Intelligent archive archiving method for electric unattended archive repository

Abstract

The invention relates to the technical field of storehouse archive management, in particular to an intelligent archive archiving method for an electric unattended archive storehouse, which comprises the following steps: an intelligent robot takes out archived archives from a storehouse of an archive access all-in-one machine; the archived archives are analyzed, optimized archiving positions are found, and the intelligent robot stores the archived archives in specified archive overhead archive positions according to the archive positions; the method for searching the optimized archiving position comprises the following steps of: searching a first associated archive of an archived archive; the first associated file refers to an in-library file which is borrowed at the same time with the archived file in the historical file borrowing record, and the proportion corresponding to the ranking of the simultaneous borrowing times is less than or equal to a first threshold value; and the file taking cost of the nearest empty file position beside each first associated file is calculated in sequence, and the empty file position with the minimum file taking cost is selected as the optimized archiving position. The intelligent robot can prevent files which are not borrowed by people from occupying convenient positions as much as possible, and the working efficiency of the intelligent robot is improved.

Description

Technical Field

[0001] The invention relates to an intelligent archive method for an electric power unattended 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 realizes intelligent monitoring of the archive warehouse environment, automatic storage and intelligent management of archives, as well as remote monitoring and alarm functions through the integration of smart devices, Internet of Things technology, big data analysis and artificial intelligence algorithms.

[0003] Common unattended power 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 archive warehouse of the power industry is as follows: the staff performs identity authentication through the archive storage and retrieval machine; the archive warehouse management system performs identity authentication and obtains the list of archives borrowed by the staff; the staff selects the list of archives that need to be borrowed and returned; the archive storage and retrieval machine opens the corresponding number of warehouse doors; the staff puts the archives to be archived into the storage and retrieval warehouse and closes the warehouse door; the archive storage and retrieval machine automatically identifies the RFID tag attached to the archive through RFID (radio frequency identification) technology, which stores detailed information of the archive, such as archive number, name, category, storage time, etc., 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, puts them into the storage and retrieval warehouse, and the staff takes out the archives; the intelligent robot stores the stored archives in the nearest intelligent dense overhead space.

[0005] The above-mentioned unmanned power 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 archived in the nearest place, archives that have been stored historically but are no longer borrowed gradually occupy the position of the nearest archive compact shelving, resulting in the intelligent robot being able to retrieve and archive files at locations farther and farther away from the archive storage and retrieval machine, 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 unattended 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 unattended power archive warehouse, comprising the following steps: The intelligent robot takes out the archived files from the storage room of the archive storage and retrieval machine; Analyze archived files and find the optimized archive location. The intelligent robot will store the archived files in the designated archive overhead file location according to the file location; Among them, the method of finding the optimized save 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, which is borrowed at the same time as the archived file and the proportion corresponding to the ranking of the number of simultaneous borrowings is ≤ the first threshold; Calculate the retrieval cost of the nearest empty file slot 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 archived file and the first associated file; Select the empty file location with the lowest retrieval cost as the optimized archive location.

[0008] The present invention finds out several related files that are 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 retrieval cost, thereby avoiding the situation where the archived files that no one has borrowed gradually occupy the nearest file rack. At the same time, the association relationship between the 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 work efficiency of the intelligent robot. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] The present invention will be further described below in conjunction with the accompanying drawings.

[0010] Figure 1 This is a schematic diagram of the unmanned power archive warehouse.

[0011] Figure 2 It is the file coordinate design Figure 1 .

[0012] Figure 3 It is the file coordinate design Figure 2 . DETAILED DESCRIPTION

[0013] This embodiment shows a method for intelligent archiving of archives in an unattended power archive warehouse, comprising the following steps: The staff member performs identity authentication through the archive storage and retrieval machine; the archive warehouse management system performs identity authentication and obtains the list of files borrowed by the staff member; the staff member selects the list of files that need to be borrowed and returned; the archive storage and retrieval machine opens the corresponding number of doors; the staff member puts the files to be archived into the storage and retrieval bin and closes the door; the archive storage and retrieval machine automatically identifies the RFID tag attached to the file through RFID (radio frequency identification) technology. The tag stores detailed information of the file, such as file number, name, category, storage time, etc., to complete the verification of the file; the intelligent robot takes out the files that need to be borrowed from the corresponding bin one by one, puts them into the storage and retrieval 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 retrieval machine.

