Warehouse full-process intelligent closed-loop warehouse-in and warehouse-out management system and method
By analyzing ammunition status scores through an intelligent closed-loop management system and generating adaptive detection cycles, the problem of untimely anomaly detection in ammunition storage has been solved, thereby improving the safety and flexibility of ammunition storage.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- 安徽省人工影响天气办公室
- Filing Date
- 2025-12-09
- Publication Date
- 2026-04-17
AI Technical Summary
In existing technologies, ammunition storage inspections mainly rely on regular manual inspections, which makes it difficult to detect abnormalities in a timely manner, resulting in low ammunition storage security.
The warehouse adopts an intelligent closed-loop inbound and outbound management system. By acquiring information on incoming ammunition, analyzing ammunition status scores, generating detection cycles, and adaptively updating based on detection data, a phased storage code is generated and transmitted to the Tiangong platform to achieve timely detection and alarm of ammunition status.
It improves the safety of ammunition storage, ensures that abnormal situations can be detected and alarmed in a timely manner, and enhances the safety and flexibility of ammunition storage.
Smart Images
Figure CN121882872A_ABST
Abstract
Description
Technical Field
[0001] This application belongs to the field of ammunition testing and management technology, specifically a warehouse intelligent closed-loop inbound and outbound management system and method. Background Technology
[0002] Weather munitions mainly refer to special munitions used for artificial weather modification operations, such as rain-inducing munitions and rockets. These munitions are mainly used for artificial weather modification operations, such as hail suppression and rain enhancement. Actual artificial weather modification operations fall under the civilian category and are aimed at disaster prevention and mitigation. However, the storage and transportation of munitions still face safety challenges and must strictly follow operating procedures. For example, munitions must be stored separately from pyrotechnics, and the ambient temperature and humidity must be checked regularly.
[0003] Existing ammunition storage and monitoring solutions mostly rely on regular manual inspections or periodic checks of temperature and humidity sensors within the warehouse. However, due to the diversity of ammunition conditions and storage environments, the degree of impact on ammunition varies, leading to different probabilities of ammunition malfunction. Simply relying on regular inspections to monitor ammunition conditions is clearly insufficient to detect anomalies in a timely manner, thus posing a significant threat to the safety of ammunition storage. Therefore, there is an urgent need for a fully intelligent, closed-loop warehouse inbound and outbound management system and method. Summary of the Invention
[0004] This application provides a warehouse end-to-end intelligent closed-loop inbound and outbound management system and method, which solves the technical problem that the existing technology of storing and inspecting ammunition through regular inspections makes it difficult to detect ammunition abnormalities in a timely manner, resulting in low ammunition storage security.
[0005] To achieve the above objectives, this application adopts the following technical solution: Firstly, a method for intelligent closed-loop inbound and outbound management of the entire warehouse process is provided, including: Obtain information on incoming ammunition. The ammunition status score is obtained by analyzing the ammunition information upon its arrival in the warehouse; the ammunition status score indicates the condition of the ammunition upon its arrival in the warehouse. Detection cycles are generated based on ammunition status scores; Ammunition testing data is updated based on the testing cycle; The ammunition detection status is evaluated based on the ammunition detection data to obtain the ammunition detection result, which includes a detection status score and a detection status. Based on ammunition detection data and detection status scores, a phased ammunition storage code is generated, stored, and transmitted to the Tiangong platform.
[0006] Based on the above technical solution, in the warehouse end-to-end intelligent closed-loop inbound and outbound management system and method provided in this application, the following steps are taken: ammunition information is acquired upon entry into the warehouse; the ammunition status score is obtained by analyzing the ammunition information; a detection cycle is generated based on the ammunition status score; the ammunition detection data is updated based on the detection cycle; the detection status of the ammunition is evaluated based on the ammunition detection data to obtain the ammunition detection result; a staged ammunition storage code is generated based on the ammunition detection data and the detection status score, and stored and transmitted to the Tiangong platform; by generating a targeted detection cycle based on the information when the ammunition enters the warehouse, and adaptively updating the ammunition detection cycle according to the actual storage environment and the ammunition status during subsequent detection processes, the flexibility of the ammunition detection cycle and the matching degree between the ammunition detection cycle and the ammunition status are ensured; thus, timely detection and alarms can be triggered when ammunition anomalies occur, improving the security of ammunition storage.
