Intelligent archiving method for archives in unattended power archive warehouses

Abstract

The present invention relates to the technical field of warehouse archive management, and in particular to an intelligent archive archiving method for an unmanned electric power archive warehouse, comprising the following steps: an intelligent robot retrieves archived files from a compartment of an archive storage and retrieval integrated machine; an intelligent robot analyzes the archived files and searches for an optimized archiving location, and the intelligent robot stores the archived files in a designated overhead file location according to the file location; wherein the method for searching for the optimized archiving location is: searching for a first associated file of the archived files; the first associated file refers to an in-stock file in a historical archive borrowing record that is borrowed at the same time as the archived files and whose proportion of the number of simultaneous borrowings is ≤ a first threshold; and sequentially calculating the retrieval cost of the nearest empty file location next to each first associated file, and selecting the empty file location with the smallest retrieval cost as the optimized archiving location. The present invention can minimize the occupation of convenient locations by unborrowed files and improve the working efficiency of the intelligent robot.

Description

Technical Field

[0001] The invention relates to an intelligent archiving method for an electric power unmanned archive warehouse, belonging to the technical field of warehouse archive management. Background Art

[0002] An unmanned power archive warehouse refers to an archive warehouse that integrates smart devices, Internet of Things technology, big data analysis, and artificial intelligence algorithms to achieve intelligent monitoring of the archive warehouse environment, automatic storage and intelligent management of archives, as well as remote monitoring and alarm functions.

[0003] Common power unattended archive warehouses such as Figure 1 As shown, it is mainly divided into two parts: the area where the intelligent compact shelving is placed and the integrated file storage and retrieval machine. The area where the intelligent compact shelving is placed is under closed management, and intelligent robots are responsible for storing and retrieving files; the integrated file storage and retrieval machine is a window for external interaction, through which staff members borrow and deposit files.

[0004] The archive management process of the above-mentioned unmanned power archive warehouse is as follows: the staff member performs identity authentication through the archive storage and access machine; the archive warehouse management system performs identity authentication and obtains the list of archives borrowed by the staff member; the staff member selects the list of archives that need to be borrowed and returned; the archive storage and access machine opens the corresponding number of doors; the staff member puts the archives to be archived into the access archive warehouse and closes the door; the archive storage and access machine automatically identifies the RFID tag attached to the archive through RFID (radio frequency identification) technology. The tag stores detailed information of the archive, such as the archive number, name, category, and storage time, to complete the verification of the archive; the intelligent robot takes out the archives that need to be borrowed from the corresponding warehouse one by one and puts them into the access archive warehouse, and the staff member takes out the archive; the intelligent robot stores the stored archives in the nearest intelligent dense overhead space.

[0005] The above-mentioned unmanned electric archive warehouse can solve the problems of backward equipment, single management and control methods, and low work efficiency in the management of traditional archive warehouses. It can improve the efficiency of archive management, reduce management costs, and enhance the security of archives to a certain extent. However, since the existing archives are stored nearby, archives that have been stored historically but are no longer borrowed gradually occupy the position of the nearest archive compact shelving, resulting in intelligent robots being able to retrieve and archive files at locations farther and farther away from the archive storage and retrieval machines, resulting in a continuous decline in the efficiency of archive borrowing and archiving. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to provide an intelligent archiving method for archives in an unmanned electric archive warehouse, which can avoid unborrowed archives occupying convenient locations as much as possible and improve the archiving efficiency of intelligent robots.

[0007] In order to solve the above technical problems, the technical solution proposed by the present invention is: an intelligent archiving method for archives in an unmanned power archive warehouse, comprising the following steps:

[0008] The intelligent robot retrieves archived files from the storage and retrieval machine;

[0009] Analyze archived files and find the optimized archive location. The intelligent robot will store the archived files in the designated overhead archive location according to the archive location;

[0010] Among them, the method to find the optimized archive location is:

[0011] Find the first associated file of the archived file; the first associated file refers to the archived file in the historical archive borrowing record that was borrowed at the same time as the archived file and the corresponding ratio of the number of simultaneous borrowings is less than or equal to the first threshold;

[0012] Calculate the retrieval cost of the nearest empty file location next to each first associated file in turn.

[0013] Fetch cost = e*s,

[0014] Where, e is the number of times the archived file and the first associated file are borrowed at the same time; s is the distance between the archived file and the first associated file;

[0015] Select the empty file location with the lowest retrieval cost as the optimized archive location.

[0016] The present invention finds out several related files that have been borrowed the most times at the same time as the archived files, and places the archived files in an empty file position next to one of the related files with the lowest retrieval cost, thereby avoiding the situation where unborrowed archived files gradually occupy the nearest file rack. At the same time, the association relationship between files is fully considered, so that when the intelligent robot performs the retrieval task, it can take away the files that are related and have a high probability of being needed at the same time at one time, thereby improving the working efficiency of the intelligent robot. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The present invention will be further described below with reference to the accompanying drawings.

