Temperature monitoring method, system, electronic device and storage medium of a drying system

Abstract

The application discloses a kind of temperature monitoring method, system, electronic equipment and storage medium of drying system, it is related to drying system monitoring technical field, method includes: to the temperature value of each preset position of reference drying system is associated degree analysis, according to the result of associated degree analysis, determine multiple target positions;Temperature acquisition is carried out by setting the temperature sensor of each target position of target drying system, and according to the temperature value of each target position, back-propagation temperature value of each non-target position of target drying system;In the application, only need to install temperature sensor in each target position, can monitor the temperature value of all preset positions, on the one hand, can reduce the operation such as punching or recess on the equipment of drying system, guarantee the running stability of drying system, on the other hand, can effectively reduce the interference caused by optimization design to drying system, and, can also effectively reduce cost.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of drying system monitoring, and particularly relates to a temperature monitoring method and system for a drying system, an electronic device and a storage medium. BACKGROUND

[0002] The drying system is a system device for dewatering and drying slurry. For example, the drying system can be used for dewatering and drying cellulose, ammonium sulfate, ammonium chloride and mirabilite. At present, a plurality of temperature sensors are installed in the drying system to monitor the temperature of a plurality of positions of the drying system, so that the temperature abnormality can be learned in time. On the one hand, in order to better fix the temperature sensors, holes or grooves are often punched or formed on the equipment of the drying system, which affects the running stability of the drying system. On the other hand, when the temperature sensors are arranged at a plurality of positions, the optimal design of the drying system is affected, and the cost is increased. SUMMARY

[0003] The present application solves the technical problems of the prior art, and specifically provides a temperature monitoring method and system for a drying system, an electronic device and a storage medium, which are as follows.

[0004] 1) In a first aspect, the present application provides a temperature monitoring method for a drying system, and the specific technical solutions are as follows.

[0005] The temperature values of each preset position of a reference drying system are analyzed in terms of correlation degree, and a plurality of target positions are determined according to the correlation degree analysis result.

[0006] The temperature sensors of each target position of a target drying system are set to collect the temperature, and the temperature values of each non-target position of the target drying system are inversely deduced according to the temperature values of each target position.

[0007] The reference drying system and the target drying system are two identical drying systems.

[0008] The temperature monitoring method for the drying system provided by the present application has the following beneficial effects.

[0009] Only the temperature sensors need to be installed at each target position, so that the temperature values of all preset positions can be monitored. On the one hand, the operation of punching holes or forming grooves on the equipment of the drying system can be reduced, so that the running stability of the drying system is ensured. On the other hand, the interference caused by the optimal design of the drying system can be effectively reduced, and the cost can be effectively reduced.

[0010] On the basis of the above-mentioned scheme, the temperature monitoring method for the drying system of the present application can be further improved as follows.

[0011] Further, the temperature values of each preset position of the reference drying system are subjected to correlation degree analysis, and according to the correlation degree analysis result, a plurality of target positions are determined, including:

[0012] The temperature values of each preset position of the reference drying system within a preset time period are acquired to obtain a plurality of time-temperature sequence data;

[0013] The plurality of time-temperature sequence data are subjected to similarity analysis, and according to the similarity analysis result, all the preset positions are divided into a plurality of groups, wherein the similarity between the time-temperature sequence data of each two preset positions in the same group all exceeds a preset similarity threshold, and the similarity represents the correlation degree;

[0014] One preset position in each group is selected as a target position.

[0015] The beneficial effect of the above further scheme is that since the similarity between the time-temperature sequence data of each two preset positions in the same group all exceeds the preset similarity threshold, the correlation degree between the temperature values of each two preset positions in the same group is high, and therefore, one preset position in each group is selected as a target position, and the temperature value of each non-target position in the group where the target position is located can be accurately back-calculated through any target position, thereby ensuring the accuracy of temperature monitoring.

[0016] Further, according to the temperature value of each target position, the temperature value of each non-target position of the target drying system is back-calculated, including:

[0017] Based on the time-temperature sequence data of each preset position in each group, the temperature value of each non-target position of the target drying system is back-calculated.

[0018] The beneficial effect of the above further scheme is that based on the functional relationship between the time-temperature sequence data of each preset position in each group and the corresponding fitting curve, the accuracy of the calculated temperature value of each non-target position of the target drying system can be ensured.

[0019] Further, it further includes determining whether to issue a warning information according to the temperature value of each target position and the temperature value of each non-target position of the target drying system.

[0020] The beneficial effect of the above further scheme is that when a temperature abnormality occurs, a warning information can be timely issued so as to facilitate timely processing by the operation and maintenance personnel.