[0007] In conjunction with the first aspect above, in one possible implementation, the step of analyzing the ammunition based on the ammunition information to obtain an ammunition status score includes: Extract the ammunition type and weight from the ammunition information; obtain the standard ammunition weight and production error ratio corresponding to the ammunition type; substitute the ammunition weight, standard ammunition weight, and production error ratio into the state evaluation function to obtain the ammunition state score for the corresponding ammunition; one expression of the state evaluation function is as follows: ; Wherein, DP is the ammunition condition score, DZ is the ammunition weight, BDZ is the standard ammunition weight, WCB is the production error ratio, which is the proportion of the high standard weight error of the ammunition when it leaves the factory due to the production process, such as 1%; μ1 is the first proportional coefficient; μ2 is the second proportional coefficient; and 0 < μ1 < μ2.
[0008] In conjunction with the first aspect above, in one possible implementation, the generation of the detection cycle based on the ammunition status score includes: Obtain the ammunition status score (DP) and standard inspection cycle (BT); through the formula The detection cycle JT is calculated; where MP is the full score of the ammunition status rating.
[0009] In conjunction with the first aspect above, in one possible implementation, updating the ammunition detection data based on the detection cycle includes: When the testing period arrives, environmental data, ammunition weight, and ammunition image data are acquired. The ammunition testing data includes environmental data, ammunition weight, and ammunition image data. The environmental data consists of data recorded for each environmental item of the ammunition at each acquisition time during the testing period. The ammunition weight data is the ammunition weight acquired at the end of the testing period, and the ammunition image data is the ammunition image acquired at the end of the testing period.
[0010] In conjunction with the first aspect above, in one possible implementation, the step of evaluating the detection status of ammunition based on ammunition detection data to obtain the ammunition detection result includes: Extract ammunition weight and images from ammunition inspection data; The ammunition image is input into the surface detection scoring model to obtain the surface detection score corresponding to the ammunition image; the surface detection scoring model is obtained through training an artificial intelligence model. Substituting the ammunition weight into the condition evaluation function yields the ammunition condition score for the corresponding ammunition. The surface inspection score and the ammunition condition score are weighted and summed to obtain the inspection condition score; the ammunition inspection condition is generated based on the inspection condition score.
[0011] In conjunction with the first aspect above, in one possible implementation, one training method for the surface detection scoring model includes: Acquire several ammunition images, along with corresponding deduction areas and deduction values. The deduction areas are regions on the ammunition images that exhibit abnormalities, such as rust and stains, and the deduction values correspond to these areas. It is understood that the initial ammunition images used for training the artificial intelligence, as well as the corresponding deduction areas and values, are manually labeled. The magnitude of the deduction value is related to the size and type of its corresponding deduction area. The larger the area of the deduction area, the larger the corresponding deduction value; the more severe the impact of the abnormality type of the deduction area on the ammunition's condition, the larger the corresponding deduction value. Integrate the ammunition images, deduction areas, and deduction values into training data, validation data, and test data. The artificial intelligence model is trained using training data, validated using validation data, and tested using test data; the result is an artificial intelligence model whose input is an ammunition image and whose output is several deduction areas and deduction values corresponding to the ammunition image. The total deduction value is obtained by summing the deduction values corresponding to each deduction area, and a full score is set for the surface detection score. The full score minus the total deduction value is recorded as the surface detection score and used as the final output. The final result is that the input is the ammunition image and the output is the surface detection score corresponding to the ammunition image. The artificial intelligence model includes recurrent neural network model and convolutional neural network model, etc.
[0012] In conjunction with the first aspect above, in one possible implementation, generating the ammunition detection status based on the detection status score includes: When the detection status score is greater than or equal to the set normal status score threshold, the ammunition detection status is set to normal status. When the detection status score is less than the set normal status score threshold and greater than or equal to the set warning status score threshold, the ammunition detection status is set to a warning status. When the detection status score is less than the set warning status score threshold, the ammunition detection device is set to a dangerous state.
[0013] In conjunction with the first aspect above, in one possible implementation, the generation of a phased ammunition storage code based on ammunition detection data and detection status score includes: Environmental data is extracted from ammunition detection data, and environmental temperature and humidity change curves are extracted from the environmental data. Environmental detection results are generated based on the environmental temperature and humidity change curves. The environmental detection results include environmental impact score and environmental status. Acquire ammunition weight, ammunition images, environmental data, surface inspection scores, ammunition condition scores, and environmental impact scores, and integrate ammunition inspection status and environmental status into phased inspection data; The process involves acquiring the cycle corresponding to the ammunition detection data, generating a staged ammunition storage code based on the cycle, and storing the staged detection data into the content corresponding to the staged ammunition storage code. Specifically, the staged ammunition storage code can be generated by the time corresponding to the cycle, or it can be generated by combining the time and length of the cycle, making the staged ammunition storage code unique.
