Three-dimensional warehouse capacity online measurement system and measurement method

Abstract

The invention relates to the technical field of three-dimensional warehouse capacity measurement, in particular to a three-dimensional warehouse capacity online measurement system and method, and the system comprises a 3D radar which is used for measuring the height of materials in each warehouse in real time; the material distribution belt conveyor is mounted on the three-dimensional warehouse; the storage capacity calculation module is used for calculating the weight of the material according to the material height data obtained through 3D radar scanning and the size of the geometrical shape of the three-dimensional storage; the data acquisition and processing module is used for receiving and processing the storage capacity data scanned by the 3D radar; the control module is used for monitoring and early warning the storage capacity and automatically adjusting the purchase plan and the production scheduling operation; through mutual cooperative work of all the modules, the accuracy and reliability of measurement are improved, and powerful support is provided for purchase planning, production scheduling, asset inventory and the like.

Description

Technical Field

[0001] The invention belongs to the technical field of storage capacity measurement of a three-dimensional warehouse, and in particular relates to an online storage capacity measurement system and a measurement method of a three-dimensional warehouse. Background Art

[0002] The bulk powder three-dimensional warehouse is composed of multiple neatly arranged warehouses. Each warehouse can store different bulk materials. Through real-time high-precision measurement of the warehouse feeding and storage capacity during use, the material inventory is recorded in real time, which serves as a reliable basis for procurement planning, production scheduling, and asset inventory.

[0003] In the prior art, the patent application number is 202311200392.1, which discloses a bulk powder warehouse monitoring system, including a fixed seat, a hemispherical cover, a semi-circular cleaning piece, a driving piece and a monitoring assembly; the hemispherical cover is installed on the surface of the fixed seat; the two ends of the semi-circular cleaning piece are respectively installed on both sides of the hemispherical cover, and the surface of the semi-circular cleaning piece is in contact with the hemispherical cover; the driving end of the driving piece is connected to the semi-circular cleaning piece by transmission; the monitoring assembly includes a monitoring head, a control unit and a detection device, the control unit is installed in the fixed seat, the monitoring head and the detection device are installed on the surface of the fixed seat within the range of the hemispherical cover, the monitoring head and the detection device are both electrically connected to the control unit, and the control unit is electrically connected to the driving piece; when the detection device detects that the surface visibility of the semi-circular cleaning piece is lower than the set threshold, the control unit controls the driving piece to drive the semi-circular cleaning piece to clean the hemispherical cover according to the detection signal. The monitoring system can ensure that the monitoring head can always accurately obtain the corresponding environmental information.

[0004] However, when the above-mentioned three-dimensional warehouse is in use, the stacking state of bulk powder changes dynamically, which may cause the storage capacity detection result to deviate from the actual situation. In particular, when the material is stacked too high or too low, the monitoring system may find it difficult to accurately capture its changes, thereby affecting the accuracy of the storage capacity measurement. Therefore, we need to propose a three-dimensional warehouse capacity online measurement system and measurement method to solve the above-mentioned problems, so that it can effectively improve the accuracy and reliability of the measurement. Summary of the invention

[0005] In view of the above problems, the present invention provides a three-dimensional warehouse capacity online measurement system, comprising: a 3D radar, the 3D radar is used to measure the height of materials in each warehouse in real time;

[0006] A material distribution belt conveyor installed on the three-dimensional warehouse, the material distribution belt conveyor includes a continuous material distribution belt for uniformly conveying bulk materials to each warehouse top and a driving mechanism for driving the continuous material distribution belt to move, and the 3D radar is installed at the material drop point of the continuous material distribution belt;

[0007] A storage capacity calculation module is used to calculate the volume of materials in each storage according to the material height data obtained by 3D radar scanning and the size of the geometric shape of the three-dimensional storage, and then calculate the weight of the material according to the density of the material or the relationship between weight and volume;

[0008] A data acquisition and processing module, which is used to receive and process the storage capacity data scanned by the 3D radar;

[0009] A control module, which is used to monitor and warn the storage capacity and automatically adjust the purchase plan and production scheduling operation;

[0010] The 3D radar is electrically connected to the storage capacity calculation module and the data acquisition and processing module respectively, and the storage capacity calculation module and the data acquisition and processing module are both electrically connected to the control module.

