An intelligent warehousing supervision system and method based on intelligent transformation and data analysis

Abstract

The present invention relates to the field of warehouse supervision technology, and specifically to an intelligent warehouse supervision system and method based on intelligent transformation and digital data analysis, including: a warehouse item supervision module, a supervision information collection module, a data management center, a target equipment screening module and an equipment adjustment management module. The warehouse item supervision module is used to monitor the flow status of goods in the warehouse in real time and conduct information sharing and interaction. The supervision information collection module is used to collect equipment information and historical supervision information used for goods supervision. The data management center stores and manages all collected data. The target equipment screening module is used to analyze the reasonable installation coefficients of different equipment and screen out equipment to be adjusted. The equipment to be adjusted is replaced through the equipment adjustment management module, and the improperly selected reading equipment is promptly replaced with equipment with a suitable working frequency, thereby reducing unnecessary supervision costs while ensuring maximum coverage and capture of goods information and warehouse supervision efficiency.

Description

Technical Field

[0001] The present invention relates to the field of warehouse supervision technology, and specifically to an intelligent warehouse supervision system and method based on smart transformation and digital data analysis. Background Art

[0002] With the development of the logistics industry and the continuous advancement of automation technology, the warehouse supervision system has become an important means for enterprises to improve efficiency and reduce costs. RFID technology, as a wireless communication technology, has the characteristics of real-time, high efficiency and automation. It is widely used in warehouse supervision in the logistics field. It can realize the automatic storage, outbound and positioning of goods, reduce the errors and time costs of manual operations, and can also be seamlessly connected with other information systems to achieve data sharing and management integration.

[0003] When using RFID reading devices for warehouse supervision, for fixed RFID reading devices in the warehouse, relevant personnel or machines are required to transport the goods to the identification range of the reading device in order to successfully identify the goods information. In order to cover and capture the goods' inbound, outbound and location information to the greatest extent, it is necessary to select RFID reading devices with appropriate working frequencies to reduce the probability of missed goods identification. If the reading device is improperly selected, for example, an RFID reading device with too high a working frequency is selected, it is easy to have the problem that although the goods label identification is not missed, the warehouse supervision cost will increase unnecessarily. The existing technology does not require timely replacement of improperly selected RFID reading devices to reduce unnecessary warehouse supervision costs.

[0004] Therefore, people need an intelligent warehousing supervision system and method based on intelligent transformation and digital data analysis to solve the above problems. Summary of the invention

[0005] The purpose of the present invention is to provide an intelligent warehousing supervision system and method based on intelligent transformation and digital data analysis to solve the problems raised in the above background technology.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: an intelligent warehouse supervision system based on intelligent transformation and data analysis, the system comprising: a warehouse goods supervision module, a supervision information collection module, a data management center, a target equipment screening module and an equipment adjustment management module;

[0007] The output end of the storage goods supervision module is connected to the input end of the supervision information collection module, the output end of the supervision information collection module is connected to the input end of the data management center, the output end of the data management center is connected to the input end of the target device screening module, and the output end of the target device screening module is connected to the input end of the device adjustment management module;

[0008] The storage goods supervision module monitors the flow status of goods in the warehouse in real time and interacts with the supervision terminal through information communication;

[0009] Collecting equipment information and historical supervision information used for goods supervision through the supervision information collection module, and transmitting all collected data to the data management center;

[0010] Storing and managing all collected data through the data management center;

[0011] The target equipment screening module retrieves and analyzes the equipment information and historical supervision information of cargo supervision, analyzes the reasonable installation coefficients of different equipment and screens out the equipment to be adjusted;

[0012] The device adjustment management module replaces the device to be adjusted with a device with the best operating frequency;

[0013] The equipment used for cargo supervision refers to an RFID reading equipment.

[0014] Furthermore, the storage goods supervision module includes a goods label recognition unit, an in-and-out warehouse information collection unit, and a goods information communication unit;

[0015] The output end of the cargo label identification unit is connected to the input end of the in-and-out information collection unit, and the output end of the in-and-out information collection unit is connected to the input end of the cargo information communication unit;

[0016] The cargo tag identification unit uses an RFID reader to identify cargo tags in the warehouse, and obtains information about the cargo in and out of the warehouse, as well as the location of the cargo in the warehouse. The RFID reader is a fixed RFID reader / writer installed in different areas of the warehouse.