[0014] In conjunction with the first aspect above, in one possible implementation, generating environmental monitoring results based on environmental temperature change curves and environmental humidity change curves includes: By substituting the environmental temperature change curve and the environmental humidity change curve into the set environmental impact quantification function, the corresponding environmental impact score is obtained. One form of the environmental impact quantification function is as follows: ; in, Assess the environmental impact rating; This is a curve showing the change in ambient temperature. The set standard storage temperature value; This is a curve showing the change in ambient humidity. The set standard storage humidity value; t is time, t∈[0,T], and T is the total time length of the corresponding period; When the environmental impact score is greater than the set ideal environmental score threshold, the environmental state is set to normal; otherwise, the environmental state is set to abnormal. The environmental status and environmental status score are integrated into the environmental monitoring results.
[0015] In conjunction with the first aspect above, one possible implementation also includes updating the detection cycle based on the ammunition detection results and environmental detection results; Extract the detection status score from the ammunition detection results and the environmental impact score from the environmental detection results; substitute the detection status score and environmental impact score into a set period adjustment function to obtain the updated detection period; one form of the period adjustment function is as follows: ; Where GT is the updated detection cycle, JT is the original detection cycle, JP is the detection status score, and HP is the environmental impact score.
[0016] Secondly, this application provides a warehouse end-to-end intelligent closed-loop inbound and outbound management device, comprising: a processor and an inbound medium; the inbound medium includes instructions, and the processor is used to execute the instructions to implement the method described in the first aspect and any possible implementation thereof. This warehouse end-to-end intelligent closed-loop inbound and outbound management device can be an electronic device or a chip within an electronic device.
[0017] Thirdly, this application provides a warehouse end-to-end intelligent closed-loop inbound and outbound management system, including: a data acquisition module, a data analysis module, and an early warning module; The data acquisition module is used to collect warehousing information and ammunition detection data. The data analysis module includes an ammunition status assessment unit, a detection cycle autonomous update unit, and a storage unit. The ammunition status assessment unit is used to analyze ammunition based on the ammunition information received into the warehouse to obtain an ammunition status score; and to assess the detection status of ammunition based on ammunition detection data to obtain a detection result, the detection result including a detection status score and a detection status. The detection cycle autonomous update unit is used to generate a detection cycle based on the ammunition status score; and to update the detection cycle based on the ammunition detection results and environmental detection results; the environmental detection results are generated from environmental data in the ammunition detection data. The storage unit is used to generate and store staged ammunition storage codes based on ammunition detection data and detection status scores, and transmit them to the Tiangong platform; the Tiangong platform is a platform for information storage. The early warning module is used to issue early warnings based on ammunition detection results and environmental detection results. Specifically, it includes: extracting the detection status from the ammunition detection results; issuing a first-level early warning when the detection status is a dangerous status; and issuing a second-level early warning when the detection status is an early warning status. The first-level early warning includes an audible and visual alarm, and the second-level early warning includes a display prompt. Extract the environmental status from the environmental monitoring results, and issue a level-two early warning when the environmental status is abnormal.
[0018] Fourthly, this application provides a computer-readable storage medium containing storage instructions. When these instructions are executed on a warehouse end-to-end intelligent closed-loop storage management device, the device performs the method described in the first aspect and any possible implementation thereof.
[0019] Fifthly, this application provides a computer program product containing instructions that, when the computer program product is run on a warehouse end-to-end intelligent closed-loop inbound and outbound management device, causes the warehouse end-to-end intelligent closed-loop inbound and outbound management device to perform the methods described in the first aspect and any possible implementation thereof.
[0020] This application provides a warehouse intelligent closed-loop inbound and outbound management method and system. It can acquire inbound ammunition information, analyze the ammunition based on this information to obtain an ammunition status score; generate a detection cycle based on the ammunition status score; update the ammunition detection data according to the detection cycle; evaluate the ammunition detection status based on the ammunition detection data to obtain the ammunition detection result; generate a staged ammunition storage code based on the ammunition detection data and detection status score, store it, and transmit it to the Tiangong platform. By generating a targeted detection cycle based on the information when the ammunition enters the warehouse, and adaptively updating the ammunition detection cycle according to the actual storage environment and ammunition status during subsequent detection processes, it ensures the flexibility of the ammunition detection cycle and the matching degree between the ammunition detection cycle and the ammunition status. This enables timely detection and alarm of ammunition anomalies, improving the security of ammunition storage.
