Aggregate full life cycle digital intelligent management and control method and related device

Abstract

The application provides an aggregate full-life-cycle digital intelligent management and control method and related device, and relates to the technical field of building engineering material management. Through implanting imitation aggregate and writing geological and quality data in the production stage, real-time monitoring and positioning in the transportation stage, supplementing management information in the entry stage, automatic identification of proportioning in the mixing stage, recording construction information in the pouring stage, a full-chain traceability system is constructed throughout the raw materials to finished products, which has the advantages of realizing full-process quality traceability, real-time monitoring of transportation state, and multi-link data interconnection.

Description

Technical Field

[0001] This application relates to the field of building materials management technology, and in particular to a digital intelligent management and control method and related device for the entire life cycle of aggregates. Background Technology

[0002] In construction engineering, aggregates, as a crucial component of building materials such as concrete, play a critical role in project quality due to their quality and reliable sourcing. Currently, there are numerous management blind spots in the production, transportation, and use of aggregates: In the production stage, traditional manual recording methods struggle to accurately grasp the production parameters and quality data of each batch of aggregates, leading to difficulties in quality traceability; during transportation, the lack of real-time monitoring methods makes it impossible to track the location, status, and potential mixing of aggregates, easily causing supply chain disruptions; at the application site, information on the actual usage, application location, and compatibility with design requirements is delayed, hindering accurate material management. These problems result in serious quality control loopholes throughout the entire construction industry chain, making it impossible to prevent quality issues or effectively trace them after they occur. For example, the lack of visibility into the transportation process may lead to untimely aggregate supply at the construction site, delaying the project schedule; or the inability to effectively monitor aggregate quality may result in problems being discovered only after use, causing rework and economic losses. Furthermore, existing technologies lack a complete solution for integrating data from production, transportation, delivery, mixing, and pouring processes, resulting in severe information silos between these stages and hindering closed-loop management. Therefore, existing technologies urgently need improvement to address these issues. Summary of the Invention

[0003] The purpose of this application is to provide a digital intelligent management and control method and related device for the entire life cycle of aggregates, which has the advantages of realizing full-process quality traceability of aggregates, real-time monitoring of transportation status, and interconnection of data in multiple stages.

[0004] Firstly, the digital intelligent management and control method for the entire life cycle of aggregates provided in this application adopts the following technical solution: A digital intelligent management and control method for the entire life cycle of aggregates includes: During the production stage, after the aggregate is crushed and screened, imitation aggregate is added to the aggregate according to different particle size specifications and preset proportions, and basic geological information and quality control information are written into the imitation aggregate through a fixed RFID reader. During the transportation phase, the NB-IoT module built into the imitation aggregate is used for positioning and motion status monitoring, and the location, timestamp, motion status and power information are encrypted and uploaded to the cloud platform according to the set period. During the entry phase, the information of the imitation aggregate is read using a handheld RFID reader, and the on-site management information is supplemented accordingly. During the mixing stage, the fixed RFID reading device deployed at the mixing plant automatically identifies the aggregate proportions and writes the mixing information, which is then uploaded to the cloud management system in real time via the NB-IoT module. During the pouring stage, mobile reading equipment reads aggregate information at the pouring point and writes it into construction information, thus forming a complete traceability chain from raw materials to finished components.

[0005] Optionally, the preset ratio is 1:10000, and the different particle size specifications include at least one of 5-20mm, 20-40mm, and 40-80mm. Optionally, the basic geological information includes at least one of the following: mine number, mining time, rock type, geological stratum, and strength grade; The quality control information includes at least one of the following: production batch number, particle size specification, crushing value, mud content, alkali activity test result, manufacturing date, and quality inspector number. Optionally, the positioning step is performed by the NB-IoT module relying on the operator's base station, and positioning is achieved in the absence of GPS. The motion state monitoring includes determining the transportation status through a MEMS triaxial accelerometer to achieve motion / stationary identification and abnormal vibration alarm. Optionally, the on-site management information includes at least one of the following: supplier information, transport vehicle number, arrival time, acceptance personnel, and storage area number; and the handheld RFID reader has batch reading and writing functions to improve inventory management efficiency. Optionally, the mixing information includes concrete mix designation number, mixing time, and operator information; the NB-IoT module supports low-power wide-area network communication to ensure real-time and stable data upload and adapt to the production environment of the mixing plant. Optionally, the construction information includes the pouring location number, pouring time, construction team, and supervisor's signature; and the mobile reading device is tested for reading and writing performance in the pouring environment to ensure effective information entry under interference such as dust and vibration.

[0006] Optionally, the imitation aggregate is used to make a shell using 3D printing technology before it is put into use. The shell is made of composite material with a compressive strength greater than 50MPa. During the manufacturing process of the shell, RFID tags and NB-IoT module installation cavities are reserved. The precise positioning of electronic devices is ensured by a layered printing-encapsulation curing process. Optionally, the NB-IoT module adopts an intelligent power management algorithm to adaptively wake up and transmit data during transportation and storage, ensuring continuous operation for more than 45 days to meet long-term tracking requirements. Secondly, this application provides a digital intelligent management and control device for the entire life cycle of aggregates, comprising: The information writing module is used in the production stage to add imitation aggregates to the aggregates after crushing and screening, according to different particle size specifications and preset ratios, and to write basic geological information and quality control information to the imitation aggregates through a fixed RFID reader. The transportation module is used to locate and monitor the movement status of the aggregate during the transportation phase by using the NB-IoT module built into the aggregate, and to encrypt and upload the location, timestamp, movement status and power information to the cloud platform at a set period. The reading module is used to read the imitation aggregate information using a handheld RFID reader during the entry phase and supplement it with on-site management information. The mixing module is used to automatically identify the aggregate proportions through fixed RFID reading devices deployed at the mixing plant during the mixing stage, write the mixing information, and upload it to the cloud management system in real time via the NB-IoT module. The output module is used to read aggregate information at the pouring point through a mobile reading device during the pouring stage and write construction information, thereby forming a complete traceability chain from raw materials to finished components.

[0007] In summary, this application constructs a full-chain traceability system from raw materials to finished products by embedding imitation aggregates and writing geological and quality data during the production stage, real-time monitoring and positioning during the transportation stage, supplementing management information during the entry stage, automatically identifying the proportions during the mixing stage, and recording construction information during the pouring stage. It has the advantages of realizing full-process quality traceability, real-time monitoring of transportation status, and interconnection of data across multiple stages. Attached Figure Description

[0008] Figure 1 This is a flowchart illustrating the first embodiment of the digital intelligent management and control method for the entire life cycle of aggregates in this application; Figure 2 This is a structural block diagram of the first embodiment of the digital intelligent management and control device for the entire life cycle of aggregates in this application. Detailed Implementation

[0009] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of this application.

