A cold storage operation and maintenance intelligent management system and method based on distributed system

Abstract

The invention relates to the technical field of cold storage operation and maintenance inventory management, and discloses a cold storage operation and maintenance intelligent management system and method based on a distributed system, wherein the system comprises a cold storage refrigerated goods information processing module, a cold storage refrigerated goods storage status analysis module, and a cold storage refrigerated goods operation and maintenance information feedback module; the current refrigeration time and date parameters are dynamically and accurately collected through a time timing module to provide data support for accurately evaluating the storage status of the refrigerated goods in the cold storage; based on a distributed cold storage operation and maintenance sub-platform, the current refrigeration time and date parameters are compared with the standard storage time interval of the refrigerated goods and the near-expiry storage time interval of the refrigerated goods, and the storage status parameters of the refrigerated goods are intelligently analyzed, so as to realize the standardized operation and maintenance management of the storage status of the refrigerated goods in the cold storage based on the distributed system, thereby improving the quality and reliability of the cold storage operation and maintenance management.

Description

Technical Field

[0001] The present invention relates to the technical field of cold storage operation and maintenance inventory management, and in particular to a cold storage operation and maintenance intelligent management system and method based on a distributed system. Background Art

[0002] Cold storage is a type of refrigeration equipment. Cold storage refers to equipment that uses artificial means to create an environment with a different temperature or humidity from the outdoor environment. It is also used as a constant temperature and humidity storage equipment in the fields of food, liquids, chemicals, medicines, vaccines, scientific experiments, etc. Cold storage is usually located near the transportation port or place of origin. Compared with refrigerators, cold storage has a larger refrigeration area and shares the same refrigeration principle. Intelligent management of cold storage operation and maintenance can realize scientific and accurate online monitoring of the operating status of the cold storage. However, the existing cold storage operation and maintenance management cannot realize scientific analysis of the storage time of refrigerated goods, nor can it perform dynamic feedback management of refrigerated goods that are near or expired, which reduces the management quality of cold storage operation and maintenance.

[0003] The Chinese invention patent with the announcement number CN111915255B discloses an intelligent cold storage management and information sharing platform, which collects environmental data in the cold storage through the collection end, and sets them in different partitions of the cold storage respectively, and each collection end has its own number; the processing end is used to receive the data collected by the collection end, and the processing end stores a corresponding relationship table between the collection end number and the cold storage partition; the management end is used to view the environmental data in the corresponding partition according to the area code of the cold storage partition; the management end is also used to input or modify the standard temperature of each cold storage partition, and the processing end is also used to store or update the standard temperature of each cold storage partition. However, the above technical scheme cannot scientifically evaluate and manage the storage time and storage status of the goods stored in the cold storage. Summary of the invention

[0004] 1. Technical issues to be solved

[0005] In order to solve the problem that the existing cold storage operation and maintenance management cannot realize scientific analysis of the storage time of refrigerated goods, and cannot perform dynamic feedback management on refrigerated goods in the expiring and expired status, which reduces the management quality of cold storage operation and maintenance, the above purpose is to accurately collect the characteristic information of refrigerated goods in cold storage, scientifically establish the standard storage time interval of refrigerated goods and the expiring storage time interval of refrigerated goods, accurately collect the data at the current time point, intelligently judge the storage status of refrigerated goods, and realize the distributed cold storage operation and maintenance information management.

[0006] (II) Technical solution

[0007] The present invention is implemented by the following technical solution: a cold storage operation and maintenance intelligent management method based on a distributed system, the method comprising the following steps:

[0008] S1. Collect characteristic text data of refrigerated goods in cold storage;

[0009] S2. Search and process the production date and storage time length of the refrigerated goods according to the characteristic text data of the refrigerated goods in the cold storage to generate the production time point data of the refrigerated goods and the storage time length data of the refrigerated goods;

[0010] S3, based on the cold storage refrigerated goods characteristic text data and different refrigerated goods near expiration time length data, perform refrigerated goods near expiration time length identification processing, and generate specific refrigerated goods near expiration time length data;

[0011] S4. Perform storage and near-expiry time interval construction processing for refrigerated goods according to the production time point, storage time length and near-expiry time length parameters of the refrigerated goods, and generate a standard storage time interval for refrigerated goods and a near-expiry storage time interval for refrigerated goods;

[0012] S5, collecting current refrigeration time point data;

[0013] S6, performing storage status judgment processing of the refrigerated goods according to the current refrigeration time point data, the standard storage time interval of the refrigerated goods, and the near-expiry storage time interval of the refrigerated goods, generating and outputting current storage status judgment data of the refrigerated goods;

[0014] S7. Construct the refrigerated cargo operation and maintenance characteristic data and push it back to the cold storage operation and maintenance management center.

[0015] Preferably, the operation steps for collecting characteristic text data of refrigerated goods in cold storage are as follows:

[0016] S11. Scan the barcode of the refrigerated goods in the cold storage online with a barcode scanner to obtain characteristic text information of the refrigerated goods and generate characteristic text data A of the refrigerated goods in the cold storage, wherein the characteristic text data of the refrigerated goods in the cold storage includes the production date, shelf life, manufacturer, brand name, production address and product description of the refrigerated goods.

[0017] The present invention collects characteristic information of refrigerated goods in a cold storage through a barcode scanner, thereby providing data support for subsequent digital establishment of storage time parameters of refrigerated goods in the cold storage.

[0018] Preferably, the steps of searching and processing the production date and storage time length of the refrigerated goods according to the characteristic text data of the refrigerated goods in the cold storage to generate the production time point data of the refrigerated goods and the storage time length data of the refrigerated goods are as follows:

[0019] S21, using the BERT language model to search for the production date and shelf life parameters of the refrigerated goods in the cold storage refrigerated goods feature text data A according to the production date keywords and the shelf life keywords, and generate the refrigerated goods production time point data T through data identification. shengchan and refrigerated cargo storage time length data ΔT cunchu , where T shengchan and ΔT cunchu The units are composed of year, month and day.

