CN115564348B - Digital twinning-based 3D intelligent warehouse monitoring and guiding system and method - Google Patents

Digital twinning-based 3D intelligent warehouse monitoring and guiding system and method Download PDF

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CN115564348B
CN115564348B CN202211232919.4A CN202211232919A CN115564348B CN 115564348 B CN115564348 B CN 115564348B CN 202211232919 A CN202211232919 A CN 202211232919A CN 115564348 B CN115564348 B CN 115564348B
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陈松宇
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Jiangsu Zhifang Data Technology Co ltd
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Abstract

The invention relates to the technical field of warehouse management, in particular to a digital twinning-based 3D intelligent warehouse monitoring and guiding system and method, wherein a comprehensive environment information management module predicts comprehensive influence values corresponding to all materials stored in a warehouse under different conditions of warehouse environment comprehensive information, and selects the warehouse environment comprehensive information corresponding to the minimum comprehensive influence value as the optimal storage environment comprehensive information of a current time warehouse. According to the method, a three-dimensional model of the warehouse is built through a digital twin technology, and the positions of the sensors in the warehouse are in one-to-one correspondence with the corresponding positions in the built three-dimensional model, so that the visualization of monitoring information of the warehouse is realized; the optimal storage environment of the current time of the warehouse can be predicted according to the type and duration of the stored materials and the influence degree of different storage environments on the quality of the stored materials, which are monitored in the prior art, so that the warehouse can be effectively supervised.

Description

Digital twinning-based 3D intelligent warehouse monitoring and guiding system and method
Technical Field
The invention relates to the technical field of warehouse management, in particular to a digital twinning-based 3D intelligent warehouse monitoring and guiding system and method.
Background
Along with the rapid development of internet technology, people are more and more widely applied to the internet technology, in the field of warehouse management, people can monitor warehouse data through sensors, and the mode enables people to manage the warehouse more intuitively and effectively to a certain extent, so that the inspection workload of people to the warehouse is reduced, the acquisition accuracy of people to the warehouse data is improved, and great convenience is brought to people.
The digital twin is to fully utilize data such as a physical model, sensor update, operation history and the like, integrate simulation processes of multiple disciplines, multiple physical quantities, multiple scales and multiple probabilities, and complete mapping in a virtual space, thereby reflecting the full life cycle process of corresponding entity equipment.
The existing digital twinning-based 3D intelligent warehouse monitoring and guiding system simply constructs a three-dimensional model of the warehouse through a digital twinning technology, and the positions of sensors in the warehouse are in one-to-one correspondence with the corresponding positions in the constructed three-dimensional model and are presented in the three-dimensional model, so that the visualization of warehouse monitoring information is realized; however, the prior art cannot predict the optimal storage environment of the current time of the warehouse according to the existing monitoring data (the type and duration of the stored materials and the influence degree of different storage environments on the quality of the stored materials).
Disclosure of Invention
The invention aims to provide a digital twinning-based 3D intelligent warehouse monitoring and guiding system and method, which are used for solving the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: a digital twinning-based 3D intelligent warehouse monitoring and guiding method, the method comprising the steps of:
S1, constructing a three-dimensional model with the same proportion as a warehouse based on a digital twin technology, dividing a storage space in the warehouse into a plurality of storage areas, and numbering the divided storage areas respectively;
S2, acquiring storage environment information which is respectively monitored by sensors arranged in storage areas with different numbers in the warehouse at time t, recording the storage environment information as corresponding environment information in the storage area with the corresponding number at time t, acquiring environment information displayed by an environment adjusting device in the warehouse at time t, recording the environment information as corresponding comprehensive warehouse environment information at time t, wherein the environment information comprises temperature and humidity;
S3, acquiring types and corresponding storage time lengths of materials stored in storage areas of each number at time t, combining environmental information in a warehouse at time t to acquire material storage information in the storage areas of each number at time t, and displaying the acquired material storage information in a three-dimensional model in real time, wherein the environmental information in the warehouse at time t comprises environmental information corresponding to the storage areas of the corresponding numbers at time t and warehouse environmental comprehensive information corresponding to time t;
s4, obtaining optimal storage environment information corresponding to different materials respectively through a database, analyzing the relation between different material storage environment deviation values and material quality influence rates by combining historical data,
The material storage environment deviation value represents the deviation condition of the material storage environment information relative to the optimal storage environment information corresponding to the corresponding material; calculating the damage rate HS1 in the material when the material storage environment information is unchanged and the storage time length is t1 and the damage rate HS2 in the material when the material optimal storage environment information is unchanged and the storage time length is t1, wherein the material quality influence rate is equal to (HS 2-HS 1)/t 1;
S5, analyzing the relation between the storage environment information and the warehouse environment comprehensive information in the storage areas with different numbers according to the historical data;
s6, combining the analysis results in S4 and S5, predicting the comprehensive influence values corresponding to all materials stored in the warehouse under different conditions of the comprehensive information of the warehouse environment, selecting the comprehensive information of the warehouse environment corresponding to the minimum comprehensive influence value as the best comprehensive information of the storage environment at the current time, acquiring the time length of the last change of the comprehensive information of the warehouse environment from the current time, marking the time length as a first time length, comparing the first time length with t1,
When the first time length is greater than or equal to t1, the comprehensive information of the warehouse environment corresponding to the current time is adjusted to the comprehensive information of the optimal storage environment of the current time warehouse; when the first time length is smaller than t1, the comprehensive information of the warehouse environment corresponding to the current time is not adjusted, and t1 is a first preset time length preset in a database.
Further, the method for dividing the storage space in the warehouse into a plurality of storage areas in S1 includes the following steps:
S1.1, acquiring a length a1, a width a2 and a height a3 corresponding to a space region in each storage shelf in a warehouse, wherein the specifications of different storage shelves are the same by default, and the storage space in the warehouse is a union of the space regions in each storage shelf in the warehouse;
S1.2, obtaining the greatest common divisor corresponding to the three numbers a1, a2 and a3, and recording the greatest common divisor as a4;
S1.3, equally dividing the space area in each storage shelf in the warehouse into a1 a 2a 3/a4 3 storage areas with the same specification, wherein the specification of each storage area is as follows: the length, width and height of the storage area are equal to a4;
Numbering each storage area in all storage shelves in the warehouse from 1, wherein each storage area corresponds to one number, the numbers corresponding to different storage areas are different,
The three-dimensional model with the same size as the warehouse comprises the distribution positions of all storage shelves in the warehouse relative to the center point of the warehouse.
In the process of dividing the storage space in the warehouse into a plurality of storage areas, the greatest common divisor of a1, a2 and a3 is obtained to determine the number of the storage areas divided by the storage space of the warehouse, so that the specification of each divided storage area is ensured to be the same.
