55 results about "Intelligent maintenance system" patented technology

The invention relates to the field of intelligent transportation systems, discloses an intelligent highway maintenance system and method, and aims to solve the fundamental defects that in the prior art, the data acquisition dimension is single, the maintenance decision depends on artificial experience, and prospective prediction is lacked. The method comprises the following steps: acquiring multi-modal dynamic sensing data covering a whole road domain; constructing and updating a four-dimensional space-time digital twinborn model in real time; driving the causal graph neural network model to perform structure health state prediction and diagnosis; generating an active maintenance instruction through a multi-objective optimization engine; and the autonomous maintenance execution unit is dispatched to complete unmanned closed-loop operation. According to the method and the system, fundamental transformation of road maintenance from passive response to active prevention, from artificial experience to intelligent decision making and from discrete operation to closed-loop automation is realized, and the maintenance efficiency, the safety and the health level of the whole life cycle of the road are remarkably improved.

The invention relates to a balanced color perception enhancement method for rail transit target detection, and belongs to the technical field of rail transit and computer vision. According to the method, brightness channel adaptive histogram equalization enhancement CLAHE-LC, a multi-segment tone channel mask mechanism MSHCM-M and a three-stage hybrid mechanism non-maximum suppression TSLSH-NMS technology are combined, so that the problems of complex illumination, multi-target shielding, color interference and the like in a rail transit scene are solved, and the accuracy and recall rate of target detection are improved. The method can be seamlessly integrated into an existing deep learning target detection framework, is compatible with multi-label, multi-category and multi-scale features, and remarkably improves the precision and recall rate of target detection in a rail transit scene. Experimental verification shows that the real-time performance is guaranteed, meanwhile, the detection performance is obviously improved compared with a traditional scheme, and the method is suitable for being applied to an actual rail transit safety monitoring and intelligent maintenance system.

The invention belongs to the technical field of wind power operation and maintenance, and discloses a wind turbine generator intelligent maintenance system combined with component residual life evaluation, which comprises a sensing edge layer, a station cooperation layer, a cloud intelligent center, an execution and safety interlocking layer and a credible evidence storage layer. The system collects unit operation and environment data through the edge layer, gathers the data through the station cooperation layer, inputs the data into the cloud intelligent center for multi-domain degradation modeling and life prediction, and determines a maintenance window and a resource scheduling scheme based on a comprehensive cost optimization model. The cloud center realizes cross-station model sharing and self-learning through a federated learning mechanism, the execution layer completes maintenance tasks and safety locking control, and the trusted evidence storage layer performs block chain abstract evidence storage on key data. According to the system, health state evaluation, intelligent maintenance decision making and whole-process credible tracing of the wind turbine generator are realized, and the operation and maintenance safety and economy are improved.

The invention discloses a laboratory equipment fault diagnosis and maintenance decision generation system based on a large language model, and relates to the technical field of fault diagnosis. According to the system, a cross-device and multi-data type intelligent maintenance system in an AI For Science black light laboratory scene is constructed, standardized processing and intelligent fusion of multi-modal data are realized, and fault diagnosis, root cause tracing and executable maintenance decision generation are enabled through association of a large language model and knowledge, so that the maintenance efficiency is improved. A self-learning optimization closed loop is formed based on decision feedback and a knowledge vector library, the maintenance operation convenience is improved in combination with man-machine collaborative interaction, manual misjudgment and downtime are reduced, intelligent, standardized and traceable support is provided for full-life-cycle operation and maintenance of black light laboratory equipment, and the maintenance efficiency is improved. The problems that traditional maintenance is slow in response and low in accuracy, fault diagnosis lacks semantic understanding and causal reasoning ability, operation and maintenance knowledge is difficult to accumulate and inherit, and a full-life-cycle maintenance closed loop is lacked are solved.

The invention belongs to the technical field of vehicle maintenance, and particularly relates to a vehicle intelligent maintenance system and a vehicle, the vehicle intelligent maintenance system comprises a multi-source data acquisition module, a fault reasoning module, a maintenance knowledge graph engine module, a central control screen augmented reality maintenance guidance module and a maintenance process information interaction and support module; the multi-source data acquisition module is used for acquiring operation data of the vehicle in a preset time period before and after a fault; the fault reasoning module is used for analyzing the fault data, calculating the part failure probability and generating a fault influence degree thermodynamic diagram; the maintenance knowledge graph engine module is used for storing and managing a maintenance knowledge graph and supporting natural language interactive query; the central control screen augmented reality maintenance guidance module is used for providing maintenance guidance in a three-dimensional animation and augmented reality form; and the maintenance process information interaction and support module is used for realizing information interaction between maintenance personnel and the system and providing operation guidance for the maintenance personnel. According to the invention, functions of vehicle intelligent maintenance and fault prediction can be realized.