[0021] 2) In a second aspect, the present application further provides a temperature monitoring system of a drying system, and the specific technical scheme is as follows:

[0022] The temperature monitoring system includes a target position determination module and a temperature back-calculation module;

[0023] The target position determining module is configured to: perform correlation degree analysis on temperature values of each preset position of the reference drying system, and determine a plurality of target positions according to a result of the correlation degree analysis.

[0024] The temperature back-calculation module is configured to: collect temperature values of each target position of the target drying system by setting temperature sensors of the target drying system, and back-calculate temperature values of each non-target position of the target drying system according to the temperature values of each target position.

[0025] The reference drying system and the target drying system are two identical drying systems.

[0026] Based on the above scheme, the temperature monitoring system of the drying system can be further improved as follows.

[0027] Further, the target position determining module is specifically configured to:

[0028] obtain temperature values of each preset position of the reference drying system in a preset time period, and obtain a plurality of time-temperature sequence data;

[0029] perform similarity analysis on the plurality of time-temperature sequence data, and divide all the preset positions into a plurality of groups according to a result of the similarity analysis, wherein a similarity between time-temperature sequence data of each two preset positions in a same group exceeds a preset similarity threshold, and the similarity represents a correlation degree;

[0030] select one preset position in each group as a target position.

[0031] Further, the temperature back-calculation module is specifically configured to: back-calculate the temperature values of each non-target position of the target drying system based on the time-temperature sequence data of each preset position in each group.

[0032] Further, the temperature monitoring system further comprises a warning module, the warning module is configured to: determine whether to send a warning information according to the temperature values of each target position and the temperature values of each non-target position of the target drying system.

[0033] 3) In a third aspect, the present application further provides an electronic device, the electronic device comprising a processor and a memory, the memory storing at least one computer program, the at least one computer program being loaded and executed by the processor to enable the electronic device to implement any of the above drying system temperature monitoring methods.

[0034] 4) In a fourth aspect, the present application further provides a computer readable storage medium, the computer readable storage medium storing a computer program, the computer program being executed by a processor to implement any of the above drying system temperature monitoring methods.

[0035] It should be noted that the technical solutions of the second aspect to the fourth aspect of the present application and the corresponding possible implementation manners have the beneficial effects as described above for the first aspect and its corresponding possible implementation manners, which will not be repeated here. BRIEF DESCRIPTION OF DRAWINGS

[0036] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments of the present application will be briefly introduced as follows:

[0037] Figure 1 A flowchart of a temperature monitoring method of a drying system according to an embodiment of the present application;

[0038] Figure 2 A structural diagram of a temperature monitoring system of a drying system according to an embodiment of the present application;

[0039] Figure 3 A structural diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0040] The principles and features of the present application will be described below, and the examples are only used to explain the present application, and are not used to limit the scope of the present application.

[0041] The technical solutions of the present application and how the technical solutions of the present application solve the above technical problems will be described in detail below. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of the present application will be described below with reference to the drawings.

[0042] As shown in Figure 1 A temperature monitoring method of a drying system according to an embodiment of the present application includes the following steps:

[0043] S1, correlation degree analysis is performed on the temperature values of each preset position of the reference drying system, and according to the correlation degree analysis result, a plurality of target positions are determined;

[0044] The drying system includes a feeding device, an air chamber, a steam device, a heating device, a fan, a condenser, an evaporator, and a boiling bed or a fluidized bed arranged in the air chamber.

[0045] The heat exchange medium of the boiling bed in the drying system can be air, nitrogen, carbon dioxide, water, glycerol, ethylene glycol, insulating oil, or heat conducting oil, and the heat exchange medium of the fluidized bed can be air, nitrogen, carbon dioxide, water, or heat conducting oil.

[0046] The preset positions can be set according to experience, for example, a plurality of preset positions are determined on a boiling bed or a fluidized bed, a plurality of preset positions are determined at the center or each side of the air chamber, a plurality of preset positions are determined on the heating device, etc.

[0047] S2, collecting temperature through a temperature sensor arranged at each target position of the target drying system, and inversely deducing a temperature value of each non-target position of the target drying system according to the temperature value of each target position;

[0048] The reference drying system and the target drying system are two identical drying systems, and it should be noted that the difference between the reference drying system and the target drying system is the number of temperature sensors arranged, the reference drying system is a drying system used for experiments to determine a plurality of target positions, and the target drying system is an actually used drying system.