[0014] Next, the archive files are analyzed to find the optimized archive location. The intelligent robot stores the archive files in the designated archive overhead file location according to the file location: Among them, the method for obtaining the file position coordinates can be based on the intelligent robot access movement time to perform Cartesian coordinate system mapping, such as Figure 2 , 3 As shown, with the position of the integrated file storage and retrieval machine as the origin, the direction of the file racks 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 racks in the same row is d (greater than 1 and less than 10); the direction of the file racks 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 file racks in adjacent channels (or file racks in adjacent rooms) are configured with a coordinate deviation of D (greater than 100) according to the distance; the height direction of the file rack is determined as the Z-axis; and a Cartesian coordinate system is established.

[0015] Among them, the method of finding the optimized save location is: Find the first associated file of the archived file; the first associated file refers to the in-library file in the historical archive borrowing record, which is 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.

[0016] 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 the historical borrowing records to obtain the data on the number of archive borrowings and the number of simultaneous borrowings.

[0017] 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 file, rank these files according to the number of simultaneous borrowings, and find the top 3 files in the library with the top number of simultaneous borrowings as the first associated files.

[0018] Calculate the retrieval cost of the nearest empty file slot 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 archived file and the first associated file; 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; 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.

[0019] This embodiment finds out several related files that are 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 archived file cost, thereby avoiding the situation where archived files that no one has borrowed 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.

[0020] After the warehouse is closed, it will no longer accept the archiving and borrowing needs of the staff. The intelligent robot will sort the archives in the archive warehouse according to the optimization plan. The generation method of 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 in the file rack; Step 2: Sort the files according to the distance between the file rack and the file storage and retrieval machine. The closer the distance, the higher the ranking. For two adjacent file racks, if the thermal intensity of the front file rack is lower than that of the rear file rack, and the thermal intensity ratio of the front and rear file racks is ≤ the second threshold, the files in the front and rear file racks are swapped according to step 3. The second threshold can be 60%-70%, and can also be adjusted according to actual needs. The purpose is not to adjust the front and rear file racks with similar thermal intensity to avoid waste of resources. Alternatively, the files in the front and rear file racks with thermal intensity lower than that of the rear file rack can be adjusted. Step 3, sorting the files in the front and rear file racks according to the number of borrowings, and swapping the files with the most borrowings in the rear file rack with the files with the least borrowings in the front file rack; after each swap, new files with the most and least borrowings will appear, and step 3 will be executed repeatedly, and the swapping will continue until the heat intensity of the front file rack after the swap is higher than that of the rear file rack; 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 position, 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.

[0021] Step 4: Sort the borrowing times of the archives in the archive warehouse, and find the archives whose proportion corresponding to the borrowing times ranking is ≤ the third threshold, which 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 proportion of the third threshold; assuming that the third threshold is 20%, there are 100 archives in the archive warehouse, then the popular archives are the top 20 archives in terms of borrowing times; Step 5: Sort the archives borrowed at the same time as the popular archives in the historical archive borrowing records by the number of simultaneous borrowings, and find the archives whose proportion corresponding to the ranking of the number of simultaneous borrowings is ≤ the fourth threshold value as the second associated archives; the fourth threshold value can be 20%-30%, and can also be adjusted according to actual needs. If you want to optimize more second associated archives, you should increase the proportion of the fourth threshold value; assuming that the fourth threshold value can be 20%, and there are 20 popular archives, then the second associated archives are the top 4 archives with the number of simultaneous borrowings of the corresponding popular archives; 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; Step 6: When the popular file and the corresponding second associated file are not in the same file rack or the same channel file rack, determine whether to move the second associated file to the file rack of the popular file or an empty file position of the file rack in the same channel according to the following method: S6-1, searching for empty file positions on the same file rack or file rack on the same channel closest to the popular file, the number of empty file positions being equal to the number of the second associated files; S6-2, according to the principle of moving the second associated file with a stronger association with the popular file to an empty file position on the same file rack or the same channel file rack that is closer to the popular file, simulate moving the second associated file to the corresponding empty file position, and calculate the file retrieval cost before and after the move: Before moving, the fetch cost and Q1=∑e i *s i1 , After moving, the cost of fetching the file is Q2=∑e i *s i2 , In the formula, e iis the number of times the i-th second associated 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; s i2 is the distance between the i-th second associated file and the corresponding popular file after the second associated file is moved; 0<i≤number of second associated files; Assuming that there are 20 popular files, each popular file has 4 second-related files. Take one of the popular files and its second-related files as an example; 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, then 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, then the retrieval cost and Q2 are 94; S6-3, if Q2<Q1, then the second associated file with a stronger association with the popular file is moved to an empty file position on the same file rack or the same channel file rack 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 position.