Further, the method for obtaining the material storage information in the storage area of each number at the time t in S3 includes the following steps:
s3.1, acquiring types of stored materials and corresponding storage time lengths in storage areas of each number at time t, inquiring type numbers corresponding to different types of stored materials preset in a database, wherein the types of the stored materials correspond to different type numbers,
The type number corresponding to the type of the stored material in the storage area with the number B at the time t is marked as BLt, and the storage time length of the stored material in the storage area with the number B at the time t is marked as BtT;
S3.2, acquiring environment information in a warehouse at time t, namely { (WBt, SBt), (WZt, SZt) }, WBt representing the corresponding temperature in a storage area with the number B at time t, SBt representing the corresponding humidity in the storage area with the number B at time t, WZt representing the temperature in the comprehensive information of the warehouse environment at time t, and SZt representing the humidity in the comprehensive information of the warehouse environment at time t;
and S3.3, obtaining material storage information in a storage area with the number of B at the time t, and recording the material storage information as { BtT, BLt, (WBt, SBt), (WZt, SZt) }.
The method and the system for obtaining the material storage information in the storage area of each number at the time t are used for binding the types of the storage materials in the storage area of each number at the time t, the storage time, the environment information in the corresponding storage area and the comprehensive information of the warehouse environment, and further display the information in a three-dimensional model constructed by a digital twin technology, so that the visualization of the warehouse monitoring data is realized.
Further, the method for analyzing the relationship between the different material storage environment deviation values and the material quality influence rate by combining the historical data in the step S4 includes the following steps:
S4.1, obtaining optimal storage environment information corresponding to the material type number WZB in a database, marking the temperature in the optimal environment information corresponding to the WZB as W1 WZB, and marking the humidity in the optimal environment information corresponding to the WZB as S1 WZB;
S4.2, acquiring historical data, wherein when the type number of the stored material is WZB, the storage environment information of the material is (W WZB,SWZB) and the corresponding material quality influence rate V WZB,WWZB under the corresponding storage environment represents the temperature in the storage environment information of the material when the type number of the stored material is WZB, and S WZB represents the humidity in the storage environment information of the material when the type number of the stored material is WZB;
S4.3, constructing a first relation data pair （WPWZB,SPWZB,V1WZB）,WPWZB=WWZB-W1WZB,SPWZB=SWZB-S1WZB,
WP WZB represents the deviation temperature in the deviation value of the material storage environment when the type number of the stored material in the history data is WZB,
SP WZB indicates the deviation humidity in the deviation value of the material storage environment when the material type number stored in the history data is WZB,
The material storage environment deviation value comprises deviation temperature and deviation humidity,
V1 WZB is equal to the average value of the corresponding mass influence rate of each material under the condition that the material storage environment deviation value is (WP WZB,SPWZB) when the type number of the stored material in the historical data is WZB,
When the historical data (W WZB,SWZB) are different, respectively constructing each first relation data pair, controlling the obtained change step length corresponding to W WZB and S WZB in (W WZB,SWZB), marking the change step length corresponding to W WZB as c1, marking the change step length corresponding to S WZB as c2, and then marking the change step length of the first data pair to the strain quantity as c1, wherein the change step length of the second data pair to the strain quantity is c2, c1 is more than 0, c2 is more than 0 and c1 is not equal to c2;
S4.4, constructing a space rectangular coordinate system by taking o as an origin, taking temperature as an x-axis, taking humidity as a y-axis and taking a material quality influence rate as a z-axis, and marking the obtained first relation data on corresponding coordinate points in the space rectangular coordinate system;
s4.5, dividing four adjacent coordinate points projected as rectangles on the xoy plane in a space plane rectangular coordinate system into an array, and obtaining a relation surface formed by the four coordinate points in each array;
And S4.6, summarizing the relation surfaces formed by the arrays in a space rectangular coordinate system to obtain a relation surface between the material storage environment deviation value and the material quality influence rate when the type number of the stored material is WZB, and marking the relation surface as GM WZB, thereby obtaining the relation between different material storage environment deviation values and the material quality influence rate.
In the process of analyzing the relation between different material storage environment deviation values and material quality influence rates by combining historical data, the material quality influence rates corresponding to the material storage environment deviation values of various storage material types are analyzed, in the process of analyzing, as the storage environment information comprises two data of temperature and humidity, the material storage environment deviation values are two-dimensional concepts (namely temperature deviation and humidity deviation), and the material quality influence rates are combined, a three-dimensional data relation model is formed, when the relation between the different material storage environment deviation values and the material quality influence rates is analyzed, a space rectangular coordinate system is needed to be constructed for analysis, the analyzed relation corresponds to not one line, but one curved surface, and the material storage environment deviation values formed by the different temperature deviation values and the different humidity deviation values in the curved surface only correspond to one material quality influence rate, so that data reference is provided for the comprehensive influence values corresponding to all materials stored in a subsequent analysis warehouse.
Further, the method for obtaining the relationship surface formed by the four coordinate points in each array in S4.5 includes the following steps:
S4.5.1, obtaining four coordinate points in each array,
The coordinate point with the smallest sum of the x-axis coordinate and the y-axis coordinate in the four coordinate points in the array is marked as a first coordinate point,
Subtracting the sum of the x-axis coordinate and the y-axis coordinate in the first coordinate point from the sum of the x-axis coordinate and the y-axis coordinate in the four coordinate points in the array, marking the coordinate point with the result of c1 as a second coordinate point,
Subtracting the sum of the x-axis coordinate and the y-axis coordinate in the first coordinate point from the sum of the x-axis coordinate and the y-axis coordinate in the four coordinate points in the array, marking the coordinate point with the result of c2 as a third coordinate point,
Marking the coordinate point with the largest sum of the x-axis coordinate and the y-axis as a fourth coordinate point in the four coordinate points in the array;
s4.5.2, obtaining a fifth coordinate point (x 1, y1, z 1) corresponding to the array,
X1 is equal to the average value of x-axis coordinates corresponding to four coordinate points in the array, y1 is equal to the average value of y-axis coordinates corresponding to four coordinate points in the array, and z1 is equal to the average value of z-axis coordinates corresponding to four coordinate points in the array;
S4.5.3, obtaining a relation surface formed by four coordinate points in the array, wherein the relation surface corresponding to the array is formed by a first relation surface, a second relation surface, a third relation surface and a fourth relation surface,
The first relation surface is an area surrounded by the three points in the plane where the first coordinate point, the second coordinate point and the fifth coordinate point are located in the array,
The second relation surface is an area surrounded by the three points in the plane where the first coordinate point, the third coordinate point and the fifth coordinate point are located in the array,
The third relation surface is an area surrounded by the second coordinate point, the fourth coordinate point and the fifth coordinate point in the plane where the second coordinate point, the fourth coordinate point and the fifth coordinate point are positioned,
The fourth relation surface is an area surrounded by the third coordinate point, the fourth coordinate point and the fifth coordinate point in the plane where the third coordinate point, the fourth coordinate point and the fifth coordinate point are located in the array.
