Temperature measurement validity checking method, temperature distribution cloud picture reconstruction method and system

Abstract

The application provides a temperature measurement effectiveness verification method and a temperature distribution cloud diagram reconstruction method and system. The temperature measurement effectiveness verification method comprises: performing effectiveness verification on a temperature signal of a single measurement point, performing effectiveness verification on a temperature signal in a single heat dissipation hole, and performing verification on a temperature deviation between heat dissipation holes. The effectiveness of the slot shell temperature measurement is comprehensively and systematically verified, so that possible measurement faults can be found in time and the faults can be processed in a targeted manner. The temperature distribution cloud diagram reconstruction method reconstructs a temperature distribution cloud diagram by using the temperature signal that has passed the effectiveness verification.

Description

Technical Field

[0001] This invention relates to the field of pipeline temperature measurement technology, and in particular to a method for verifying the effectiveness of temperature measurement, a method for reconstructing temperature distribution cloud maps, and a system thereof. Background Technology

[0002] Aluminum electrolytic cells are the main equipment in aluminum smelting. The safety of these cells is crucial to electrolytic production. The stable operation of an aluminum electrolytic cell directly affects technical and economic indicators such as current efficiency, anode consumption, primary aluminum yield, and quality. Therefore, stable control of the aluminum electrolytic cell production process to achieve the best production and operational results is paramount in electrolytic production. Major accidents such as cell leakage or sidewall burn-through in an electrolytic cell lead to production stoppages, maintenance shutdowns, and restarts, all of which result in significant economic losses for aluminum electrolytic enterprises. The cell shell temperature is a critical parameter in production operation. Online monitoring of the cell shell temperature allows for real-time monitoring of the cell's operating status, effectively preventing accidents such as leakage, ensuring safe production, and extending the cell's service life. Furthermore, it provides valuable reference for studying the shape of the cell chamber, as the shape directly impacts the cell's insulation and energy consumption. Considering the high-temperature (electrolyte temperature 940℃~950℃) and strong magnetic (cathode bus current hundreds of kiloamperes) environment during electrolytic cell operation, the stable and effective operation of the real-time tank shell temperature measurement system faces challenges. This not only threatens the stability of the thermocouple probe itself but also interferes with the signal acquisition and processing process, leading to phenomena such as measuring point detachment, signal disturbance, and signal drift. Currently, there is no technology to verify the effectiveness of tank shell temperature measurement. Summary of the Invention

[0003] In order to address the problems existing in the prior art, the present invention aims to provide a method for verifying the validity of temperature measurement, a method for reconstructing temperature distribution cloud maps, and a system that can verify the validity of temperature information.

[0004] To achieve the above objectives, the present invention adopts the following technical solution:

[0005] A method for verifying the validity of a temperature measurement includes the following steps:

[0006] S1. Verify the validity of the temperature signal at a single measurement point and process any temperature signals that do not meet the requirements;

[0007] S2. Based on the validity check results of step S1, verify the validity of the temperature signal in a single heat dissipation hole, and process the temperature signals that do not meet the requirements.

[0008] S3. Based on the validity test results of step S2, verify the temperature deviation between the heat dissipation holes, and issue a fault alarm signal if the temperature deviation between the heat dissipation holes is abnormal.

[0009] As a further improvement of the present invention, step S1 includes:

[0010] For each temperature signal at a single measurement point, an out-of-limit judgment is performed. If the temperature signal exceeds the limit, the temperature signal is processed; if the temperature signal does not exceed the limit, the temperature signal stability is judged. If the temperature signal is unstable, the temperature signal is processed.

[0011] As a further improvement of the present invention, the present invention also includes a step for determining whether the temperature signal exceeds the limit:

[0012] Set an out-of-limit range; when the temperature signal is outside the out-of-limit range, the temperature signal is judged as out of limit.

[0013] As a further improvement of the present invention, the present invention also includes a step for determining the stability of the temperature signal:

[0014] Calculate the absolute value between the real-time measured temperature signal and the average value of the measured temperature signal. If the absolute value exceeds the first set value, the temperature signal is judged to be unstable.

[0015] As a further improvement of the present invention, the step of processing the temperature signal includes:

[0016] Temperature signals that are deemed to be out of range or unstable will be marked as invalid.

[0017] The effective temperature signal at the previous moment or the temperature signal obtained by real-time measurement is used to replace the temperature signal that is judged to be out of limit or unstable.

[0018] Issue a fault alarm signal.

[0019] As a further improvement of the present invention, step S2 includes:

[0020] If the number of effective temperature signals at a single measurement point within the same heat dissipation hole is less than the minimum effective temperature signal limit, the heat dissipation hole will be marked as a faulty heat dissipation hole, and a heat dissipation hole fault alarm signal will be issued.