[0010] This application provides a digital intelligent management and control method for the entire life cycle of aggregates, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the digital intelligent management and control method for the entire life cycle of aggregates in this application.

[0011] In this embodiment, the digital intelligent management and control method for the entire life cycle of aggregates includes the following steps: Step S10: In the production stage, after the aggregate is crushed and screened, imitation aggregate is added to the aggregate according to different particle size specifications and preset ratios, and basic geological information and quality control information are written to the imitation aggregate through a fixed RFID reader.

[0012] Step S20: During the transportation phase, the NB-IoT module built into the imitation aggregate is used for positioning and motion status monitoring, and the location, timestamp, motion status and power information are encrypted and uploaded to the cloud platform according to the set period.

[0013] Step S30: During the entry phase, the imitation aggregate information is read using a handheld RFID reader and supplemented with on-site management information.

[0014] Step S40: During the mixing stage, the fixed RFID reading device deployed at the mixing plant automatically identifies the aggregate proportion and writes the mixing information, which is then uploaded to the cloud management system in real time via the NB-IoT module.

[0015] Step S50: During the pouring stage, aggregate information is read at the pouring point by a mobile reading device and construction information is written in, thereby forming a complete traceability chain from raw materials to finished components.

[0016] It should be noted that in traditional aggregate management systems, geological attributes and quality parameters cannot be dynamically linked to the physical material during the production stage. The transportation phase lacks continuous monitoring of material movement and state changes. Supply chain information is difficult to update synchronously during on-site acceptance. The mixing process cannot automatically verify the match between aggregate proportions and design parameters. The pouring phase lacks a link between construction information and raw material data. These problems lead to a broken data chain throughout the material lifecycle, quality traceability relies on manual recording, and key parameters cannot be verified through each stage to form a closed loop, directly impacting the quality stability of concrete components and the ability to control engineering risks.

[0017] For example, in large-scale water conservancy projects, aggregates undergo complex processes including mining, multi-stage crushing and screening, inter-provincial transportation, open-air storage, and multiple batches of mixing. When aggregates with a particle size of 5-20mm are mixed with materials with a particle size of 20-40mm during transportation, the existing system cannot distinguish between different batches through physical markings. This makes it impossible to verify whether key quality parameters such as crushing value and alkali activity meet design requirements during on-site acceptance. After receiving the mixed aggregates, operators at the mixing plant cannot obtain the actual proportions of each aggregate size in real time, causing the concrete compressive strength dispersion coefficient to exceed the specified threshold. During the pouring stage, the lack of material traceability data makes it difficult to locate the source of raw materials for components with abnormal quality.

[0018] Failure to address these issues will lead to potential risks such as strength degradation and alkali-aggregate reaction during the service life of concrete structures, making it impossible to provide a complete chain of quality certifications during project acceptance. Information silos in the material flow process will cause difficulties in defining supplier responsibilities and hinder the rapid identification of problematic links under abnormal operating conditions. Data gaps will also reduce the decision-making accuracy of intelligent construction systems, restrict the standardized production process of precast components, and increase the overall lifecycle maintenance costs.

[0019] To address the aforementioned challenges, this embodiment first tackles the inability to dynamically bind geological attributes and quality parameters during the production stage by exploring data binding through physical marking. Considering the wear and tear of traditional QR codes and the limited capacity of barcodes, the focus shifts to embedded electronic tag technology. Taking into account the characteristics of mining operations, durable RFID tags are directly embedded after crushing and screening. To resolve blind spots in trajectory and status monitoring during transportation, GPS and NB-IoT positioning characteristics are compared, and base station positioning technology is chosen to adapt to complex transportation environments, integrating motion sensors for status perception. For the need to update entry acceptance information, an scalable RFID information structure is designed to support incremental writing of on-site management data. Facing the challenge of verifying mixing ratios, a linkage mechanism between fixed reading equipment and the production system is developed to ensure automatic verification of aggregate proportions. To address the issue of missing construction information, a mapping relationship between mobile terminals and component codes is established, forming a closed-loop data loop at the end point. Through end-to-end electronic identification and multi-source data fusion, the traditional manual recording mode is broken through, constructing a verifiable digital traceability system.

[0020] In response, this embodiment proposes a digital intelligent management and control method for the entire life cycle of aggregates, including: in the production stage, after the aggregates are crushed and screened, imitation aggregates are added to the aggregates according to different particle size specifications and preset proportions, and basic geological information and quality control information are written to the imitation aggregates through a fixed RFID reader; in the transportation stage, the imitation aggregates are positioned and their movement status is monitored through the NB-IoT module built into them, and the location, timestamp, movement status and power information are encrypted and uploaded to the cloud platform at a set period; in the site entry stage, the imitation aggregate information is read through a handheld RFID reader and supplemented with site management information; in the mixing stage, the aggregate mixing ratio is automatically identified through the fixed RFID reading device deployed at the mixing plant, and the mixing information is written and uploaded to the cloud management system in real time through the NB-IoT module; in the pouring stage, the aggregate information is read at the pouring point through a mobile reading device and the construction information is written, thereby forming a complete traceability chain from raw materials to finished components.

[0021] Among them, imitation aggregate refers to aggregate substitutes that are artificially made and embedded with electronic identification modules. Specifically, this can be achieved by combining a 3D-printed shell with composite materials, used to carry and transmit data information throughout the entire lifecycle of the aggregate. Fixed RFID readers refer to radio frequency identification devices installed in fixed locations, specifically implemented using high-frequency or ultra-high-frequency readers, used to quickly write geological and quality control information during the aggregate production stage. NB-IoT modules refer to narrowband IoT communication units, specifically implemented using low-power embedded chips, used to encrypt and transmit location, movement status, and power data to a cloud platform during transportation. Handheld RFID readers refer to portable radio frequency identification devices, specifically implemented using industrial-grade terminals supporting batch reading and writing functions, used to supplement on-site management information when aggregates arrive at the site. Fixed RFID reading devices refer to automated identification devices deployed at the mixing plant, specifically implemented by combining anti-interference antennas with industrial controllers, used to verify aggregate proportions in real time and upload mixing information. Among them, the mobile reading device refers to the identification terminal that can be flexibly operated at the pouring point. Specifically, it can be implemented using portable devices with dustproof and shockproof design, used to record the pouring location and construction information during the construction phase to form a traceability chain. The core innovation of this embodiment lies in the combination of imitation aggregate and multi-stage information reading and writing technology to construct a closed-loop data system covering the entire life cycle of production, transportation, delivery, mixing and pouring, thereby achieving full traceability of aggregate from raw materials to finished construction products.

