineral oil and palm oil-based modified natural ester, and the inherent high flash point characteristic of the natural ester improves the fireproof safety of the insulating oil. The modified hexagonal boron nitride (h-BN), the magnesium hydroxide nano material and the microcapsule repairing agent are added into the insulating oil, and the h-BN can capture free electrons in the oil, so that the formation and expansion of electric arcs are inhibited, and the breakdown voltage is improved. Magnesium hydroxide is heated to decompose and absorb heat, the fault temperature is reduced, and therefore the arc self-extinguishing effect is achieved. Under the action of a high electric field and a high temperature, the capsule wall of the microcapsule repairing agent is broken, meanwhile, the repairing material is released, a chemical reaction is carried out, and the insulating property of the insulating oil is repaired. The modified insulating oil prepared by the invention has high insulating strength and high flame retardance, and also has a performance self-repairing function, so that the service life of the insulating oil is prolonged.

The invention relates to the field of high polymer materials, and discloses a high-wear-resistance elastomer sole material and a preparation method thereof.The material comprises an elastomer matrix and surface-modified boron nitride nanosheets; the elastomer matrix comprises a first dynamic network and a second dynamic network which are formed through crosslinking of dynamic covalent bonds, and the first dynamic network and the second dynamic network are based on different types of dynamic covalent bonds and have different dissociation activation energy barriers or external stimulus response conditions. The surface-modified boron nitride nanosheet and the second dynamic network form a selective interface enhancement effect; the preparation method comprises the steps of polymer functionalization, nanosheet surface modification, melt blending reaction net forming, forming and the like. The obtained elastomer sole material not only has excellent wear resistance and mechanical properties, but also can realize self-repair of graded response aiming at damages of different degrees, and the service life of the material is remarkably prolonged.

The invention relates to a multi-gray-scale printing ink supply system monitoring diagnosis and intelligent pressure regulation strategy, and aims to provide a multi-gray-scale printing ink supply system monitoring diagnosis and intelligent pressure regulation strategy through an intelligent dynamic pressure regulation algorithm, a self-adaptive pressure balance mechanism, multi-parameter fusion control, modular design, an intelligent fault diagnosis and self-repairing function and gray-scale printing application. Intelligent pressure regulation of a multi-nozzle ink supply system in the gray-scale printing process is achieved, the printing quality and efficiency are improved, gray-scale printing is mainly conducted on a sand mold, the ink jet amount of the outer contour of the sand mold is large, and the strength of the sand mold is improved; the inner contour ink-jet amount is small, and the sand mold air permeability is reduced.

The invention relates to an intelligent vending machine and a remote management system. The intelligent vending machine and the remote management system comprise the intelligent vending machine and a remote management platform. The intelligent vending machine is provided with a movable goods shelf or a mechanical arm used for storing and dynamically adjusting the positions of commodities. The sensor is used for monitoring commodity inventory, mechanical part states and environmental parameters, and is in bidirectional communication with the remote management platform through the communication module. The remote management platform comprises a commodity configuration module, generates a commodity position adjustment instruction based on real-time sales data, sales promotion activities or customer behavior analysis, and sends the instruction to the intelligent vending machine to realize real-time commodity layout adjustment. The system further comprises a fault prevention and self-repair module which analyzes sensor data through machine learning, predicts potential faults of the mechanical part and executes self-diagnosis. And the customer service module provides a video call function and realizes purchase suggestion, fault processing and refunding and changing services. According to the invention, intelligentization and adaptive optimization of commodity management are realized, and the operation efficiency and user experience of the vending machine are improved.

The invention discloses a Java code generation and self-repairing system, which comprises a natural language processing module, a data processing module, a self-repairing module and a self-repairing module, the code generation module is used for generating code snippets or complete codes according with Java grammar specifications and coding habits through a deep learning model; and the intelligent repair module is used for performing static analysis and dynamic test on the Java code to find errors and defects in the code. According to the method, advanced technologies such as deep learning and natural language processing are introduced, high-quality and maintainable codes are automatically generated according to natural language description or specific requirements of developers, and the flexibility and maintainability of code generation are improved.

The invention provides a double-layer self-healing microcapsule, a self-healing asphalt mixture and a preparation method of the double-layer self-healing microcapsule and the self-healing asphalt mixture, and aims to solve the technical problem that an asphalt pavement is easy to damage and difficult to repair fundamentally. The double-layer self-healing microcapsule shell is broken under the change of stress or temperature, and a healing agent is automatically released to a damaged part, so that a quick and accurate self-repairing function is realized; the self-healing asphalt mixture disclosed by the invention is excellent in pavement performance, simple in preparation process and non-toxic and harmless in raw materials, can enhance the high-temperature stability, low-temperature crack resistance, water stability, maximum load ratio and crack healing rate of an asphalt pavement, and has great significance in prolonging the service life of the asphalt pavement.