[0017] The in-warehouse and out-warehouse information collection unit collects the in-warehouse and out-warehouse information of the goods and the location information in the warehouse from the identification results;

[0018] The collected cargo information is transmitted to the supervision terminal through the cargo information communication unit.

[0019] Further, the supervision information collection module includes a device information collection unit and an identification data collection unit;

[0020] The input end of the equipment information collection unit is connected to the output end of the cargo information transmission unit, and the output ends of the equipment information collection unit and the identification data collection unit are connected to the input end of the data management center;

[0021] The device information collection unit collects the working frequency of the RFID reading devices installed in different areas of the warehouse and the farthest recognition distance of the devices;

[0022] A distance sensor is installed at the location where the RFID reading device is installed through the identification data collection unit, and the distance sensor is used to collect the straight-line distance information between the RFID reading devices installed in different areas and the successfully identified goods when the goods were previously identified.

[0023] Further, the target device screening module includes an installation rationality analysis unit and a to-be-adjusted device screening unit;

[0024] The input end of the installation rationality analysis unit is connected to the output end of the data management center, and the output end of the installation rationality analysis unit is connected to the input end of the device screening unit to be adjusted;

[0025] The installation rationality analysis unit retrieves the straight-line distance information between the RFID reading devices installed in different areas and the successfully identified goods when the goods were previously identified, and analyzes the installation rationality coefficients of the RFID reading devices in different areas based on the retrieved data;

[0026] The device to be adjusted screening unit compares the installation rationality coefficients of the RFID reading devices in different areas, and screens out the devices that need to be replaced and adjusted as the devices to be adjusted.

[0027] Further, the equipment adjustment management module includes a supervision information analysis unit and a reading equipment adjustment unit;

[0028] The input end of the supervision information analysis unit is connected to the output end of the device screening unit to be adjusted, and the output end of the supervision information analysis unit is connected to the input end of the reading device adjustment unit;

[0029] Establishing an operating frequency analysis model through the supervision information analysis unit to analyze the optimal operating frequency of the equipment in the area where the screened equipment to be adjusted is located;

[0030] The device to be adjusted is replaced with an RFID reading device with an optimal operating frequency through the reading device adjustment unit.

[0031] An intelligent warehousing supervision method based on intelligent transformation and data analysis includes the following steps:

[0032] Z1: Monitor the flow status of goods in the warehouse in real time and communicate with the monitoring terminal;

[0033] Z2: Collect equipment information and historical supervision information used for cargo supervision;

[0034] Z3: retrieve and analyze the equipment information and historical supervision information of cargo supervision, and analyze the reasonable installation coefficient of different equipment;

[0035] Z4: Compare the installation rationality coefficients of different equipment and select the equipment to be adjusted based on the comparison results;

[0036] Z5: Replace the equipment to be adjusted.

[0037] Furthermore, in step Z1: the RFID reading device is used to identify the cargo tags in the warehouse, obtain the cargo information of the cargo in the warehouse, the cargo information of the cargo in the warehouse, and the cargo information in the warehouse, transmit the obtained cargo information to the supervision terminal, and communicate and interact with the supervision terminal;

[0038] Smart transformation refers to the investment in hardware transformation: enterprises have achieved "machine replacement" through equipment upgrades and intelligent transformation of production lines, and used RFID reading equipment instead of manual labor for warehouse supervision, realizing "machine replacement", that is, the function of smart transformation. At the same time, the wireless communication technology of RFID reading equipment is used to share the identified cargo information with the supervision terminal in real time, which is conducive to the supervision terminal to grasp the cargo information in real time, discover cargo abnormalities in time and take relevant measures to solve the abnormal problems, thereby improving the safety of stored goods.