[0021] It should be understood that the descriptions of technical features, technical solutions, beneficial effects, or similar language in this application do not imply that all features and advantages can be achieved in any single embodiment. Rather, it is understood that the description of a feature or beneficial effect means that a specific technical feature, technical solution, or beneficial effect is included in at least one embodiment. Therefore, the descriptions of technical features, technical solutions, or beneficial effects in this specification do not necessarily refer to the same embodiment. Furthermore, the technical features, technical solutions, and beneficial effects described in this embodiment can be combined in any suitable manner. Those skilled in the art will understand that embodiments can be implemented without one or more specific technical features, technical solutions, or beneficial effects of a particular embodiment. In other embodiments, additional technical features and beneficial effects may be identified in specific embodiments that do not embody all embodiments. Attached Figure Description
[0022] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0023] Figure 1 This is a schematic diagram illustrating the steps of the intelligent closed-loop warehouse inbound and outbound management method in this application. Figure 2 This is a schematic diagram of the module connections for the intelligent closed-loop warehouse inbound and outbound management method in this application. Detailed Implementation
[0024] The technical solutions of this application will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.
[0025] Please see Figure 1 The first aspect of this application provides a warehouse end-to-end intelligent closed-loop inbound and outbound management method, including: Obtain information on incoming ammunition, including information measured at the time of entry, such as the ammunition's condition, type, and weight. The ammunition status score is obtained by analyzing the ammunition information upon its arrival in the warehouse; the ammunition status score indicates the condition of the ammunition upon its arrival in the warehouse. The detection cycle is generated based on the ammunition condition score; the detection cycle is the period for processing and analyzing the detection data related to the ammunition condition. For example, if the detection cycle is 1 hour, then the storage environment and ammunition condition need to be analyzed once every hour. Ammunition testing data is updated based on the testing cycle; the ammunition testing data includes relevant environmental data during ammunition storage and relevant data about the ammunition itself, such as temperature, humidity, weight, and external images of the ammunition during storage. The ammunition testing results are obtained by evaluating the testing status of the ammunition based on the ammunition testing data. The ammunition testing results include a testing status score and a testing status. The testing status is the result of evaluating the ammunition based on relevant testing data within the current testing cycle. Based on ammunition detection data and detection status scores, a phased ammunition storage code is generated, stored, and transmitted to the Tiangong platform; the Tiangong platform is the platform for information storage.
[0026] Based on the above technical solution, in the warehouse end-to-end intelligent closed-loop inbound and outbound management system and method provided in this application, the following steps are taken: ammunition information is acquired upon entry into the warehouse; the ammunition status score is obtained by analyzing the ammunition information; a detection cycle is generated based on the ammunition status score; the ammunition detection data is updated based on the detection cycle; the detection status of the ammunition is evaluated based on the ammunition detection data to obtain the ammunition detection result; a staged ammunition storage code is generated based on the ammunition detection data and the detection status score, and stored and transmitted to the Tiangong platform; by generating a targeted detection cycle based on the information when the ammunition enters the warehouse, and adaptively updating the ammunition detection cycle according to the actual storage environment and the ammunition status during subsequent detection processes, the flexibility of the ammunition detection cycle and the matching degree between the ammunition detection cycle and the ammunition status are ensured; thus, timely detection and alarms can be triggered when ammunition anomalies occur, improving the security of ammunition storage.
[0027] In one possible implementation, the step of analyzing ammunition based on warehousing ammunition information to obtain an ammunition status score includes: extracting the ammunition type and weight from the ammunition information; obtaining the standard ammunition weight and production error ratio corresponding to the ammunition type; and substituting the ammunition weight, standard ammunition weight, and production error ratio into a status evaluation function to obtain the ammunition status score for the corresponding ammunition. One expression of the status evaluation function is as follows: ; Wherein, DP is the ammunition condition score, DZ is the ammunition weight, BDZ is the standard ammunition weight, WCB is the production error ratio, which is the proportion of the high standard weight error of the ammunition when it leaves the factory due to the production process, such as 1%; μ1 is the first proportional coefficient; μ2 is the second proportional coefficient; and 0 < μ1 < μ2. In this embodiment, μ1 = 0.1 and μ2 = 10.