[0022] The working process and principle of this embodiment are as follows: the digital intelligent management and control method for the entire life cycle of aggregates includes five stages: production, transportation, delivery, mixing and pouring.

[0023] During the production stage, after the aggregates are crushed and screened, imitation aggregates are added according to different particle size specifications. The imitation aggregate is a specially designed electronic tag carrier that integrates RFID tags and NB-IoT modules. Basic geological information and quality control information are written to the imitation aggregate using a fixed RFID reader, thus binding data to the material.

[0024] During transportation, the NB-IoT module embedded in the imitation aggregate uses operator base stations for positioning and monitors its movement status through built-in motion sensors. The NB-IoT module encrypts and uploads location, timestamp, movement status, and battery level information to the cloud platform at preset intervals, enabling real-time tracking of the aggregate transportation process.

[0025] During the on-site entry phase, handheld RFID readers are used to read the information of the simulated aggregates and supplement it with on-site management information. This step links supply chain information with aggregate data, providing a basis for subsequent use.

[0026] During the mixing stage, fixed RFID readers deployed at the mixing plant automatically identify the aggregate proportions and write the mixing information. This information is then uploaded to the cloud management system in real time via an NB-IoT module, ensuring the accuracy and traceability of the concrete mix design.

[0027] During the pouring stage, mobile reading equipment reads aggregate information at the pouring point and writes it into the construction information. This step links raw material information with the final component, forming a complete traceability chain from raw materials to finished components.

[0028] Throughout the process, the simulated aggregate serves as the data carrier, enabling digital management and control of the aggregate's entire lifecycle. The combination of RFID and NB-IoT technologies ensures accurate data collection and real-time transmission. The cloud platform integrates data from each stage, providing support for quality management and traceability.

[0029] In its implementation, this digital intelligent management method for the entire lifecycle of aggregates was adopted at a large-scale water conservancy project's aggregate production base. First, after the aggregates are crushed and screened, one imitation aggregate is added for every 10,000 aggregates, according to three particle size specifications: 5-20mm, 20-40mm, and 40-80mm. The imitation aggregate has the same appearance as the real aggregate and integrates an RFID tag and an NB-IoT module internally.

[0030] Fixed RFID readers are installed on the production line to write basic geological information (including mine number, mining time, rock type) and quality control information (including production batch number, particle size, crushing value, and mud content) into the imitation aggregate.

[0031] After the aggregate is loaded onto the truck, the NB-IoT module built into the imitation aggregate begins to operate. The module locates itself via a base station every 30 minutes and monitors its motion using a built-in MEMS triaxial accelerometer. Location, timestamp, motion status, and battery information are encrypted and uploaded to the cloud platform.

[0032] After the aggregates arrive at the construction site, quality inspectors use handheld RFID readers to read the information of the imitation aggregates and add on-site management information such as supplier information, transport vehicle number, and arrival time.

[0033] At the mixing plant, fixed RFID readers are installed at the silo inlet to automatically identify the aggregate mix proportions of the incoming materials. The mixing system writes the mixing information (including concrete mix designation number and mixing time) into the simulated aggregate and uploads it to the cloud management system via an NB-IoT module.

[0034] At the pouring site, construction workers use mobile reading devices to read aggregate information at the pouring point and write down construction information such as the pouring location number, pouring time, and construction team. This information, together with data collected in previous stages, forms a complete traceability chain.

[0035] Through the above-described scheme, this embodiment achieves digital control over the entire process of aggregate production and use. In the production stage, the dynamic binding of geological properties and quality parameters is achieved through simulated aggregate implantation, solving the problem of data and material separation in traditional methods. During transportation, the application of NB-IoT technology fills the blind spots in trajectory and status monitoring, improving logistics management efficiency. In the on-site acceptance stage, the scalable RFID information structure supports real-time updates of on-site management data, enhancing the accuracy of supply chain information. In the mixing stage, the automatic identification system ensures precise control of aggregate proportions, improving the stability of concrete quality. In the pouring stage, the association between mobile terminals and component codes establishes a connection between construction information and raw material data, forming a complete quality traceability system. This end-to-end digital management method significantly improves the accuracy and efficiency of aggregate quality control, providing reliable assurance for the long-term performance of concrete structures, and also providing strong support for engineering quality management and rapid identification of potential problems.

[0036] In some of the above-mentioned solutions in this embodiment, if the proportion of imitation aggregate is not set properly when it is added during the aggregate production stage, it may lead to insufficient tracking samples or excessive interference with aggregate performance. At the same time, the mismatch between the particle size and the actual needs of the project will affect the adaptability of subsequent construction.

[0037] This embodiment further proposes a preset ratio of 1:10000, and different particle size specifications include at least one of 5-20mm, 20-40mm, and 40-80mm.

[0038] The preset ratio, configured by adding one imitation aggregate per 10,000 parts of natural aggregate, ensures uniform distribution of tracking nodes without affecting aggregate gradation characteristics. Particle size classification is based on conventional concrete mix design requirements: 5-20mm corresponds to the fine aggregate gradation range, 20-40mm covers the applicable range of medium-sized aggregates, and 40-80mm is suitable for coarse aggregate construction scenarios. Imitation aggregates of different particle sizes are stored independently in separate containers and simultaneously mixed into the corresponding particle size stream of natural aggregate according to a preset ratio using a metering device.

[0039] Specifically, after the aggregate crushing and screening process, the sorting equipment classifies the natural aggregate into three particle size ranges: 5-20mm, 20-40mm, and 40-80mm. Each particle size range's conveyor belt is equipped with an independent feeding mechanism. When natural aggregate is detected passing through, the feeding mechanism inserts the corresponding imitation aggregate into the material flow at a feeding frequency of 1:10000. For example, during the conveying of 40-80mm coarse aggregate, 1 liter of imitation aggregate is automatically added for every 10 cubic meters of natural aggregate conveyed. This ratio has been verified in the laboratory to ensure at least 3-5 identifiable tracking points in each construction section. The particle size specifications are set within commonly used ranges in construction engineering: 5-20mm imitation aggregate is used for beam and column structural concrete, 20-40mm is suitable for road pavement layers, and 40-80mm is for large-volume foundation pouring. Particle size matching avoids gradation imbalances during construction. This implementation method ensures that quality data collection covers all aggregate specifications while balancing tracking density with project costs.

[0040] In practice, the preset ratio is 1:10000, and the different particle sizes include 5-20mm, 20-40mm, and 40-80mm. On the aggregate production line, one imitation aggregate is added for every 10,000 natural aggregates produced. The imitation aggregate is similar in appearance and weight to the natural aggregate, but integrates an RFID tag and an NB-IoT module. For the 5-20mm particle size, the imitation aggregate is approximately 15mm in size; for the 20-40mm particle size, it is approximately 30mm; and for the 40-80mm particle size, it is approximately 60mm. This tiered placement method ensures that there is a sufficient number of imitation aggregates in each particle size range for comprehensive tracking.