[0039] Furthermore, in step Z2: the set of working frequencies of the RFID reading devices installed in different areas of the warehouse is collected as W = {W1, W2, ..., W m}, the longest identification distance set of the corresponding RFID reading device is d = {d1, d2, ..., d m}, where m represents the number of RFID readers installed in the warehouse. Distance sensors are installed at the locations where the RFID readers are installed. The distance sensors are used to collect the straight-line distance information between the RFID readers installed in different areas and the successfully identified goods when they were previously identified.

[0040] Further, in step Z3: the set of straight-line distances between the RFID reading device installed in a random area and the successfully identified goods in the past f times by reading the goods tags is retrieved as D = {D1, D2, ..., D f}, the maximum recognition distance of the corresponding reading device is d i , d i ∈d, calculate the installation rationality coefficient P of the RFID reading device installed in a random area according to the following formula i :

[0041]

[0042] Among them, D jIt represents the straight-line distance between an RFID reader installed in a random area and the successfully identified goods when it reads the goods tag for the jth time in the past. The installation rationality coefficient of all RFID readers is calculated in the same way;

[0043] The historical data of goods identification by RFID readers installed in different areas of the warehouse are collected through big data technology: the distance data between the goods and the reading device when the goods were successfully identified in the past is used to analyze the installation rationality coefficient of the RFID reading devices installed in different areas. When analyzing the installation rationality coefficient, the reference factor is not only the difference between the farthest identification distance of the corresponding reading device and the actual distance when reading, but also the stability of the historical distance data obtained is considered. The larger the distance difference, the closer the interval between the goods label and the reading device is when the corresponding area identifies the goods, the higher the probability that the corresponding device can successfully identify the goods in the corresponding area by adjusting the corresponding device to a device with a lower working frequency, and the more unreasonable the reading device currently installed in the corresponding area is. Combined with the analysis of the stability of the historical distance data, the smaller the actual distance difference during reading, the more concentrated and stable the distance between the corresponding area and the device when identifying the goods, the lower the probability that the distance between the goods and the device is suddenly very far when a certain product is identified, the higher the probability that the corresponding device can successfully identify the goods in the corresponding area by adjusting the corresponding device to a device with a lower working frequency, and the more unreasonable the reading device currently installed in the corresponding area is. The above two factors are considered and analyzed to consider the installation rationality coefficient of the RFID reading devices installed in different areas, which improves the rationality of the subsequent screening of the equipment to be adjusted.

[0044] Furthermore, in step Z4: compare the installation rationality coefficients of all RFID reading devices, arrange the m devices in ascending order of the installation rationality coefficient and divide them into e categories, wherein the installation rationality coefficients of all devices in the former category are smaller than those in the latter category, and obtain a random classification result, the average value set of the installation rationality coefficients of a random class of devices in class e is Q = {Q1, Q2, ..., Q e}, according to the formula Calculate the screening reference coefficient F of a random classification result, where Q c Indicates the average value of the installation rationality coefficient of the c-th device in the e-th category in a random classification result, calculates the screening reference coefficients of different classification results in the same way, compares the screening reference coefficients, selects the classification result with the highest screening reference coefficient, and selects the RFID reading device in the first category from the selected classification results as the device to be adjusted;

[0045] In order to accurately and centrally screen out the equipment to be adjusted, after analyzing the installation rationality coefficient of each equipment, the equipment is classified according to the installation rationality coefficient. The classification results are selected by calculating the differences in the installation rationality coefficients between various types of equipment in different classification results. The greater the difference, the greater the reference value of the classification result for the screening of the equipment to be adjusted. The installation rationality data obtained is classified to maximize the data reference value, realizing the function of data conversion, and at the same time is conducive to accurately and centrally screening out the equipment to be adjusted with a relatively small installation rationality coefficient.