[0020] The present invention uses the BERT language model and based on the characteristic information of refrigerated goods in cold storage to perform precise search for the production date and storage shelf life parameters of refrigerated goods, thereby achieving the effect of accurate and autonomous retrieval of the production date and storage shelf life of refrigerated goods.

[0021] Preferably, based on the cold storage refrigerated goods characteristic text data and different refrigerated goods near expiration time length data, the refrigerated goods near expiration time length identification processing is performed to generate specific refrigerated goods near expiration time length data as follows:

[0022] S31. Establish different refrigerated goods expiration time length data set B = (b 1 ,…,b o ,…,b μ ), o=1,2,3,…,μ; where b o represents the different refrigerated goods near expiration time length data corresponding to the oth refrigerated goods characteristic type, μ represents the maximum number of refrigerated goods characteristic types, and the different refrigerated goods near expiration time length data represent the time length data before the refrigerated goods reach the expiration state, b o The unit is composed of year, month and day;

[0023] S32, when the refrigerated goods production time point data T shengchan and the refrigerated cargo storage time length data ΔT cunchu When the generation is completed, the cold storage refrigerated goods characteristic text data A and the different refrigerated goods expiration time length data b in the different refrigerated goods expiration time length data set B are combined. o Perform refrigerated goods feature keyword matching to search for the different refrigerated goods expiration time length data b corresponding to the cold storage refrigerated goods feature text data A o And generate specific refrigerated goods expiration time length data b through data identification A ; Execute and generate specific refrigerated goods expiration time length data b A The specific steps are as follows:

[0024] S321, initializing the algorithm iteration data and executing the ocean current simulation process; setting the maximum algorithm iteration data to N, performing ocean current simulation in the search space of different refrigerated goods expiration time length data sets B and generating different refrigerated goods expiration time length data b o Nutrients, expiration time search jellyfish by different refrigerated goods expiration time length data b o Nutrient attraction, the direction of the ocean current is determined by the average of all vectors of each jellyfish in the ocean towards the jellyfish in the best position;

[0025] S322, during the algorithm execution process, the jellyfish in the swarm of jellyfish move around their own positions in the search space of different refrigerated goods expiring time length data set B and search for all different refrigerated goods expiring time length data set B. o , the corresponding position update formula for searching jellyfish at each approaching time is as follows: i (n+1)=Y i (n)+α×rand(0,1)×(β-χ), where Y i (n+1) represents the position of jellyfish individual i in the search space of different refrigerated goods expiration time length data set B after the n+1th iteration of the expiration time search, Y i (n) represents the position of the jellyfish individual i in the search space in the different refrigerated goods near expiration time length data set B after the nth iteration of the near expiration time search, rand represents the random function data in the value interval (0,1); β and χ represent the upper and lower bound parameters of the search space of the different refrigerated goods near expiration time length data set B, that is, the different refrigerated goods near expiration time length data b matching the cold storage refrigerated goods feature text data A are searched in the different refrigerated goods near expiration time length data set B. o The upper and lower bounds of the data, α = 0.1 represents the kinematic system data;

[0026] S323, during the algorithm execution, the jellyfish group searches for the jellyfish in the jellyfish group ... o The time is measured and processed by the time control formula, which is as follows: in It represents the time required to search for jellyfish individuals after the nth iteration, N represents the maximum number of iterations, and rand(0,1) represents the random function data in the interval (0,1);

[0027] S324, the algorithm execution satisfies the boundary condition. When the jellyfish searching for the expiration time moves out of the bounded search area in the search space of the different refrigerated goods expiration time length data set B, the jellyfish searching for the expiration time returns to the opposite search area in the search space of the different refrigerated goods expiration time length data set B. The moving boundary condition of the jellyfish searching for the expiration time satisfies the following formula:

[0028] Where Y' i,ε represents the updated position of the jellyfish individual i in the ε-dimensional space when searching for the expiration time, that is, the updated position in the search space in the data set B of different refrigerated goods expiration time lengths with a spatial dimension of μ, Y i,ε represents the position of the jellyfish individual i in the ε-dimensional space before the update of the expiration time search, that is, the position before the update in the search space in the data set B of the expiration time length of different refrigerated goods with a spatial dimension of μ;

[0029] S325. When the algorithm meets the maximum iteration number data, output the different refrigerated goods expiration time length data b that match the cold storage refrigerated goods characteristic text data A. o ;

[0030] S33, the expiration time length data b of the different refrigerated goods output in step S325 o And generate specific refrigerated goods expiration time length data b through data identification A , where b A The unit is composed of year, month and day.

[0031] The present invention scientifically sets different refrigerated goods near-expiry time parameters and combines an artificial jellyfish search algorithm with characteristic information of refrigerated goods in cold storage to perform scientific identification and analysis of the near-expiry time lengths of refrigerated goods, thereby achieving the effect of efficient and accurate analysis of the near-expiry time parameters of refrigerated goods in cold storage.