[0011] Furthermore, the 3D radar includes a signal driving unit responsible for generating and adjusting the low-frequency pulse signal required by the radar, an electronic circuit for receiving the reflected pulse signal, and a plurality of transmitting antennas arranged in an array for transmitting the low-frequency pulse. The electronic circuit is mainly composed of a receiver and a processor, which converts the received pulse signal into a digital signal for processing.

[0012] Furthermore, the 3D radar transmits low-frequency pulses through the transmitting antenna during detection. When the pulses encounter the surface of the material, reflected echoes are generated. The receiver receives these reflected echoes and samples and analyzes the reflected echo signals through the processor to obtain the time and speed of light at each point. The distance D of the material surface relative to the 3D radar is calculated based on the time and speed of light. The calculation formula for distance D is: distance D = speed of light * time / 2. The calculated distances D are then combined to form a three-dimensional image of the material surface.

[0013] Furthermore, the process of calculating the material weight by the storage capacity calculation module is as follows:

[0014] A1. Determine the material height data h, which is the same as the distance D of the material surface relative to the 3D radar;

[0015] A2. Measure the geometric dimensions of the three-dimensional warehouse, including the length and width of the warehouse body;

[0016] A3. Calculate the volume V of a single material based on the material height data h and the geometric dimensions of the three-dimensional warehouse 单 , single material volume V 单 The formula is as follows: 单 =Ah, where A is the bottom area of ​​the silo, which is the length multiplied by the width;

[0017] A4. Add up the individual volumes of all measurement points to get the total volume V 总 ;

[0018] A5. According to the total volume V 总 Calculate the mass m of the material. The mass m calculation formula is: m = ρV 总 , where ρ represents the density of the material.

[0019] Furthermore, the process of the data acquisition and processing module processing the storage capacity data is as follows:

[0020] B1. Receive the original storage capacity data scanned by 3D radar, which includes point cloud data and material surface height;

[0021] B2. Preprocess the received storage capacity data. The preprocessing process includes denoising, filtering and outlier detection operations;

[0022] B3. Integrate the data from 3D radar to form a unified data set;

[0023] B4. Analyze the integrated data set to obtain the material volume reduction trend and predict future inventory requirements, and transmit it to the control module for processing.

[0024] Furthermore, in step B2, when preprocessing the reservoir capacity data, first use statistical methods or machine learning algorithms to identify and remove noise in the data; then apply spatial filters to smooth the data and reduce the impact of high-frequency noise; and then use statistical tests to identify outliers in the data.

[0025] Furthermore, the control module's process for storage capacity monitoring and early warning is as follows:

[0026] C1, the control module receives the storage capacity data from the data acquisition and processing module;

[0027] C2, analyze the received data and extract key information;

[0028] C3. Set the warning threshold of storage capacity based on historical data and business rules;

[0029] C4. When the actual storage capacity exceeds or falls below the preset threshold, the control module will trigger the early warning mechanism, and the early warning signal will be conveyed to relevant personnel via SMS, email or system pop-up window;

[0030] C5. Continuously optimize warning thresholds and warning strategies based on business development and environmental changes.

[0031] Furthermore, the process of the control module automatically adjusting the procurement plan and production scheduling operation is as follows:

[0032] C11. Develop production plans based on market demand, material volume reduction trends, and forecast future inventory requirements, and determine production quantity and time;

[0033] C12. Convert the production plan into specific production tasks, assign them to the corresponding production lines or work centers, and schedule and dispatch them according to the priority and resource conditions of the production tasks;

[0034] C13. Real-time monitoring of production progress, resource utilization and production quality;

[0035] C14. Generate various production reports to analyze and evaluate the production situation, including production cost analysis, production efficiency analysis and production quality analysis;

[0036] C15. Visualize the analysis results in the form of charts and curves.

[0037] Furthermore, in step C11, when formulating the production plan, first collect market demand data, analyze the trend of material volume reduction, understand the impact of material volume reduction on production, predict future inventory demand, combine sales forecasts, order status, and safety stock level factors, and then conduct a comprehensive assessment of existing production resources. Then, according to market demand and inventory forecasts, formulate a preliminary production plan, and then use linear programming or integer programming algorithms to optimize the production plan. Then, by simulating different production scenarios, find the best production strategy.