[0018] Figure 1 This is a schematic diagram of an unmanned power archive warehouse.

[0019] Figure 2 It is the file coordinate design Figure 1 .

[0020] Figure 3 It is the file coordinate design Figure 2 . DETAILED DESCRIPTION

[0021] This embodiment shows a method for intelligent archiving of archives in an unmanned power archive warehouse, including the following steps:

[0022] The staff member authenticates their identity through the archive storage and access machine; the archive warehouse management system authenticates their identity and obtains a list of files borrowed by the person; the staff member selects a list of files to be borrowed and returned; the archive storage and access machine opens the corresponding number of doors; the staff member places the files to be archived into the storage and access file bin and closes the door; the archive storage and access machine automatically identifies the RFID tag attached to the file through RFID (radio frequency identification) technology. The tag stores detailed information about the file, such as the file number, name, category, and entry time, to complete the verification of the file; the intelligent robot takes out the files to be borrowed from the corresponding bin one by one and puts them into the storage and access file bin, and the staff member takes out the files; the intelligent robot takes out the archived files from the bin of the archive storage and access machine.

[0023] Next, the archive files are analyzed to find the optimized archive location. The intelligent robot stores the archive files in the designated overhead archive location according to the archive location:

[0024] The method for obtaining the file location coordinates can be to map the Cartesian coordinate system based on the access motion time of the intelligent robot, such as Figure 2 、 3 As shown in the figure, with the location of the integrated file storage and retrieval machine as the origin, the direction of the file shelves in the same row is determined as the X-axis, the x-axis coordinate deviation of the left and right adjacent gears is 1, and the spatial coordinate deviation of the file shelves in the same row is d (greater than 1, less than 10); the direction of the file shelves in the same channel is determined as the Y-axis, the y-axis coordinate deviation of the upper and lower adjacent gears is 1, and the coordinate deviation of the file shelves in adjacent channels (or file shelves in adjacent rooms) is D (greater than 100) according to the distance configuration; the height direction of the file shelves is determined as the Z-axis; and a Cartesian coordinate system is established.

[0025] Among them, the method to find the optimized archive location is:

[0026] Find the first associated file of the archived file; the first associated file refers to the file in the historical archive borrowing record that was borrowed at the same time as the archived file and whose proportion corresponding to the ranking of the number of simultaneous borrowings is ≤ the first threshold.

[0027] The association between archives can be established by constructing an archive relationship spectrum, that is, a weighted undirected graph: the graph node information includes the archive unique identifier and the number of archive borrowings; when different archives are borrowed in the same borrowing order, an edge will be constructed between the nodes corresponding to these archives; the weight of the edge is the number of simultaneous borrowings, and the higher the weight, the stronger the association. It is also possible to directly read historical borrowing records to obtain data on the number of archive borrowings and the number of simultaneous borrowings.

[0028] The first threshold can be 20%-40%. Assuming the first threshold is 30%, find 10 files that are borrowed at the same time as the archived files, rank these files according to the number of simultaneous borrowings, and find the top 3 files in the library with the highest number of simultaneous borrowings as the first associated files.

[0029] Calculate the retrieval cost of the nearest empty file location next to each first associated file in turn.

[0030] Fetch cost = e*s,

[0031] Where, e is the number of times the archived file and the first associated file are borrowed at the same time; s is the distance between the archived file and the first associated file;

[0032] Assume that the number of simultaneous borrowings of the three first-linked files is 10, 8, and 5 respectively; the Euclidean distances between the archived files and these first-linked files are 5, 7, and 12 respectively; then the retrieval costs are 50, 56, and 60 respectively;

[0033] The empty file position with the lowest retrieval cost is selected as the optimized archiving position. In this embodiment, the archived file should be placed in the empty file position closest to the first relationship file with the highest number of simultaneous borrowing times.

[0034] This embodiment finds out several related files that have been borrowed the most times at the same time as the archived file, and places the archived file in an empty file position next to one of the related files with the lowest archiving cost, thereby avoiding the situation where unborrowed archived files gradually occupy the nearest file shelf. At the same time, the association relationship between files is fully considered, so that when the intelligent robot performs the file retrieval task, it can take away the files that are related and have a high probability of being needed at the same time at one time, thereby improving the work efficiency of the intelligent robot.