[0032] Preferably, the steps of constructing the storage and near-expiry time intervals of refrigerated goods according to the production time point, storage time length and near-expiry time length parameters of the refrigerated goods, and generating the standard storage time interval of refrigerated goods and the near-expiry storage time interval of refrigerated goods are as follows:

[0033] S41, the refrigerated goods production time point data T shengchan and the refrigerated cargo storage time length data ΔT cunchu Perform time value addition processing to generate refrigerated goods expiration time point data T guoqi , where T guoqi =T shengchan +ΔT cunchu , T guoqiThe unit is composed of year, month and day, and the refrigerated goods expiration time point data represents the maximum time point data of the refrigerated goods that have not reached the expiration state;

[0034] The expiration time point data T of the refrigerated goods guoqi and the specific refrigerated goods expiry time length data b A Perform time value subtraction processing to generate the expiration time point data T of refrigerated goods linqi , where T linqi =T guoqi -b A , T linqi The unit is composed of year, month and day, and the refrigerated goods near-expiry time point data represents the minimum time point data when the refrigerated goods reach the expiration state;

[0035] S42, the refrigerated goods production time point data T shengchan and the refrigerated cargo expiry time data T guoqi Perform storage time interval numerical construction processing for refrigerated goods to generate standard storage time interval C for refrigerated goods 1 =[T shengchan ,T guoqi ], the standard storage time interval for refrigerated goods indicates the standard storage time point range for refrigerated goods in a specific cold storage that are not expired;

[0036] The refrigerated goods expiration time point data T linqi and the refrigerated cargo expiry time data T guoqi Perform numerical construction processing on the expiration time interval of refrigerated goods to generate the storage time interval C of refrigerated goods 2 =[T linqi ,T guoqi ], the refrigerated goods near-expiry storage time interval represents the standard storage time point range when the refrigerated goods in the specific cold storage are in a transitional state between a normal state and an expired state.

[0037] The present invention achieves the effect of digital processing of the normal storage time range and the near-expiry storage time range of refrigerated goods in a cold storage by scientifically constructing the standard storage time interval and the near-expiry storage time range of refrigerated goods based on the production time, storage shelf life length and near-expiry time length parameters of the refrigerated goods.

[0038] Preferably, the operation steps of collecting the current refrigeration time point data are as follows:

[0039] S51, collect the current time point information of the refrigerated goods in the cold storage online through the time timing module and generate the current refrigeration time point data T dangqian , where T dangqian The unit is composed of year, month and day.

[0040] The present invention dynamically and accurately collects the current refrigeration time and date parameters through the time timing module, so as to provide data support for accurately evaluating the storage status of refrigerated goods in the cold storage.

[0041] Preferably, the steps of performing storage status judgment processing of refrigerated goods based on the current refrigeration time point data, the standard storage time interval of refrigerated goods, and the near-expiry storage time interval of refrigerated goods, generating and outputting the current storage status judgment data of refrigerated goods are as follows:

[0042] S61, the current refrigeration time point data T is uploaded online through the cold storage operation and maintenance management sub-platform dangqian Respectively with the standard storage time interval C of the refrigerated goods 1 and the refrigerated goods near expiration storage time interval C 2 Perform time value comparison, and generate current storage status judgment data D of refrigerated goods according to the time value comparison result. The cold storage operation and maintenance management sub-platform represents a distributed platform installed outside each specific cold storage object and performing cold storage operation and maintenance management operations;

[0043] When the T dangqian ∈C 1 And T dangqian ∈C 2 , indicating that the refrigerated goods in the cold storage are in the near-expiry state, then the output refrigerated goods current storage state judgment data D is the near-expiry state;

[0044] When the T dangqian ∈C 1 and Indicates that the refrigerated goods in the cold storage are in normal state, then the current storage state judgment data D of the refrigerated goods is output as normal, and the operation and maintenance management of the cold storage is ended;

[0045] When the It indicates that the refrigerated goods in the cold storage are in an expired state, and the output refrigerated goods current storage state judgment data D is an expired state.

[0046] The present invention compares the current refrigeration time and date parameters with the standard storage time interval of refrigerated goods and the near-expiry storage time interval of refrigerated goods based on a distributed cold storage operation and maintenance sub-platform, so as to achieve the effect of intelligently analyzing the storage status parameters of refrigerated goods.

[0047] Preferably, the steps of constructing the refrigerated cargo operation and maintenance characteristic data and pushing it back to the cold storage operation and maintenance management center are as follows:

[0048] S71, when the current storage state judgment data D of the refrigerated goods is near expiration or expired, the cold storage refrigerated goods characteristic text data A is combined with the current storage state judgment data D of the refrigerated goods, the near expiration storage time interval C of the refrigerated goods, 2 Combine the data to construct the refrigerated cargo operation and maintenance characteristic data M, where M = (A, C 2 ,D); S72, the cold storage operation and maintenance management sub-platform pushes the refrigerated goods operation and maintenance characteristic data M to the cold storage operation and maintenance management center through the Internet of Things communication network.

[0049] The present invention efficiently constructs the operation and maintenance characteristic parameters of refrigerated goods in the near-expiry and expired states based on the characteristic information of refrigerated goods in cold storage, the near-expiry storage time interval and the storage status parameters in combination with data processing, and pushes the operation and maintenance characteristic parameters of refrigerated goods to the cold storage operation and maintenance management center through the Internet of Things communication network based on the cold storage operation and maintenance management sub-platform, so as to achieve the effect of accurate construction and scientific feedback of the operation and maintenance characteristic parameters of refrigerated goods.

[0050] A cold storage operation and maintenance intelligent management system based on a distributed system, used to implement the cold storage operation and maintenance intelligent management method based on a distributed system, the system includes a cold storage refrigerated goods information processing module, a cold storage refrigerated goods storage status analysis module, and a cold storage refrigerated goods operation and maintenance information feedback module;

[0051] The cold storage refrigerated goods information processing module includes a cold storage refrigerated goods characteristic information collection unit, a refrigerated goods time information search unit, a different refrigerated goods expiration time information storage unit, a refrigerated goods expiration time information identification unit, and a refrigerated goods storage time interval establishment unit;

[0052] The cold storage refrigerated goods characteristic information collection unit collects the cold storage refrigerated goods characteristic text data through a barcode scanner; the refrigerated goods time information search unit searches for the production date and storage time length of the refrigerated goods according to the cold storage refrigerated goods characteristic text data, and generates the refrigerated goods production time point data and the refrigerated goods storage time length data; the different refrigerated goods near expiration time information storage unit is used to store different refrigerated goods near expiration time length data; the refrigerated goods near expiration time information identification unit identifies the near expiration time length of the refrigerated goods based on the cold storage refrigerated goods characteristic text data and the different refrigerated goods near expiration time length data, and generates specific refrigerated goods near expiration time length data; the refrigerated goods storage time interval establishment unit performs storage and near expiration time interval construction processing of the refrigerated goods according to the production time point, storage time length and near expiration time length parameters of the refrigerated goods, and generates the refrigerated goods standard storage time interval and the refrigerated goods near expiration storage time interval;