[0028] This embodiment analyzes the ammunition weight upon entering the warehouse using the aforementioned formula to obtain an ammunition condition score. When the ammunition weight is within the production error ratio, the closer the ammunition weight is to the standard ammunition weight, the higher the production quality of the ammunition, the better the current condition of the ammunition, and the lower the probability of leakage and moisture absorption of the filling material. Therefore, the corresponding ammunition condition score is set higher. When the ammunition weight is outside the production error ratio, the further the ammunition weight is from the standard ammunition weight, the lower the production quality of the ammunition, the worse the current condition of the ammunition, and the higher the probability of leakage and moisture absorption of the filling material. Therefore, the corresponding ammunition condition score is set lower. At the same time, by setting ratio coefficient one and ratio coefficient two, the difference in ammunition condition scores between ammunition within the production standard and ammunition outside the production standard can be increased, facilitating more targeted processing in the future.
[0029] In one possible implementation, generating the detection cycle based on the ammunition status score includes: acquiring the ammunition status score DP and the standard detection cycle BT; and using the formula... The detection cycle JT is calculated; where MP is the full score of the ammunition status rating.
[0030] In this embodiment, the detection cycle is calculated using the above method. When the ammunition's condition score is higher, it indicates that the ammunition is in better condition and does not require enhanced detection. The initial standard detection cycle can be used for detection. When the ammunition's condition score is lower, it indicates that the ammunition is in poor condition and requires enhanced detection. In this case, the cycle is set to be shorter to achieve enhanced detection of the ammunition.
[0031] In one possible implementation, updating ammunition detection data based on a detection cycle includes: when the detection cycle arrives, acquiring environmental data of ammunition storage, ammunition weight, and ammunition image data; the ammunition detection data includes environmental data, ammunition weight, and ammunition image data, wherein the environmental data is the data recorded for each environmental item of the ammunition at each acquisition time during the detection cycle; the ammunition weight data is the ammunition weight acquired at the end of the detection cycle, and the ammunition image data is the ammunition image acquired at the end of the detection cycle.
[0032] In one possible implementation, the ammunition detection result is obtained by evaluating the detection status of the ammunition based on the ammunition detection data, including: extracting the ammunition weight and ammunition image from the ammunition detection data; inputting the ammunition image into a surface detection scoring model to obtain the surface detection score corresponding to the ammunition image; the surface detection scoring model is trained using an artificial intelligence model; substituting the ammunition weight into a status evaluation function to obtain the corresponding ammunition status score; and performing a weighted summation of the surface detection score and the ammunition status score to obtain the detection status score; generating the ammunition detection status based on the detection status score. It is understood that the surface detection score and the ammunition status score have the same maximum score for easy addition. The weighted summation of the surface detection score and the ammunition status score yields the detection status score. Specifically, the weight coefficients for both the ammunition status score and the surface detection score are set based on expert experience; in this embodiment, the weight coefficients are all set to 0.5.
[0033] In one possible implementation, a training method for the surface detection scoring model includes: acquiring several ammunition images, and several deduction regions and deduction values corresponding to the ammunition images; the deduction regions are areas on the ammunition images where abnormalities occur, such as rust and stains, and the deduction values are the deduction values corresponding to the deduction regions; it is understood that the ammunition images initially used for training the artificial intelligence, as well as the corresponding deduction regions and deduction values on the ammunition images, are all manually labeled, and the magnitude of the deduction value is related to the size and type of its corresponding deduction region; the larger the area of the deduction region corresponding to the deduction value, the larger its corresponding deduction value; the more severe the impact of the abnormal type corresponding to the deduction region on the state of the ammunition, the larger the corresponding deduction value, such as the deduction value of rust of the same area being larger than that of stains; a 2 square millimeter rust deduction region having a larger deduction value than a 1 square millimeter rust deduction region; the specific deduction values are set by experts based on experience; it is understood that there may be multiple different deduction regions on a single ammunition image; several ammunition images, deduction regions, and deduction values are integrated into several training data, validation data, and test data; The artificial intelligence model is trained using training data, validated using validation data, and tested using test data; the result is an artificial intelligence model whose input is an ammunition image and whose output is several deduction areas and deduction values corresponding to the ammunition image. The total deduction value is obtained by summing the deduction values corresponding to each deduction area, and a full score is set for the surface detection score. The full score minus the total deduction value is recorded as the surface detection score and used as the final output. The final result is that the input is the ammunition image and the output is the surface detection score corresponding to the ammunition image. The artificial intelligence model includes recurrent neural network model and convolutional neural network model, etc.
[0034] It is understandable that the process of training an image recognition model is a relatively existing technology, and will not be elaborated on here.