[0041] Through the above technical solution, this embodiment achieves precise tracking of aggregates with different particle sizes. By adding simulated aggregates at a ratio of 1:10000 during the production process, the representativeness and economy of the tracking are ensured. Simultaneously, simulated aggregates of corresponding sizes are set for different particle sizes such as 5-20mm, 20-40mm, and 40-80mm, enabling tracking to cover the full size range of aggregates. This graded tracking method improves the accuracy of aggregate quality control and helps to promptly identify and resolve potential problems with aggregates of specific particle sizes.

[0042] In some of the solutions described above in this embodiment, the basic geological information and quality control information in the aggregate production process lack specific data dimensions, making it impossible to accurately trace the source of raw materials and verify quality compliance, thus affecting the reliability of the entire life cycle management.

[0043] This embodiment further proposes that basic geological information includes at least one of the following: mine number, mining time, rock type, geological stratum, and strength grade; and quality control information includes at least one of the following: production batch number, particle size specification, crushing value, mud content, alkali activity test result, manufacturing date, and quality inspector number.

[0044] Among these features, the mine number and mining time form a spatiotemporal identifier, which is linked to mining operation records through the mining enterprise database; rock type and geological strata are combined with geological exploration reports to establish a correspondence between aggregate mineral composition and original rock strata; strength grade is classified and labeled according to laboratory test data. Production batch number is linked to quality inspector number to achieve traceability of quality responsibility; crushing value, mud content, and alkali reactivity test results are generated into quantitative indicators through standardized testing procedures. For example, crushing value is tested according to GB / T14685 standard, and alkali reactivity test is performed according to JGJ52 specification; particle size specification is linked to production equipment parameters and storage cycle data with the date of manufacture.

[0045] Specifically, during the production stage, fixed RFID readers input the mine number and rock type into the simulated aggregate, and the mechanical properties of the raw materials are marked by strength grade. In the quality control information, the production batch number is matched with the particle size specification to the crushing and screening process parameters, and the crushing value and alkali reactivity test results are entered after laboratory testing. The quality inspector's number is linked to the personnel information database. During the transportation stage, the cloud platform retrieves geological stratum data through the mine number to verify the compliance of the raw material source. During the arrival stage, the acceptance personnel check the test report based on the production batch number and judge the storage status of the aggregate through the mud content index. During the mixing stage, the strength grade is linked with the concrete mix proportion parameters to ensure that the mechanical properties match the design requirements. This forms a full-dimensional data chain from the geological source to the construction application, enabling precise location of quality problems and traceability of responsibility.

[0046] In practice, basic geological information includes mine number, mining time, rock type, geological stratum, and strength grade. Quality control information includes production batch number, particle size specification, crushing value, mud content, alkali reactivity test result, date of manufacture, and quality inspector number. During aggregate production, this information is written to the imitation aggregate using a fixed RFID reader. For example, for a batch of granite aggregate, the following information is written: mine number GS001, mining time May 15, 2023, rock type granite, geological stratum Yanshanian, and strength grade R90. Simultaneously, the following information is written: production batch number B20230515, particle size specification 20-40mm, crushing value 12%, mud content 0.5%, alkali reactivity test result qualified, date of manufacture May 20, 2023, and quality inspector number QC007. This information is written into the RFID chip embedded in the imitation aggregate, forming an electronic ID card for the aggregate.

[0047] Through the above technical solution, this embodiment achieves digital management of the entire lifecycle of aggregates. Recording basic geological information ensures the traceability of aggregate sources, facilitating the identification of quality issues. Recording quality control information directly reflects the key performance indicators of the aggregates, making quality control easier during subsequent use. This method of recording information down to the individual aggregate greatly improves the accuracy and efficiency of aggregate quality management, effectively reducing the risks of mixing and quality problems. Simultaneously, the recording of this digital information provides a foundation for subsequent data analysis and quality improvement, contributing to the continuous optimization of aggregate production and usage processes.

[0048] In some of the solutions described above in this embodiment, the NB-IoT module is used for positioning and motion monitoring to track the aggregate transportation process. However, effective positioning cannot be achieved in scenarios without GPS signals. At the same time, there is a lack of means to monitor abnormal vibrations during transportation, which makes it impossible to accurately determine whether the aggregate is damaged due to bumps or collisions, affecting the controllability of the transportation process. This embodiment further proposes that the positioning step is carried out by the NB-IoT module relying on the operator's base station, and the positioning is achieved in the absence of GPS; the motion status monitoring includes judging the transportation status through the MEMS triaxial accelerometer, realizing motion / stationary identification and abnormal vibration alarm. Among them, the positioning function uses the cellular network signal of the operator's base station for triangulation positioning, without relying on the GPS module, and is suitable for signal-limited scenarios such as tunnels and underground warehouses; the MEMS triaxial accelerometer collects acceleration data in the X, Y and Z axes, and combines it with preset thresholds to determine whether the transport vehicle is in motion or stationary state. When the acceleration fluctuation exceeds the safe range, it triggers an abnormal vibration alarm. Specifically, during the transportation phase, the NB-IoT module obtains vehicle location information through operator base stations, encrypts and uploads the location data to the cloud platform after associating it with a timestamp, ensuring continuous tracking of aggregate location even when GPS fails. The MEMS triaxial accelerometer collects vibration data 10 times per second. After eliminating high-frequency noise through a low-pass filtering algorithm, the valid data is compared with a preset vibration threshold. If an acceleration value exceeding 0.5g is detected three consecutive times, it is considered abnormal vibration, and an alarm message is immediately uploaded to the cloud management system via the NB-IoT module. This solution, through the synergy of base station positioning and acceleration monitoring, achieves all-weather tracking of the transportation trajectory and early warning of physical damage risks, preventing aggregate quality deterioration due to positioning interruptions or improper transportation, while also reducing manual inspection costs.

[0049] In practice, the positioning process relies on operator base stations via the NB-IoT module, enabling location tracking even in GPS-free environments. Specifically, the NB-IoT module utilizes the signal strength and time difference of multiple base stations for triangulation, achieving positioning accuracy within a range of 50-100 meters. In areas with limited GPS signals, such as underground or tunnels, the system automatically switches to base station positioning mode to ensure continuous tracking.

[0050] Motion status monitoring includes using a MEMS triaxial accelerometer to determine the transportation status, enabling motion / stationary identification and abnormal vibration alarms. The accelerometer collects data at a sampling frequency of 100Hz, and a set threshold is used to determine stationary / motion status. When abnormal vibration is detected for more than 5 seconds, the system triggers an alarm and uploads the information to a cloud platform.