[0049] Optionally, in S1, a correlation degree analysis is performed on the temperature value of each preset position of the reference drying system, and a plurality of target positions are determined according to the correlation degree analysis result, including:

[0050] S10, obtaining a temperature value of each preset position of the reference drying system within a preset time period to obtain a plurality of time-temperature sequence data;

[0051] The temperature value of each preset position of the reference drying system within the preset time period is collected through a temperature sensor (denoted as a first temperature sensor) arranged at each preset position of the reference drying system, the collection frequency of all first temperature sensors is the same, and the specific value of the collection frequency can be set according to actual conditions.

[0052] The start time and the end time of the preset time period can be set according to actual conditions, and the length of the preset time period can also be set according to actual conditions, for example, the length of the preset time period is 1 hour or 2 hours, etc.

[0053] The temperature value collected by each first temperature sensor within the preset time period forms a time-temperature sequence data.

[0054] S11, performing similarity analysis on the plurality of time-temperature sequence data, and dividing all preset positions into a plurality of groups according to the similarity analysis result, wherein the similarity between the time-temperature sequence data of each two preset positions in the same group exceeds a preset similarity threshold, and the similarity represents a correlation degree;

[0055] The similarity analysis on any two time-temperature sequence data can be performed in the following manner, for the convenience of description, any two time-temperature sequence data are denoted as a first time-temperature sequence data and a second time-temperature sequence data, and then:

[0056] 1) The first similarity calculation method:

[0057] The Fourier transform is performed on the first time temperature sequence data and the second time temperature sequence data respectively to obtain a Fourier transform curve corresponding to the first time temperature sequence data and a Fourier transform curve corresponding to the second time temperature sequence data. A plurality of peak points are selected from the Fourier transform curve corresponding to the first time temperature sequence data and the Fourier transform curve corresponding to the second time temperature sequence data respectively, and the abscissa and ordinate of each peak point are obtained. Then, the similarity of the two groups of peak points is calculated as the similarity between the first time temperature sequence data and the second time temperature sequence data. The similarity can be a cosine similarity, or other types of similarity. Through the two groups of peak points, the calculation amount can be greatly reduced, and the calculation efficiency can be improved.

[0058] 2) The second similarity calculation method:

[0059] The first time temperature sequence data and the second time temperature sequence data are respectively curve fitted, and the curve corresponding to the first time temperature sequence data and the curve corresponding to the second time temperature sequence data are respectively placed in a layer to obtain a first image and a second image. The first image includes the curve corresponding to the first time temperature sequence data, and the second image includes the curve corresponding to the second time temperature sequence data. The similarity between the first image and the second image is calculated, and the similarity between the first image and the second image is taken as the similarity between the first time temperature sequence data and the second time temperature sequence data.

[0060] It should be noted that the similarity calculated by the first similarity calculation method and the second similarity calculation method is the similarity between the data trends of the first time temperature sequence data and the second time temperature sequence data, rather than the similarity of the data size. The advantage is that the temperature values of each preset position in each group tend to be consistent, so that the temperature values of other preset positions of the group can be inferred from the temperature values of any preset position.

[0061] Through the first similarity calculation method or the second similarity calculation method, similarity analysis can be performed on each two time temperature sequence data to obtain a similarity analysis result. The similarity analysis result includes the similarity between each two time temperature sequence data.

[0062] The preset similarity threshold can be set according to actual conditions, for example, the preset similarity threshold can be 0.8, etc.

[0063] S12, a preset position is selected as a target position in each group.

[0064] Among them, a preset position in each group can be randomly selected as a target position, and other preset positions are non-target positions.

[0065] In S10 to S12, the correlation degree is represented by similarity, and therefore, similarity analysis on the plurality of time-temperature sequence data is equivalent to correlation degree analysis on the temperature values of each preset position of the reference drying system, and the similarity analysis result is the correlation degree analysis result.

[0066] Optionally, in S2, the temperature values of each non-target position of the target drying system are inversely deduced according to the temperature values of each target position, including:

[0067] Based on the time-temperature sequence data of each preset position in each group, the temperature values of each non-target position of the target drying system are inversely deduced, and the specific implementation process is as follows:

[0068] S20, the time-temperature sequence data of each preset position in each group is fitted respectively to obtain a fitting curve corresponding to each group respectively.

[0069] In each group, the time-temperature sequence data of each preset position is data cleaned (noise and outliers are removed), and then a polynomial regression method, a nonlinear regression method, a spline interpolation method or a machine learning algorithm (such as a support vector machine or a neural network) is used to fit the time-temperature sequence data of each preset position in each group to obtain a fitting curve corresponding to each group respectively.

[0070] S21, according to the time-temperature sequence data of each preset position in each group and the corresponding fitting curve, a function relationship between the temperature value of each preset position in each group and the temperature value in the corresponding fitting curve is constructed.