[0035] After the warehouse is closed, it will no longer accept archiving and borrowing requests from staff. The intelligent robot will organize the archives in the archive warehouse according to the optimization plan. The generation method of the optimization plan is as follows:

[0036] Step 1: Generate the heat intensity of each file rack, where the heat intensity refers to the average borrowing times of all files in the historical file borrowing records of the file rack;

[0037] Step 2: Sort the file racks based on their distance from the integrated file storage and retrieval machine, with closer distances leading to higher rankings. For two adjacent file racks, if the thermal intensity of the front rack is lower than that of the rear rack, and the thermal intensity ratio of the front and rear racks is less than or equal to a second threshold, swap the files in the front and rear racks according to step 3. The second threshold can be 60%-70%, and can be adjusted based on actual needs. The purpose is to not swap the front and rear racks with similar thermal intensity differences to avoid wasting resources. Alternatively, all files in the front and rear racks where the thermal intensity of the front rack is lower than that of the rear rack can be swapped.

[0038] Step 3: Sort the files in the front and rear file racks by the number of borrowings, and swap the file with the most borrowings in the rear file rack with the file with the least borrowings in the front file rack. After each swap, new files with the most and least borrowings will appear. Repeat step 3 until the heat intensity of the front file rack is higher than that of the rear file rack.

[0039] This embodiment ensures that the heat intensity of the front file shelf is higher than that of the rear file shelf by swapping the files in the front and rear file shelves, thereby preventing files that have been stored historically but are no longer borrowed from gradually occupying the nearest file location, causing the intelligent robot to be able to retrieve and archive files at locations farther and farther away from the file storage and retrieval machine, thereby improving the efficiency of file borrowing and archiving.

[0040] Step 4: Sort the borrowing times of the archives in the archives warehouse and find the archives whose borrowing times ranking ratio is less than or equal to the third threshold. These are called popular archives. The third threshold can be 20%-30%, and can also be adjusted according to actual needs. If you want to optimize more popular archives, you should increase the ratio of the third threshold. Assuming the third threshold is 20%, and there are 100 archives in the archives warehouse, the popular archives are the top 20 archives in terms of borrowing times.

[0041] Step 5: Sort the files borrowed at the same time as the popular files in the historical file borrowing records by the number of simultaneous borrowings, and find the files whose corresponding ratio of the number of simultaneous borrowings is less than or equal to the fourth threshold, and use them as the second associated files; the fourth threshold can be 20%-30%, and can also be adjusted according to actual needs. If you want to optimize more second associated files, you should increase the ratio of the fourth threshold; assuming that the fourth threshold can be 20%, and there are 20 popular files, then the second associated files are the files with the top 4 simultaneous borrowings with the corresponding popular files;

[0042] At the same time, the more times the second associated file is borrowed, the stronger the association relationship is. The association relationship is equal to the weight of the edge of the previously established file relationship spectrum, which can be directly obtained from the spectrum or by directly reading the historical borrowing records.

[0043] Step 6: When the popular file and the corresponding second associated file are not on the same file shelf or the same channel file shelf, determine whether to move the second associated file to the file shelf of the popular file or an empty file location on the same channel file shelf according to the following method:

[0044] S6-1, searching for empty file slots on the same file rack or file rack on the same channel closest to the popular file, where the number of empty file slots is equal to the number of the second associated files;

[0045] S6-2: Based on the principle of moving the second-related file with a stronger association with the popular file to an empty file location on the same file shelf or the same channel file shelf that is closer to the popular file, simulate moving the second-related file to the corresponding empty file location and calculate the sum of the file retrieval costs before and after the move:

[0046] Before moving, the cost of fetching the file is Q1=∑e i *s i1 ,

[0047] After moving, the cost of retrieving the file is Q2=∑e i *s i2 ,

[0048] Where, e i is the number of times the i-th second-related file and the corresponding popular file are borrowed at the same time; s i1 is the distance between the i-th second associated file and the corresponding popular file before moving the second associated file; s i2 is the distance between the i-th second-related file and the corresponding popular file after the second-related file is moved; 0<i≤number of second-related files;

[0049] Assuming there are 20 popular profiles, each popular profile has 4 second-related profiles. Take one of the popular profiles and its second-related profile as an example;

[0050] Assume that the number of simultaneous borrowings of the second associated file is 10, 8, and 5 respectively; before simulating the movement of the second associated file, the distances between the second associated file and the corresponding popular file are 3, 5, and 7 respectively, so the retrieval cost and Q1 are 105; after simulating the movement of the second associated file, the distances between the second associated file and the corresponding popular file are 1, 8, and 4 respectively, so the retrieval cost and Q2 are 94;

[0051] S6-3, if Q2 < Q1, then the second associated file with a stronger association with the popular file is moved to an empty file location on the same file shelf or file shelf in the same channel that is closer to the popular file; otherwise, it is not moved. In this embodiment, if Q2 < Q1, the second associated file should be moved to the corresponding empty file location.

[0052] This embodiment moves the associated files of the popular files to the file rack of the popular files or the empty file position of the file rack in the same channel, so that the intelligent robot can take away the files that are associated and likely to be needed at the same time at one time, thereby improving work efficiency; and the second associated file is only moved when the file retrieval gain is obtained, avoiding excessive adjustment and waste of resources.