[0051] Through the above technical solution, this embodiment achieves precise positioning and status monitoring throughout the entire aggregate transportation process. Positioning functionality remains intact even in areas without GPS signal coverage, avoiding the blind spots inherent in traditional GPS positioning in special environments. Simultaneously, real-time motion monitoring promptly detects anomalies during transportation, such as prolonged vehicle stillness or severe vibration, thereby improving management efficiency and safety in the transportation process. This end-to-end monitoring mechanism effectively reduces the risk of aggregate loss and mixing during transportation, enhancing the reliability and transparency of the aggregate supply chain.

[0052] In some of the solutions described above in this embodiment, when supplementing on-site management information by using a handheld RFID reader during the entry stage, there are problems such as low information entry efficiency and easy errors in manual operation, which leads to limited inventory management efficiency.

[0053] This embodiment further proposes that on-site management information includes at least one of the following: supplier information, transport vehicle number, arrival time, acceptance personnel, and storage area number; and the handheld RFID reader has batch reading and writing function to improve inventory management efficiency.

[0054] Supplier information is precisely linked using the enterprise's unified social credit code or supplier database number; transport vehicle numbers are recorded using license plate numbers or electronic identification codes; arrival time is automatically timestamped using the reader's built-in clock module; acceptance personnel information is bound to the user account of the on-site management system; and storage area numbers are consistent with the coding rules of the warehouse's physical partitions. Batch read / write functionality is achieved through a multi-tag anti-collision algorithm, allowing for the simultaneous reading or writing of multiple RFID tag data points for imitation aggregates in a single operation.

[0055] Specifically, during the acceptance process, operators use handheld RFID readers to scan the entire batch of imitation aggregates. The reader, employing multi-tag recognition technology, completes batch reading of 50 tags within 0.5 seconds, automatically extracting the production batch and transportation information for each aggregate. Acceptance personnel select the corresponding supplier profile through the device interface, and the system automatically links the company's qualification documents. After entering the vehicle's license plate number, the system matches and verifies it against the waybill record in the logistics tracking system. The device's built-in GNSS module acquires the current geographical location and, combined with a real-time clock, generates an arrival time record accurate to the second. After acceptance, operators select the target storage area, and the reader batch-writes information including the acceptance personnel's employee number and storage location code onto all imitation aggregate tags, writing 100 tags at a time in no more than 3 seconds. This process avoids potential information omissions or transcription errors that can occur with manual recording, ensuring real-time correspondence between inventory data and physical location, improving warehousing efficiency by over 80%.

[0056] In practice, on-site management information includes at least one of the following: supplier information, transport vehicle number, arrival time, acceptance personnel, and storage area number. Handheld RFID readers have batch read / write capabilities to improve inventory management efficiency. Specifically, when aggregates arrive on site, staff use handheld RFID readers to scan the RFID tags on the imitation aggregates. The reader automatically identifies and displays the basic geological information and quality control information of the aggregates. Subsequently, staff input on-site management information such as supplier name, transport vehicle license plate number, arrival date and time, acceptance personnel name and employee number, and designated storage area number through the reader's touchscreen interface. The reader supports reading multiple RFID tags at once and batch writing the same on-site management information, significantly improving the efficiency of on-site acceptance and information entry. For example, for a truck carrying 100 tons of aggregates, the reader can complete the reading and writing of all imitation aggregate information within 30 seconds. The reader also has offline storage capabilities, allowing data to be temporarily stored when the network is unstable and automatically synchronized to the cloud management system after the network is restored.

[0057] Through the above technical solution, this embodiment achieves efficient information collection and management in the aggregate entry process. The batch reading and writing function of the handheld RFID reader significantly improves inventory management efficiency and reduces manual data entry errors. The timely recording and uploading of on-site management information provides a reliable data foundation for subsequent aggregate usage and quality traceability. This intelligent entry management method effectively solves the problems of time-consuming and error-prone traditional manual registration, and improves the transparency and traceability of the aggregate supply chain.

[0058] In some of the solutions described above in this embodiment, there are problems with unstable communication signals and data upload delays in the production environment of the mixing plant, which prevents concrete mix proportion information from being synchronized to the management system in real time, affecting the timeliness and accuracy of quality traceability. This embodiment further proposes that during the mixing stage, a fixed RFID reading device deployed at the mixing plant automatically identifies the aggregate proportions and writes the mixing information, which is then uploaded to the cloud management system in real time via an NB-IoT module. The mixing information includes the concrete mix design number, mixing time, and operator information. The NB-IoT module supports low-power wide-area network communication, ensuring real-time and stable data upload, and is compatible with the production environment of the mixing plant. Fixed RFID readers are linked to the mixing machine control system, automatically triggering information reading and writing when aggregates are added to the mixer. The NB-IoT module has a built-in industrial-grade communication chip, establishing a long-term connection with the cloud management system through the operator's network. The concrete mix design number is associated with the engineering design documents, operator information is automatically associated via RFID tags, and the mixing time is accurate to the second with a timestamp. Specifically, when aggregates enter the mixing plant, fixed RFID readers automatically verify the aggregate proportions based on preset mixing ratio thresholds. Upon successful verification, the system writes mixing information, including a unique mix design number, mixing time accurate to the second, and operator ID, to the simulated aggregate. The NB-IoT module utilizes narrowband IoT technology to maintain signal stability in the high-dust, high-vibration environment of the mixing plant. It transmits data packets per second via a carrier base station, ensuring the cloud management system receives mixing data in real time. For example, when an operator starts the mixing program, the equipment automatically compares the mix design number with the design parameters in the engineering BIM model. If the deviation exceeds ±2%, an alarm is triggered. Operator information is written in encrypted form to prevent tampering. The NB-IoT module automatically switches to high-power mode during data transmission and immediately enters sleep mode after transmission, with single-transmission power consumption controlled below 5mA, adapting to the continuous operation requirements of the mixing plant.

[0059] In practice, the mixing plant deploys fixed RFID readers to automatically identify aggregate proportions. Mixing information includes the concrete mix designation number, mixing time, and operator information. The NB-IoT module supports low-power wide-area network communication, ensuring real-time and stable data uploads and adapting to the mixing plant's production environment.

[0060] Specifically, the mixing plant is equipped with multiple fixed RFID readers, located near the aggregate inlet, cement silo, and admixture storage tank. When aggregates, cement, and admixtures enter the mixing system, the RFID readers automatically identify information about each material, including aggregate particle size, cement type, and admixture type. The mixing control system automatically adjusts the dosage of each material according to the preset mix proportion.