[0021] If the number of valid temperature signals at a single measurement point is greater than or equal to the minimum valid temperature signal limit, calculate the average value of all valid temperature signals, calculate the deviation of a single valid temperature signal from the average value, and if the deviation is greater than the second set value, then process the valid temperature signal.

[0022] As a further improvement of the present invention, before the step of calculating the average value of all valid temperature signals, the method further includes:

[0023] Correct the effective temperature signal.

[0024] As a further improvement of the present invention, the step of processing the effective temperature signal includes:

[0025] Valid temperature signals with a deviation greater than the second set value are marked as invalid.

[0026] The effective temperature signal at the previous moment is used to replace the effective temperature signal with a deviation greater than the second set value.

[0027] As a further improvement of the present invention, step S3 includes:

[0028] Select each heat dissipation hole that is not marked as a faulty heat dissipation hole, and determine whether the heat dissipation holes adjacent to it are marked as faulty heat dissipation holes.

[0029] If not, the average temperature deviation between the selected heat dissipation hole effective temperature signal and the average temperature deviation between the adjacent heat dissipation hole effective temperature signals is calculated. If the temperature deviation is greater than the third set threshold, it is determined that the temperature difference deviation between the heat dissipation holes is abnormal and a fault signal is issued.

[0030] This invention provides a temperature measurement validity verification system, comprising:

[0031] Temperature measurement sensors are installed on the aluminum electrolysis cell to acquire temperature information;

[0032] A computer device is connected to the temperature measurement sensor to obtain the temperature information. The computer device includes a processor and a memory. The memory stores at least one instruction, which is loaded and executed by the processor to implement the temperature measurement validity verification method described above.

[0033] This invention provides a method for reconstructing temperature distribution cloud maps, comprising the following steps:

[0034] The temperature measurement area is divided into several coarse grids, and each coarse grid is further divided into several fine grids.

[0035] The temperature information obtained by the temperature measurement validity verification method described above is used to assign values ​​to the grid nodes of the coarse network;

[0036] Determine the temperature values ​​of the grid nodes in a coarse mesh.

[0037] The temperature of the fine mesh nodes is obtained by solving for the temperature value of each coarse mesh node.

[0038] A temperature distribution cloud map is constructed using the temperature of the grid nodes in the fine mesh.

[0039] The beneficial effects of this invention are as follows: This invention comprehensively and systematically verifies the effectiveness of the temperature measurement of the tank shell through steps such as validity verification of a single measurement point, validity verification of a single heat dissipation hole, and temperature deviation verification between heat dissipation holes. It can promptly detect possible measurement faults and process fault signals in a targeted manner, thereby ensuring the stability and robustness of the entire temperature monitoring system. Attached Figure Description

[0040] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments.

[0041] Figure 1 This is a diagram showing the arrangement of temperature measuring points on the shell of the aluminum electrolytic cell in Example 1.

[0042] Figure 2 This is a flowchart of the temperature measurement validity verification method described in Example 1;

[0043] Figure 3 This is a flowchart of step S1 as described in Example 1;

[0044] Figure 4 This is a flowchart of step S2 as described in Example 1;

[0045] Figure 5 This is a flowchart of step S3 as described in Example 1;

[0046] Figure 6 This is a flowchart of the temperature distribution cloud map reconstruction method described in Example 3;

[0047] Figure 7 This is a schematic diagram of the mesh division in Example 3;

[0048] Figure 8 This is a schematic diagram of a grid in Example 3;

[0049] Figure 9 This is the temperature distribution cloud map described in Example 3.

[0050] Markings: 101, gaseous state; 102, electrolyte; 103, molten aluminum; 104, support plate; 105, electrolyte level; 106, thermocouple measuring point; 107, aluminum level; 108, heat dissipation hole. Detailed Implementation

[0051] To make the technical problems solved by the present invention, the technical solutions adopted, and the technical effects achieved clearer, the technical solutions of the embodiments of the present invention will be further described in detail below. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0052] Example 1

[0053] This embodiment illustrates a method for verifying the effectiveness of temperature measurement using one application scenario. The outer periphery of the aluminum electrolytic cell shell features parallelly arranged heat dissipation holes. To cover the entire area within each hole as much as possible, the present invention deploys temperature measurement points in a dot matrix configuration. The present invention does not specifically limit the type of temperature measurement sensor. Preferably, armored thermocouples can be used to monitor the temperature of the electrolytic cell shell. The armored thermocouples are arranged in a one-to-six configuration (one signal acquisition and processing unit to acquire six thermocouple signals) within the heat dissipation holes of the electrolytic cell shell. As an example, Figure 1 A six-point arrangement of thermocouples within a single heat dissipation hole is presented.