The present invention discloses a bio-based coating material with super mechanical properties and self-repairing modification and a preparation method thereof, and belongs to the technical field of controlled release fertilizer production. The bio-based coating material of the present invention is made of the following raw materials in parts by weight: 100-120 parts of coating liquid matrix, 0.5-1 parts of toughening agent, and 5-10 parts of self-repairing material. The present invention uses livestock farm waste as the raw material for making coated controlled release fertilizer membrane shell, which reduces costs and promotes the recycling and reuse of waste. By introducing metal ions into the covalent network, the stability of the network and the mobility of covalent bonds and hydrogen bonds are improved, the metal ions and the toughening agent undergo complexation reaction, and the presence of multiple complex molecules promotes the dissipation of energy when the covalent bonds are broken and reorganized, giving the coating super mechanical properties and the ability to continuously self-repair damaged areas at room temperature, effectively solving the problem of poor elasticity and easy damage of the membrane shell of the bio-based slow-release fertilizer, which is of great significance for improving the quality and utilization rate of slow-release fertilizers.

The invention discloses a logistics supply chain dynamic management method based on the Internet of Things, and relates to the technical field of logistics management, and the method comprises the following steps: constructing a radio frequency interference space fingerprint database, and recognizing an interference region and generating a radio frequency interference distribution map through collecting the emission frequencies, signal intensities and spatial distributions of a plurality of radio frequency identification read-write devices. According to the method, interference hotspots are accurately identified by constructing a radio frequency interference space fingerprint database and a distribution map, and signal conflicts and response failures are avoided in combination with dynamic tag gain and time sequence management. And the communication stability is monitored in real time, local adjustment and self-checking are implemented, and rapid abnormal response and self-repair are realized. Equipment deployment and transmitting power are optimized, interference blind areas are dynamically eliminated, identification stability and data accuracy are improved, logistics errors and risks are reduced, transparency and response capability of a supply chain are enhanced, intelligent and reliable logistics management is promoted, and anti-interference capability and overall operation efficiency of the system are improved.

The invention discloses a printed circuit board defect online full-automatic detection method and system based on data analysis, relates to the technical field of printed circuit board performance testing, and realizes comprehensive evaluation of circuit board performance through steps 1 to 4. By configuring a test system and setting test conditions, accurate installation and debugging of each test module are ensured; a power supply stability index Dyw, a power supply switching fault-tolerant index Qhrc, a thermal stress index Ryl, a mechanical stress index Mvz, an electromagnetic compatibility index Jrx, a resource contention index Zyzq and a self-repairing index Xfz are calculated, a comprehensive evaluation index Pc is obtained through associated calculation, performance evaluation is carried out, and whether the circuit board is qualified or not is effectively judged. And when the comprehensive evaluation index Pc is lower than a first performance threshold value X, generating a performance disqualification label, and performing in-depth grading evaluation through a second multi-stage evaluation module, thereby promoting identification of specific performance defects.

The invention relates to the technical field of welding, in particular to an intelligent welding control method and equipment for a gate, and the method comprises the following steps: collecting residual stress distribution data of a welding area of a gate structure in real time; performing effective screening on the residual stress distribution data, and extracting feature data segments to obtain residual stress distribution data of the welding area; based on the residual stress distribution data, whether stress abnormity exists in the welding area or not is judged, and the abnormal influence level is determined; when it is detected that stress abnormity exists in the welding area, reverse disturbance control is conducted on the basis of the abnormal influence level, the sampling frequency of the residual stress distribution data is synchronously increased, and effectiveness screening of the residual stress distribution data is relaxed; and the corrected welding effect data are fed back to a historical case database, and stress characteristics and optimization parameters of typical working conditions are stored. According to the method, the self-repairing capability of the material is excited in exception handling, and the defect of response lag of a traditional method is overcome.