[0053] Step 7: Loop through steps 1 to 6 until no more files need to be moved. The intelligent robot organizes the files in the archive warehouse according to the optimization plan determined by steps 1 to 7.

[0054] This embodiment effectively avoids the loss of intelligent robots due to blind decision-making through this scientific process of simulation first and then execution.

Claims

1. A method for intelligent archiving of archives in an unmanned power archive warehouse, comprising the following steps: The intelligent robot retrieves archived files from the storage and retrieval machine; Analyze archived files and find the optimized archive location. The intelligent robot will store the archived files in the designated overhead archive location according to the archive location; Among them, the method to find the optimized archive location is: Find the first associated file of the archived file; the first associated file refers to the archived file in the historical archive borrowing record that was borrowed at the same time as the archived file and the corresponding ratio of the number of simultaneous borrowings is less than or equal to the first threshold; Calculate the retrieval cost of the nearest empty file location next to each first associated file in turn. Fetch cost = e*s, Where, e is the number of times the archived file and the first associated file are borrowed at the same time; s is the distance between the empty file slot and the first associated file; Select the empty file location with the lowest retrieval cost as the optimized archive location.

2. The intelligent archiving method for an unmanned power archive warehouse according to claim 1, characterized in that: After the warehouse is closed, the intelligent robot organizes the archives in the archive warehouse according to the optimization plan. The method for generating the optimization plan is as follows: Step 1: Generate the heat intensity of each file rack, where the heat intensity refers to the average borrowing times of all files in the historical file borrowing records of the file rack; Step 2: Sort the files based on their distance from the file storage and access machine, with the closer the distance, the higher the ranking. For two adjacent file racks, if the thermal intensity of the front rack is lower than that of the rear rack, and the thermal intensity ratio of the front and rear racks is less than or equal to a second threshold, swap the files in the front and rear racks according to Step 3. Step 3: sort the files in the front and back file racks by the number of borrowings, and swap the file with the most borrowings in the back file rack with the file with the least borrowings in the front file rack; Repeat step 3 until the heat intensity of the front file rack after adjustment is higher than that of the rear file rack; Step 4: Sort the borrowing times of the archives in the archive warehouse and find the archives whose borrowing times ranking ratio is less than or equal to the third threshold, which are called popular archives; Step 5: Sort the files borrowed at the same time as the popular file in the historical file borrowing records by the number of simultaneous borrowings, and find the files whose corresponding ratio of the number of simultaneous borrowings is less than or equal to the fourth threshold value as the second associated files; the second associated files with more simultaneous borrowings have a stronger association with the popular file; Step 6: When the popular file and the corresponding second associated file are not on the same file shelf or the same channel file shelf, determine whether to move the second associated file to an empty file location on the same file shelf or the same channel file shelf as the popular file using the following method: S6-1, searching for empty file slots on the same file rack or file rack on the same channel closest to the popular file, where the number of empty file slots is equal to the number of the second associated files; S6-2: Based on the principle of moving the second-related file with a stronger association with the popular file to an empty file location on the same file shelf or the same channel file shelf that is closer to the popular file, simulate moving the second-related file to the corresponding empty file location and calculate the sum of the file retrieval costs before and after the move: Before moving, the cost of fetching the file is Q1=∑e i *s i1 , After moving, the cost of retrieving the file is Q2=∑e i *s i2 , Where, e i is the number of times the i-th second-related file and the corresponding popular file are borrowed at the same time; s i1 is the distance between the ith second associated file and the corresponding popular file before the second associated file is moved; si2 is the distance between the ith second associated file and the corresponding popular file after the second associated file is moved; 0<i≤number of second associated files; S6-3, if Q2 < Q1, then move the second associated file with a stronger association with the popular file to an empty file position on the same file rack or file rack in the same channel that is closer to the popular file; otherwise, do not move it; Step 7: Repeat steps 1 to 6 until no more files need to be moved.

3. The intelligent archiving method for an unmanned power archive warehouse according to claim 2, characterized in that: When calculating the retrieval cost, the distance between the empty file slot and the first associated file is calculated using the Euclidean distance; the distance between the second associated file and the corresponding popular file is calculated using the Euclidean distance.

4. The intelligent archiving method for an unmanned power archive warehouse according to claim 1, characterized in that: The first threshold is 20%-40%.

5. The intelligent archiving method for an unmanned power archive warehouse according to claim 2, characterized in that: The second threshold is 60%-70%.

6. The intelligent archiving method for an unmanned power archive warehouse according to claim 2, characterized in that: The third threshold is 20%-30%.

7. The intelligent archiving method for an unmanned power archive warehouse according to claim 2, characterized in that: The fourth threshold is 20%-30%.

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