[0046] Further, in step Z5: the linear distance set between a random device among all the remaining devices except the device to be adjusted and the successfully identified goods in the past f times of identifying goods is L = {L1, L2, ..., L f}, calculate the average recognition distance of the corresponding device in the past Among them, L j It represents the straight-line distance between the corresponding device and the successfully identified goods when it identified the goods for the jth time in the past. The mean set of identification distances of all devices except the device to be adjusted is calculated in the same way: Where n represents the number of all remaining devices except the device to be adjusted, and the set of working frequencies of all remaining devices is w = {w1, w2, ..., w n}, The data points Perform straight line fitting to establish the working frequency analysis model: Y = γ1*X + γ2, where X represents the independent variable of the working frequency analysis model, Y represents the dependent variable, γ1 represents the bias, and γ2 represents the intercept. Solve γ1 and γ2 according to the following formulas:

[0047]

[0048]

[0049] in, represents the mean recognition distance of the bth device except the device to be adjusted, w bIndicates the working frequency of the remaining b-th device, obtains the straight-line distance between a random device to be adjusted and the successfully identified goods in the past, and obtains the mean of the identification distance of the corresponding device to be adjusted by summing the straight-line distance and dividing it by the number of identifications, and substitutes K into the working frequency analysis model: Let X = K, and obtain the optimal working frequency of the RFID reading device that should be installed in the area where the corresponding device to be adjusted is γ1*K+γ2, and replace the corresponding device to be adjusted with an RFID reading device with a working frequency of γ1*X+γ2. Perform the same replacement on the remaining devices to be adjusted, and replace the remaining devices to be adjusted with the RFID reading device with the optimal working frequency that should be installed in the area where the corresponding device is located;

[0050] In addition to the screened equipment, the installation of the remaining equipment is more reasonable and the working frequency is more appropriate. The working frequency analysis model is established with reference to the remaining equipment data. When each device to be adjusted is used to identify goods, the distance data between the goods and the equipment is substituted into the working frequency analysis model to obtain the optimal working frequency, and the equipment to be adjusted in the corresponding area is replaced with the equipment with the optimal working frequency. Improperly selected RFID reading equipment needs to be replaced in time, which reduces unnecessary warehousing supervision costs while ensuring maximum coverage, capture of goods information and warehousing supervision efficiency.

[0051] Compared with the prior art, the beneficial effects achieved by the present invention are:

[0052] The present invention uses RFID reading equipment to replace manual work for warehouse supervision, realizing the function of "machine replacement", that is, intelligent transformation. At the same time, the wireless communication technology of the RFID reading equipment is used to share the identified cargo information with the supervision terminal in real time, which is conducive to the supervision terminal to grasp the cargo information in real time and timely discover cargo abnormalities and take relevant measures to solve the abnormal problems, thereby improving the safety of stored cargo;

[0053] The historical data of goods identification by RFID readers installed in different areas of the warehouse is collected through big data technology: the distance data between the goods and the reading device when the goods were successfully identified in the past is used to analyze the installation rationality coefficient of the RFID reading devices installed in different areas. When analyzing the installation rationality coefficient, the reference factor is not only the difference between the farthest identification distance of the corresponding reading device and the actual distance when reading, but also the stability of the acquired historical distance data is considered, which improves the rationality of the subsequent selection of the equipment to be adjusted based on the installation rationality coefficient;

[0054] After analyzing the installation rationality coefficient of each device, the equipment is classified according to the installation rationality coefficient. The classification results are selected by calculating the differences in the installation rationality coefficients of various types of equipment in different classification results. The installation rationality data obtained is classified to maximize the data reference value, realizing the function of data conversion, and at the same time, it is conducive to accurately and centrally screening out the equipment to be adjusted with a small installation rationality coefficient;

[0055] The working frequency analysis model is established with reference to the remaining equipment data. When each device to be adjusted is used for cargo identification, the distance data between the cargo and the device is substituted into the working frequency analysis model to obtain the optimal working frequency. The devices to be adjusted in the corresponding area are replaced with devices with the optimal working frequency. Improperly selected RFID reading devices need to be replaced in a timely manner, which reduces unnecessary warehousing supervision costs while ensuring maximum coverage, capture of cargo information and warehousing supervision efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0057] Figure 1 It is a structural diagram of an intelligent warehousing supervision system based on intelligent transformation and data analysis of the present invention;

[0058] Figure 2 It is a flow chart of an intelligent warehousing supervision method based on intelligent transformation and digital data analysis of the present invention. DETAILED DESCRIPTION

[0059] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0060] Combine the following Figure 1-Figure 2 The present invention is further described with reference to the accompanying drawings and specific embodiments.