The invention discloses a method for complementing data in a cigarette manufacturing process based on a GAN (Germanic Analysis)-Transformer (Germanic Analysis-Transformer). The method comprises the following steps: acquiring multi-modal time sequence data in a cigarette manufacturing process, performing preliminary interpolation to obtain a multi-modal original tensor, and generating a missing mask at the same time; performing feature extraction on the multi-modal original tensor, and embedding process prior to obtain sparse perception unified representation; inputting the sparse perception unified representation and the missing mask into the generative adversarial network to obtain a preliminary completion sample; and inputting the preliminary completion sample and the multi-modal original tensor into a mixed Transform model in parallel for fine calibration, and obtaining a corrected completion sequence. Through cooperation of multi-modal deep fusion, physical knowledge embedding, uncertainty quantification and online reinforcement learning, the problem of data missing is solved, and data support is provided for a credible, reliable and evolvable cigarette manufacturing data intelligent maintenance system.

The application discloses a PC intelligent maintenance system, method and medium, which is applied to a PC device to be maintained, the PC device to be maintained is provided with hardware to be maintained, and the system comprises an information collection module, a maintenance item confirmation module, a scheme generation module, a maintenance execution module and a backup processing module; the information collection module is used for acquiring hardware information and hardware use duration of the hardware to be maintained, and the information collection module generates device information based on the hardware information and the hardware use duration; the maintenance item confirmation module is used for acquiring a first maintenance time of the hardware to be maintained, and calculating a health degree score based on the device information and the first maintenance time; the maintenance item confirmation module sets a maintenance item based on a benchmark score and the health degree score; the scheme generation module is used for acquiring user feedback information corresponding to the maintenance item, and generating a maintenance scheme based on the user feedback information, the maintenance item, a scheme template and a plurality of maintenance strategies; and the application can realize intelligent maintenance of the hardware, and prevent invalid maintenance and over-maintenance.

The invention relates to the technical field of intelligent agricultural equipment and nondestructive testing, and discloses a stadium lawn intelligent maintenance system and method based on AI vision, and the system comprises a mobile operation platform, a frequency conversion pneumatic excitation module, a bimodal vision collection module and an edge calculation processing module. The system applies controllable pulsating airflow to a lawn by using a variable-frequency pneumatic excitation module, induces blade resonance and destroys an air boundary layer; and after the airflow stops instantaneously, the bimodal visual acquisition module synchronously acquires free attenuation vibration and a thermal recovery image sequence of the blade. And the edge calculation processing module calculates an equivalent stiffness coefficient, a damping ratio and a thermal time constant of the blade through decoupling analysis, and evaluates the water deficit, disease or growth potential state of the lawn based on multi-dimensional parameter joint distribution. According to the method, the non-contact early warning and accurate identification of the microscopic physiological characteristics of the lawn are realized by actively constructing the mechanical thermal unbalanced state.

This invention provides a method and apparatus for controlling the entry and exit of specimens in an intelligent curing system, relating to the field of data processing technology. The method includes: acquiring entry information of specimens to be cured; verifying the specimens based on the entry information to obtain verified specimens; determining target curing environment parameters based on the verified specimens and preset curing requirements; controlling the curing chamber according to the target curing environment parameters to obtain cured specimens; generating quality inspection data related to the cured specimens when an exit instruction for the cured specimens is received; comparing the quality inspection data with preset exit conditions to determine whether exit is permitted, and controlling the exit operation when exit is permitted. This invention achieves intelligent control of the entire process of specimen entry and exit, while ensuring the accuracy and completeness of the verified specimen exit information.