[0038] Based on the above-described three-dimensional warehouse capacity online measurement system, the present invention also provides a three-dimensional warehouse capacity online measurement method, comprising the following steps:

[0039] S1. Install the 3D radar at the material drop point of the continuous fabric belt, and use the 3D radar to measure the material scheduling in each inventory in real time;

[0040] S2. Calculate the volume of materials in each warehouse by combining the size of the geometric shape of the three-dimensional warehouse through the warehouse capacity calculation module, and then calculate the weight of the material according to the density of the material or the relationship between weight and volume;

[0041] S3, the control module performs real-time monitoring and early warning of the storage capacity according to the preset control logic and algorithm;

[0042] S4, the original storage capacity data collected in real time by 3D radar is analyzed and processed by the data acquisition and processing module and transmitted to the control module;

[0043] S5. After receiving the data from the data acquisition and processing module, the control module automatically adjusts the purchase plan and production scheduling operations in combination with the material weight obtained by the storage capacity calculation module.

[0044] The beneficial effects of the present invention are:

[0045] 1. The present invention cooperates with 3D radar, material distribution belt conveyor, storage capacity calculation module, data acquisition and processing module and control module. The 3D radar can quickly and accurately obtain the three-dimensional data of the material, providing a reliable basis for calculating the volume and weight of the material. The continuous material distribution belt can ensure that the material is evenly distributed in the warehouse, thereby reducing measurement errors. The storage capacity calculation module calculates the volume of the material in each warehouse based on the size of the geometric shape of the three-dimensional warehouse, and then further calculates the weight of the material based on the density or weight and volume of the material. The control module monitors and warns the storage capacity in real time according to the preset control logic and algorithm. At the same time, the control module automatically adjusts the procurement plan, production scheduling and other operations according to the material inventory situation. Through the mutual cooperation of various modules, the accuracy and reliability of measurement are improved, providing strong support for procurement plans, production scheduling, asset inventory, etc.

[0046] 2. The present invention cooperates with a 3D radar and a material distribution belt conveyor. The 3D radar is driven by the material distribution belt conveyor to move continuously across the top of each warehouse. The 3D radar scans the height of the materials in each warehouse, establishes a three-dimensional model, calculates the volume and weight of the materials in each warehouse, and improves the accuracy of calculating the materials in each three-dimensional warehouse.

[0047] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0049] Figure 1 A block diagram of an online measurement system according to an embodiment of the present invention is shown;

[0050] Figure 2 A flowchart of material weight calculation by a storage capacity calculation module according to an embodiment of the present invention is shown;

[0051] Figure 3 A flowchart of the data acquisition and processing module processing storage capacity data according to an embodiment of the present invention is shown;

[0052] Figure 4A flowchart of the control module for storage capacity monitoring and early warning according to an embodiment of the present invention is shown;

[0053] Figure 5 A flowchart showing the process of automatically adjusting the purchase plan and production scheduling operation of the control module according to an embodiment of the present invention is shown;

[0054] Figure 6 A flowchart of online measurement according to an embodiment of the present invention is shown;

[0055] Figure 7 A schematic diagram showing the 3D radar detecting materials in different states in a stereoscopic warehouse according to an embodiment of the present invention is shown;

[0056] Figure 8 A schematic diagram of the distribution of cloth belts in a rectangular array stereoscopic warehouse according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0058] The embodiment of the present invention provides a three-dimensional warehouse storage capacity online measurement system, such as Figure 1-5 As shown, it includes a 3D radar, a material distribution belt conveyor, a storage capacity calculation module, a data acquisition and processing module and a control module. The 3D radar is used to measure the height of materials in each warehouse in real time; the material distribution belt conveyor includes a continuous material distribution belt for evenly conveying bulk materials to the top of each warehouse and a driving mechanism for driving the continuous material distribution belt to move. The 3D radar is installed at the drop point of the continuous material distribution belt. The 3D radar is driven by the material distribution belt conveyor to move and continuously pass through each warehouse top. The 3D radar scans the height of the materials in each warehouse, establishes a three-dimensional model, calculates the volume and weight of the materials in each warehouse, and improves the accuracy of the calculation of the materials in each three-dimensional warehouse;