[0061] During the mixing process, the system records information such as the concrete mix design number, start and end times of mixing, and operator ID. This information is uploaded to the cloud management system in real time via an NB-IoT module. The NB-IoT module features a low-power design, enabling it to operate stably for extended periods in harsh mixing plant environments. The module also possesses anti-interference capabilities, maintaining stable communication even in high-noise and high-dust environments.

[0062] Through the above technical solution, this embodiment achieves automated monitoring and data acquisition of the mixing process. Real-time uploading of mixing information enables quality management personnel to promptly grasp the production status and quickly identify and handle abnormalities. The application of NB-IoT technology solves the communication challenges in the complex environment of the mixing plant, ensuring the reliability and real-time nature of data transmission. This intelligent mixing management method improves the quality control level of concrete production, reduces human error, and provides reliable data support for subsequent quality traceability.

[0063] In some of the solutions described above in this embodiment, the mobile reading device can complete information entry under normal working conditions. However, in concrete pouring scenarios, high-concentration dust environments can easily cause optical scanning failures, and mechanical vibration interference can easily lead to displacement or poor contact of the contact reading and writing device, which may result in omissions or errors in the recording of construction information.

[0064] This embodiment further proposes that during the pouring stage, a mobile reading device is used to read aggregate information at the pouring point and write construction information, including the pouring location number, pouring time, construction team, and supervisor's signature. The mobile reading device is tested for reading and writing performance in the pouring environment to ensure effective information entry under interference such as dust and vibration.

[0065] The mobile reading device features an IP67-rated housing to prevent dust intrusion and an internal shock-absorbing bracket to buffer the impact of pouring vibrations. The read / write antenna employs a dual-band redundant design, automatically switching to the 915MHz band to maintain communication when interference occurs in the 2.4GHz band. The device has a built-in gyroscope to detect displacement, triggering a data retransmission mechanism when the vibration amplitude exceeds 5mm. Construction information entry uses a tiered verification mode; pouring location numbers are automatically generated from BIM model coordinates; and supervisor signatures are authenticated using both encrypted electronic seals and biometric features.

[0066] Specifically, during concrete pumping operations, operators hold a mobile reading device close to the simulated aggregate. The device captures RFID signals through an anti-interference antenna array, analyzes the aggregate mix proportion data, and automatically generates a pouring location number by associating it with the construction drawings. The device has a built-in triaxial vibration sensor that monitors the amplitude in real time. When the vibration reaches 3 m / s², a data caching mechanism is activated, and the complete data packet is transmitted back via NB-IoT after the vibration weakens. For the supervisor's signature process, the device automatically generates a hash verification code containing a timestamp after the electronic signature is completed, and stores it synchronously with the cloud blockchain node to prevent information tampering. Laboratory simulation tests show that the device maintains a reading success rate of over 98% when PM10 concentration reaches 500 μg / m³, and a data integrity rate of 99.2% under continuous vibration at a frequency of 10 Hz and an amplitude of 8 mm.

[0067] In practice, during the pouring phase, the mobile reading device is configured to read aggregate information and write construction information at the pouring point. This construction information includes the pouring location number, pouring time, construction team, and supervisor's signature. The mobile reading device is tested in the pouring environment to ensure effective information entry even under conditions of dust, vibration, and other interference.

[0068] Specifically, the mobile reading device features a dustproof and waterproof design with an IP67 protection rating. It is equipped with a shock-resistant solid-state drive to ensure stable data storage even in vibrating environments. The read / write module utilizes high-frequency 13.56MHz RFID technology, with a reading distance of up to 30cm, capable of penetrating concrete surfaces to identify internal simulated aggregates. The device screen is a high-brightness display that is readable in sunlight, with a brightness of up to 1000 nits, facilitating operation by construction workers in outdoor environments.

[0069] In practical applications, construction workers use a mobile reading device to scan the simulated aggregate in the pouring area before pouring begins. The device automatically identifies the aggregate information and prompts for input of information such as the pouring location number and construction team. During the pouring process, the device automatically records the pouring time every 15 minutes. After pouring is completed, the supervisor confirms the pouring by electronically signing on the device. This information is uploaded to the cloud management system in real time, forming a complete traceability chain from raw materials to finished components.

[0070] Through the above technical solution, this embodiment achieves accurate collection and recording of aggregate information during the pouring process. The mobile reading device maintains stable performance in complex construction environments, ensuring the accuracy and completeness of data collection. Real-time uploading of construction information establishes a digital traceability system covering the entire process from aggregate production to concrete pouring, improving quality management efficiency and reducing the risk of potential quality problems. Simultaneously, electronic information recording reduces human error and enhances the standardization and traceability of the construction process.

[0071] In some of the solutions described above in this embodiment, a solution for full life-cycle tracking by feeding imitation aggregates is proposed. However, during the aggregate crushing and screening process, conventional packaging processes cannot ensure the accurate positioning of electronic devices inside the shell, and ordinary materials are easily damaged by mechanical impact, causing the shell to break, resulting in the displacement or damage of RFID tags and NB-IoT modules.

[0072] This embodiment further proposes to use 3D printing technology to create a shell for the imitation aggregate before it is put into use. The shell is made of a composite material with a compressive strength greater than 50MPa. The shell manufacturing process is designed to include RFID tags and NB-IoT module installation cavities. The layered printing-encapsulation curing process ensures the precise positioning of electronic components.

[0073] The 3D printing technology forms a shell with a predetermined cavity structure by stacking materials layer by layer. The cavity size matches the shape of the electronic device, with the error controlled within ±0.2mm. The composite material with a compressive strength greater than 50MPa is made by mixing epoxy resin and carbon fiber in a 1:3 mass ratio. After hot pressing, its compressive strength reaches 52-55MPa. During the layer-by-layer printing process, the thickness of each layer is set to 0.1mm. After printing, a silicone buffer layer is injected into the cavity, followed by UV curing and encapsulation, with a curing time of 30-40 seconds.

[0074] Specifically, in the 3D printing stage, a 3D model of the outer shell containing a cylindrical cavity is generated through computer modeling. The cavity diameter is set to 12mm to fit the standard RFID tag size. During the printing process, each layer of material is precisely deposited after being melted at high temperature, forming the main body of the outer shell with the through-cavity. After the outer shell is printed, the NB-IoT module is embedded in the bottom of the cavity, the RFID tag is placed on top of the module, and then liquid silicone is injected to fill the remaining gaps. In the encapsulation and curing stage, ultraviolet light with a wavelength of 365nm is used to irradiate the silicone layer, causing it to form an elastic buffer structure that effectively absorbs vibration and shock during transportation and construction. Tests have shown that this process results in the electronic components having a displacement of less than 0.5mm within the shell, and the shell did not structurally rupture under a pressure of 50MPa.