The application discloses an intelligent predictive maintenance system for an external pressure type ultrafiltration membrane based on a pollution state sensing, relates to the technical field of ultrafiltration membrane maintenance, and is characterized in that the system is a closed-loop intelligent maintenance system, which is constructed through a collaborative architecture of a sensing layer and an execution layer, data sharing and dynamic optimization decision-making, forms a closed-loop maintenance process of'sensing-analysis-early warning-decision execution', breaks the problem of fragmentation of each link of a traditional system, improves the intelligent level and operation efficiency of the maintenance system, promotes the transformation of ultrafiltration membrane maintenance from 'after-the-fact remediation' to 'prior prediction', and provides a core technical guarantee for the large-scale and efficient application of the ultrafiltration membrane technology.

The invention provides a concrete curing device and method for tunnel construction. The curing device comprises a base, a supporting table, a guide rail, a mounting plate and a spraying pipe, and a driving assembly used for driving the spraying pipe to slide along the guide rail is arranged at the top of the supporting table; the intelligent maintenance system further comprises an intelligent control system, and the maintenance method comprises the steps that the inner wall of the tunnel is scanned through the humidity sensor, humidity information of the concrete surface is obtained, and corresponding coordinate position information is obtained through the positioning module; comparing the humidity information with a preset standard humidity value, and determining a spraying grade according to a humidity difference value; according to the spraying grade, obtaining a corresponding spraying control parameter from a pre-stored spraying strategy table; and the conveying assembly is started, accurate spraying is conducted on the target coordinate position according to the spraying control parameters, and the problem that in the prior art, existing concrete spraying and curing equipment cannot conduct accurate spraying and curing according to the humidity of the inner wall of the tunnel is solved.

The invention relates to the technical field of concrete curing, in particular to a mass concrete temperature control anti-cracking intelligent curing system and method.The mass concrete temperature control anti-cracking intelligent curing system comprises a multi-parameter sensing module used for collecting temperature, humidity and environment temperature and humidity and wind speed parameters; the enclosure maintenance wallboard is arranged on the outer side of the mass concrete and forms an enclosure space, and the enclosure maintenance wallboard at least comprises an adjustable thermal resistance unit, a controlled convection unit, a surface electric heating unit and a wet maintenance water return unit; the edge control module is in communication connection with the multi-parameter sensing module and the enclosure maintenance wallboard, comprises a local calculation unit and a local storage unit, and is used for performing rolling optimization solution under the condition that the maximum temperature, the temperature difference, the cooling rate and the enclosure space humidity constraint are met; and control instructions for the adjustable thermal resistance unit, the controlled convection unit, the surface electric heating unit and the wet maintenance water return unit are output so as to realize cooperative regulation and control. According to the invention, the temperature control efficiency and the quality controllability can be improved.

The invention provides a trimming disc loading and unloading device and an intelligent maintenance system and method.The trimming disc is used for trimming a polishing pad in chemical mechanical polishing equipment, the unloading device comprises a base, a stripping assembly and a grabbing assembly, and lossless and automatic separation of the trimming disc and the trimming disc base is achieved.

The invention discloses a power station intelligent installation and intelligent maintenance system based on a wireless ad hoc network, and relates to the field of power station operation and maintenance technology and industrial internet technology, and the system comprises a plurality of node devices which are used for data collection, edge calculation, wireless networking and data multi-hop transmission and forwarding; a plurality of node devices form a system through wireless networking, and the system has a distributed multi-copy data storage function and is applied to intelligent installation and intelligent maintenance of a power station. The networking mode of a plurality of node devices in the system adopts a decentralized distributed network, a dynamic source routing protocol and an active bridging protocol are used among the node devices, and the protocols are automatically switched according to the number of the node devices in the network to form a Mesh network. According to the invention, a base station, a wireless router or a switch and other network devices are not needed, and the network can be automatically organized to transmit and share data in the network by taking the network as a collection device and a network communication node device.

The invention discloses a thermal power plant boiler equipment intelligent maintenance system and method based on dynamic monitoring, and relates to the technical field of boiler intelligent maintenance. Boiler operation training data, maintenance time length label data and maintenance system label data are collected in advance, and a maintenance time prediction model and a system fault probability prediction model are trained; for a boiler to be monitored, historical overhaul data are collected in advance, actual boiler operation data and actual system efficiency data are collected in real time when the boiler to be monitored operates, and whether overhaul monitoring needs to be carried out or not is judged. If yes, obtaining predicted detection time and the maintenance probability of each operation system, and generating a maintenance sequence of each operation system based on the predicted detection time, the maintenance probability of each operation system and historical maintenance data; the maintenance accuracy of each operation system is quantified for maintenance personnel, and the fault risk of the boiler is reduced.