The relation curved surface between the material storage environment deviation value and the material quality influence rate is formed by splicing a plurality of relation surfaces corresponding to a plurality of arrays respectively; the corresponding relation surface of each data group is composed of a corresponding first relation surface, a corresponding second relation surface, a corresponding third relation surface and a corresponding fourth relation surface.
Further, the method in S5 for analyzing the relationship between the storage environment information and the warehouse environment comprehensive information in the storage areas with different numbers according to the historical data includes the following steps:
S5.1, when the temperature in the comprehensive information of the warehouse environment in the historical data is WZ, various monitoring temperatures of the sensor in the storage area with the number of B and the total duration corresponding to each monitoring temperature are obtained,
S5.2, when the humidity in the comprehensive information of the warehouse environment in the historical data is SZ, various monitoring humidity of the sensor in the storage area with the number of B and the total duration corresponding to each monitoring humidity are obtained,
S5.3, when the comprehensive information of the warehouse environment is (WZ, SZ), storing the prediction result (WBWZ, SBSZ) of the environment information in the storage area with the number of B,
Wherein n1 represents the number of types of the temperature monitored by the sensor in the storage area with the number of B when the temperature in the comprehensive information of the warehouse environment in the historical data is WZ,
WBWZn shows the nth temperature corresponding value monitored by the sensor in the storage area with the number of B when the temperature in the comprehensive information of the warehouse environment in the historical data is WZ,
TBWZn denotes the total time length corresponding to the nth temperature monitored by the sensor in the storage area with the number B when the temperature in the comprehensive information of the warehouse environment in the historical data is WZ,
Wherein n3 represents the number of types of humidity monitored by the sensor in the storage area with the number of B when the humidity in the comprehensive information of the warehouse environment in the historical data is SZ,
SBSZn2 denotes the corresponding value of the n 2-th humidity monitored by the sensor in the storage area with the number B when the humidity in the comprehensive information of the warehouse environment in the historical data is SZ,
TBSZn2 is the total time length corresponding to the nth 2 humidity monitored by the sensor in the storage area with the number of B when the humidity in the comprehensive information of the warehouse environment in the historical data is SZ;
s5.4, when B is obtained to be different values, respectively corresponding (WBWZ, SBSZ) to each (WZ, SZ), and inputting each (WBWZ, SBSZ) into a blank set one by one to obtain a set corresponding to (WZ, SZ);
and S5.5, when the WZ or the SZ is obtained to be different values, respectively corresponding sets of the WZ and the SZ to obtain the relation between the storage environment information and the warehouse environment comprehensive information in the storage areas with different numbers.
In the process of analyzing the relation between the storage environment information and the warehouse environment comprehensive information in the storage areas with different numbers according to the historical data, the invention acquires the corresponding sets of (WZ, SZ) respectively, so as to acquire the storage environment information in the storage areas corresponding to the numbers when the warehouse environment comprehensive information is (WZ, SZ) according to the elements in the corresponding sets of (WZ, SZ), and further provide data reference for calculating the comprehensive influence values corresponding to all materials stored in the warehouse in the subsequent steps.
Further, the method for predicting the comprehensive influence value corresponding to all materials stored in the warehouse in the S6 under different conditions includes the following steps:
S6.1, acquiring the times and the time length of each storage of the storage materials with the category number WZB in the warehouse in the latest first time period in the historical data, calculating the average value of the time length of each storage of the storage materials with the category number WZB in the warehouse as a storage time length reference value corresponding to the storage materials with the category number WZB, and marking as TG WZB;
S6.2, acquiring material storage information { BtT, BLt, (WBt, SBt), (WZt, SZt) } in a storage area with the number B at the time T, marking a time point corresponding to the current time as T2, and obtaining material storage information { Bt2T, BLt2, (WBt, SBt 2), (WZt, SZt) in the storage area with the number B at the time T2;
s6.3, when the comprehensive information of the warehouse environment is (YWZ, YSZ), the comprehensive influence values ZYX corresponding to all materials stored in the warehouse are obtained,
Wherein B1 represents the total number of storage areas divided in the warehouse,
G (B, YWZ, YSZ) represents the material quality impact rate corresponding to the material stored in the storage area with the current time number B when the comprehensive information of the warehouse environment is (YWZ, YSZ).
Further, the method for obtaining G (B, YWZ, YSZ) comprises the following steps:
Step one, obtaining the type number BLt2 of the storage material in the storage area with the current time number B,
Step two, when the type number of the stored material is BLt2, a relation curved surface GM BLt2 between a material storage environment deviation value and a material quality influence rate is obtained,
Step three, in the relation between the storage environment information in the storage areas with different numbers and the warehouse environment comprehensive information, when the warehouse environment comprehensive information is (YWZ, YSZ), the storage environment information in the storage area with the number B is marked as (YWZB, YSZB),
Step four, obtaining the optimal storage environment information corresponding to the stored material type number BLt2 in the database (W1 BLt2,S1BLt2）,W1BLt2 represents the temperature in the optimal environment information corresponding to BLt2, S1 BLt2 represents the humidity in the optimal environment information corresponding to BLt 2;
Substituting the (YWZB-W1 BLt2,YSZB-S1BLt2) serving as a storage deviation value into GM BLt2 to obtain a corresponding material quality influence rate G (B, YWZ, YSZ);
the method for acquiring E (Bt 2T, BLt 2) comprises the following steps:
firstly, obtaining a storage time length reference value TG BLt2 corresponding to a storage material with a type number BLt 2;
Step two, acquiring a storage time BtT of a storage material in a storage area with the current time number B;
A third step of obtaining the value of E (Bt 2T, BLt 2),
When TG BLt2 -BtT2 is not less than T1, then E (Bt 2T, BLt 2) =t1 is determined,
When TG BLt2 -BtT2 < T1, then E (Bt 2T, BLt 2) =tg BLt2 -BtT is determined.
The invention judges that when TG BLt2 -BtT is larger than or equal to T1, E (Bt 2T, BLt 2) =t1, considers that the minimum time interval of adjacent twice adjustment of the comprehensive information of the warehouse environment is T1, further predicts the comprehensive influence values corresponding to all materials stored in the warehouse under different conditions of the comprehensive information of the warehouse environment, and judges that the maximum value of E (Bt 2T, BLt 2) is T1 by taking T1 as a reference standard; and when TG BLt2 -BtT2 < T1, E (Bt 2T, BLt 2) =tg BLt2 -BtT2 is determined, considering that the materials in the storage area with the number B may go out of the warehouse based on the subsequent TG BLt2 -BtT of the current time, further predicting that the remaining storage time of the materials in the storage area with the number B is TG BLt2 -BtT (the time period that the materials in the storage area with the number B are affected by the warehouse environment comprehensive information is TG BLt2 -BtT2 based on the subsequent T1 of the current time), and providing a data reference for predicting the comprehensive impact values corresponding to all the materials stored in the warehouse under different conditions of the warehouse environment comprehensive information.