[0071] S22, according to the temperature value of each target position, and in combination with the corresponding function relationship and fitting curve, the temperature value of each non-target position of the target drying system is determined, specifically:

[0072] When the temperature value of any target position is obtained, the temperature value in the fitting curve corresponding to the temperature value of the target position can be calculated according to the function relationship between the temperature value of the target position and the temperature value in the corresponding fitting curve, and then the temperature value of each non-target position in the group where the target position is located can be calculated using the function relationship between each non-target position in the group and the temperature value in the corresponding fitting curve, until the temperature value of each non-target position of the target drying system is calculated.

[0073] Optionally, in the above technical solution, it further includes:

[0074] S3, determine whether to issue a warning information according to the temperature value of each target position and the temperature value of each non-target position of the target drying system, which can be realized by the following way:

[0075] 1) The first implementation manner:

[0076] A temperature range is set for each target position and each non-target position, and when the temperature value of any target position or non-target position is not in the corresponding temperature range, a temperature abnormality warning information is issued.

[0077] 2) The second implementation manner:

[0078] A temperature range is set for each target position and each non-target position, and when the temperature value of any target position or non-target position is not in the corresponding temperature range, a temperature abnormality warning information is issued.

[0079] 3) The third implementation manner:

[0080] A temperature range is set for each target position and each non-target position, and a plurality of sub-ranges are determined outside each temperature range, each sub-range is set with a warning information, and the warning information to be issued is determined according to the range of the temperature value of each target position and the temperature value of each non-target position.

[0081] Optionally, in the above technical solution, each target position and each non-target position is taken as a node (for easy distinction, referred to as a first node), in each group, a target position and each non-target position are connected by an edge (for easy distinction, referred to as a first edge), a topology structure is constructed, and the corresponding position information is associated with each first node of the topology structure, the position information includes a three-dimensional structure diagram and material, etc., when a temperature abnormality warning information is issued, the first node (target position or non-target position) corresponding to the warning information is displayed differently in the graph structure, and each node associated with the first node is displayed differently (if two nodes are connected by a first edge, it is said that the two first nodes are associated), specifically, it can be highlighted or displayed differently by color, and when the first node is clicked, the position information is popped up for the maintenance personnel to view, improving the processing effect.

[0082] Optionally, a three-dimensional structure model of the drying system is constructed, the temperature value of each target position and the temperature value of each non-target position collected are associated with the corresponding position in the three-dimensional structure model, and different colors are used to distinguish the ranges to which the temperature values belong, thereby obtaining a three-dimensional temperature distribution cloud map, wherein, a plurality of temperature value ranges are pre-divided, and corresponding colors are set.

[0083] Optionally, in the above technical solution, further comprising:

[0084] S101, when the operation and maintenance personnel check the three-dimensional temperature distribution cloud picture, if a request of obtaining and saving the three-dimensional temperature distribution cloud picture is sent, a coordinate (x-axis coordinate value, y-axis coordinate value and z-axis coordinate value) of any preset position in the three-dimensional structure model and a temperature value of the preset position are combined to form an array, the format of the array is: (x-axis coordinate value, y-axis coordinate value, z-axis coordinate value, temperature value), until the array corresponding to each preset position is obtained, the array corresponding to the target position in each group and the array corresponding to each non-target position are taken as nodes (denoted as second nodes), edges (denoted as second edges) are connected between each two second nodes corresponding to each group, thereby obtaining an undirected graph (denoted as a first undirected graph for convenience of distinction) corresponding to each group, and an adjacency matrix of each first undirected graph is generated.

[0085] S102, the adjacency matrix corresponding to each group is taken as a perturbation of each array in the corresponding group, specifically, all elements in each adjacency matrix are divided into 4 parts according to the order, the number of elements in the 4 parts can be the same or different, the 4 parts correspond to each data (x-axis coordinate value, y-axis coordinate value, z-axis coordinate value and temperature value) in the corresponding each array one by one, and the sum of the products of each part and the corresponding data is taken as new data, until each new data in each array is obtained.

[0086] S103, each new data in each array is sent to the cloud, and the three-dimensional temperature distribution cloud picture is sent to the cloud (specifically, a cloud server), the cloud verifies the identity information provided by the operation and maintenance personnel, when the verification is passed, the cloud sends each new data in each array to the intelligent terminal of the operation and maintenance personnel, and sends the three-dimensional temperature distribution cloud picture to the intelligent terminal of the operation and maintenance personnel.