[0059] The 3D radar includes a signal driving unit responsible for generating and adjusting the low-frequency pulse signal required by the radar, an electronic circuit for receiving the reflected pulse signal, and a plurality of transmitting antennas arranged in an array for transmitting the low-frequency pulse. Each transmitting antenna has good directivity and can scan the material surface at thousands of points, thereby realizing accurate measurement of the surface morphology of the material. The electronic circuit is mainly composed of a receiver and a processor, which converts the received pulse signal into a digital signal for processing. When the 3D radar is detecting, it transmits a low-frequency pulse through the transmitting antenna. When the pulse encounters the material surface, a reflected echo is generated. The receiver receives these reflected echoes, and samples and analyzes the reflected echo signal through the processor to obtain the time and speed of light of each point, and then calculates the distance D of the material surface relative to the 3D radar according to the time and speed of light. The calculation formula of the distance D is: distance D = speed of light * time / 2, and then the calculated distance D is combined to form a three-dimensional image of the material surface, which not only provides the highest point, the lowest point and the average height of the material, but also can calculate the volume and weight of the material.

[0060] When forming a three-dimensional image of the material surface, the calculated distance D is first denoised and filtered, and then the polar coordinates of the processed data are converted into three-dimensional coordinates. The shape of the material surface is reconstructed based on the three-dimensional coordinate data, and finally the accuracy of the generated three-dimensional image is verified by comparing it with the actual measured data source.

[0061] The storage capacity calculation module is used to calculate the volume of materials in each storage according to the material height data obtained by 3D radar scanning and the size of the geometric shape of the three-dimensional storage, and then calculate the weight of the material according to the density of the material or the relationship between weight and volume;

[0062] The geometrical dimensions of the three-dimensional warehouse include the length, width and height of the warehouse body, and the geometrical dimensions of the three-dimensional warehouse are obtained by on-site measurement with a laser rangefinder.

[0063] The process of calculating material weight by the storage capacity calculation module is as follows:

[0064] A1. Determine the material height data h, which is the same as the distance D of the material surface relative to the 3D radar;

[0065] A2. Measure the geometric dimensions of the three-dimensional warehouse, including the length and width of the warehouse body;

[0066] A3. Calculate the volume V of a single material based on the material height data h and the geometric dimensions of the three-dimensional warehouse 单 , single material volume V 单 The formula is as follows: 单 =Ah, where A is the bottom area of ​​the silo, which is the length multiplied by the width;

[0067] A4. Add up the individual volumes of all measurement points to get the total volume V 总 ;

[0068] A5. According to the total volume V 总 Calculate the mass m of the material. The mass m calculation formula is: m = ρV 总 , where ρ represents the density of the material.

[0069] The data acquisition and processing module is used to receive and process the storage capacity data scanned by the 3D radar;

[0070] The process of the data acquisition and processing module processing the storage capacity data is as follows:

[0071] B1. Receive the original storage capacity data scanned by 3D radar, which includes point cloud data and material surface height;

[0072] B2. Preprocess the received storage capacity data. The preprocessing process includes denoising, filtering and outlier detection operations;

[0073] B3. Integrate the data from 3D radar to form a unified data set;

[0074] B4. Analyze the integrated data set to obtain the material volume reduction trend and predict future inventory demand, and transmit it to the control module for processing;

[0075] Material volume reduction trend uses statistical analysis methods to identify the trend of material volume changes. For example, you can calculate the mean, standard deviation and other statistics of the material volume in each time period, and apply time series analysis techniques such as moving average, exponential smoothing or ARIMA model to detect the trend of material volume reduction over time.

[0076] Forecasting future inventory requirements Based on historical sales data, market trends and seasonal factors, combined with the trend of material volume reduction, use forecasting models (such as linear regression, time series forecasting, neural networks) to estimate future inventory requirements.

[0077] Among them, in step B2, when preprocessing the reservoir capacity data, statistical methods or machine learning algorithms are first used to identify and remove noise in the data. For example, the average distance between each point and its neighbors can be calculated, and those points whose distance is significantly greater than the average value can be regarded as noise and removed; then a spatial filter, such as a Gaussian filter, is applied to smooth the data and reduce the impact of high-frequency noise. This helps to highlight the main features of the signal while suppressing unimportant details; then a statistical test (such as a Z-score or an IQR method) is used to identify outliers in the data. These outliers may be caused by sensor errors, environmental interference, or other abnormal operating conditions; once outliers are detected, they are deleted or replaced with reasonable estimates.