A digital twinning-based 3D intelligent warehouse monitoring guidance system, the system comprising the following modules:
The model construction module is used for constructing a three-dimensional model with the same proportion as the warehouse on the basis of a digital twin technology, dividing a storage space in the warehouse into a plurality of storage areas, and numbering the divided storage areas respectively;
The monitoring data acquisition module acquires storage environment information which is respectively monitored by sensors arranged in storage areas with different numbers in the warehouse at time t and is marked as corresponding environment information in the storage area with the corresponding number at time t, acquires environment information displayed by an environment adjusting device in the warehouse at time t and is marked as corresponding comprehensive warehouse environment information at time t, wherein the environment information comprises temperature and humidity;
the material storage information acquisition module acquires the types and corresponding storage time of the stored materials in the storage areas with the numbers at the time t, combines the environmental information in the warehouse at the time t to acquire the material storage information in the storage areas with the numbers at the time t, and presents the acquired material storage information in a three-dimensional model in real time, wherein the environmental information in the warehouse at the time t comprises the environmental information corresponding to the storage areas with the corresponding numbers at the time t and the comprehensive warehouse environmental information corresponding to the time t;
The environment information influence relation analysis module is used for acquiring optimal storage environment information corresponding to different materials respectively through a database and analyzing the relation between the storage environment deviation values of the different materials and the material quality influence rate by combining historical data;
The environment information relation analysis module is used for analyzing the relation between the storage environment information and the warehouse environment comprehensive information in the storage areas with different numbers according to the historical data;
A comprehensive environment information management module, which predicts the comprehensive influence values corresponding to all materials stored in the warehouse under different conditions of the comprehensive information of the warehouse environment, selects the comprehensive information of the warehouse environment corresponding to the minimum comprehensive influence value as the best comprehensive information of the storage environment at the current time, obtains the time length of the last change of the comprehensive information of the warehouse environment from the current time, marks the time length as a first time length, compares the first time length with t1,
When the first time length is greater than or equal to t1, the comprehensive information of the warehouse environment corresponding to the current time is adjusted to the comprehensive information of the optimal storage environment of the current time warehouse; when the first time length is smaller than t1, the comprehensive information of the warehouse environment corresponding to the current time is not adjusted, and t1 is a first preset time length preset in a database.
Compared with the prior art, the invention has the following beneficial effects: according to the method, a three-dimensional model of the warehouse is built through a digital twin technology, and the positions of the sensors in the warehouse are in one-to-one correspondence with the corresponding positions in the built three-dimensional model, so that the visualization of monitoring information of the warehouse is realized; the optimal storage environment of the current time of the warehouse can be predicted according to the type and duration of the stored materials and the influence degree of different storage environments on the quality of the stored materials, which are monitored in the prior art, so that the warehouse can be effectively supervised.
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The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a schematic diagram of a digital twinning-based 3D intelligent warehouse monitoring and guiding system;
fig. 2 is a schematic flow chart of a digital twinning-based 3D intelligent warehouse monitoring and guiding method.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1-2, the present invention provides the following technical solutions: a digital twinning-based 3D intelligent warehouse monitoring and guiding method, the method comprising the steps of:
S1, constructing a three-dimensional model with the same proportion as a warehouse based on a digital twin technology, dividing a storage space in the warehouse into a plurality of storage areas, and numbering the divided storage areas respectively;
S2, acquiring storage environment information which is respectively monitored by sensors arranged in storage areas with different numbers in the warehouse at time t, recording the storage environment information as corresponding environment information in the storage area with the corresponding number at time t, acquiring environment information displayed by an environment adjusting device in the warehouse at time t, recording the environment information as corresponding comprehensive warehouse environment information at time t, wherein the environment information comprises temperature and humidity;
S3, acquiring types and corresponding storage time lengths of materials stored in storage areas of each number at time t, combining environmental information in a warehouse at time t to acquire material storage information in the storage areas of each number at time t, and displaying the acquired material storage information in a three-dimensional model in real time, wherein the environmental information in the warehouse at time t comprises environmental information corresponding to the storage areas of the corresponding numbers at time t and warehouse environmental comprehensive information corresponding to time t;
s4, obtaining optimal storage environment information corresponding to different materials respectively through a database, analyzing the relation between different material storage environment deviation values and material quality influence rates by combining historical data,
The material storage environment deviation value represents the deviation condition of the material storage environment information relative to the optimal storage environment information corresponding to the corresponding material; calculating the damage rate HS1 in the material when the material storage environment information is unchanged and the storage time length is t1 and the damage rate HS2 in the material when the material optimal storage environment information is unchanged and the storage time length is t1, wherein the material quality influence rate is equal to (HS 2-HS 1)/t 1;
S5, analyzing the relation between the storage environment information and the warehouse environment comprehensive information in the storage areas with different numbers according to the historical data;
s6, combining the analysis results in S4 and S5, predicting the comprehensive influence values corresponding to all materials stored in the warehouse under different conditions of the comprehensive information of the warehouse environment, selecting the comprehensive information of the warehouse environment corresponding to the minimum comprehensive influence value as the best comprehensive information of the storage environment at the current time, acquiring the time length of the last change of the comprehensive information of the warehouse environment from the current time, marking the time length as a first time length, comparing the first time length with t1,
When the first time length is greater than or equal to t1, the comprehensive information of the warehouse environment corresponding to the current time is adjusted to the comprehensive information of the optimal storage environment of the current time warehouse; when the first time length is smaller than t1, the comprehensive information of the warehouse environment corresponding to the current time is not adjusted, and t1 is a first preset time length preset in a database.
In this embodiment, the first preset time period t1 is 5 minutes;
The method for dividing the storage space in the warehouse into a plurality of storage areas in S1 comprises the following steps:
S1.1, acquiring a length a1, a width a2 and a height a3 corresponding to a space region in each storage shelf in a warehouse, wherein the specifications of different storage shelves are the same by default, and the storage space in the warehouse is a union of the space regions in each storage shelf in the warehouse;
S1.2, obtaining the greatest common divisor corresponding to the three numbers a1, a2 and a3, and recording the greatest common divisor as a4;
S1.3, equally dividing the space area in each storage shelf in the warehouse into a1 a 2a 3/a4 3 storage areas with the same specification, wherein the specification of each storage area is as follows: the length, width and height of the storage area are equal to a4;
Numbering each storage area in all storage shelves in the warehouse from 1, wherein each storage area corresponds to one number, the numbers corresponding to different storage areas are different,
The three-dimensional model with the same size as the warehouse comprises the distribution positions of all storage shelves in the warehouse relative to the center point of the warehouse.
In this embodiment, if the storage space in the first warehouse includes 30 storage shelves, each storage shelf has a specification of 20 dm long, 5 dm wide and 20 dm high,
Since the greatest common divisor between 20 and 5 is 5,
Each memory fetch in the a warehouse may be divided into 20 x 5 x 20/5 (5 x 5) =16 memory regions,
The number of storage areas divided by the storage space in the warehouse a is 30×16=480.