[0075] In practice, the outer shell is manufactured using 3D printing technology, employing an epoxy resin-based composite material with a compressive strength of 60 MPa as the raw material. During the printing process, a cylindrical cavity is pre-reserved inside the shell, with a diameter of 12 mm and a depth of 8 mm, to accommodate the RFID tag and NB-IoT module. Specifically, a layer-by-layer printing process is used, with each layer controlled to a thickness of 0.1 mm, forming a shell with a cavity structure through layer-by-layer stacking. After each layer is printed, it is immediately subjected to ultraviolet curing treatment for 30 seconds to ensure interlayer bonding strength. Furthermore, after all printing layers are completed, the RFID tag and NB-IoT module are embedded in the cavity and sealed using the same composite material, forming a complete replica of the original material.

[0076] Through the above technical solution, this embodiment solves the problem of insufficient strength in traditional imitation aggregate shells leading to easy damage to electronic components. By combining high-strength composite materials with a layered curing process, the shell achieves pressure resistance while enabling precise positioning and installation of electronic components. This solution further avoids displacement or damage to internal components caused by mechanical impact during transportation and construction, ensuring the continuity and reliability of data acquisition throughout the entire lifecycle.

[0077] In some of the solutions described above in this embodiment, the imitation aggregate must ensure that the outer shell has sufficient structural strength to protect the internal electronic components during the feeding process. At the same time, it is necessary to solve the problem of accurate positioning of electronic components during the manufacturing process of the outer shell to avoid information loss or tracking failure due to damage to the outer shell or displacement of components during transportation and use.

[0078] This embodiment further proposes to create a replica aggregate shell using 3D printing technology, using a composite material with a compressive strength greater than 50MPa. During the shell manufacturing process, RFID tags and NB-IoT module mounting cavities are reserved, and the precise positioning of electronic components is ensured through a layered printing-encapsulation curing process.

[0079] In this process, 3D printing technology forms the outer shell structure by stacking materials layer by layer, and the cavity position is formed synchronously according to the preset model during the printing process. The composite material with a compressive strength greater than 50MPa is a mixture of epoxy resin and quartz sand, which forms a dense structure after high-temperature curing. In the layered printing stage, the outer shell is divided into an inner cavity forming layer and an outer encapsulation layer. After the inner cavity is positioned, printing is paused, and RFID tags and NB-IoT modules are embedded into the cavity. Then, the outer layer is printed and cured and encapsulated by ultraviolet irradiation.

[0080] Specifically, in the manufacturing process of the imitation aggregate shell, a shell model containing the cavity locations is first generated using 3D modeling software. After the model data is imported into a 3D printer, composite material powder is used for layer-by-layer printing. When printing reaches the height of the cavity, printing is paused, and RFID tags and NB-IoT modules are manually placed in their designated positions. Printing of the outer structure then continues until the entire shell is complete. During the encapsulation and curing stage, a layer-by-layer curing process is used. After each 0.2mm thick printed layer, ultraviolet light is applied to rapidly harden the material and fix the internal components. The final shell, after pressure testing, demonstrates a compressive strength of 52-55MPa, and the internal electronic components exhibit displacement of less than 0.1mm during vibration testing. This process ensures that the shell does not suffer structural damage during the mechanical impact of the imitation aggregate during transportation, mixing, and casting, and that the internal electronic components maintain stable operation.

[0081] In practical implementation, the intelligent power management algorithm is configured to dynamically adjust the operating mode of the NB-IoT module based on the transportation status. When the transport vehicle is stationary, the module enters a deep sleep mode, maintaining only the base station registration status; when the vehicle enters the road transport phase, the module uploads location data every 30 minutes; when the vehicle experiences abnormal vibration, the module immediately wakes up and initiates emergency data upload. During the storage phase, the module is activated twice daily for data synchronization according to a preset schedule, remaining in low-power standby mode for the rest of the time. The power supply system uses a rechargeable lithium thionyl chloride battery, and the voltage monitoring circuit feeds back the power information to the control unit in real time.

[0082] Through the above technical solution, this embodiment effectively solves the problem of traditional tracking equipment running out of power due to continuous operation in long-cycle transportation scenarios. By dynamically matching state perception and transmission strategies, energy allocation is optimized while ensuring the integrity of data collection, enabling electronic tags to operate continuously for more than 45 days without external power supply. This ensures the full traceability of aggregates in scenarios such as warehousing and cross-regional transportation, and avoids the break in the quality traceability chain caused by equipment power failure.

[0083] In some of the solutions described above in this embodiment, the NB-IoT module needs to work continuously during transportation and storage to achieve tracking. However, traditional power management methods cannot guarantee the stable operation of the module in long-term scenarios, and there is a risk of data interruption due to power depletion.

[0084] This embodiment further proposes that the NB-IoT module adopts an intelligent power management algorithm to adaptively wake up and transmit data during transportation and storage, ensuring continuous operation for more than 45 days to meet long-term tracking requirements.

[0085] Among them, the intelligent power consumption management algorithm dynamically adjusts the wake-up interval according to the transportation status, increases the data upload frequency during transportation, and extends the sleep time during storage; the module has a built-in motion state detection unit, which combines the acceleration sensor data during the transportation stage to determine the current status and trigger the corresponding power consumption mode; and adopts a low-power wide area network communication protocol to optimize the data transmission packet size and frequency, thereby reducing the energy consumption of a single transmission.

[0086] Specifically, during transportation, the module monitors vibration frequency and identifies vehicle movement status through a MEMS triaxial accelerometer. When continuous movement is detected, the algorithm shortens the wake-up cycle to 10 minutes and uploads location and status data in real time. During storage, the module switches to deep sleep mode and wakes up every 6 hours to transmit heartbeat signals. If abnormal movement is detected, it is activated immediately. By dynamically adjusting the working mode, the module ensures data real-time performance while keeping the average daily power consumption below 20mAh. Combined with a high-capacity battery design, it achieves a continuous working range of more than 45 days, covering the entire lifecycle tracking needs from transportation to concrete pouring.

[0087] In practice, the shell of the imitation aggregate is manufactured using a 3D printer, employing a high-strength composite material with a compressive strength of 55 MPa. The shell printing process is divided into two stages: inner layer structure forming and outer encapsulation. First, according to preset cavity size parameters, the inner layer printing stage forms an mounting cavity to accommodate the RFID tag and NB-IoT module, with a slot structure at the cavity opening. Then, the outer encapsulation is printed, covering the inner layer structure layer by layer, and each layer is cured by ultraviolet light after printing, ultimately forming a uniformly thick sealed shell. After pressure testing, the printed shell is fitted with electronic components and sealed with epoxy resin. Through the above technical solution, this embodiment achieves precise positioning and reliable encapsulation of electronic devices inside the aggregate, avoiding damage to electronic components caused by mechanical impact during transportation and construction. At the same time, the high-strength shell material ensures the structural integrity of the imitation aggregate during concrete mixing, ensuring the continuity of data collection throughout the entire life cycle, and effectively solving the technical defects of electronic tags that are prone to falling off and failing in traditional tracking methods.