[0061] Example 1: Figure 1As shown, this embodiment provides an intelligent warehouse supervision system based on intelligent transformation and digital data analysis, and the system includes: a warehouse item supervision module, a supervision information collection module, a data management center, a target equipment screening module and an equipment adjustment management module. The warehouse item supervision module is used to monitor the flow status of goods in the warehouse in real time and to communicate with the supervision terminal. The supervision information collection module is used to collect equipment information and historical supervision information used for goods supervision, and all collected data are transmitted to the data management center. The data management center stores and manages all collected data. The target equipment screening module is used to retrieve and analyze the equipment information and historical supervision information of goods supervision, analyzes the reasonable installation coefficients of different equipment and screens out equipment to be adjusted, and the equipment to be adjusted is replaced by the equipment adjustment management module, and the equipment to be adjusted is replaced with equipment with the optimal working frequency.

[0062] The storage goods supervision module includes a cargo label identification unit, an in-warehouse information collection unit and a cargo information communication unit. The cargo label identification unit uses an RFID reading device to identify the cargo labels in the warehouse, obtain the in-warehouse, in-warehouse and placement information of the cargo in the warehouse, and collect the in-warehouse, in-warehouse and location information of the cargo from the identification results through the in-warehouse information collection unit, and transmit the collected cargo information to the supervision terminal through the cargo information communication unit.

[0063] The supervision information collection module includes an equipment information collection unit and an identification data collection unit. The equipment information collection unit collects the working frequency of the RFID reading devices installed in different areas of the warehouse and the farthest identification distance of the devices. The identification data collection unit installs a distance sensor at the installation position of the RFID reading device. The distance sensor is used to collect the straight-line distance information between the RFID reading devices installed in different areas and the successfully identified goods when they were previously identified.

[0064] The target equipment screening module includes an installation rationality analysis unit and an equipment to be adjusted screening unit. The installation rationality analysis unit retrieves the straight-line distance information between the RFID reading devices installed in different areas and the successfully identified goods when they were previously identified. The installation rationality coefficients of the RFID reading devices in different areas are analyzed based on the retrieved data. The equipment to be adjusted screening unit compares the installation rationality coefficients of the RFID reading devices in different areas, and screens out the equipment that needs to be replaced and adjusted as the equipment to be adjusted.

[0065] The equipment adjustment management module includes a supervision information analysis unit and a reading device adjustment unit. The supervision information analysis unit is used to establish a working frequency analysis model, analyze the optimal working frequency of the equipment to be installed in the area where the screened equipment to be adjusted is located, and replace the equipment to be adjusted with an RFID reading device with the optimal working frequency through the reading device adjustment unit.

[0066] Example 2: Figure 2 As shown, this embodiment provides an intelligent warehousing supervision method based on intelligent transformation and data analysis, which is implemented based on the intelligent warehousing supervision system in the embodiment and specifically includes the following steps:

[0067] Z1: Monitor the flow status of goods in the warehouse in real time and communicate with the supervision terminal. Use RFID reading equipment to identify the goods tags in the warehouse, obtain the goods out of the warehouse, in the warehouse and the location information in the warehouse, transmit the obtained goods information to the supervision terminal, and communicate with the supervision terminal;

[0068] Z2: Collect equipment information and historical supervision information used for cargo supervision. The set of working frequencies of RFID reading devices installed in different areas of the warehouse is W = {W1, W2, ..., W m}, the longest identification distance set of the corresponding RFID reading device is d = {d1, d2, ..., d m}, where m represents the number of RFID reading devices installed in the warehouse, and distance sensors are installed at the locations where the RFID reading devices are installed. The distance sensors are used to collect the straight-line distance information between the RFID reading devices installed in different areas and the successfully identified goods when they were previously identified;