[0035] In one possible implementation, generating an ammunition detection status based on a detection status score includes: setting the ammunition detection status to a normal state when the detection status score is greater than or equal to a set normal state score threshold; setting the ammunition detection status to a warning state when the detection status score is less than the set normal state score threshold but greater than or equal to a set warning state score threshold; and setting the ammunition detection device to a dangerous state when the detection status score is less than the set warning state score threshold.
[0036] In one possible implementation, generating a staged ammunition storage code based on ammunition detection data and detection status score includes: extracting environmental data from the ammunition detection data, extracting environmental temperature change curves and environmental humidity change curves from the environmental data, and generating environmental detection results based on the environmental temperature change curves and environmental humidity change curves; the environmental detection results include environmental impact score and environmental status. Acquire ammunition weight, ammunition images, environmental data, surface inspection scores, ammunition condition scores, and environmental impact scores, and integrate ammunition inspection status and environmental status into phased inspection data; The process involves acquiring the cycle corresponding to the ammunition detection data, generating a staged ammunition storage code based on the cycle, and storing the staged detection data into the content corresponding to the staged ammunition storage code. Specifically, the staged ammunition storage code can be generated by the time corresponding to the cycle, or it can be generated by combining the time and length of the cycle, making the staged ammunition storage code unique.
[0037] In one possible implementation, generating environmental monitoring results based on environmental temperature and humidity change curves includes: substituting the environmental temperature and humidity change curves into a predefined environmental impact quantification function to obtain a corresponding environmental impact score. One expression of the environmental impact quantification function is as follows: ; in, Assess the environmental impact rating; This is a curve showing the change in ambient temperature. The set standard storage temperature value; This is a curve showing the change in ambient humidity. The set standard storage humidity value; t is time, t∈[0,T], and T is the total time length of the corresponding period; When the environmental impact score is greater than the set ideal environmental score threshold, the environmental state is set to normal; otherwise, the environmental state is set to abnormal. The environmental status and environmental status score are integrated into the environmental monitoring results.
[0038] This embodiment quantifies the impact of changes in the ammunition storage environment on ammunition storage using the above formula. When the difference between the ammunition storage temperature and the standard storage temperature set for the ammunition is large and lasts for a long time, the ammunition is more affected by temperature. For example, a lower temperature may cause metal shrinkage and stress reduction, etc.; the corresponding environmental impact score is higher. When the difference between the ammunition storage humidity and the standard storage humidity set for the ammunition is large and lasts for a long time, the ammunition is more affected by temperature. For example, in a high humidity environment for a long time, the corrosion rate will be accelerated; therefore, the corresponding environmental impact score is set to be higher.
[0039] In one possible implementation, the method further includes updating the detection cycle based on the ammunition detection results and environmental detection results; extracting the detection status score from the ammunition detection results and the environmental impact score from the environmental detection results; substituting the detection status score and the environmental impact score into a set cycle adjustment function to obtain the updated detection cycle; one expression of the cycle adjustment function is as follows: ; Where GT is the updated detection cycle, JT is the original detection cycle, JP is the detection status score, and HP is the environmental impact score.
[0040] This embodiment adjusts the testing cycle based on the storage environment and ammunition status within the current testing cycle to obtain the length of the next testing cycle. When the environment of the current cycle differs significantly from the standard storage environment, the cycle length is appropriately reduced to enhance ammunition testing. When the ammunition testing status is poor in the current cycle, the cycle length is appropriately reduced to enhance ammunition testing. Targeted testing of ammunition based on its storage environment and status facilitates timely detection of ammunition anomalies and improves testing efficiency.
[0041] Secondly, this application provides a warehouse end-to-end intelligent closed-loop inbound and outbound management device, comprising: a processor and an inbound medium; the inbound medium includes instructions, and the processor is used to execute the instructions to implement the method described in the first aspect and any possible implementation thereof. This warehouse end-to-end intelligent closed-loop inbound and outbound management device can be an electronic device or a chip within an electronic device.