[0053] The cold storage refrigerated goods storage status analysis module includes a current refrigeration time information collection unit, a refrigerated goods storage status judgment unit, and a refrigerated goods storage status judgment result output unit;

[0054] The current refrigeration time information collection unit collects the current refrigeration time point data through the time timing module; the refrigerated goods storage status judgment unit performs storage status judgment processing of the refrigerated goods based on the distributed cold storage operation and maintenance sub-platform according to the current refrigeration time point data and the refrigerated goods standard storage time interval and the refrigerated goods near-expiry storage time interval to generate the refrigerated goods current storage status judgment data; the refrigerated goods storage status judgment result output unit is used to output the refrigerated goods current storage status judgment data;

[0055] The cold storage refrigerated goods operation and maintenance information feedback module includes a refrigerated goods operation and maintenance information generation unit and a refrigerated goods storage status judgment result output unit;

[0056] The refrigerated goods operation and maintenance information generation unit is used to construct refrigerated goods operation and maintenance characteristic data; the refrigerated goods storage status judgment result output unit, the cold storage operation and maintenance management sub-platform pushes the refrigerated goods operation and maintenance characteristic data to the cold storage operation and maintenance management center through the Internet of Things communication network.

[0057] (III) Beneficial effects

[0058] The present invention provides a cold storage operation and maintenance intelligent management system and method based on a distributed system. It has the following beneficial effects:

[0059] 1. Through the cold storage refrigerated goods characteristic information collection unit, a barcode scanner is used to collect the characteristic information of the cold storage refrigerated goods, so as to provide data support for the subsequent digital establishment of the storage time parameters of the cold storage refrigerated goods; the refrigerated goods time information search unit adopts an intelligent search algorithm and accurately searches the production date and storage shelf life parameters of the refrigerated goods based on the characteristic information of the cold storage refrigerated goods. Different refrigerated goods near-expiry time information storage units and refrigerated goods near-expiry time information identification units cooperate with each other, scientifically set different refrigerated goods near-expiry time parameters, and combine the intelligent identification algorithm with the characteristic information of the cold storage refrigerated goods to scientifically identify and analyze the near-expiry time length of the refrigerated goods, so as to achieve efficient and accurate analysis of the near-expiry time parameters of the cold storage refrigerated goods; the refrigerated goods storage time interval establishment unit scientifically constructs the standard storage time interval and near-expiry storage time interval of refrigerated goods based on the production time, storage shelf life and near-expiry time parameters of the refrigerated goods, realizes the digital processing of the normal storage time range and near-expiry storage time range of the cold storage refrigerated goods, and realizes the refined operation and maintenance management of the storage time of the cold storage refrigerated goods.

[0060] 2. Through the current refrigeration time information collection unit, the time timing module is used to dynamically and accurately collect the current refrigeration time and date parameters, providing data support for accurately evaluating the storage status of refrigerated goods in the cold storage; the refrigerated goods storage status judgment unit, based on the distributed cold storage operation and maintenance sub-platform, compares the current refrigeration time and date parameters with the standard storage time interval of refrigerated goods and the refrigerated goods near-expiry storage time interval, and intelligently analyzes the storage status parameters of the refrigerated goods, realizing standardized operation and maintenance management of the storage status of refrigerated goods in the cold storage based on the distributed system, thereby improving the quality and reliability of the cold storage operation and maintenance management.

[0061] 3. Through the refrigerated goods operation and maintenance information generation unit, based on the characteristic information of refrigerated goods in the cold storage, the expiring storage time interval and storage status parameters combined with data processing, the operation and maintenance characteristic parameters of refrigerated goods in the expiring and expired states are efficiently constructed; the refrigerated goods storage status judgment result output unit, based on the cold storage operation and maintenance management sub-platform, pushes the refrigerated goods operation and maintenance characteristic parameters to the cold storage operation and maintenance management center through the Internet of Things communication network, realizes efficient feedback operation and maintenance management of the storage status of refrigerated goods in the cold storage based on the distributed system, and improves the efficiency and applicability of cold storage operation and maintenance management. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 A schematic diagram of a module of a cold storage operation and maintenance intelligent management system based on a distributed system provided by the present invention;

[0063] Figure 2 The present invention provides a flow chart of a cold storage operation and maintenance intelligent management method based on a distributed system. DETAILED DESCRIPTION

[0064] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only 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.

[0065] The embodiments of the cold storage operation and maintenance intelligent management system and method based on the distributed system are as follows:

[0066] Embodiment 1:

[0067] See also Figure 1 - Figure 2 , a cold storage operation and maintenance intelligent management method based on a distributed system, the method comprises the following steps:

[0068] S1. Collect characteristic text data of refrigerated goods in cold storage;

[0069] S2. Search and process the production date and storage time length of the refrigerated goods according to the characteristic text data of the refrigerated goods in the cold storage, and generate the production time point data of the refrigerated goods and the storage time length data of the refrigerated goods;

[0070] S3, based on the characteristic text data of refrigerated goods in the cold storage and the data of the length of time of different refrigerated goods approaching expiration, the length of time of refrigerated goods approaching expiration is identified and processed, and specific data of the length of time of refrigerated goods approaching expiration is generated;

[0071] S4. Perform storage and near-expiry time interval construction processing for refrigerated goods according to the production time point, storage time length and near-expiry time length parameters of the refrigerated goods, and generate a standard storage time interval for refrigerated goods and a near-expiry storage time interval for refrigerated goods;

[0072] S5, collecting current refrigeration time point data;

[0073] S6. Perform storage status judgment processing on the refrigerated goods based on the current refrigeration time point data, the standard storage time interval of the refrigerated goods, and the near-expiry storage time interval of the refrigerated goods, generate and output the current storage status judgment data of the refrigerated goods;

[0074] S7. Construct the refrigerated cargo operation and maintenance characteristic data and push it back to the cold storage operation and maintenance management center.