The invention discloses a self-repairing material formula for surface insulation of power equipment and a method. The method comprises the following steps: step S1, material selection; s2, preparing a substrate; step S21, pretreatment of polyether amine; step S22, preparation of an isocyanate prepolymer; step S23, preparing the self-repairing polyurea; the self-repairing material is obtained by the preparation method. Compared with a traditional insulating material, the polyurea material has better mechanical performance and electrical performance and can be used as external insulation of power equipment, flashover faults are prevented, and safe operation of the power equipment is guaranteed. Meanwhile, the polyurea-based material can be self-repaired under the condition of damage, and the performance of the polyurea-based material can be recovered to about 90% of the performance of the original material, so that the maintenance workload of power equipment is reduced, and the maintenance cost and the labor cost are reduced; the self-repairing material disclosed by the invention has good mechanical performance and electrical performance, also has certain self-repairing performance, and meets the material use requirements of various scenes.

The utility model discloses an anti-puncture rubber tire, which comprises a main tire and an outer-layer rubber tread, the outer-layer rubber tread is positioned on the periphery of the main tire, the main tire is connected with the outer-layer rubber tread through a plurality of groups of spokes, the main tire comprises a tread part, an inner layer is arranged on the inner side surface of the tread part, and an outer layer is arranged on the outer side surface of the tread part. A sealant layer is filled between the inner layer and the inner side surface of the tread part, and the inner layer comprises a dividing strip assembly; the outer-layer rubber tread is in contact with the ground, and a gap formed by the avoiding cavity is formed between the outer-layer rubber tread and the main tire, so that a sharp object is blocked by the outer-layer rubber tread when being punctured into the outer-layer rubber tread and is not easy to puncture into the tread part of the main tire, and the puncture prevention of the main tire is realized; the self-repairing of the tire is realized by the sealant layer depending on the viscosity of the sealant layer; and the sealant layers are filled in the multiple groups of separation cavities in a split manner, so that the influence of the mobility of the sealant layers on the dynamic balance of the tire is reduced.

The invention relates to the technical field of network operation and maintenance, in particular to a network health automatic diagnosis and closed-loop repair method and related products, and the method comprises the steps: establishing a dynamic health baseline; abnormal deviation of the real-time operation data is recognized; predicting the risk probability that the network equipment has an operation fault in the future; selecting and executing a corresponding repairing action; verifying whether the abnormal deviation is eliminated; if the abnormal deviation is not eliminated, continuing to execute repair until the abnormal deviation is eliminated or the maximum repair frequency is reached; according to the method, the accuracy and the foresight of network fault diagnosis are improved by deeply fusing the artificial intelligence algorithm into a network operation and maintenance scene, and the intelligent and autonomous management of the network is realized by introducing a closed-loop repair mechanism with autonomous learning and decision-making capabilities. And the reliability, the stability and the self-repairing capability of the whole network infrastructure are enhanced.

The invention provides a foundation treatment process, and relates to the technical field of foundation treatment. The foundation treatment process specifically comprises the following steps: S1, geological survey and three-dimensional modeling; s2, establishing a micro-seismic monitoring system; s3, applying a self-healing material; s4, construction of a rotary drilling rig; s5, performing real-time construction monitoring and adjustment; s6, detecting the hole forming quality of the pile foundation; s7, concrete is poured, and a self-healing material is injected; and S8, geological treatment and acceptance after construction. Safety and accuracy of the construction process can be guaranteed by monitoring changes of underground rock strata and karst caves in real time, the construction quality of each pile foundation is guaranteed through data analysis and dynamic adjustment of a construction scheme, self-repairing of the material can be achieved through the fungus self-healing cement-based material, durability and stability of the pile foundations are enhanced, and the construction quality of the pile foundations is improved. The long-term effect of foundation treatment is improved, the later maintenance cost is reduced, the pile foundation construction quality under the complex karst geological condition can be ensured, the construction efficiency is improved, the cost is reduced, and the engineering safety and stability are ensured.

The invention relates to the technical field of high polymer materials, in particular to modified natural rubber and a preparation method thereof.The preparation method comprises the steps that S1, in the inert gas atmosphere, rubber and a dopamine solution are mixed and react to form a rubber system containing dopamine; s2, adding a ferric salt solution (such as a ferric chloride solution) into the rubber system containing the dopamine, stirring, gradually condensing and separating out, then washing with distilled water, and drying, so as to obtain the self-repairing modified natural rubber; the technical process is simple, preparation is easy, in the preparation process, dopamine is introduced, free iron elements are added into a system, reversible metal complex bonds are formed through the iron elements and dopamine molecules, and therefore when rubber is damaged, the iron elements and hydrogen bonds between rubber macromolecules act together, a synergistic self-repairing mechanism is formed, and the self-repairing performance of the rubber is improved. The self-repairing of the rubber material is realized, and the application requirements are better met.