[0088] Reference Figure 2 , Figure 2 This is a structural block diagram of the first embodiment of the digital intelligent management and control device for the entire life cycle of aggregates in this application.

[0089] like Figure 2 As shown in the embodiments of this application, the digital intelligent management and control device for the entire life cycle of aggregates includes: The information writing module 10 is used to add imitation aggregates to the aggregates according to different particle size specifications and preset ratios after the aggregates are crushed and screened during the production stage, and to write basic geological information and quality control information to the imitation aggregates through a fixed RFID reader. The transportation module 20 is used to locate and monitor the movement status by imitating the NB-IoT module built into the aggregate during the transportation stage, and to encrypt and upload the location, timestamp, movement status and power information to the cloud platform according to the set period. The reading module 30 is used to read the imitation aggregate information through a handheld RFID reader during the entry stage and supplement it with on-site management information. The mixing module 40 is used to automatically identify the aggregate proportions through the fixed RFID reading device deployed at the mixing plant during the mixing stage, write the mixing information, and upload it to the cloud management system in real time via the NB-IoT module. The output module 50 is used to read aggregate information at the pouring point through a mobile reading device during the pouring stage and write construction information, thereby forming a complete traceability chain from raw materials to finished components.

[0090] It should be understood that the above are merely illustrative examples and do not constitute any limitation on the technical solution of this application. In specific applications, those skilled in the art can make settings as needed, and this application does not impose any restrictions on this.

[0091] This embodiment constructs a full-chain traceability system from raw materials to finished products by embedding imitation aggregates and writing geological and quality data during the production stage, real-time monitoring and positioning during the transportation stage, supplementing management information during the entry stage, automatically identifying the proportions during the mixing stage, and recording construction information during the pouring stage. It has the advantages of realizing full-process quality traceability, real-time monitoring of transportation status, and interconnection of data across multiple stages.

[0092] It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of this application. In practical applications, those skilled in the art can select some or all of it to achieve the purpose of this embodiment according to actual needs, and no restrictions are imposed here.

[0093] In addition, for technical details not described in detail in this embodiment, please refer to the method for digital intelligent management and control of aggregate throughout its entire life cycle provided in any embodiment of this application, which will not be repeated here.

[0094] Furthermore, it should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0095] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0096] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as read-only memory (ROM) / RAM, magnetic disk, optical disk), and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods of the various embodiments of this application. The above are only preferred embodiments of this application and do not limit the patent scope of this application. All equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A digital intelligent management and control method for the entire life cycle of aggregates, characterized in that, include: During the production stage, after the aggregate is crushed and screened, imitation aggregate is added to the aggregate according to different particle size specifications and preset proportions, and basic geological information and quality control information are written into the imitation aggregate through a fixed RFID reader. During the transportation phase, the NB-IoT module built into the imitation aggregate is used for positioning and motion status monitoring, and the location, timestamp, motion status and power information are encrypted and uploaded to the cloud platform according to the set period. During the entry phase, the information of the imitation aggregate is read using a handheld RFID reader, and the on-site management information is supplemented accordingly. During the mixing stage, the fixed RFID reading device deployed at the mixing plant automatically identifies the aggregate proportions and writes the mixing information, which is then uploaded to the cloud management system in real time via the NB-IoT module. During the pouring stage, mobile reading equipment reads aggregate information at the pouring point and writes it into construction information, thus forming a complete traceability chain from raw materials to finished components.

2. The method according to claim 1, characterized in that, The preset ratio is 1:10000, and the different particle size specifications include at least one of 5-20mm, 20-40mm, and 40-80mm.

3. The method according to claim 1, characterized in that, The basic geological information includes at least one of the following: mine number, mining time, rock type, geological strata, and strength grade; The quality control information includes at least one of the following: production batch number, particle size specification, crushing value, mud content, alkali activity test result, manufacturing date, and quality inspector number.

4. The method according to claim 1, characterized in that, The positioning step is performed by the NB-IoT module relying on the operator's base station, and positioning is achieved in the absence of GPS. The motion state monitoring includes determining the transportation status through a MEMS triaxial accelerometer to achieve motion / stationary identification and abnormal vibration alarm.

5. The method according to claim 1, characterized in that, The on-site management information includes at least one of the following: supplier information, transport vehicle number, arrival time, acceptance personnel, and storage area number; and the handheld RFID reader has batch reading and writing capabilities to improve inventory management efficiency.

6. The method according to claim 1, characterized in that, The mixing information includes concrete mix designation number, mixing time, and operator information; the NB-IoT module supports low-power wide-area network communication to ensure real-time and stable data upload, adapting to the production environment of the mixing plant.

7. The method according to claim 1, characterized in that, The construction information includes the pouring location number, pouring time, construction team, and supervisor's signature; and the mobile reading device is tested for reading and writing performance in the pouring environment to ensure effective information entry under interference such as dust and vibration.

8. The method according to claim 1, characterized in that, Before being used, the imitation aggregate is made into a shell using 3D printing technology. It is made of composite material with a compressive strength greater than 50MPa. During the manufacturing process of the shell, RFID tags and NB-IoT module installation cavities are reserved. The precise positioning of electronic components is ensured through a layered printing-encapsulation curing process.

9. The method according to claim 1, characterized in that, The NB-IoT module adopts an intelligent power management algorithm, which adaptively wakes up and transmits data during transportation and storage, ensuring continuous operation for more than 45 days to meet long-term tracking requirements.

10. A digital intelligent control device for the entire life cycle of aggregates, characterized in that, include: The information writing module is used in the production stage to add imitation aggregates to the aggregates after crushing and screening, according to different particle size specifications and preset ratios, and to write basic geological information and quality control information to the imitation aggregates through a fixed RFID reader. The transportation module is used to locate and monitor the movement status of the aggregate during the transportation phase by using the NB-IoT module built into the aggregate, and to encrypt and upload the location, timestamp, movement status and power information to the cloud platform at a set period. The reading module is used to read the imitation aggregate information using a handheld RFID reader during the entry phase and supplement it with on-site management information. The mixing module is used to automatically identify the aggregate proportions through fixed RFID reading devices deployed at the mixing plant during the mixing stage, write the mixing information, and upload it to the cloud management system in real time via the NB-IoT module. The output module is used to read aggregate information at the pouring point through a mobile reading device during the pouring stage and write construction information, thereby forming a complete traceability chain from raw materials to finished components.

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