[0087] S104, the adjacency matrix corresponding to each group and the corresponding relationship between the adjacency matrix and the group are sent to the intelligent terminal of the operation and maintenance personnel, so that the intelligent terminal of the operation and maintenance personnel respectively constructs equations according to the received adjacency matrix corresponding to each group and each new data in each array, calculates to obtain each data (x-axis coordinate value, y-axis coordinate value, z-axis coordinate value and temperature value) in each array, and then associates each data (x-axis coordinate value, y-axis coordinate value, z-axis coordinate value and temperature value) in each array to the three-dimensional temperature distribution cloud picture, and reconstructs to obtain the three-dimensional temperature distribution cloud picture.

[0088] Through S101 to S104, without uploading real data to the cloud, data leakage can be effectively prevented, and data security can be ensured. Moreover, in the manner of an adjacency matrix, each data in each array is encrypted, the data calculation amount is small, and the calculation amount of each data in each array is small, and there has never been a technology of using an adjacency matrix for data encryption in the prior art, which can further improve data security. It should be noted that by sending each new data in each array and the three-dimensional temperature distribution cloud to the intelligent terminal of the operation and maintenance personnel through the cloud, the data transmission amount between the intelligent terminal of the operation and maintenance personnel and the execution subject (such as a computer device) of the temperature monitoring method of the drying system can be effectively reduced, and the execution subject of the temperature monitoring method of the drying system can be ensured to be in a good operating state.

[0089] Optionally, in the above technical solution, further comprising:

[0090] S201, a feedback request is sent to the intelligent terminal of the operation and maintenance personnel, and the intelligent terminal of the operation and maintenance personnel uses a preset hash function to perform hash calculation on an array sequence composed of all arrays calculated in a preset order to obtain a first hash calculation result;

[0091] S202, the execution subject (such as a computer device) of the temperature monitoring method of the drying system uses a preset hash function to perform hash calculation on an array sequence composed of all arrays in a preset order to obtain a second hash calculation result, receives the first hash calculation result returned by the intelligent terminal of the operation and maintenance personnel, and judges whether the first hash calculation result and the second hash calculation result are the same. If they are the same, it means that all arrays calculated by the intelligent terminal of the operation and maintenance personnel are accurate, and if they are not the same, it means that all arrays calculated by the intelligent terminal of the operation and maintenance personnel are inaccurate, and a prompt is sent to the intelligent terminal of the operation and maintenance personnel in time.

[0092] The preset hash function and the preset order can be set according to actual conditions.

[0093] Through S201 to S202, it can be effectively judged whether all arrays calculated by the intelligent terminal of the operation and maintenance personnel are correct, and through hash calculation, data security can be ensured, and the data transmission amount between the intelligent terminal of the operation and maintenance personnel and the execution subject of the temperature monitoring method of the drying system can be reduced.

[0094] Optionally, in the above technical solution, further comprising: when the execution subject of the temperature monitoring method of the drying system of the application receives a sharing request sent by the intelligent terminal, judging whether the to-be-shared intelligent terminal and the user of the to-be-shared intelligent terminal involved in the sharing request are trustworthy, if yes, issuing an allowed sharing permission to the intelligent terminal, if no, prohibiting the intelligent terminal from issuing an allowed sharing permission. Wherein, the sharing request refers to a request for sharing the three-dimensional temperature distribution cloud picture generated by the intelligent terminal, the allowed sharing permission refers to allowing the intelligent terminal to send the generated three-dimensional temperature distribution cloud picture to the to-be-shared intelligent terminal, and the sharing request includes the unique identification code (which can be MAC address and mobile phone number, etc.) of the to-be-shared intelligent terminal and the identity information (including name, face image and fingerprint, etc.) of the user of the to-be-shared intelligent terminal.

[0095] Wherein, judging whether the to-be-shared intelligent terminal and the user of the to-be-shared intelligent terminal involved in the sharing request are trustworthy is specifically realized by the following way:

[0096] S301, a white list and a black list are set in advance, the white list records a plurality of unique identification codes, and the intelligent terminal corresponding to the unique identification code in the white list and the corresponding user are trustworthy by default, and the black list also records a plurality of unique identification codes, and the intelligent terminal corresponding to the unique identification code in the black list is untrustworthy by default.

[0097] S302, judging whether the unique identification code of the to-be-shared intelligent terminal is on the black list or the white list, then:

[0098] 1) When the unique identification code of the to-be-shared intelligent terminal is on the white list, it is determined that the to-be-shared intelligent terminal is trustworthy.

[0099] 2) When the unique identification code of the to-be-shared intelligent terminal is on the black list, it is determined that the to-be-shared intelligent terminal is untrustworthy, and the corresponding user is also untrustworthy by default, so S303 need not be executed.

[0100] 3) When the unique identification code of the to-be-shared intelligent terminal is not on the white list and the black list, S303 is executed.