[0078] The control module is used to monitor and warn the storage capacity and automatically adjust the procurement plan and production scheduling operations. The 3D radar is electrically connected to the storage capacity calculation module and the data acquisition and processing module respectively, and the storage capacity calculation module and the data acquisition and processing module are both electrically connected to the control module.

[0079] The control module's process for storage capacity monitoring and early warning is as follows:

[0080] C1. The control module receives the storage capacity data from the data acquisition and processing module to achieve real-time monitoring of the material inventory in the three-dimensional warehouse. The monitoring content includes key information such as the height, volume and distribution of the materials, ensuring that the management personnel can grasp the inventory status at any time;

[0081] C2. Analyze the received data and extract key information, such as material volume, material surface height, etc. By analyzing historical data, the system can predict future inventory demand and provide a scientific basis for procurement planning and production scheduling;

[0082] C3. Set warning thresholds for inventory capacity based on historical data and business rules. Warning thresholds can be key indicators such as maximum inventory, minimum inventory, or safety inventory.

[0083] C4. When the actual storage capacity exceeds or falls below the preset threshold, the control module will trigger the early warning mechanism, and the early warning signal will be conveyed to relevant personnel via SMS, email or system pop-up window;

[0084] C5. Continuously optimize warning thresholds and warning strategies based on business development and environmental changes.

[0085] Among them, when setting the preset threshold of storage capacity, it is necessary to first collect and analyze the sales data of the past period of time, understand the product's sales cycle, seasonal fluctuations, trend changes, etc., and then evaluate the supplier's delivery time, production capacity and logistics transportation stability. Based on the above analysis, determine a minimum inventory level, that is, the safety inventory level, to prevent supply interruptions or sudden increases in demand to maintain normal operations, and then classify and manage the inventory goods, dividing them into three categories: A, B, and C. Among them, Class A goods are important goods and a lower warning threshold should be set; for Class B and Class C goods, the warning threshold should be appropriately increased according to actual conditions. According to different product characteristics and market demands, formulate corresponding replenishment strategies, such as regular replenishment, quantitative replenishment or dynamic replenishment, etc., regularly review inventory status and sales, and adjust the warning threshold according to actual conditions.

[0086] The process of the control module to automatically adjust the procurement plan and production scheduling operation is as follows:

[0087] C11. Develop production plans based on market demand, material volume reduction trends, and forecast future inventory demand, determine production quantity and time, and consider the supply of production resources to ensure the rationality of the production plan;

[0088] When formulating a production plan, first collect market demand data, including historical sales data, market trends, seasonal fluctuations, etc.; analyze the trend of material volume reduction, understand the impact of material volume reduction on production, predict future inventory demand, combine sales forecasts, order status, and safety stock level factors, and then conduct a comprehensive assessment of existing production resources, including manpower, equipment, raw materials, etc., considering resource availability, efficiency and cost, to ensure that the implementation of the production plan will not be limited by resources, and then formulate a preliminary production plan based on market demand and inventory forecasts, including production quantity and schedule, to ensure that the production plan matches the sales forecast and avoid overproduction or insufficient inventory, and then use linear programming or integer programming algorithms to optimize the production plan, considering various constraints in the production process, such as production capacity, delivery deadlines, cost constraints, etc., and then find the best production strategy by simulating different production scenarios. When formulating a production plan, it is necessary to consider the stability and reliability of the supply chain, establish a close cooperative relationship with suppliers, ensure the timely supply of raw materials, monitor potential risks in the supply chain, such as supplier bankruptcy, logistics delays, etc., and formulate corresponding response measures.

[0089] C12. Convert the production plan into specific production tasks, assign them to the corresponding production lines or work centers, and schedule and dispatch them according to the priority and resource conditions of the production tasks;

[0090] C13. Real-time monitoring of production progress, resource utilization and production quality to identify and resolve production problems in a timely manner;

[0091] C14. Generate various production reports to analyze and evaluate the production situation, including production cost analysis, production efficiency analysis and production quality analysis;

[0092] C15. Visualize the analysis results in the form of charts and curves to help managers understand the inventory situation more intuitively. Visual information display helps to quickly identify potential problems and make decisions.