[0075] For further information, see Figure 1 - Figure 2 The steps for collecting characteristic text data of cold storage refrigerated goods are as follows:

[0076] S11. Scan the barcode of the refrigerated goods in the cold storage online with a barcode scanner to obtain characteristic text information of the refrigerated goods and generate characteristic text data A of the refrigerated goods in the cold storage. The characteristic text data of the refrigerated goods in the cold storage includes the production date, shelf life, manufacturer, brand name, production address and product description of the refrigerated goods.

[0077] The steps for searching and processing the production date and storage time length of refrigerated goods based on the characteristic text data of refrigerated goods in cold storage to generate the production time point data and storage time length data of refrigerated goods are as follows:

[0078] S21, using the BERT language model to search for the production date and shelf life parameters of the refrigerated goods in the cold storage refrigerated goods feature text data A according to the production date keywords and the shelf life keywords, and generate the refrigerated goods production time point data T through data identification shengchan and refrigerated cargo storage time length data ΔT cunchu , where T shengchan and ΔT cunchu The units are composed of year, month and day.

[0079] Based on the characteristic text data of refrigerated goods in cold storage and the data of the length of time of different refrigerated goods approaching expiration, the steps for identifying the length of time of refrigerated goods approaching expiration and generating the data of the length of time of specific refrigerated goods approaching expiration are as follows:

[0080] S31. Establish different refrigerated goods expiration time length data set B = (b 1 ,…,b o ,…,b μ ), o=1,2,3,…,μ; where b o represents the length of time of different refrigerated goods approaching expiration corresponding to the oth refrigerated goods characteristic type, μ represents the maximum number of refrigerated goods characteristic types, and the length of time of different refrigerated goods approaching expiration represents the length of time before the refrigerated goods reach the expiration state, b o The unit is composed of year, month and day;

[0081] S32, when the refrigerated goods production time point data T shengchan and refrigerated cargo storage time length data ΔT cunchu When the generation is completed, the cold storage refrigerated goods feature text data A and the different refrigerated goods expiration time length data set B of different refrigerated goods expiration time length data b are combined. o Perform keyword matching of refrigerated goods characteristics to search for different refrigerated goods expiration time length data b corresponding to the cold storage refrigerated goods characteristic text data A o And generate specific refrigerated goods expiration time length data b through data identification A ; Execute and generate specific refrigerated goods expiration time length data b A The specific steps are as follows:

[0082] S321, initializing the algorithm iteration data and executing the ocean current simulation process; setting the maximum algorithm iteration data to N, performing ocean current simulation in the search space of different refrigerated goods expiration time length data sets B and generating different refrigerated goods expiration time length data b o Nutrients, expiration time search jellyfish by different refrigerated goods expiration time length data b o Nutrient attraction, the direction of the ocean current is determined by the average of all vectors of each jellyfish in the ocean towards the jellyfish in the best position;

[0083] S322, during the algorithm execution process, the jellyfish in the swarm of jellyfish move around their own positions in the search space of different refrigerated goods expiring time length data set B and search for all different refrigerated goods expiring time length data set B. o , the corresponding position update formula for searching jellyfish at each approaching time is as follows: i(n+1)=Y i (n)+α×rand(0,1)×(β-χ), where Y i (n+1) represents the position of jellyfish individual i in the search space of different refrigerated goods expiration time length data set B after the n+1th iteration of the expiration time search, Y i (n) represents the position of the jellyfish individual i in the search space of different refrigerated goods near expiration time length data set B after the nth iteration of the near expiration time search, rand represents the random function data in the value interval (0,1); β and χ represent the upper and lower bound parameters of the search space of different refrigerated goods near expiration time length data set B, that is, different refrigerated goods near expiration time length data b matching the cold storage refrigerated goods feature text data A are searched in the different refrigerated goods near expiration time length data set B. o The upper and lower bounds of the data, α = 0.1 represents the kinematic system data;

[0084] S323, during the algorithm execution, the jellyfish group searches for the jellyfish group in ... o The time is measured and processed by the time control formula, which is as follows: in It represents the time required to search for jellyfish individuals after the nth iteration, N represents the maximum number of iterations, and rand(0,1) represents the random function data in the interval (0,1);

[0085] S324, the algorithm execution satisfies the boundary condition. When the jellyfish searching for the expiration time moves out of the bounded search area in the search space of the different refrigerated goods expiration time length data set B, the jellyfish searching for the expiration time returns to the opposite search area in the search space of the different refrigerated goods expiration time length data set B. The moving boundary condition of the jellyfish searching for the expiration time satisfies the following formula:

[0086] Where Y' i,ε represents the updated position of the jellyfish individual i in the ε-dimensional space when searching for the expiration time, that is, the updated position in the search space in the data set B of different refrigerated goods expiration time lengths with a spatial dimension of μ, Y i,ε represents the position of the jellyfish individual i in the ε-dimensional space before the update of the expiration time search, that is, the position before the update in the search space in the data set B of the expiration time length of different refrigerated goods with a spatial dimension of μ;

[0087] S325. When the algorithm meets the maximum iteration number data, output different refrigerated goods expiration time length data b that match the cold storage refrigerated goods feature text data A.o ;

[0088] S33, the different refrigerated goods expiration time length data b output in step S325 o And generate specific refrigerated goods expiration time length data b through data identification A , where b A The unit is composed of year, month and day.