The invention relates to the technical field of bridge engineering materials, in particular to an epoxy resin self-repairing material with dynamic covalent bonds for a large-span steel bridge deck and a preparation method of the epoxy resin self-repairing material. According to modified bisphenol A epoxy resin, flexible chain segments and rigid groups are introduced into an epoxy resin molecular chain, so that the toughness and heat resistance of the material are improved; the modified aliphatic amine curing agent and the modified epoxy resin matrix have good compatibility, the formed network structure is more compact, the hardness and the heat resistance of the material are improved, the dynamic covalent bond cross-linking agent adopts a furan-maleimide system containing Diels-Alder reaction, and the dynamic covalent bond cross-linking agent has good mechanical properties and mechanical properties. Wherein a furan group and a maleimide group can be subjected to reversible addition reaction under a mild condition to form a dynamic covalent bond, so that rapid and effective self-repairing of the material when the material is damaged is realized, the self-repairing material adopting the technical scheme has an excellent self-repairing function, a repairing process can be triggered without external stimulation, and the self-repairing material has a good application prospect. And the applicability is higher.

The invention relates to a non-container application arrangement method and device based on a Kubernetes CRI plug-in. The non-container application arrangement method comprises the steps that S1, description information of a non-container application is defined; s2, creating and starting a container; s3, configuration of a container; and S4, managing the patch of the container. According to the method, the original non-container application can be hosted to the Kubernetes cluster without modifying the original non-container application, and the characteristics of automatic deployment and expansion capability, health examination and self-repairing capability, monitoring and log collection capability, safety, isolation and the like provided by Kubernetes can be fully utilized, so that a developer is allowed to uniformly manage the non-container application and the container application; the operation and maintenance work can be simplified, the management efficiency can be improved, and after the non-container application is hosted, the Kubernetes can be utilized to dynamically schedule and allocate the resource capacity, and the resource use efficiency can be optimized.

The invention discloses a robot fault self-diagnosis system and method, relates to the technical field of robot fault diagnosis, and solves the technical problem of low automation degree of a robot caused by incapability of accurate self-diagnosis and self-repair of the robot in the prior art. The method comprises the following steps: collecting real-time operation data of a robot, and extracting real-time error logs and historical fault data from a database; the fault state of the robot is monitored according to the real-time operation data of the robot, a historical fault library is constructed based on historical fault data, the fault state is input into the historical fault library for matching, and mismatched faults, matched faults and corresponding matching repair methods are obtained. Different self-repairing methods are adopted for different faults, the historical fault library is updated, the repairing effect is monitored, and the matched repairing method is updated according to the repairing effect; and when the robot cannot complete self-repair, planning an optimal maintenance path and controlling to go to repair.

The utility model discloses an operation traction frame for spine correction, and belongs to the technical field of spine correction instruments. Comprising a head fixing part and a pelvic end fixing part, the head fixing part and the pelvic end fixing part are connected through a connecting rod assembly, the connecting rod assembly comprises a supporting rod and an automatic adjusting push rod, the end of the supporting rod is connected with the automatic adjusting push rod through an adjusting part, the supporting rod is connected with the pelvic end fixing part, and the automatic adjusting push rod is connected with the head fixing part. The supporting rod and the automatic adjusting push rod form a spine correction space. The spine traction device is simple in structure and convenient to operate, traction of the spine of a patient is achieved through cooperation of the head fixing piece, the pelvis end fixing piece and the connecting rod assembly, pressure of the spine can be relieved through the traction frame, and self-repairing of the spine is promoted; and through the arrangement of the automatic adjusting push rod, the height of the connecting rod assembly can be automatically adjusted through intelligent control, so that the supporting length is rapidly adjusted, the operation efficiency can be improved, and the operation time is saved.

The invention relates to the technical field of spacecraft electronic systems, and discloses a satellite-borne computer multi-stage fault-tolerant starting method which comprises the following steps: step 1, a management FPGA (Field Programmable Gate Array) reads a starting source identification bit of a BIOSBOOT register, and selects a main BIOS (Basic Input / Output System) storage address or a standby BIOS storage address according to an identification bit value; 2, the management FPGA starts a BIOS level watchdog timer corresponding to the BIOS storage address, and the duration of the timer is configured by a BIOSWDT register; and 3, when the BIOS-level watchdog timer is overtime and does not receive the reset signal, the management FPGA modifies the starting source identification bit of the BIOSBOOT register, and a system reset signal is generated. According to the method, the management FPGA is taken as a core, and a double-BIOS redundant architecture and a multi-disk hot standby mechanism are combined, so that the problem of system startup single-point failure caused by BIOS firmware code bit flipping or startup disk physical damage is solved, autonomous fault-tolerant recovery of firmware and a storage medium is realized, and the defect that an existing single-BIOS single-storage-medium architecture cannot self-repair hardware failure is overcome.