The method for obtaining the material storage information in the storage area of each number at the time t in the S3 comprises the following steps:
s3.1, acquiring types of stored materials and corresponding storage time lengths in storage areas of each number at time t, inquiring type numbers corresponding to different types of stored materials preset in a database, wherein the types of the stored materials correspond to different type numbers,
The type number corresponding to the type of the stored material in the storage area with the number B at the time t is marked as BLt, and the storage time length of the stored material in the storage area with the number B at the time t is marked as BtT;
S3.2, acquiring environment information in a warehouse at time t, namely { (WBt, SBt), (WZt, SZt) }, WBt representing the corresponding temperature in a storage area with the number B at time t, SBt representing the corresponding humidity in the storage area with the number B at time t, WZt representing the temperature in the comprehensive information of the warehouse environment at time t, and SZt representing the humidity in the comprehensive information of the warehouse environment at time t;
and S3.3, obtaining material storage information in a storage area with the number of B at the time t, and recording the material storage information as { BtT, BLt, (WBt, SBt), (WZt, SZt) }.
The method for analyzing the relation between the different material storage environment deviation values and the material quality influence rate by combining the historical data in the S4 comprises the following steps:
S4.1, obtaining optimal storage environment information corresponding to the material type number WZB in a database, marking the temperature in the optimal environment information corresponding to the WZB as W1 WZB, and marking the humidity in the optimal environment information corresponding to the WZB as S1 WZB;
S4.2, acquiring historical data, wherein when the type number of the stored material is WZB, the storage environment information of the material is (W WZB,SWZB) and the corresponding material quality influence rate V WZB,WWZB under the corresponding storage environment represents the temperature in the storage environment information of the material when the type number of the stored material is WZB, and S WZB represents the humidity in the storage environment information of the material when the type number of the stored material is WZB;
S4.3, constructing a first relation data pair （WPWZB,SPWZB,V1WZB）,WPWZB=WWZB-W1WZB,SPWZB=SWZB-S1WZB,
WP WZB represents the deviation temperature in the deviation value of the material storage environment when the type number of the stored material in the history data is WZB,
SP WZB indicates the deviation humidity in the deviation value of the material storage environment when the material type number stored in the history data is WZB,
The material storage environment deviation value comprises deviation temperature and deviation humidity,
V1 WZB is equal to the average value of the corresponding mass influence rate of each material under the condition that the material storage environment deviation value is (WP WZB,SPWZB) when the type number of the stored material in the historical data is WZB,
When the historical data (W WZB,SWZB) are different, respectively constructing each first relation data pair, controlling the obtained change step length corresponding to W WZB and S WZB in (W WZB,SWZB), marking the change step length corresponding to W WZB as c1, marking the change step length corresponding to S WZB as c2, and then marking the change step length of the first data pair to the strain quantity as c1, wherein the change step length of the second data pair to the strain quantity is c2, c1 is more than 0, c2 is more than 0 and c1 is not equal to c2;
S4.4, constructing a space rectangular coordinate system by taking o as an origin, taking temperature as an x-axis, taking humidity as a y-axis and taking a material quality influence rate as a z-axis, and marking the obtained first relation data on corresponding coordinate points in the space rectangular coordinate system;
s4.5, dividing four adjacent coordinate points projected as rectangles on the xoy plane in a space plane rectangular coordinate system into an array, and obtaining a relation surface formed by the four coordinate points in each array;
the method for acquiring the relation surface formed by four coordinate points in each array in S4.5 comprises the following steps:
S4.5.1, obtaining four coordinate points in each array,
The coordinate point with the smallest sum of the x-axis coordinate and the y-axis coordinate in the four coordinate points in the array is marked as a first coordinate point,
Subtracting the sum of the x-axis coordinate and the y-axis coordinate in the first coordinate point from the sum of the x-axis coordinate and the y-axis coordinate in the four coordinate points in the array, marking the coordinate point with the result of c1 as a second coordinate point,
Subtracting the sum of the x-axis coordinate and the y-axis coordinate in the first coordinate point from the sum of the x-axis coordinate and the y-axis coordinate in the four coordinate points in the array, marking the coordinate point with the result of c2 as a third coordinate point,
Marking the coordinate point with the largest sum of the x-axis coordinate and the y-axis as a fourth coordinate point in the four coordinate points in the array;
s4.5.2, obtaining a fifth coordinate point (x 1, y1, z 1) corresponding to the array,
X1 is equal to the average value of x-axis coordinates corresponding to four coordinate points in the array, y1 is equal to the average value of y-axis coordinates corresponding to four coordinate points in the array, and z1 is equal to the average value of z-axis coordinates corresponding to four coordinate points in the array;
S4.5.3, obtaining a relation surface formed by four coordinate points in the array, wherein the relation surface corresponding to the array is formed by a first relation surface, a second relation surface, a third relation surface and a fourth relation surface,
The first relation surface is an area surrounded by the three points in the plane where the first coordinate point, the second coordinate point and the fifth coordinate point are located in the array,
The second relation surface is an area surrounded by the three points in the plane where the first coordinate point, the third coordinate point and the fifth coordinate point are located in the array,
The third relation surface is an area surrounded by the second coordinate point, the fourth coordinate point and the fifth coordinate point in the plane where the second coordinate point, the fourth coordinate point and the fifth coordinate point are positioned,
The fourth relation surface is an area surrounded by the third coordinate point, the fourth coordinate point and the fifth coordinate point in the plane where the third coordinate point, the fourth coordinate point and the fifth coordinate point are located in the array;
And S4.6, summarizing the relation surfaces formed by the arrays in a space rectangular coordinate system to obtain a relation surface between the material storage environment deviation value and the material quality influence rate when the type number of the stored material is WZB, and marking the relation surface as GM WZB, thereby obtaining the relation between different material storage environment deviation values and the material quality influence rate.