[0022] 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 have a high probability of being 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 causing waste of resources.

[0023] Step seven, loop through steps one to six until no more files need to be moved, and the intelligent robot organizes the files in the archive warehouse according to the optimization plan determined by steps one to seven.

[0024] This embodiment effectively avoids the loss of intelligent robots due to blind decision-making through the scientific process of simulation first and then execution.

Claims

1. An intelligent archiving method for archives in an unattended power archive warehouse, comprising the following steps: The intelligent robot takes out the archived files from the storage room of the archive storage and retrieval machine; Analyze archived files and find the optimized archive location. The intelligent robot will store the archived files in the designated archive overhead file location according to the file location; Among them, the method of finding the optimized save 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, which is borrowed at the same time as the archived file and the proportion corresponding to the ranking of the number of simultaneous borrowings is ≤ the first threshold; Calculate the retrieval cost of the nearest empty file slot 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 archived file 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 electric power unattended 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 generation method of 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 in the file rack; Step 2: Sort the files according to the distance between the file rack and the file storage and retrieval machine. The closer the distance, the higher the ranking. For two adjacent file racks, if the heat intensity of the front file rack is lower than that of the rear file rack, and the heat intensity ratio of the front and rear file racks is ≤ the second threshold, the files in the front and rear file racks are swapped according to step 3. Step 3: sort the files in the front and rear file racks according to the borrowing times, and swap the file with the most borrowing times in the rear file rack with the file with the least borrowing times in the front file rack; Execute step 3 repeatedly until the heat intensity of the front file rack after adjustment is higher than the heat intensity of the rear file rack; Step 4: Sort the borrowing times of the archives in the archive warehouse, and find the archives whose proportion corresponding to the ranking of borrowing times is ≤ the third threshold, which are called popular archives; Step 5: sort the archives borrowed at the same time as the popular archive in the historical archive borrowing records by the number of simultaneous borrowings, and find the archives whose proportion corresponding to the ranking of the number of simultaneous borrowings is ≤ the fourth threshold value as the second associated archives; the second associated archives with more simultaneous borrowings have a stronger association with the popular archives; Step 6: When the popular file and the corresponding second associated file are not on the same file rack or the same channel file rack, determine whether to move the second associated file to an empty file position on the same file rack or the same channel file rack as the popular file by the following method: S6-1, searching for empty file positions on the same file rack or file rack on the same channel closest to the popular file, the number of empty file positions being equal to the number of the second associated files; S6-2, according to the principle of moving the second associated file with a stronger association with the popular file to an empty file position on the same file rack or the same channel file rack that is closer to the popular file, simulate moving the second associated file to the corresponding empty file position, and calculate the file retrieval cost before and after the move: Before moving, the fetch cost and Q1=∑e i *s i1 , After moving, the cost of fetching the file is Q2=∑e i *s i2 , In the formula, e i is the number of times the i-th second associated 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 the second associated file with a stronger association with the popular file is moved to an empty file position on the same file rack or file rack on the same channel that is closer to the popular file, otherwise it is not moved; Step 7: Repeat steps 1 to 6 until no more files need to be moved.

3. The intelligent archiving method for archives in an unattended power archive warehouse according to claim 1 or 2, characterized in that: When calculating the retrieval cost, the distance between the archived file and the first associated file adopts the Euclidean distance; the distance between the second associated file and the corresponding popular file adopts the Euclidean distance.

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

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

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

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

Images