The invention discloses a side slope ecological restoration intelligent maintenance system and method, and relates to the technical field of ecological restoration, and the system comprises a data collection module which obtains real-time patrol data and environment monitoring signals from a sensor array deployed in a road network, and the environment monitoring signals comprise side slope surface displacement, soil humidity, vegetation coverage and rainfall intensity; the event judging module is used for obtaining the initial position and severity description of the emergency through fusing the multi-source input signals, and judging whether the event exceeds the processing capacity of a single area or not by adopting a preset threshold value according to the obtained initial position and severity description of the emergency; if so, extracting state records and position coordinates of the ecological restoration equipment in the adjacent areas from the central database; the intelligent maintenance system and method for ecological restoration of the side slope have the beneficial effects of intelligent monitoring, rapid response and accurate restoration.

The application discloses an anti-combustion oil moisture monitoring system and a control method. The method adopts an online monitoring technology, can directly and real-timely measure the moisture value in the anti-combustion oil after the anti-combustion oil intelligent maintenance system is operated, and overcomes the problems of poor timeliness and limited sample quantity in the existing anti-combustion oil filtering technology, i.e. the moisture is measured in a laboratory after sampling on site, so that the measurement result data are less. The use cost of equipment is greatly reduced, the service life of a dehydration filter core is prolonged under the condition that the moisture of the oil is qualified, intelligent control is realized, the operation is simple, and the problem of high labor intensity is solved.

The application discloses an intelligent maintenance method suitable for a multifunctional power supply interface of a transformer substation, belongs to the field of power system operation and maintenance, and systematically solves core problems such as disconnection of parameters and decision-making, rigid process and rough evaluation in traditional maintenance through a progressive intelligent maintenance system with parameter quantization, condition triggering, dynamic correction and closed-loop output. The method mainly comprises the following steps: safety isolation chain forced verification, precise screening of internal resistance deviation of a battery group, temperature compensation current sharing detection of a charging device, precise diagnosis of a direct-current bus ripple coefficient and multi-parameter fusion health degree decision output. The application is mainly used for maintenance of a direct-current power supply system of a transformer substation.

The invention relates to a method for maintaining a rotating machine in a thermal power generating unit, which comprises the following steps of: acquiring the running full life cycle data of the rotating machine in the thermal power generating unit, including multi-source information such as vibration monitoring, oil analysis, infrared temperature measurement, equipment performance parameter analysis and the like, and performing data fusion on the multi-source information after data preprocessing and normalization; a data set constructed by the method is input into a model constructed by the method, the constructed model is divided into a fault recognition model and an equipment service life prediction model, the constructed model is deployed in a unit intelligent maintenance system after being trained, tested and evaluated, equipment operation data input in real time is subjected to fault analysis and recognition through the fault recognition model, and the service life of the equipment is predicted. The fault type, position and degree can be accurately diagnosed, misdiagnosis and missed diagnosis are reduced, and the running reliability of the unit is improved; and the residual life and the fault risk of the equipment are pre-estimated through the life prediction model, so that scientific maintenance measures are formulated, and the fault risk and the maintenance cost are reduced.

The present application belongs to the field of artificial intelligence and rail transit intelligent operation and maintenance technology, and specifically relates to a subway intelligent maintenance system for collaborative optimization of braking energy consumption, aiming to solve the problems of low braking energy recovery efficiency, equipment perception lag and passive maintenance strategy. The system realizes the determination of regenerative braking energy absorbability and the quantitative evaluation of component health state by constructing a whole-network train dynamic topology and energy-health coupling analysis engine. Combined with a four-quadrant decision matrix, the system generates a hierarchical maintenance instruction and uses a rolling time domain optimization algorithm to coordinate train group operation time to improve energy matching degree. The system integrates a self-adaptive learning hub to continuously calibrate model parameters. The system realizes the collaborative optimization of braking energy efficiency improvement and key component life extension, and reduces the measured resistance energy consumption by more than 28% and the sudden failure rate by 41%.