The method for analyzing the relation between the storage environment information and the warehouse environment comprehensive information in the storage areas with different numbers according to the historical data in the S5 comprises the following steps:
S5.1, when the temperature in the comprehensive information of the warehouse environment in the historical data is WZ, various monitoring temperatures of the sensor in the storage area with the number of B and the total duration corresponding to each monitoring temperature are obtained,
S5.2, when the humidity in the comprehensive information of the warehouse environment in the historical data is SZ, various monitoring humidity of the sensor in the storage area with the number of B and the total duration corresponding to each monitoring humidity are obtained,
S5.3, when the comprehensive information of the warehouse environment is (WZ, SZ), storing the prediction result (WBWZ, SBSZ) of the environment information in the storage area with the number of B,
Wherein n1 represents the number of types of the temperature monitored by the sensor in the storage area with the number of B when the temperature in the comprehensive information of the warehouse environment in the historical data is WZ,
WBWZn shows the nth temperature corresponding value monitored by the sensor in the storage area with the number of B when the temperature in the comprehensive information of the warehouse environment in the historical data is WZ,
TBWZn denotes the total time length corresponding to the nth temperature monitored by the sensor in the storage area with the number B when the temperature in the comprehensive information of the warehouse environment in the historical data is WZ,
Wherein n3 represents the number of types of humidity monitored by the sensor in the storage area with the number of B when the humidity in the comprehensive information of the warehouse environment in the historical data is SZ,
SBSZn2 denotes the corresponding value of the n 2-th humidity monitored by the sensor in the storage area with the number B when the humidity in the comprehensive information of the warehouse environment in the historical data is SZ,
TBSZn2 is the total time length corresponding to the nth 2 humidity monitored by the sensor in the storage area with the number of B when the humidity in the comprehensive information of the warehouse environment in the historical data is SZ;
s5.4, when B is obtained to be different values, respectively corresponding (WBWZ, SBSZ) to each (WZ, SZ), and inputting each (WBWZ, SBSZ) into a blank set one by one to obtain a set corresponding to (WZ, SZ);
and S5.5, when the WZ or the SZ is obtained to be different values, respectively corresponding sets of the WZ and the SZ to obtain the relation between the storage environment information and the warehouse environment comprehensive information in the storage areas with different numbers.
The method for predicting the comprehensive influence values corresponding to all materials stored in the warehouse under different conditions in the S6 comprises the following steps:
S6.1, acquiring the times and the time length of each storage of the storage materials with the category number WZB in the warehouse in the latest first time period in the historical data, calculating the average value of the time length of each storage of the storage materials with the category number WZB in the warehouse as a storage time length reference value corresponding to the storage materials with the category number WZB, and marking as TG WZB;
S6.2, acquiring material storage information { BtT, BLt, (WBt, SBt), (WZt, SZt) } in a storage area with the number B at the time T, marking a time point corresponding to the current time as T2, and obtaining material storage information { Bt2T, BLt2, (WBt, SBt 2), (WZt, SZt) in the storage area with the number B at the time T2;
s6.3, when the comprehensive information of the warehouse environment is (YWZ, YSZ), the comprehensive influence values ZYX corresponding to all materials stored in the warehouse are obtained,
Wherein B1 represents the total number of storage areas divided in the warehouse,
G (B, YWZ, YSZ) represents the material quality impact rate corresponding to the material stored in the storage area with the current time number B when the comprehensive information of the warehouse environment is (YWZ, YSZ).
The method for obtaining G (B, YWZ, YSZ) comprises the following steps:
Step one, obtaining the type number BLt2 of the storage material in the storage area with the current time number B,
Step two, when the type number of the stored material is BLt2, a relation curved surface GM BLt2 between a material storage environment deviation value and a material quality influence rate is obtained,
Step three, in the relation between the storage environment information in the storage areas with different numbers and the warehouse environment comprehensive information, when the warehouse environment comprehensive information is (YWZ, YSZ), the storage environment information in the storage area with the number B is marked as (YWZB, YSZB),
Step four, obtaining the optimal storage environment information corresponding to the stored material type number BLt2 in the database (W1 BLt2,S1BLt2）,W1BLt2 represents the temperature in the optimal environment information corresponding to BLt2, S1 BLt2 represents the humidity in the optimal environment information corresponding to BLt 2;
Substituting the (YWZB-W1 BLt2,YSZB-S1BLt2) serving as a storage deviation value into GM BLt2 to obtain a corresponding material quality influence rate G (B, YWZ, YSZ);
the method for acquiring E (Bt 2T, BLt 2) comprises the following steps:
firstly, obtaining a storage time length reference value TG BLt2 corresponding to a storage material with a type number BLt 2;
Step two, acquiring a storage time BtT of a storage material in a storage area with the current time number B;
A third step of obtaining the value of E (Bt 2T, BLt 2),
When TG BLt2 -BtT2 is not less than T1, then E (Bt 2T, BLt 2) =t1 is determined,
When TG BLt2 -BtT2 < T1, then E (Bt 2T, BLt 2) =tg BLt2 -BtT is determined.
A digital twinning-based 3D intelligent warehouse monitoring guidance system, the system comprising the following modules:
The model construction module is used for constructing a three-dimensional model with the same proportion as the warehouse on the basis of a digital twin technology, dividing a storage space in the warehouse into a plurality of storage areas, and numbering the divided storage areas respectively;
The monitoring data acquisition module acquires storage environment information which is respectively monitored by sensors arranged in storage areas with different numbers in the warehouse at time t and is marked as corresponding environment information in the storage area with the corresponding number at time t, acquires environment information displayed by an environment adjusting device in the warehouse at time t and is marked as corresponding comprehensive warehouse environment information at time t, wherein the environment information comprises temperature and humidity;
the material storage information acquisition module acquires the types and corresponding storage time of the stored materials in the storage areas with the numbers at the time t, combines the environmental information in the warehouse at the time t to acquire the material storage information in the storage areas with the numbers at the time t, and presents the acquired material storage information in a three-dimensional model in real time, wherein the environmental information in the warehouse at the time t comprises the environmental information corresponding to the storage areas with the corresponding numbers at the time t and the comprehensive warehouse environmental information corresponding to the time t;
The environment information influence relation analysis module is used for acquiring optimal storage environment information corresponding to different materials respectively through a database and analyzing the relation between the storage environment deviation values of the different materials and the material quality influence rate by combining historical data;
The environment information relation analysis module is used for analyzing the relation between the storage environment information and the warehouse environment comprehensive information in the storage areas with different numbers according to the historical data;
A comprehensive environment information management module, which predicts the comprehensive influence values corresponding to all materials stored in the warehouse under different conditions of the comprehensive information of the warehouse environment, selects the comprehensive information of the warehouse environment corresponding to the minimum comprehensive influence value as the best comprehensive information of the storage environment at the current time, obtains the time length of the last change of the comprehensive information of the warehouse environment from the current time, marks the time length as a first time length, compares the first time length with t1,
When the first time length is greater than or equal to t1, the comprehensive information of the warehouse environment corresponding to the current time is adjusted to the comprehensive information of the optimal storage environment of the current time warehouse; when the first time length is smaller than t1, the comprehensive information of the warehouse environment corresponding to the current time is not adjusted, and t1 is a first preset time length preset in a database.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (2)