[0101] S303, obtaining the communication record of the to-be-shared intelligent terminal, determining the intelligent terminal having a communication relationship with the to-be-shared intelligent terminal, for the convenience of distinction, the intelligent terminal having a communication relationship with the to-be-shared intelligent terminal is recorded as the first intelligent terminal, and then based on the communication record, a undirected graph (for the convenience of distinction, recorded as the second undirected graph) is constructed, in the second undirected graph, the to-be-shared intelligent terminal and each first intelligent terminal are nodes (for the convenience of distinction, recorded as the third node), and there is an edge (for the convenience of distinction, recorded as the third edge) between two third nodes having a communication relationship.

[0102] A complete graph including the nodes corresponding to the smart terminals to be shared is obtained from the second undirected graph, and in the complete graph, each two third nodes are connected by a third edge, that is, each two third nodes have a communication relationship.

[0103] Each first smart terminal corresponding to each third node other than all the nodes included in the complete graph in the second undirected graph is recorded as a second smart terminal, one second smart terminal is randomly selected, and one first smart terminal is randomly selected from all the first smart terminals in the complete graph, the name and / or face information of the smart terminal to be shared are assistedly authenticated by using the randomly selected first smart terminal and the randomly selected second smart terminal, and the identity information of the user of the smart terminal to be shared is verified by the execution subject of the temperature monitoring method of the drying system, and after both the authentication and the verification are passed, it is determined that the user of the shared smart terminal and the unique identification code are reliable, and the unique identification code of the smart terminal to be shared and the user of the smart terminal to be shared are added to the white list.

[0104] In S303, the smart terminals having a communication relationship with the smart terminal to be shared are classified (the first smart terminals corresponding to each third node included in the complete graph are one class, and all the second smart terminals are another class), and then a first smart terminal and a second smart terminal are randomly selected from each class for assisted authentication, which can enhance the reliability of the identity verification of the smart terminal to be shared and further ensure data security.

[0105] In the above embodiments, although the steps are numbered S1, S2, etc., this is only a specific embodiment given by the present application, and those skilled in the art can adjust the execution order of S1, S2, etc. according to the actual situation, which is within the protection scope of the present application. It can be understood that in some embodiments, some or all of the above embodiments can be included.

[0106] As shown in FIG. 1, a temperature monitoring system 200 of a drying system according to an embodiment of the present application includes a target position determination module 201 and a temperature back calculation module 202. Figure 2

[0107] The target position determination module 201 is configured to perform correlation degree analysis on the temperature values of each preset position of a reference drying system, and determine a plurality of target positions according to the correlation degree analysis result.

[0108] The temperature back calculation module 202 is configured to collect temperature values by setting temperature sensors at each target position of a target drying system, and back calculate temperature values of each non-target position of the target drying system according to the temperature values of each target position.

[0109] The reference drying system and the target drying system are two identical drying systems.​

[0110] Optionally, in the above technical solution, the target position determination module 201 is specifically configured to:

[0111] obtain temperature values of each preset position of the reference drying system within a preset time period to obtain a plurality of time-temperature sequence data;

[0112] perform similarity analysis on the plurality of time-temperature sequence data, and divide all the preset positions into a plurality of groups according to the similarity analysis result, wherein the similarity between the time-temperature sequence data of each two preset positions in the same group exceeds a preset similarity threshold, and the similarity represents the degree of association;

[0113] select one preset position in each group as a target position.

[0114] Optionally, in the above technical solution, the temperature backstepping module 202 is specifically configured to: backstep the temperature value of each non-target position of the target drying system based on the time-temperature sequence data of each preset position in each group.

[0115] Optionally, in the above technical solution, further comprising a warning module, the warning module is configured to: determine whether to issue a warning information according to the temperature value of each target position and the temperature value of each non-target position of the target drying system.

[0116] It should be noted that the beneficial effects of the drying system temperature monitoring system 200 provided by the above embodiment are the same as those of the above drying system temperature monitoring method, and will not be repeated here. In addition, the system provided in the above embodiment is only exemplified by the division of the above functional modules when realizing its function, and in actual application, the above functions can be completed by different functional modules according to the needs, that is, the system is divided into different functional modules according to the actual situation to complete all or part of the above described functions. In addition, the system and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is shown in the method embodiment, which will not be repeated here.

[0117] Among them, the drying system temperature monitoring system of the present application can be a computer program (including program code) running in a computer device, for example, the drying system temperature monitoring system of the present application is an application software, which can be used to execute the corresponding steps in the drying system temperature monitoring method of the present application.