The invention relates to the technical field of environmental protection engineering, in particular to an intelligent maintenance system and method for a mine bag type dust collector. The system comprises a main body equipment unit, a detection unit, a host display unit, a judgment unit and a result feedback unit, the detection unit collects operation data of key equipment such as a dust removal fan, a chimney and a bag-type dust remover in real time, and the judgment unit performs intelligent analysis and outputs a fault judgment result by utilizing a PLC (Programmable Logic Controller). The technical problems that in a traditional manual maintenance mode, point inspection is not in time, and the environmental protection problems such as filter bag damage, pipeline blockage and chimney dust emission are easily caused are solved; automatic monitoring and early warning of the dust removal equipment are achieved, the manual maintenance workload is remarkably reduced, the dust leakage risk is greatly reduced, meanwhile, the operation reliability and safety of the equipment are improved, and technical support is provided for intelligent transformation of mines.

The invention discloses an intelligent maintenance system based on the RFID technology and a maintenance tool kit thereof, and relates to the technical field of RFID maintenance tool kitchens.The intelligent maintenance system comprises a box body, a handle is fixedly connected to the upper side of the box body, two straps are fixedly connected to one side of the box body, and a control screen is fixedly connected to the other side of the box body; one end of the control screen penetrates into the box body, the other end of the control screen penetrates into the box body, the other end of the control screen is fixedly connected with a reader-writer, the intelligent maintenance system is in signal connection with the control screen, and the intelligent maintenance system comprises a tool recognition subsystem, a tool positioning subsystem, a central control subsystem and a cloud analysis subsystem. According to the system, a rigid safety defense line for preventing human errors is constructed through a technical means, and the core of the system is that forced closed-loop management of tools, especially key safety tools such as test wires and grounding wires which are easy to omit, is realized by utilizing RFID (Radio Frequency Identification) automatic identification and intelligent work order verification.

The application relates to the technical field of intelligent manufacturing equipment reliability, and discloses a data-driven intelligent manufacturing equipment fault prediction and intelligent maintenance system, which comprises a multidimensional sensor module, a data acquisition and preprocessing unit, an FMEA reliability evaluation unit, a fault prediction modeling unit, an intelligent maintenance strategy generation unit and an early warning execution unit, the units are sequentially signal-connected to form a complete fault prediction and maintenance closed loop; the multidimensional sensor module comprises a vibration sensor, a temperature sensor and an operating parameter sensor, which are respectively arranged at key parts of equipment and used for collecting vibration amplitude, temperature rise data, core component rotating speed and load state parameters of the equipment in real time. The application combines the FMEA reliability evaluation and the Weibull distribution+double algorithm cooperative modeling mode, realizes 3-7-day advanced fault prediction, effectively avoids production line shutdown caused by fault burst, and reduces economic losses and product quality defects caused by shutdown.

The invention discloses an intelligent maintenance system and method for subway station concrete, and the maintenance system at least comprises a maintenance shed, a water energy moisturizing film, a spraying pipe, a steam pipe, a maintenance water heater, a temperature sensor and a central control system. Curing temperature and humidity are scientifically set, quality problems such as cracks caused by too large temperature difference of concrete are effectively avoided, the strength and durability of the concrete are improved, the curing quality is improved, further, the most appropriate curing environment can be provided according to the requirements of different curing stages of the concrete, fine management of the curing process is achieved, and the maintenance efficiency is improved. The condition of excessive or insufficient maintenance is reduced.

The invention relates to the technical field of concrete curing, in particular to a mass concrete temperature control anti-cracking and intelligent curing system and a construction method. The mass concrete temperature control anti-cracking and intelligent curing system comprises (1) a three-dimensional temperature field monitoring module comprising a distributed optical fiber temperature measurement sensor, a pre-embedded thermocouple array and a thermal infrared imager; the distributed optical fiber temperature measurement sensors are arranged in a layered manner along the depth direction of concrete (the interlayer spacing is 0.5 m), the temperature measurement range is-20 to 150 DEG C, the precision is + / -0.5 DEG C, and the spatial resolution is 0.1 m; through three-dimensional temperature field real-time monitoring and dynamic thermal stress prediction, the internal and external temperature difference of the concrete is accurately controlled to be less than or equal to 20 DEG C, the cooling rate is less than or equal to 1.5 DEG C / d, the thermal stress is always lower than the tensile strength of the concrete in the same period, and zero temperature crack of the mass concrete is realized; the flow (0-5 m / h) of a cooling water pipe, the spraying amount (0-20 L / min) of maintenance water and the heating power (0-1000 W) of a heat preservation layer are adjusted in a self-adaptive mode on the basis of real-time temperature data, extensibility of manual adjustment is avoided, and water and electricity are saved by 30% or above.