[0042] Please see Figure 2 Thirdly, this application provides a warehouse end-to-end intelligent closed-loop inbound and outbound management system, including: a data acquisition module, a data analysis module, and an early warning module; The data acquisition module is used to collect warehousing information and ammunition detection data. The data analysis module includes an ammunition status assessment unit, a detection cycle autonomous update unit, and a storage unit. The ammunition status assessment unit is used to analyze ammunition based on the ammunition information received into the warehouse to obtain an ammunition status score; and to assess the detection status of ammunition based on ammunition detection data to obtain a detection result, the detection result including a detection status score and a detection status. The detection cycle autonomous update unit is used to generate a detection cycle based on the ammunition status score; and to update the detection cycle based on the ammunition detection results and environmental detection results; the environmental detection results are generated from environmental data in the ammunition detection data. The storage unit is used to generate and store staged ammunition storage codes based on ammunition detection data and detection status scores, and transmit them to the Tiangong platform; the Tiangong platform is a platform for information storage. The early warning module is used to issue early warnings based on ammunition detection results and environmental detection results. Specifically, it includes: extracting the detection status from the ammunition detection results; issuing a first-level early warning when the detection status is a dangerous status; and issuing a second-level early warning when the detection status is an early warning status. The first-level early warning includes an audible and visual alarm, and the second-level early warning includes a display prompt. Extract the environmental status from the environmental monitoring results, and issue a level-two early warning when the environmental status is abnormal.
[0043] Fourthly, this application provides a computer-readable storage medium containing storage instructions. When these instructions are executed on a warehouse end-to-end intelligent closed-loop storage management device, the device performs the method described in the first aspect and any possible implementation thereof.
[0044] Fifthly, this application provides a computer program product containing instructions that, when the computer program product is run on a warehouse end-to-end intelligent closed-loop inbound and outbound management device, causes the warehouse end-to-end intelligent closed-loop inbound and outbound management device to perform the methods described in the first aspect and any possible implementation thereof.
[0045] Some of the data in the above formula are calculated by removing dimensions and taking their numerical values. The formula is the closest to the real situation obtained by software simulation of a large amount of collected data. The preset parameters and preset thresholds in the formula are set by those skilled in the art according to the actual situation or obtained through simulation of a large amount of data.
[0046] How this application works: By acquiring information about incoming ammunition, analyzing the ammunition based on this information to obtain an ammunition status score, generating a detection cycle based on the ammunition status score, updating the ammunition detection data according to the detection cycle, evaluating the ammunition's detection status based on the ammunition detection data to obtain the ammunition detection result, generating a staged ammunition storage code based on the ammunition detection data and detection status score, storing it, and transmitting it to the Tiangong platform; by generating a targeted detection cycle based on the information when the ammunition is received, and adaptively updating the ammunition detection cycle according to the actual storage environment and ammunition status during subsequent detection processes, the flexibility of the ammunition detection cycle and the matching degree between the ammunition detection cycle and the ammunition status are ensured, thereby enabling timely detection and alarm of ammunition anomalies and improving the security of ammunition storage.
[0047] The above embodiments are only used to illustrate the technical methods of this application and are not intended to limit it. Although this application has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of this application without departing from the spirit and scope of the technical methods of this application.
Claims
1. A warehouse end-to-end intelligent closed-loop inbound and outbound management method, characterized in that, include: Obtain information on incoming ammunition and analyze the ammunition based on this information to obtain an ammunition status score; Detection cycles are generated based on ammunition status scores; Ammunition testing data is updated based on the testing cycle; The ammunition detection status is evaluated based on the ammunition detection data to obtain the ammunition detection result, which includes a detection status score and a detection status. Based on ammunition detection data and detection status scores, a phased ammunition storage code is generated, stored, and transmitted to the Tiangong platform. 2.The warehouse full-process intelligent closed-loop warehouse management method according to claim 1, characterized in that, The process of analyzing ammunition based on incoming ammunition information to obtain an ammunition status score includes: Extract the ammunition type and weight from the ammunition information; obtain the standard ammunition weight and production error ratio corresponding to the ammunition type; substitute the ammunition weight, standard ammunition weight, and production error ratio into the state evaluation function to obtain the ammunition state score for the corresponding ammunition; one expression of the state evaluation function is as follows: ； Wherein, DP is the ammunition condition score, DZ is the ammunition weight, BDZ is the standard ammunition weight, WCB is the production error ratio; μ1 is the first proportionality coefficient, μ2 is the second proportionality coefficient; and 0 < μ1 < μ2. 3.The warehouse full-process intelligent closed-loop warehouse management method according to claim 1, characterized in that, The generation of the detection cycle based on ammunition status scoring includes: Obtaining a propellant state score DP and a standard detection period BT; calculating a detection period JT by the formula JT = (MP - DP) / BT; wherein MP is a full score of the propellant state score. 