1. A digital twinning-based 3D intelligent warehouse monitoring and guiding method, characterized in that the method comprises the following steps:
S1, constructing a three-dimensional model with the same proportion as a warehouse based on a digital twin technology, dividing a storage space in the warehouse into a plurality of storage areas, and numbering the divided storage areas respectively;
S2, acquiring storage environment information which is respectively monitored by sensors arranged in storage areas with different numbers in the warehouse at time t, recording the storage environment information as corresponding environment information in the storage area with the corresponding number at time t, acquiring environment information displayed by an environment adjusting device in the warehouse at time t, recording the environment information as corresponding comprehensive warehouse environment information at time t, wherein the environment information comprises temperature and humidity;
S3, acquiring types and corresponding storage time lengths of materials stored in storage areas of each number at time t, combining environmental information in a warehouse at time t to acquire material storage information in the storage areas of each number at time t, and displaying the acquired material storage information in a three-dimensional model in real time, wherein the environmental information in the warehouse at time t comprises environmental information corresponding to the storage areas of the corresponding numbers at time t and warehouse environmental comprehensive information corresponding to time t;
s4, obtaining optimal storage environment information corresponding to different materials respectively through a database, analyzing the relation between different material storage environment deviation values and material quality influence rates by combining historical data,
The material storage environment deviation value represents the deviation condition of the material storage environment information relative to the optimal storage environment information corresponding to the corresponding material; calculating the damage rate HS1 in the material when the material storage environment information is unchanged and the storage time length is t1 and the damage rate HS2 in the material when the material optimal storage environment information is unchanged and the storage time length is t1, wherein the material quality influence rate is equal to (HS 2-HS 1)/t 1;
S5, analyzing the relation between the storage environment information and the warehouse environment comprehensive information in the storage areas with different numbers according to the historical data;
s6, combining the analysis results in S4 and S5, predicting the comprehensive influence values corresponding to all materials stored in the warehouse under different conditions of the comprehensive information of the warehouse environment, selecting the comprehensive information of the warehouse environment corresponding to the minimum comprehensive influence value as the best comprehensive information of the storage environment at the current time, acquiring the time length of the last change of the comprehensive information of the warehouse environment from the current time, marking the time length as a first time length, comparing the first time length with t1,
When the first time length is greater than or equal to t1, the comprehensive information of the warehouse environment corresponding to the current time is adjusted to the comprehensive information of the optimal storage environment of the current time warehouse; when the first time length is smaller than t1, not adjusting the comprehensive information of the warehouse environment corresponding to the current time, wherein t1 is a first preset time length preset in a database;
The method for obtaining the material storage information in the storage area of each number at the time t in the S3 comprises the following steps:
s3.1, acquiring types of stored materials and corresponding storage time lengths in storage areas of each number at time t, inquiring type numbers corresponding to different types of stored materials preset in a database, wherein the types of the stored materials correspond to different type numbers,
The type number corresponding to the type of the stored material in the storage area with the number B at the time t is marked as BLt, and the storage time length of the stored material in the storage area with the number B at the time t is marked as BtT;
S3.2, acquiring environment information in a warehouse at time t, namely { (WBt, SBt), (WZt, SZt) }, WBt representing the corresponding temperature in a storage area with the number B at time t, SBt representing the corresponding humidity in the storage area with the number B at time t, WZt representing the temperature in the comprehensive information of the warehouse environment at time t, and SZt representing the humidity in the comprehensive information of the warehouse environment at time t;
S3.3, obtaining material storage information in a storage area with the number of B at time t, and recording the material storage information as { BtT, BLt, (WBt, SBt), (WZt, SZt) };
the method for analyzing the relation between the different material storage environment deviation values and the material quality influence rate by combining the historical data in the S4 comprises the following steps:
S4.1, obtaining optimal storage environment information corresponding to the material type number WZB in a database, marking the temperature in the optimal environment information corresponding to the WZB as W1 WZB, and marking the humidity in the optimal environment information corresponding to the WZB as S1 WZB;
S4.2, acquiring historical data, wherein when the type number of the stored material is WZB, the storage environment information of the material is (W WZB,SWZB) and the corresponding material quality influence rate V WZB,WWZB under the corresponding storage environment represents the temperature in the storage environment information of the material when the type number of the stored material is WZB, and S WZB represents the humidity in the storage environment information of the material when the type number of the stored material is WZB;
s4.3, constructing a first relation data pair (WPWZB,SPWZB,V1WZB),WPWZB＝WWZB-W1WZB,SPWZB＝SWZB-S1WZB,
WP WZB represents the deviation temperature in the deviation value of the material storage environment when the type number of the stored material in the history data is WZB,
SP WZB indicates the deviation humidity in the deviation value of the material storage environment when the material type number stored in the history data is WZB,
The material storage environment deviation value comprises deviation temperature and deviation humidity,
V1 WZB is equal to the average value of the corresponding mass influence rate of each material under the condition that the material storage environment deviation value is (WP WZB,SPWZB) when the type number of the stored material in the historical data is WZB,
When the historical data (W WZB,SWZB) are different, respectively constructing each first relation data pair, controlling the obtained change step length corresponding to W WZB and S WZB in (W WZB,SWZB), marking the change step length corresponding to W WZB as c1, marking the change step length corresponding to S WZB as c2, and then marking the change step length of the first data pair to the strain quantity as c1, wherein the change step length of the second data pair to the strain quantity is c2, c1 is more than 0, c2 is more than 0 and c1 is not equal to c2;
S4.4, constructing a space rectangular coordinate system by taking o as an origin, taking temperature as an x-axis, taking humidity as a y-axis and taking a material quality influence rate as a z-axis, and marking the obtained first relation data on corresponding coordinate points in the space rectangular coordinate system;
s4.5, dividing four adjacent coordinate points projected as rectangles on the xoy plane in a space plane rectangular coordinate system into an array, and obtaining a relation surface formed by the four coordinate points in each array;
s4.6, summarizing the relation surfaces formed by the arrays in a space rectangular coordinate system to obtain a relation curved surface between the material storage environment deviation value and the material quality influence rate when the type number of the stored material is WZB, and marking the relation curved surface as GM WZB, thereby obtaining the relation between different material storage environment deviation values and the material quality influence rate;
the method for acquiring the relation surface formed by four coordinate points in each array in S4.5 comprises the following steps:
S4.5.1, obtaining four coordinate points in each array,
The coordinate point with the smallest sum of the x-axis coordinate and the y-axis coordinate in the four coordinate points in the array is marked as a first coordinate point,
Subtracting the sum of the x-axis coordinate and the y-axis coordinate in the first coordinate point from the sum of the x-axis coordinate and the y-axis coordinate in the four coordinate points in the array, marking the coordinate point with the result of c1 as a second coordinate point,