[0118] In some embodiments, the temperature monitoring system of the drying system of the present invention can be implemented in a combination of hardware and software. As an example, the temperature monitoring system of the drying system of the present invention can be a processor in the form of a hardware decoding processor, which is programmed to execute the temperature monitoring method of the drying system of the present invention. For example, the processor in the form of a hardware decoding processor can be one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs), or other electronic components.

[0119] The modules described in the embodiments of this invention can be implemented in software or hardware. The names of the modules are not, in some cases, limiting the scope of the module itself.

[0120] An electronic device according to an embodiment of the present invention includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements any of the above-described temperature monitoring methods for the drying system. That is, an electronic device according to an embodiment of the present invention may include, but is not limited to: a processor and a memory; the memory is used to store the computer program; the processor is used to execute the temperature monitoring method of the drying system shown in any embodiment of the present invention by calling the computer program.

[0121] In one alternative embodiment, an electronic device is provided, such as Figure 3 As shown, Figure 3 The illustrated electronic device 4000 includes a processor 4001 and a memory 4003. The processor 4001 and the memory 4003 are connected, for example, via a bus 4002. Optionally, the electronic device 4000 may further include a transceiver 4004, which can be used for data interaction between the electronic device and other electronic devices, such as sending and / or receiving data. It should be noted that in practical applications, the transceiver 4004 is not limited to one type, and the structure of the electronic device 4000 does not constitute a limitation on the embodiments of the present invention.

[0122] The processor 4001 can be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other programmable logic device, transistor logic device, hardware component, or any combination thereof. It can implement or execute various exemplary logical blocks, modules and circuits described in connection with the present disclosure. The processor 4001 can also be a combination of computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, and the like.

[0123] The bus 4002 can include a path for transmitting information between the above-mentioned components. The bus 4002 can be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, or the like. The bus 4002 can be divided into an address bus, a data bus, a control bus, and the like. For convenience of representation, Figure 3 The bus 4002 is represented by only one thick line, but it does not mean that there is only one bus or only one type of bus.

[0124] The memory 4003 can be a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, a RAM (Random Access Memory) or other type of dynamic storage device that can store information and instructions, an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited thereto.

[0125] The memory 4003 is configured to store application code (computer program) for implementing the solutions of the present application, and the processor 4001 is configured to control the execution. The processor 4001 is configured to execute the application code stored in the memory 4003 to implement the content shown in the foregoing method embodiments.

[0126] The electronic device can also be a terminal device, and the terminal device can be any device that can install an application, including at least one of a smartphone, a tablet computer, a notebook computer, a desktop computer, a smart speaker, a smart watch, a smart television, and a smart vehicle device.

[0127] It should be noted that, Figure 3 The electronic device shown is only an example and should not limit the functions and use range of the embodiments of the present application.

[0128] The computer readable storage medium of the embodiment of the present application, the computer readable storage medium stores a computer program, and the computer program is executed by the processor to realize the temperature monitoring method of any one of the above drying systems.

[0129] Optionally, the computer readable storage medium can be a read-only memory (Read-Only Memory, ROM), a random access memory (Random Access Memory, RAM), a read-only compact disc (Compact Disc Read-Only Memory, CD-ROM), a magnetic tape, a floppy disk, and an optical data storage device, etc.

[0130] In the exemplary embodiments, a computer program product or computer program is also provided, which includes computer instructions stored in a computer readable storage medium. The processor of the electronic device reads the computer instructions from the computer readable storage medium, and the processor executes the computer instructions to make the electronic device execute the temperature monitoring method of any one of the above drying systems.

[0131] Computer program code for carrying out operations of the present application can be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0132] It should be understood that the flowchart and block diagrams in the drawings illustrate the architecture, functionality, and operation of possible implementations of various embodiments of the present application. In this regard, each block in the flowchart and block diagrams can represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions noted in the blocks can occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently or the blocks can sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and / or flowchart illustrations, and combinations thereof, can be implemented by a dedicated hardware-based system that performs the specified functions or operations, or combinations of hardware and software.

[0133] The computer readable storage medium of embodiments of the present application can be, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of the computer readable storage medium can include, but are not limited to, the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present application, the computer readable storage medium can be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

[0134] The computer readable storage medium described above bears one or more programs, when the one or more programs are executed by the electronic device, the electronic device executes the method shown in the above embodiment.

[0135] The above description is merely exemplary of the application and the application principles of the technology used. Those skilled in the art should understand that the disclosed range of the application is not limited to the technical solutions formed by the specific combinations of the above technical features, and should also cover other technical solutions formed by any combinations of the above technical features or their equivalent features without departing from the disclosed concept. For example, the above features are replaced with the technical features disclosed in the application (but not limited to) having similar functions to form technical solutions.