[0089] According to the production time point, storage time length and near-expiry time length parameters of refrigerated goods, the storage and near-expiry time intervals of refrigerated goods are constructed and processed. The steps for generating the standard storage time interval of refrigerated goods and the near-expiry storage time interval of refrigerated goods are as follows:

[0090] S41, the refrigerated goods production time point data T shengchan and refrigerated cargo storage time length data ΔT cunchu Perform time value addition processing to generate refrigerated goods expiration time point data T guoqi , where T guoqi =T shengchan +ΔT cunchu , T guoqi The unit is composed of year, month and day. The expiration time point data of refrigerated goods indicates the maximum time point data of refrigerated goods that have not reached the expiration state;

[0091] The expiration time point data of refrigerated goods T guoqi and specific refrigerated goods expiry time length datab A Perform time value subtraction processing to generate the expiration time point data T of refrigerated goods linqi , where T linqi =T guoqi -b A , T linqi The unit is composed of year, month and day. The refrigerated goods expiration time point data indicates the minimum time point data when the refrigerated goods reach the expiration state;

[0092] S42, the refrigerated goods production time point data T shengchan and refrigerated cargo expiry time data T guoqi Perform storage time interval numerical construction processing for refrigerated goods to generate standard storage time interval C for refrigerated goods 1 =[T shengchan ,T guoqi ], the standard storage time interval for refrigerated goods indicates the standard storage time range for specific cold storage refrigerated goods that are not expired;

[0093] The refrigerated goods expiration time point data T linqi and refrigerated cargo expiry time data T guoqiPerform numerical construction processing on the expiration time interval of refrigerated goods to generate the storage time interval C of refrigerated goods 2 =[T linqi ,T guoqi ], the refrigerated goods near-expiry storage time interval refers to the standard storage time point range when the refrigerated goods in the specific cold storage are in a transitional state between normal state and expired state.

[0094] The characteristic information collection unit for refrigerated goods in cold storage uses a barcode scanner to collect characteristic information of refrigerated goods in cold storage, providing data support for the subsequent digital establishment of storage time parameters for refrigerated goods in cold storage; the refrigerated goods time information search unit uses an intelligent search algorithm and accurately searches the production date and storage shelf life parameters of refrigerated goods based on the characteristic information of refrigerated goods in cold storage. Different refrigerated goods near-expiry time information storage units and refrigerated goods near-expiry time information identification units cooperate with each other to scientifically set different refrigerated goods near-expiry time parameters and combine the intelligent identification algorithm with the characteristic information of refrigerated goods in cold storage to scientifically identify and analyze the near-expiry time length of refrigerated goods, so as to achieve efficient and accurate analysis of the near-expiry time parameters of refrigerated goods in cold storage; the refrigerated goods storage time interval establishment unit scientifically constructs the standard storage time interval and near-expiry storage time interval of refrigerated goods based on the production time, storage shelf life and near-expiry time parameters of refrigerated goods, realizes digital processing of the normal storage time range and near-expiry storage time range of refrigerated goods in cold storage, and realizes refined operation and maintenance management of the storage time of refrigerated goods in cold storage.

[0095] For further information, see Figure 1 - Figure 2 , the steps to collect the current cold storage time point data are as follows:

[0096] S51, collect the current time point information of the refrigerated goods in the cold storage online through the time timing module and generate the current refrigeration time point data T dangqian , where T dangqian The unit is composed of year, month and day.

[0097] The steps for determining the storage status of refrigerated goods based on the current refrigeration time point data, the standard storage time interval for refrigerated goods, and the near-expiry storage time interval for refrigerated goods, and generating and outputting the current storage status determination data for refrigerated goods are as follows:

[0098] S61, the current refrigeration time point data T is uploaded online through the cold storage operation and maintenance management sub-platform dangqian Respectively with the standard storage time interval C for refrigerated goods 1 and refrigerated goods near expiration storage time interval C 2Perform time value comparison, and generate the current storage status judgment data D of the refrigerated goods according to the time value comparison result. The cold storage operation and maintenance management sub-platform represents a distributed platform installed outside each specific cold storage object and performing cold storage operation and maintenance management operations;

[0099] When T dangqian ∈C 1 And T dangqian ∈C 2 , indicating that the refrigerated goods in the cold storage are in the near-expiry state, then the output refrigerated goods current storage state judgment data D is the near-expiry state;

[0100] When T dangqian ∈C 1 and Indicates that the refrigerated goods in the cold storage are in normal state, then the current storage state judgment data D of the refrigerated goods is output as normal, and the operation and maintenance management of the cold storage is ended;

[0101] when It indicates that the refrigerated goods in the cold storage are in an expired state, and the output refrigerated goods current storage state judgment data D is an expired state.

[0102] Through the current refrigeration time information collection unit, the time timing module is used to dynamically and accurately collect the current refrigeration time and date parameters, providing data support for accurately evaluating the storage status of refrigerated goods in the cold storage; the refrigerated goods storage status judgment unit, based on the distributed cold storage operation and maintenance sub-platform, compares the current refrigeration time and date parameters with the standard storage time interval of refrigerated goods and the refrigerated goods near-expiry storage time interval, and intelligently analyzes the storage status parameters of the refrigerated goods, realizing standardized operation and maintenance management of the storage status of refrigerated goods in cold storage based on the distributed system, thereby improving the quality and reliability of cold storage operation and maintenance management.

[0103] For further information, see Figure 1 - Figure 2 The steps to construct the refrigerated cargo operation and maintenance characteristic data and push it back to the cold storage operation and maintenance management center are as follows:

[0104] S71, when the current storage state judgment data D of the refrigerated goods is near expiration or expired, the cold storage refrigerated goods characteristic text data A is combined with the current storage state judgment data D of the refrigerated goods, the near expiration storage time interval C of the refrigerated goods, 2 Combine the data to construct the refrigerated cargo operation and maintenance characteristic data M, where M = (A, C 2 ,D);

[0105] S72. The cold storage operation and maintenance management sub-platform pushes the refrigerated goods operation and maintenance characteristic data M to the cold storage operation and maintenance management center through the IoT communication network.