[0069] Z3: retrieve and analyze the equipment information and historical supervision information of goods supervision, analyze the installation rationality coefficients of different equipment, retrieve the linear distance set between the RFID reading device installed in a random area and the successfully identified goods when reading the goods tags for the past f times, which is D = {D1, D2, ..., D f}, the maximum recognition distance of the corresponding reading device is d i , d i ∈d, according to the formula Calculate the installation rationality coefficient P of the RFID reading device installed in a random area i ;

[0070] Among them, D j It represents the straight-line distance between an RFID reader installed in a random area and the successfully identified goods when it reads the goods tag for the jth time in the past. The installation rationality coefficient of all RFID readers is calculated in the same way;

[0071] Z4: Compare the installation rationality coefficients of different devices, select the devices to be adjusted based on the comparison results, compare the installation rationality coefficients of all RFID reading devices, arrange the m devices in order of installation rationality coefficient from small to large and divide them into e categories, where the installation rationality coefficients of all devices in the former category are smaller than those in the latter category, and obtain a random classification result. The average value set of the installation rationality coefficients of a random class of devices in class e is Q = {Q1, Q2, ..., Q e}, according to the formula Calculate the screening reference coefficient F of a random classification result, where Q c Indicates the average value of the installation rationality coefficient of the c-th device in the e-th category in a random classification result, calculates the screening reference coefficients of different classification results in the same way, compares the screening reference coefficients, selects the classification result with the highest screening reference coefficient, and selects the RFID reading device in the first category from the selected classification results as the device to be adjusted;

[0072] Z5: Replace the device to be adjusted, and retrieve a random device from all the remaining devices except the device to be adjusted. The set of straight-line distances between the device and the successfully identified goods in the past f times is L = {L1, L2, ..., L f}, calculate the average recognition distance of the corresponding device in the past Among them, L j It represents the straight-line distance between the corresponding device and the successfully identified goods when it identified the goods for the jth time in the past. The mean set of identification distances of all devices except the device to be adjusted is calculated in the same way: Where n represents the number of all remaining devices except the device to be adjusted, and the set of working frequencies of all remaining devices is w = {w1, w2, ..., w n}, The data points Perform linear fitting to establish the working frequency analysis model: Y = γ1*X+γ2, where X represents the independent variable of the working frequency analysis model, Y represents the dependent variable, γ1 represents the bias, and γ2 represents the intercept. According to the formula Solve for γ1 and γ2 respectively, where represents the mean recognition distance of the bth device except the device to be adjusted, w bIndicates the working frequency of the remaining b-th device, obtains the straight-line distance between a random device to be adjusted and the successfully identified goods in the past, and obtains the mean of the identification distance of the corresponding device to be adjusted by summing the straight-line distance and dividing it by the number of identifications, and substitutes K into the working frequency analysis model: Let X = K, and obtain the optimal working frequency of the RFID reading device that should be installed in the area where the corresponding device to be adjusted is γ1*K+γ2, and replaces the corresponding device to be adjusted with an RFID reading device with a working frequency of γ1*X+γ2;

[0073] For example: the mean set of identification distances of all devices except the device to be adjusted is obtained as follows: The unit is meter. The working frequency set of all the remaining devices is w = {w1, w2, w3, w4, w5} = {860, 865, 872, 900, 880}, and the unit is MHz. The above data points are fitted with a straight line, and the working frequency analysis model is obtained as follows: Y = γ1*X + γ2 = 34.75X + 826.75. The straight-line distance between a random device to be adjusted and the successfully identified goods in the past is obtained. The mean of the identification distance of the corresponding device to be adjusted is 2 after summing the straight-line distances and dividing by the number of identifications. Let X = 2, and the optimal working frequency of the RFID reading device that should be installed in the area where the corresponding device to be adjusted is γ1*K + γ2≈896. The corresponding device to be adjusted is replaced with an RFID reading device with a working frequency of 896 MHz.