The invention discloses a method for optimizing micro saw blade production by using a genetic algorithm. The method comprises the following steps: S1, establishing a virtual simulation environment; s2, parameter optimization is carried out in the virtual simulation environment, and a plurality of virtual production schemes are generated; s3, selecting an optimal scheme through high-dimensional topology hypersurface mapping and an asymmetric singular value perturbation technology; s4, applying the optimal scheme to actual production, and analyzing monitoring data by using a Schrodinger-Newman geometric gravitational field exceeding method; s5, when the deviation exceeds a preset threshold value, triggering a self-repairing mechanism, and performing optimization iteration again; s6, actual production parameters are adjusted based on the repairing scheme; s7, updating the digital twinborn model in real time to reflect the latest production condition; s8, analyzing historical data in combination with a machine learning algorithm, and optimizing future production parameter setting; and S9, circularly executing the steps S4 to S8 to achieve the production optimization target, the precision of the micro saw blade production process is improved, and continuous optimization and stability of the production quality are ensured.

The invention discloses an artificial grass yarn with a self-repairing function and a preparation method and application thereof.The artificial grass yarn is prepared from, by weight, 75-95 parts of linear low-density polyethylene, 5-25 parts of linear high-density polyethylene, 3-6 parts of color master batch, 3-6 parts of reversible cross-linked polymer, 1-3 parts of initiator, 2-5 parts of anti-aging additive and 1-3 parts of processing additive, the mass of the reversible cross-linked polymer accounts for 2-6% of the total mass of the artificial grass, and the mass ratio of the reversible cross-linked polymer to the initiator is 2: 1. After the interior of the material is damaged, the material can be self-repaired, and the service life of the material is prolonged.

A battery management method for intelligent diagnosis and adaptive debugging comprises the following steps: S1, initialization configuration: when a system is started, automatically reading and setting the type, capacity and maximum discharge current of a battery as basic parameters through a built-in initialization program; s2, self-calibration: reading voltage, current and temperature data of the battery unit by a sensor, and automatically adjusting deviation; s3, real-time monitoring: continuously monitoring various parameters of the battery, and identifying abnormal conditions; s4, performing fault prediction and self-repair; s5, cloud platform connection: the BMS is connected to a cloud server through Wi-Fi or a cellular network and uploads real-time data for remote monitoring; s6, OTA updating; and S7, visual debugging. According to the invention, system debugging can be automatically completed in the installation and operation process, the battery state is monitored in real time during operation, and the reliability and efficiency of the system are improved.

The invention relates to the field of floors, and particularly discloses a floor with a self-cleaning function and a preparation method.The floor comprises a main body layer, the top face of the main body layer is sequentially provided with a self-cleaning coating, an anti-fouling protection layer, a repairing function layer and a surface layer, and the self-cleaning coating is a nano composite coating; the anti-fouling protection layer is a polyurethane resin and super-hydrophobic substance mixed coating, the repairing function layer is a polyurethane resin and microcapsule mixed coating, repairing components are contained in microcapsules, the surface layer is a mixed coating of polyester resin, wear-resistant particles and an anti-ultraviolet additive, and the surface layer is a polyurethane resin and super-hydrophobic substance mixed coating. The floor with the self-cleaning function has the super-hydrophobic function, the self-cleaning function, the antifouling function, the wear-resisting function and the self-repairing function, and the high-performance requirement for the floor in the modern home and commercial environment is met.

The application provides an emulsion thickener with acid recovery stability and a preparation method thereof, and relates to the technical field of thickener.The raw materials of the emulsion thickener include polymerized monomers, emulsifiers, initiators, crosslinking agents, water and structural additives; the polymerized monomers include first monomers and second monomers, the first monomers are alpha, beta-unsaturated acid monomers, the second monomers are alpha, beta-unsaturated ester monomers, and the structural additives are polypeptides including polar amino acid residues.The emulsion thickener with acid recovery stability can quickly recover to the viscosity in the alkaline condition and gradually increase when the system changes from the alkaline condition to the acidic condition, effectively improves the response rate of network reconstruction, and realizes the self-repairing function.The preparation method of the emulsion thickener with acid recovery stability is simple and easy to operate, has good stability, and can be implemented in industrialization.