[0106] Through the refrigerated goods operation and maintenance information generation unit, based on the characteristic information of refrigerated goods in the cold storage, the expiring storage time interval and storage status parameters combined with data processing, the operation and maintenance characteristic parameters of refrigerated goods in the expiring and expired states are efficiently constructed; the refrigerated goods storage status judgment result output unit, based on the cold storage operation and maintenance management sub-platform, pushes the refrigerated goods operation and maintenance characteristic parameters to the cold storage operation and maintenance management center through the Internet of Things communication network, realizes efficient feedback operation and maintenance management of the storage status of refrigerated goods in the cold storage based on the distributed system, and improves the efficiency and applicability of cold storage operation and maintenance management.

[0107] Embodiment 2:

[0108] See also Figure 1 - Figure 2 , a cold storage operation and maintenance intelligent management system based on a distributed system, used to implement a cold storage operation and maintenance intelligent management method based on a distributed system, the system includes a cold storage refrigerated goods information processing module, a cold storage refrigerated goods storage status analysis module, and a cold storage refrigerated goods operation and maintenance information feedback module;

[0109] The cold storage refrigerated goods information processing module includes a cold storage refrigerated goods characteristic information collection unit, a refrigerated goods time information search unit, a different refrigerated goods expiration time information storage unit, a refrigerated goods expiration time information identification unit, and a refrigerated goods storage time interval establishment unit;

[0110] A cold storage refrigerated goods characteristic information collection unit, which collects the characteristic text data of the cold storage refrigerated goods through a barcode scanner; a refrigerated goods time information search unit, which searches and processes the production date and storage time length of the refrigerated goods based on the characteristic text data of the refrigerated goods in the cold storage, and generates the production time point data of the refrigerated goods and the storage time length data of the refrigerated goods; a different refrigerated goods near-expiry time information storage unit, which is used to store different refrigerated goods near-expiry time length data; a refrigerated goods near-expiry time information identification unit, which identifies the near-expiry time length of the refrigerated goods based on the cold storage refrigerated goods characteristic text data and the near-expiry time length data of different refrigerated goods, and generates specific refrigerated goods near-expiry time length data; a refrigerated goods storage time interval establishment unit, which constructs the storage and near-expiry time interval of the refrigerated goods according to the production time point, storage time length and near-expiry time length parameters of the refrigerated goods, and generates the standard storage time interval of the refrigerated goods and the near-expiry storage time interval of the refrigerated goods;

[0111] The cold storage refrigerated goods storage status analysis module includes a current refrigeration time information collection unit, a refrigerated goods storage status judgment unit, and a refrigerated goods storage status judgment result output unit;

[0112] The current refrigeration time information collection unit collects the current refrigeration time point data through the time timing module; the refrigerated goods storage status judgment unit judges the storage status of the refrigerated goods based on the distributed cold storage operation and maintenance sub-platform according to the current refrigeration time point data and the standard storage time interval of the refrigerated goods and the storage time interval of the refrigerated goods near the expiration date, and generates the current storage status judgment data of the refrigerated goods; the refrigerated goods storage status judgment result output unit is used to output the current storage status judgment data of the refrigerated goods;

[0113] The cold storage refrigerated goods operation and maintenance information feedback module includes a refrigerated goods operation and maintenance information generation unit and a refrigerated goods storage status judgment result output unit;

[0114] The refrigerated cargo operation and maintenance information generation unit is used to construct the refrigerated cargo operation and maintenance characteristic data; the refrigerated cargo storage status judgment result output unit, the cold storage operation and maintenance management sub-platform pushes the refrigerated cargo operation and maintenance characteristic data to the cold storage operation and maintenance management center through the Internet of Things communication network.

[0115] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A cold storage operation and maintenance intelligent management method based on a distributed system, characterized in that: The method comprises the following steps: S1. Collect characteristic text data A of cold storage refrigerated goods; S2, searching and processing the production date and storage time length of the refrigerated goods according to the cold storage refrigerated goods characteristic text data A, and generating the refrigerated goods production time point data T shengchan and refrigerated cargo storage time length data ΔT cunchu ; S3, based on the cold storage refrigerated goods characteristic text data A and different refrigerated goods near expiration time length data, the near expiration time length data of the refrigerated goods is identified and processed to generate specific refrigerated goods near expiration time length data, the S3 comprises the following steps: S31. Establish a data set B of different refrigerated goods near expiration time lengths (b1,…,b o ,…,b μ ), o=1,2,3,…,μ; where b o represents the length of time of different refrigerated goods approaching expiration corresponding to the oth refrigerated goods characteristic type, μ represents the maximum number of refrigerated goods characteristic types, b o The unit is composed of year, month and day; S32, when the refrigerated goods production time point data T shengchan and the refrigerated cargo storage time length data ΔT cunchu When the generation is completed, the cold storage refrigerated goods characteristic text data A and the different refrigerated goods expiration time length data b in the different refrigerated goods expiration time length data set B are combined. o Perform refrigerated goods feature keyword matching to search for the different refrigerated goods expiration time length data b corresponding to the cold storage refrigerated goods feature text data A o And generate specific refrigerated goods expiration time length data b through data identification A ; Execute and generate specific refrigerated goods expiration time length data b A The specific steps are as follows: S321, initializing the algorithm iteration data and executing the ocean current simulation process; setting the maximum algorithm iteration data to N, performing ocean current simulation in the search space of different refrigerated goods expiration time length data sets B and generating different refrigerated goods expiration time length data b o Nutrients, expiration time search jellyfish by different refrigerated goods expiration time length data b o Nutrient attraction, the direction of the ocean current is determined by the average of all vectors of each jellyfish in the ocean towards the jellyfish in the best position; S322, during the algorithm execution process, the jellyfish in the swarm of jellyfish move around their own positions in the search space of different refrigerated goods expiring time length data set B and search for all different refrigerated goods expiring time length data set B. o , the corresponding position of the searched jellyfish at each approaching time is updated according to the update formula; S323, during the algorithm execution, the jellyfish group searches for the jellyfish in the jellyfish group ... o The time is measured and processed by the time control formula; S324, the algorithm execution satisfies the boundary condition, when the jellyfish searching for the expiration time moves out of the bounded search area in the search space of the different refrigerated goods expiration time length data set B, the jellyfish searching for the expiration time returns to the opposite search area in the search space of the different refrigerated goods expiration time length data set B; S325. When the algorithm meets the maximum iteration number data, output the different refrigerated goods expiration time length data b that match the cold storage refrigerated goods characteristic text data A. o ; S33, the expiration time length data b of the different refrigerated goods output in step S325 o And generate specific refrigerated goods expiration time length data b through data identification A , where b A The unit is composed of year, month and day; S4. Perform storage and near-expiry time interval construction processing for refrigerated goods according to the production time point, storage time length and near-expiry time length parameters of the refrigerated goods, and generate a standard storage time interval for refrigerated goods and a near-expiry storage time interval for refrigerated goods; S5, collecting current refrigeration time point data; S6, performing storage status judgment processing of the refrigerated goods according to the current refrigeration time point data, the standard storage time interval of the refrigerated goods, and the near-expiry storage time interval of the refrigerated goods, generating and outputting current storage status judgment data of the refrigerated goods; S7. Construct the refrigerated cargo operation and maintenance characteristic data and push it back to the cold storage operation and maintenance management center.