[0074] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0075] Finally, it should be noted that the above description is only a preferred example of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An intelligent warehousing supervision method based on intelligent transformation and data analysis, characterized by: The following steps are involved: Z1: Monitor the flow status of goods in the warehouse in real time and communicate with the monitoring terminal; Z2: Collect equipment information and historical supervision information used for cargo supervision; Z3: retrieve and analyze the equipment information and historical supervision information of cargo supervision, and analyze the reasonable installation coefficient of different equipment; Z4: Compare the installation rationality coefficients of different equipment and select the equipment to be adjusted based on the comparison results; Z5: Replace the equipment to be adjusted; In step Z2: the set of working frequencies of the RFID reading devices installed in different areas of the warehouse is collected as W={W1, W2, ..., W m }, the corresponding maximum identification distance set of RFID reading devices is d={d1, d2, …, d m }, where m represents the number of RFID reading devices installed in the warehouse, and distance sensors are installed at the locations where the RFID reading devices are installed. The distance sensors are used to collect the straight-line distance information between the RFID reading devices installed in different areas and the successfully identified goods when they were previously identified; In step Z3, the linear distance set between the RFID reading device installed in a random area and the successfully identified goods in the past f times by reading the goods tags is retrieved as D={D1, D2, ..., D f }, the maximum recognition distance of the corresponding reading device is d i , d i ∈d, calculate the installation rationality coefficient P of the RFID reading device installed in a random area according to the following formula i : ； Among them, D j It represents the straight-line distance between an RFID reader installed in a random area and the successfully identified goods when it reads the goods tag for the jth time in the past. The installation rationality coefficient of all RFID readers is calculated in the same way; In step Z5: retrieve the linear distance set between a random device among all the remaining devices except the device to be adjusted and the successfully identified goods in the past f times of identifying goods, which is L={L1, L2, ..., L f }, calculate the average recognition distance of the corresponding device in the past , , where L j It represents the straight-line distance between the corresponding device and the successfully identified goods when it identified the goods for the jth time in the past. The mean set of identification distances of all devices except the device to be adjusted is calculated in the same way: ={ , , …, }, where n represents the number of all remaining devices except the device to be adjusted, and the set of working frequencies of all remaining devices is w={w1, w2, …, w n }, w⊂W, the data point {( , w1), ( ,w2),…,( , w n )} Perform straight line fitting and establish a working frequency analysis model: , where X represents the independent variable of the working frequency analysis model, and Y represents the dependent variable. Indicates bias, Represents the intercept, and is solved according to the following formulas and : ； ； in, Indicates the average recognition distance of the bth device except the device to be adjusted. Represents the working frequency of the remaining b-th device, obtains the straight-line distance between a random device to be adjusted and the successfully identified goods in the past, and obtains the mean of the identification distance of the corresponding device to be adjusted by summing the straight-line distance and dividing it by the number of identifications. Substitute K into the working frequency analysis model: Let X=K, and the optimal working frequency of the RFID reading device that should be installed in the area where the corresponding device to be adjusted is obtained. , replace the corresponding device to be adjusted with one with an operating frequency of RFID reading device.

2. According to claim 1, the intelligent warehousing supervision method based on intelligent transformation and digital transformation data analysis is characterized by: In step Z1: use RFID reading equipment to identify the cargo labels in the warehouse, obtain the cargo information of the cargo in the warehouse, the cargo information in the warehouse and the cargo location in the warehouse, transmit the acquired cargo information to the supervision terminal, and communicate and interact with the supervision terminal.

3. According to claim 1, the intelligent warehousing supervision method based on intelligent transformation and digital transformation data analysis is characterized by: In step Z4: compare the installation rationality coefficients of all RFID reading devices, arrange the m devices in order of installation rationality coefficient from small to large and divide them into e categories, where the installation rationality coefficients of all devices in the former category are smaller than those in the latter category, and obtain a random classification result. The average value set of the installation rationality coefficients of a random class of devices in class e is Q={Q1, Q2, …, Q e }, according to the formula Calculate the screening reference coefficient F of a random classification result, where Q c It represents the average value of the installation rationality coefficient of the C-th type equipment in the E-th type in a random classification result. The screening reference coefficients of different classification results are calculated in the same way. The screening reference coefficients are compared, and the classification result with the highest screening reference coefficient is selected. The RFID reading device in the first category is selected from the selected classification results as the device to be adjusted.