[0093] 3D radar can quickly and accurately obtain three-dimensional data of materials, providing a reliable basis for calculating material volume and weight. Continuous cloth belts can ensure that materials are evenly distributed in the warehouse, thereby reducing measurement errors. The warehouse capacity calculation module combines the geometric shape and size of the three-dimensional warehouse to calculate the volume of materials in each warehouse, and then further calculates the weight of the material based on the density or weight of the material and the relationship between the volume. The control module monitors and warns the warehouse capacity in real time based on the preset control logic and algorithm. At the same time, the control module automatically adjusts the procurement plan, production scheduling and other operations according to the material inventory situation. Through the mutual cooperation of various modules, the accuracy and reliability of measurement are improved, providing strong support for procurement plans, production scheduling, asset inventory, etc.

[0094] Based on the above-described three-dimensional warehouse storage capacity online measurement system, the present invention also provides a three-dimensional warehouse storage capacity online measurement method, such as Figure 6-8 As shown, the following steps are included:

[0095] S1. Install the 3D radar at the drop point of the continuous fabric belt, and use the 3D radar to measure the material scheduling in each inventory in real time, such as Figure 7 The figure shows the schematic diagram of 3D radar detecting materials in different states in the stereoscopic warehouse. Figure 8 This is a schematic diagram of the distribution of cloth belts in a rectangular array three-dimensional warehouse;

[0096] S2. Calculate the volume of materials in each warehouse by combining the size of the geometric shape of the three-dimensional warehouse through the warehouse capacity calculation module, and then calculate the weight of the material according to the density of the material or the relationship between weight and volume;

[0097] S3, the control module performs real-time monitoring and early warning of the storage capacity according to the preset control logic and algorithm;

[0098] S4, the original storage capacity data collected in real time by 3D radar is analyzed and processed by the data acquisition and processing module and transmitted to the control module;

[0099] S5. After receiving the data from the data acquisition and processing module, the control module automatically adjusts the purchase plan and production scheduling operations in combination with the material weight obtained by the storage capacity calculation module.

[0100] Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent substitutions for some of the technical features therein; and these modifications or substitutions do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A three-dimensional warehouse capacity online measurement system, characterized by: include: 3D radar, which is used to measure the height of materials in each warehouse in real time; A material distribution belt conveyor installed on the three-dimensional warehouse, the material distribution belt conveyor includes a continuous material distribution belt for uniformly conveying bulk materials to each warehouse top and a driving mechanism for driving the continuous material distribution belt to move, and the 3D radar is installed at the material drop point of the continuous material distribution belt; A storage capacity calculation module is used to calculate the volume of materials in each storage according to the material height data obtained by 3D radar scanning and the size of the geometric shape of the three-dimensional storage, and then calculate the weight of the material according to the density of the material or the relationship between weight and volume; A data acquisition and processing module, which is used to receive and process the storage capacity data scanned by the 3D radar; A control module, which is used to monitor and warn the storage capacity and automatically adjust the purchase plan and production scheduling operation; The 3D radar is electrically connected to the storage capacity calculation module and the data acquisition and processing module respectively, and the storage capacity calculation module and the data acquisition and processing module are both electrically connected to the control module.

2. The online measurement system for storage capacity of a three-dimensional warehouse according to claim 1 is characterized in that: The 3D radar includes a signal driving unit responsible for generating and adjusting the low-frequency pulse signal required by the radar, an electronic circuit for receiving the reflected pulse signal, and multiple transmitting antennas arranged in an array for transmitting low-frequency pulses. The electronic circuit is mainly composed of a receiver and a processor, which converts the received pulse signal into a digital signal for processing.

3. The online measurement system for storage capacity of a three-dimensional warehouse according to claim 2 is characterized in that: During detection, the 3D radar transmits low-frequency pulses through the transmitting antenna. When the pulses encounter the material surface, reflected echoes are generated. The receiver receives these reflected echoes and samples and analyzes the reflected echo signals through the processor to obtain the time and speed of light at each point. The distance D of the material surface relative to the 3D radar is calculated based on the time and speed of light. The calculation formula of distance D is: distance D = speed of light * time / 2. The calculated distances D are then combined to form a three-dimensional image of the material surface.