2. According to the distributed system-based cold storage operation and maintenance intelligent management method of claim 1, it is characterized by: The S1 comprises the following steps: S11. Scan the barcode of the refrigerated goods in the cold storage online with a barcode scanner to obtain characteristic text information of the refrigerated goods and generate characteristic text data A of the refrigerated goods in the cold storage.

3. According to claim 2, a cold storage operation and maintenance intelligent management method based on a distributed system is characterized by: The S2 comprises the following steps: S21, using the BERT language model to search for the production date and shelf life parameters of the refrigerated goods in the cold storage refrigerated goods feature text data A according to the production date keywords and the shelf life keywords, and generate the refrigerated goods production time point data T through data identification. shengchan and refrigerated cargo storage time length data ΔT cunchu , where T shengchan and ΔT cunchu The units are composed of year, month and day.

4. According to claim 3, a cold storage operation and maintenance intelligent management method based on a distributed system is characterized in that: The S4 comprises the following steps: S41, the refrigerated goods production time point data T shengchan and the refrigerated cargo storage time length data ΔT cunchu Perform time value addition processing to generate refrigerated goods expiration time point data T guoqi , where T guoqi =T shengchan +ΔT cunchu , T guoqi The unit is composed of year, month and day; The expiration time point data T of the refrigerated goods guoqi and the specific refrigerated goods expiry time length data b A Perform time value subtraction processing to generate the expiration time point data T of refrigerated goods linqi , where T linqi =T guoqi -b A , T linqi The unit is composed of year, month and day; S42, the refrigerated goods production time point data T shengchan and the refrigerated cargo expiry time data T guoqi Perform storage time interval numerical construction processing for refrigerated goods to generate a standard storage time interval for refrigerated goods C1 = [T shengchan ,T guoqi ]; The refrigerated goods expiration time point data T linqi and the refrigerated cargo expiry time data T guoqi Perform numerical construction processing on the refrigerated goods near expiration time interval to generate the refrigerated goods near expiration storage time interval C2 = [T linqi ,T guoqi ].

5. According to claim 4, a cold storage operation and maintenance intelligent management method based on a distributed system is characterized in that: The S5 comprises the following steps: S51, collect the current time point information of the refrigerated goods in the cold storage online through the time timing module and generate the current refrigeration time point data T dangqian , where T dangqian The unit is composed of year, month and day.

6. According to claim 5, a cold storage operation and maintenance intelligent management method based on a distributed system is characterized in that: The S6 comprises the following steps: S61, the current refrigeration time point data T is uploaded online through the cold storage operation and maintenance management sub-platform dangqian Compare the time values ​​with the standard storage time interval C1 of the refrigerated goods and the near-expiry storage time interval C2 of the refrigerated goods respectively, and generate the current storage state judgment data D of the refrigerated goods according to the time value comparison result; When the T dangqian ∈C1 and T dangqian ∈C2, then the output refrigerated goods current storage status judgment data D is near expiration; When the T dangqian ∈C1 and The output determines that the current storage status of the refrigerated goods is normal, and the cold storage operation and maintenance management operation is ended; When the Then the output refrigerated goods current storage status judgment data D is expired.

7. According to claim 6, a cold storage operation and maintenance intelligent management method based on a distributed system is characterized by: The S7 comprises the following steps: S71. When the current storage state judgment data D of the refrigerated goods is in the near-expiry state or expired state, the cold storage refrigerated goods characteristic text data A is combined with the current storage state judgment data D of the refrigerated goods and the near-expiry storage time interval C2 of the refrigerated goods to construct the refrigerated goods operation and maintenance characteristic data M, where M = (A, C2, D); S72. The cold storage operation and maintenance management sub-platform pushes and feeds back the refrigerated goods operation and maintenance characteristic data M to the cold storage operation and maintenance management center through the IoT communication network.

8. A cold storage operation and maintenance intelligent management system based on a distributed system, used to implement a cold storage operation and maintenance intelligent management method based on a distributed system according to any one of claims 1 to 7, characterized in that: The system comprises a cold storage refrigerated goods information processing module, a cold storage refrigerated goods storage status analysis module, and a cold storage refrigerated goods operation and maintenance information feedback module.

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