4. An intelligent warehouse supervision system based on intelligent transformation and digital data analysis, applied to an intelligent warehouse supervision method based on intelligent transformation and digital data analysis as claimed in claim 1, characterized in that: The system includes: a storage goods supervision module, a supervision information collection module, a data management center, a target equipment screening module and an equipment adjustment management module; The output end of the storage goods supervision module is connected to the input end of the supervision information collection module, the output end of the supervision information collection module is connected to the input end of the data management center, the output end of the data management center is connected to the input end of the target device screening module, and the output end of the target device screening module is connected to the input end of the device adjustment management module; The storage goods supervision module monitors the flow status of goods in the warehouse in real time and interacts with the supervision terminal through information communication; Collecting equipment information and historical supervision information used for goods supervision through the supervision information collection module, and transmitting all collected data to the data management center; Storing and managing all collected data through the data management center; The target equipment screening module retrieves and analyzes the equipment information and historical supervision information of cargo supervision, analyzes the reasonable installation coefficients of different equipment and screens out the equipment to be adjusted; The device to be adjusted is replaced by the device adjustment management module, and the device to be adjusted is replaced with a device with an optimal operating frequency.

5. The intelligent warehouse supervision system based on intelligent transformation and digital transformation data analysis according to claim 4 is characterized by: The storage goods supervision module includes a goods label recognition unit, an in-and-out information collection unit, and a goods information communication unit; The output end of the cargo label identification unit is connected to the input end of the in-and-out information collection unit, and the output end of the in-and-out information collection unit is connected to the input end of the cargo information communication unit; The cargo tag identification unit uses an RFID reader to identify cargo tags in the warehouse, and obtains information on the cargo in and out of the warehouse, as well as the location of the cargo in the warehouse; The in-warehouse and out-warehouse information collection unit collects the in-warehouse and out-warehouse information of the goods and the location information in the warehouse from the identification results; The collected cargo information is transmitted to the supervision terminal through the cargo information communication unit.

6. The intelligent warehouse supervision system based on intelligent transformation and data analysis according to claim 5 is characterized by: The supervision information collection module includes a device information collection unit and an identification data collection unit; The input end of the equipment information collection unit is connected to the output end of the cargo information transmission unit, and the output ends of the equipment information collection unit and the identification data collection unit are connected to the input end of the data management center; The device information collection unit collects the working frequency of the RFID reading devices installed in different areas of the warehouse and the farthest recognition distance of the devices; A distance sensor is installed at the location where the RFID reading device is installed through the identification data collection unit, and the distance sensor is used to collect the straight-line distance information between the RFID reading devices installed in different areas and the successfully identified goods when the goods were previously identified.

7. The intelligent warehouse supervision system based on intelligent transformation and data analysis according to claim 6 is characterized by: The target device screening module includes an installation rationality analysis unit and a device screening unit to be adjusted; The input end of the installation rationality analysis unit is connected to the output end of the data management center, and the output end of the installation rationality analysis unit is connected to the input end of the device screening unit to be adjusted; The installation rationality analysis unit retrieves the straight-line distance information between the RFID reading devices installed in different areas and the successfully identified goods when the goods were previously identified, and analyzes the installation rationality coefficients of the RFID reading devices in different areas based on the retrieved data; The device to be adjusted screening unit compares the installation rationality coefficients of the RFID reading devices in different areas, and screens out the devices that need to be replaced and adjusted as the devices to be adjusted.

8. The intelligent warehouse supervision system based on intelligent transformation and digital transformation data analysis according to claim 7 is characterized by: The equipment adjustment management module includes a supervision information analysis unit and a reading equipment adjustment unit; The input end of the supervision information analysis unit is connected to the output end of the device screening unit to be adjusted, and the output end of the supervision information analysis unit is connected to the input end of the reading device adjustment unit; Establishing an operating frequency analysis model through the supervision information analysis unit to analyze the optimal operating frequency of the equipment to be installed in the area where the screened equipment to be adjusted is located; The device to be adjusted is replaced with an RFID reading device with an optimal operating frequency through the reading device adjustment unit.

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