4. The online measurement system for storage capacity of a three-dimensional warehouse according to claim 3 is characterized in that: The process of calculating material weight by the storage capacity calculation module is as follows: A1. Determine the material height data h, which is the same as the distance D of the material surface relative to the 3D radar; A2. Measure the geometric dimensions of the three-dimensional warehouse, including the length and width of the warehouse body; A3. Calculate the volume V of a single material based on the material height data h and the geometric dimensions of the three-dimensional warehouse 单 , single material volume V 单 The formula is as follows: V 单 =Ah, where A is the bottom area of ​​the silo, which is the length multiplied by the width; A4. Add up the individual volumes of all measurement points to get the total volume V 总 ; A5. According to the total volume V 总 Calculate the mass m of the material. The mass m calculation formula is: m = ρV 总 , where ρ represents the density of the material.

5. The online measurement system for storage capacity of a three-dimensional warehouse according to claim 4 is characterized in that: The process of the data acquisition and processing module processing the storage capacity data is as follows: B1. Receive the original storage capacity data scanned by 3D radar, which includes point cloud data and material surface height; B2. Preprocess the received storage capacity data. The preprocessing process includes denoising, filtering and outlier detection operations; B3. Integrate the data from 3D radar to form a unified data set; B4. Analyze the integrated data set to obtain the material volume reduction trend and predict future inventory requirements, and transmit it to the control module for processing.

6. The online measurement system for storage capacity of a three-dimensional warehouse according to claim 5 is characterized in that: In step B2, when preprocessing the reservoir capacity data, first use statistical methods or machine learning algorithms to identify and remove noise in the data; then apply spatial filters to smooth the data and reduce the impact of high-frequency noise; and then use statistical tests to identify outliers in the data.

7. The online measurement system for storage capacity of a three-dimensional warehouse according to claim 6 is characterized by: The control module's process for storage capacity monitoring and early warning is as follows: C1, the control module receives the storage capacity data from the data acquisition and processing module; C2, analyze the received data and extract key information; C3. Set the warning threshold of storage capacity based on historical data and business rules; C4. When the actual storage capacity exceeds or falls below the preset threshold, the control module will trigger the early warning mechanism, and the early warning signal will be conveyed to relevant personnel via SMS, email or system pop-up window; C5. Continuously optimize warning thresholds and warning strategies based on business development and environmental changes.

8. The online measurement system for storage capacity of a three-dimensional warehouse according to claim 7 is characterized in that: The process of the control module to automatically adjust the procurement plan and production scheduling operation is as follows: C11. Develop production plans based on market demand, material volume reduction trends, and forecast future inventory requirements, and determine production quantity and time; C12. Convert the production plan into specific production tasks, assign them to the corresponding production lines or work centers, and schedule and dispatch them according to the priority and resource conditions of the production tasks; C13. Real-time monitoring of production progress, resource utilization and production quality; C14. Generate various production reports to analyze and evaluate the production situation, including production cost analysis, production efficiency analysis and production quality analysis; C15. Visualize the analysis results in the form of charts and curves.

9. The online measurement system for storage capacity of a three-dimensional warehouse according to claim 8 is characterized in that: In step C11, when formulating the production plan, first collect market demand data, analyze the trend of material volume reduction, understand the impact of material volume reduction on production, predict future inventory demand, combine sales forecasts, order status, and safety stock level factors, and then conduct a comprehensive assessment of existing production resources. Then, according to market demand and inventory forecasts, formulate a preliminary production plan, and then use linear programming or integer programming algorithms to optimize the production plan. Then, by simulating different production scenarios, find the best production strategy.

10. A method for measuring the storage capacity of a three-dimensional warehouse online, based on the system for measuring the storage capacity of a three-dimensional warehouse online according to any one of claims 1 to 9, characterized in that: The steps include: S1. Install the 3D radar at the material drop point of the continuous fabric belt, and use the 3D radar to measure the material scheduling in each inventory in real time; S2. Calculate the volume of materials in each warehouse by combining the size of the geometric shape of the three-dimensional warehouse through the warehouse capacity calculation module, and then calculate the weight of the material according to the density of the material or the relationship between weight and volume; S3, the control module performs real-time monitoring and early warning of the storage capacity according to the preset control logic and algorithm; S4, the original storage capacity data collected in real time by 3D radar is analyzed and processed by the data acquisition and processing module and transmitted to the control module; S5. After receiving the data from the data acquisition and processing module, the control module automatically adjusts the purchase plan and production scheduling operations in combination with the material weight obtained by the storage capacity calculation module.

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