The invention provides a method, a device and equipment for recommending maintenance suggestions based on an intelligent signal analysis system. The method comprises the following steps: acquiring alarm data to be processed of signal equipment in butt joint with the intelligent signal analysis system; based on the mapping relationship, determining a maintenance suggestion recommendation number corresponding to the alarm data to be processed; the mapping relation is used for representing a corresponding relation between the alarm data and the maintenance suggestion recommendation number; and sending the to-be-processed alarm data and the maintenance suggestion recommendation number corresponding to the to-be-processed alarm data to the intelligent maintenance system to determine a maintenance suggestion corresponding to the maintenance suggestion recommendation number. The corresponding maintenance suggestion is rapidly and automatically matched through the signal equipment alarm data and the preset mapping relation, manual intervention and manual workload are reduced, the training and learning cost of operation and maintenance personnel is reduced, equipment alarm and maintenance process electronization and intelligentization are achieved, and the maintenance efficiency and speed of the signal equipment are improved.

The invention discloses a predictive maintenance method, device and equipment for an overpressure protection system and a storage medium, and relates to the technical field of nuclear power plants, and the method comprises the steps: comprehensively collecting the multi-source operation and maintenance historical data of the system, extracting health characterization features, pre-judging the state trend through a time sequence prediction model, and analyzing the fault root cause after early warning. The technical problems that traditional maintenance lacks data support, multi-source data are not effectively fused, prediction and decision are insufficient and the model is not continuously optimized are solved by combining maintenance constraints to generate decision suggestions and executing feedback to optimize the model, accurate prediction, early warning and intelligent maintenance decision are achieved, excessive or insufficient maintenance is avoided, and the maintenance efficiency is improved. The cost and the safety risk are reduced, a closed-loop intelligent maintenance system is formed, and the safe and stable operation of the system is guaranteed.

The application discloses an external hanging type intelligent maintenance system, a lining trolley and an intelligent maintenance method, and relates to the tunnel maintenance field.The external hanging type intelligent maintenance system comprises a spraying device, a plurality of spraying components capable of spraying high-temperature steam, a first connecting structure arranged on each spraying component, and a trolley template.The first connecting structure is used for detachably connecting the two ends or the two side bottoms of the trolley template.A longitudinal sealing element is used for detachably filling between the two side bottoms of the trolley template and a secondary lining concrete structure.A ring-shaped sealing element is used for detachably filling between the two ends of the trolley template and the secondary lining concrete structure.The external hanging type intelligent maintenance system can be loaded on the lining trolley in a hanging manner, so that timely maintenance can be achieved without moving the equipment, the quality of the secondary lining concrete structure of the tunnel surface is effectively guaranteed, and the problem that the concrete lining is not maintained in time after demolding in the existing tunnel construction process is solved.

The invention discloses an axial flow fan intelligent maintenance system based on three-dimensional visualization, and relates to the field of intelligent maintenance, and the system comprises an acquisition module, an abnormity identification module and an auxiliary maintenance module; the acquisition module periodically acquires a signal set, and generates an equipment feature set and a scanning image set through a vector analysis method and a frequency domain filtering back projection method; the anomaly identification module identifies a state type by using an integrated decision network, generates a mark scanning image set based on a regional gray analysis method and decides to send maintenance data; the auxiliary maintenance module generates a maintenance marking model and a dismounting scheme through a reconstruction correction method and an ant colony algorithm, can accurately detect abnormity and provide visual auxiliary maintenance, and improves the efficiency and accuracy.

The invention provides an intelligent concrete curing system based on intelligent sensing and temperature difference self-adaptive control, and relates to the technical field of building equipment, concrete is uniformly divided to obtain a plurality of concrete partitions, and the system comprises a sensor module, a central control module and a temperature and humidity adjusting module; the sensor module is used for acquiring temperature field data and humidity data of each concrete partition; and the central control module is used for obtaining a temperature gradient value and a temperature average value according to the temperature field data, obtaining an average humidity value according to the humidity data, and controlling the temperature and humidity adjusting module to heat, cool or humidify each concrete partition according to the temperature gradient value, the temperature average value and the average humidity value. The temperature gradient in the mass concrete is monitored and regulated in real time, so that temperature cracks are effectively prevented, and the overall durability and structural safety of the concrete are improved.