4.The warehouse full-process intelligent closed-loop warehouse management method according to claim 1, characterized in that, The evaluation of the ammunition's detection status based on ammunition detection data to obtain the ammunition detection result includes: Extract ammunition weight and images from ammunition inspection data; The ammunition image is input into the surface detection scoring model to obtain the surface detection score corresponding to the ammunition image; the surface detection scoring model is obtained through training an artificial intelligence model. Substituting the ammunition weight into the condition evaluation function yields the ammunition condition score for the corresponding ammunition. The surface inspection score and the ammunition condition score are weighted and summed to obtain the inspection condition score; the ammunition inspection condition is generated based on the inspection condition score. 5.The warehouse full-process intelligent closed-loop warehouse management method according to claim 4, characterized in that, One training method for the surface detection scoring model includes: Acquire several ammunition images, as well as several deduction areas and deduction values corresponding to the ammunition images; integrate the several ammunition images, deduction areas and deduction values into several training data, validation data and test data; The artificial intelligence model is trained using training data, validated using validation data, and tested using test data; the result is an artificial intelligence model whose input is an ammunition image and whose output is an image of ammunition with several deduction regions and deduction values. The total deduction value is obtained by summing the deduction values corresponding to each deduction area, and a full score is set for the surface detection score. The full score minus the total deduction value is recorded as the surface detection score and used as the final output. The final result is that the input is the ammunition image and the output is the surface detection score corresponding to the ammunition image. 6.The warehouse full-process intelligent closed-loop warehouse management method according to claim 4, characterized in that, The generation of ammunition detection status based on detection status scoring includes: When the detection status score is greater than or equal to the set normal status score threshold, the ammunition detection status is set to normal status. When the detection status score is less than the set normal status score threshold and greater than or equal to the set warning status score threshold, the ammunition detection status is set to a warning status. When the detection status score is less than the set warning status score threshold, the ammunition detection device is set to a dangerous state.
7. The warehouse end-to-end intelligent closed-loop inbound and outbound management method according to claim 1, characterized in that, The generation of phased ammunition storage codes based on ammunition detection data and detection status scores includes: Environmental data is extracted from ammunition detection data, and environmental temperature and humidity change curves are extracted from the environmental data. Environmental detection results are generated based on the environmental temperature and humidity change curves. The environmental detection results include environmental impact score and environmental status. Acquire ammunition weight, ammunition images, environmental data, surface inspection scores, ammunition condition scores, and environmental impact scores, and integrate ammunition inspection status and environmental status into phased inspection data; The period corresponding to the ammunition detection data is obtained, a staged ammunition storage code is generated based on the period, and the staged detection data is stored in the content corresponding to the staged ammunition storage code. 8.The warehouse full-process intelligent closed-loop warehouse management method according to claim 7, characterized in that, The generation of environmental monitoring results based on environmental temperature and humidity change curves includes: Substitute the ambient temperature change curve and the ambient humidity change curve into the set environmental impact quantification function to obtain the corresponding environmental impact score; When the environmental impact score is greater than the set ideal environmental score threshold, the environmental state is set to normal; otherwise, the environmental state is set to abnormal. The environmental status and environmental status score are integrated into the environmental monitoring results. 9.The warehouse full-process intelligent closed-loop warehouse management method according to claim 1, wherein, It also includes updating the testing cycle based on the ammunition testing results and environmental testing results; Extract the detection status score from the ammunition detection results and the environmental impact score from the environmental detection results; substitute the detection status score and environmental impact score into a set period adjustment function to obtain the updated detection period; one form of the period adjustment function is as follows: ； Where GT is the updated detection cycle, JT is the original detection cycle, JP is the detection status score, and HP is the environmental impact score.
10. A warehouse end-to-end intelligent closed-loop inbound and outbound management system, based on the implementation of the warehouse end-to-end intelligent closed-loop inbound and outbound management method according to any one of claims 1-9, characterized in that, include: Data acquisition module, data analysis module, and early warning module; The data acquisition module is used to collect warehousing information and ammunition detection data. The data analysis module includes an ammunition status assessment unit, a detection cycle autonomous update unit, and a storage unit. The ammunition status assessment unit is used to analyze ammunition based on the ammunition information received from the warehouse to obtain an ammunition status score. Furthermore, the detection status of the ammunition is evaluated based on the ammunition detection data to obtain the detection result, which includes a detection status score and a detection status. The detection cycle autonomous update unit is used to generate a detection cycle based on the ammunition status score. Furthermore, the detection cycle is updated based on the ammunition detection results and environmental detection results; The environmental detection results are generated from the environmental data in the ammunition detection data; The storage unit is used to generate a staged ammunition storage code based on ammunition detection data and detection status score, store it, and transmit it to the Tiangong platform. The Tiangong platform is a platform for information storage; The early warning module is used to issue early warnings based on ammunition detection results and environmental detection results.