[0136] It should be noted that the terms "first", "second" and the like in the specification and claims of the present application are used to distinguish similar objects, and represent a specific order or sequence. The order of use of similar objects can be interchanged under appropriate circumstances, so that the embodiments of the application described herein can be implemented in an order other than that illustrated or described.

[0137] Those skilled in the art know that the application can be implemented as a system, a method or a computer program product, so the application can be specifically implemented as follows: it can be a complete hardware, a complete software (including firmware, resident software, microcode, etc.), or a combination of hardware and software, which is generally referred to as "circuit", "module" or "system" in this paper. In addition, in some embodiments, the application can also be implemented as a computer program product in one or more computer readable media, which contains computer readable program code.

[0138] Although the above has shown and described the embodiments of the application, it should be understood that the above embodiments are exemplary and cannot be understood as limiting the application, and those skilled in the art can make changes, modifications, replacements and variations to the above embodiments within the scope of the application.

Claims

1. A method of temperature monitoring of a drying system, characterized by, The method comprises the following steps: correlation degree analysis is performed on the temperature values of each preset position of a reference drying system, and a plurality of target positions are determined according to the correlation degree analysis result; temperature values of each non-target position of the target drying system are back calculated according to the temperature values of each target position of the target drying system; wherein the reference drying system and the target drying system are two identical drying systems; correlation degree analysis is performed on the temperature values of each preset position of a reference drying system, and a plurality of target positions are determined according to the correlation degree analysis result, which comprises the following steps: obtain the temperature values of each preset position of the reference drying system within a preset time period to obtain a plurality of time-temperature sequence data; perform similarity analysis on the plurality of time-temperature sequence data, and divide all the preset positions into a plurality of groups according to the similarity analysis result, wherein the similarity between the time-temperature sequence data of each two preset positions in the same group exceeds a preset similarity threshold, the similarity represents the correlation degree, and the similarity between the first time-temperature sequence data and the second time-temperature sequence data refers to the similarity between the data change trends of the first time-temperature sequence data and the second time-temperature sequence data, wherein the first time-temperature sequence data and the second time-temperature sequence data are any two time-temperature sequence data; select one preset position in each group as a target position.

2. The method of claim 1, wherein the temperature of the drying system is monitored by a temperature sensor. back calculate the temperature values of each non-target position of the target drying system according to the temperature values of each target position, which comprises the following steps: back calculate the temperature values of each non-target position of the target drying system based on the time-temperature sequence data of each preset position in each group.

3. A method of temperature monitoring of a drying system according to claim 2, characterized in that, It further comprises the following steps: determine whether to issue a warning information according to the temperature values of each target position and the temperature values of each non-target position of the target drying system.

4. A temperature monitoring system for a drying system, characterized by comprise a target position determination module and a temperature back calculation module; the target position determination module is used for performing correlation degree analysis on the temperature values of each preset position of a reference drying system, and determining a plurality of target positions according to the correlation degree analysis result; the temperature back calculation module is used for collecting temperature through temperature sensors arranged at each target position of a target drying system, and back calculating the temperature values of each non-target position of the target drying system according to the temperature values of each target position; wherein the reference drying system and the target drying system are two identical drying systems; the target position determination module is specifically used for: obtaining the temperature values of each preset position of the reference drying system within a preset time period to obtain a plurality of time-temperature sequence data; The similarity analysis is performed on the plurality of time-temperature sequence data, and all preset positions are divided into a plurality of groups according to a similarity analysis result, wherein the similarity between time-temperature sequence data of each two preset positions in a same group all exceeds a preset similarity threshold, the similarity represents a correlation degree, and the similarity between the first time-temperature sequence data and the second time-temperature sequence data refers to the similarity between data change trends of the first time-temperature sequence data and the second time-temperature sequence data, wherein the first time-temperature sequence data and the second time-temperature sequence data are any two time-temperature sequence data. One preset position in each group is selected as a target position.

5. A temperature monitoring system for a drying system as claimed in claim 4, wherein, The temperature backstepping module is specifically configured to backstep the temperature value of each non-target position of the target drying system based on the time-temperature sequence data of each preset position in each group.

6. A temperature monitoring system for a drying system as claimed in claim 5, wherein, The early warning module is further configured to determine whether to send early warning information according to the temperature value of each target position and the temperature value of each non-target position of the target drying system.

7. An electronic device, comprising: The computer readable storage medium stores a computer program, and the computer program is executed by the processor to implement the temperature monitoring method of the drying system according to any one of claims 1 to 3.

8. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program is executed by the processor to implement the temperature monitoring method of the drying system according to any one of claims 1 to 3.

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