Subtracting the sum of the x-axis coordinate and the y-axis coordinate in the first coordinate point from the sum of the x-axis coordinate and the y-axis coordinate in the four coordinate points in the array, marking the coordinate point with the result of c2 as a third coordinate point,
Marking the coordinate point with the largest sum of the x-axis coordinate and the y-axis as a fourth coordinate point in the four coordinate points in the array;
s4.5.2, obtaining a fifth coordinate point (x 1, y1, z 1) corresponding to the array,
X1 is equal to the average value of x-axis coordinates corresponding to four coordinate points in the array, y1 is equal to the average value of y-axis coordinates corresponding to four coordinate points in the array, and z1 is equal to the average value of z-axis coordinates corresponding to four coordinate points in the array;
S4.5.3, obtaining a relation surface formed by four coordinate points in the array, wherein the relation surface corresponding to the array is formed by a first relation surface, a second relation surface, a third relation surface and a fourth relation surface,
The first relation surface is an area surrounded by the three points in the plane where the first coordinate point, the second coordinate point and the fifth coordinate point are located in the array,
The second relation surface is an area surrounded by the three points in the plane where the first coordinate point, the third coordinate point and the fifth coordinate point are located in the array,
The third relation surface is an area surrounded by the second coordinate point, the fourth coordinate point and the fifth coordinate point in the plane where the second coordinate point, the fourth coordinate point and the fifth coordinate point are positioned,
The fourth relation surface is an area surrounded by the third coordinate point, the fourth coordinate point and the fifth coordinate point in the plane where the third coordinate point, the fourth coordinate point and the fifth coordinate point are located in the array;
The method for analyzing the relation between the storage environment information and the warehouse environment comprehensive information in the storage areas with different numbers according to the historical data in the S5 comprises the following steps:
S5.1, when the temperature in the comprehensive information of the warehouse environment in the historical data is WZ, various monitoring temperatures of the sensor in the storage area with the number of B and the total duration corresponding to each monitoring temperature are obtained,
S5.2, when the humidity in the comprehensive information of the warehouse environment in the historical data is SZ, various monitoring humidity of the sensor in the storage area with the number of B and the total duration corresponding to each monitoring humidity are obtained,
S5.3, when the comprehensive information of the warehouse environment is (WZ, SZ), storing the prediction result (WBWZ, SBSZ) of the environment information in the storage area with the number of B,
Wherein n1 represents the number of types of the temperature monitored by the sensor in the storage area with the number of B when the temperature in the comprehensive information of the warehouse environment in the historical data is WZ,
WBWZn shows the nth temperature corresponding value monitored by the sensor in the storage area with the number of B when the temperature in the comprehensive information of the warehouse environment in the historical data is WZ,
TBWZn denotes the total time length corresponding to the nth temperature monitored by the sensor in the storage area with the number B when the temperature in the comprehensive information of the warehouse environment in the historical data is WZ,
Wherein n3 represents the number of types of humidity monitored by the sensor in the storage area with the number of B when the humidity in the comprehensive information of the warehouse environment in the historical data is SZ,
SBSZn2 denotes the corresponding value of the n 2-th humidity monitored by the sensor in the storage area with the number B when the humidity in the comprehensive information of the warehouse environment in the historical data is SZ,
TBSZn2 is the total time length corresponding to the nth 2 humidity monitored by the sensor in the storage area with the number of B when the humidity in the comprehensive information of the warehouse environment in the historical data is SZ;
S5.4, when B is obtained to be different values, respectively corresponding (WBWZ, SBSZ) to each (WZ, SZ), and inputting each (WBWZ, SBSZ) into a blank set one by one to obtain a set corresponding to (WZ, SZ);
s5.5, when WZ or SZ is obtained to be different values, respectively corresponding sets of the WZ and the SZ to obtain the relation between the storage environment information and the warehouse environment comprehensive information in the storage areas with different numbers;
the method for predicting the comprehensive influence values corresponding to all materials stored in the warehouse under different conditions in the S6 comprises the following steps:
S6.1, acquiring the times and the time length of each storage of the storage materials with the category number WZB in the warehouse in the latest first time period in the historical data, calculating the average value of the time length of each storage of the storage materials with the category number WZB in the warehouse as a storage time length reference value corresponding to the storage materials with the category number WZB, and marking as TG WZB;
s6.2, acquiring material storage information { BtT, BLt, (WBt, SBt), (WZt, SZt) } in a storage area with the number B at the time T, marking a time point corresponding to the current time as T2, and obtaining material storage information { Bt2T, BLt2, (WBt, SBt 2), (WZt, SZt) in the storage area with the number B at the time T2;
S6.3, when the comprehensive information of the warehouse environment is (YWZ, YSZ), the comprehensive influence values ZYX corresponding to all materials stored in the warehouse are obtained,
Wherein B1 represents the total number of storage areas divided in the warehouse,
G (B, YWZ, YSZ) represents the material quality influence rate corresponding to the material stored in the storage area with the current time number B when the comprehensive information of the warehouse environment is (YWZ, YSZ);
the method for obtaining G (B, YWZ, YSZ) comprises the following steps:
Step one, obtaining the type number BLt2 of the storage material in the storage area with the current time number B,
Step two, when the type number of the stored material is BLt2, a relation curved surface GM BLt2 between a material storage environment deviation value and a material quality influence rate is obtained,
Step three, in the relation between the storage environment information in the storage areas with different numbers and the warehouse environment comprehensive information, when the warehouse environment comprehensive information is (YWZ, YSZ), the storage environment information in the storage area with the number B is marked as (YWZB, YSZB),
Step four, obtaining the optimal storage environment information corresponding to the stored material type number BLt2 in the database (W1 BLt2,S1BLt2),W1BLt2 represents the temperature in the optimal environment information corresponding to BLt2, S1 BLt2 represents the humidity in the optimal environment information corresponding to BLt 2;
Substituting the (YWZB-W1 BLt2,YSZB-S1BLt2) serving as a storage deviation value into GM BLt2 to obtain a corresponding material quality influence rate G (B, YWZ, YSZ);
The method for acquiring E (Bt 2T, BLt 2) comprises the following steps:
firstly, obtaining a storage time length reference value TG BLt2 corresponding to a storage material with a type number BLt 2;
Step two, acquiring a storage time BtT of a storage material in a storage area with the current time number B;
a third step of obtaining the value of E (Bt 2T, BLt 2),
When TG BLt2 -BtT2 is not less than T1, then E (Bt 2T, BLt 2) =t1 is determined,
When TG BLt2 -BtT2 < T1, then E (Bt 2T, BLt 2) =tg BLt2 -BtT is determined.
2. The method for monitoring and guiding a 3D intelligent warehouse based on digital twinning according to claim 1, wherein the method for dividing the storage space in the warehouse into a plurality of storage areas in S1 comprises the following steps:
S1.1, acquiring a length a1, a width a2 and a height a3 corresponding to a space region in each storage shelf in a warehouse, wherein the specifications of different storage shelves are the same by default, and the storage space in the warehouse is a union of the space regions in each storage shelf in the warehouse;
S1.2, obtaining the greatest common divisor corresponding to the three numbers a1, a2 and a3, and recording the greatest common divisor as a4;
S1.3, equally dividing the space area in each storage shelf in the warehouse into a1 a 2a 3/a4 3 storage areas with the same specification, wherein the specification of each storage area is as follows: the length, width and height of the storage area are equal to a4;
Numbering each storage area in all storage shelves in the warehouse from 1, wherein each storage area corresponds to one number, the numbers corresponding to different storage areas are different,
The three-dimensional model with the same size as the warehouse comprises the distribution positions of all storage shelves in the warehouse relative to the center point of the warehouse.
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