[0054] like Figure 1 As shown, the six temperature measuring points are deployed at the following locations: two at the electrolyte level (one on the left and one on the right), one in the middle of the electrolyte, two at the aluminum level (one on the left and one on the right), and one in the middle of the molten aluminum. This arrangement takes into account the locations where leakage is most likely to occur (the electrolyte and aluminum levels, which are considered the most vulnerable locations due to fluctuations in liquid level during aluminum electrolysis production) and covers as much of the heat dissipation hole area as possible.

[0055] like Figure 2 As shown, the method for verifying the validity of temperature measurements includes the following steps:

[0056] S1. Perform validity checks on the temperature signals at individual measurement points, and process temperature signals that do not meet the requirements. This step mainly involves judging whether the temperature signal exceeds limits and assessing its stability. Single-point validity checks primarily involve judging signal exceedances and signal stability, detecting anomalies in the temperature data, and determining the validity of the temperature signal accordingly. The purpose of stability assessment is to detect the stability of the temperature signal. If the temperature signal is unstable, it indicates that the measurement channel is subject to significant external interference, resulting in abnormal temperature signal fluctuations.

[0057] like Figure 3 As shown, step S1 includes:

[0058] For each temperature signal at a single measurement point, an out-of-limit judgment is performed. If the temperature signal exceeds the limit, the temperature signal is processed; if the temperature signal does not exceed the limit, the temperature signal stability is judged. If the temperature signal is unstable, the temperature signal is processed.

[0059] In this embodiment, the step S111 for determining if the temperature signal exceeds the limit includes:

[0060] An out-of-limit range is set; when the temperature signal is outside this range, it is considered to be out of limit. The selection of the out-of-limit range can be determined based on the measurement range of the temperature sensor and the operating parameters of the electrolytic cell. Preferably, considering that the temperature of the heat dissipation holes is maintained between 150℃ and 400℃ during normal production of the electrolytic cell, the out-of-limit range can be set as follows: lower limit 100℃, upper limit 600℃. Specifically, when the temperature signal is less than 100℃ but exceeds 600℃, it is considered to be out of limit.

[0061] The step S112 for determining the stability of the temperature signal includes:

[0062] Calculate the average value of the real-time measured temperature signal and the effective temperature signal. The absolute value between the two values ​​is considered; if the absolute value exceeds a first set value, the temperature signal is considered unstable. Specifically, the average value of the effective temperature signal... Calculated using the following formula:

[0063]

[0064] Where NC is the total number of temperature sampling points within this time period; c is the exponent of the cycle from 1 to NC; The time required for sampling point c; The temperature signal value obtained at sampling point c.

[0065] The selection of the time period can be determined based on the signal sampling period and signal processing capability of the signal acquisition and processing unit. Typically, the time period can be determined to be 120 seconds, that is, for the temperature signal obtained at the current moment, the average value of the effective temperature signal from the 120 seconds prior to the current moment is calculated. Then, calculate the average value of the temperature signal and the effective temperature signal. The absolute value of the difference. The selection of the first set value can be determined based on the operating experience data of the electrolytic cell or numerical simulation calculations, such as selecting 20℃ as the set value.

[0066] Step S113, which processes the temperature signal, includes:

[0067] S1131, mark temperature signals that are judged to be out of limit or unstable as invalid;

[0068] S1132. Replace the temperature signal judged as exceeding the limit or unstable with the valid temperature signal of the previous moment or the temperature signal obtained by real-time measurement. The determination of "previous moment" is based on factors such as the signal sampling period and signal stability judgment, and is determined according to the operating experience data of the electrolytic cell or numerical simulation calculation. Typically, to avoid the 120s signal stability judgment time limit, the temperature data 150s before the current sampling moment can be selected as the "valid temperature signal of the previous moment".

[0069] S1133. Issue a fault alarm signal. The fault alarm signal indicates a fault in the temperature signal measurement channel.

[0070] S2. Based on the validity check results of step S1, verify the validity of the temperature signal in a single heat dissipation hole, and process the temperature signals that do not meet the requirements.

[0071] like Figure 4 As shown, step S2 includes:

[0072] S21. If the number of effective temperature signals at a single measurement point within the same heat dissipation hole is less than the minimum effective temperature signal limit Nav_lim, then the heat dissipation hole will be marked as a faulty heat dissipation hole, and a heat dissipation hole fault alarm signal will be issued.

[0073] S22. If the number of valid temperature signals at a single measurement point is greater than or equal to the minimum valid temperature signal limit Nav_lim, calculate the average value T of all valid temperature signals. avg Calculate the average value of a single effective temperature signal and the effective temperature signal. If the deviation is greater than the second set value, the effective temperature signal will be processed.

[0074] For example, the minimum effective temperature signal limit Nav_lim can be determined based on the number of temperature signals arranged and experience data from aluminum electrolysis cell production. Typically, for Figure 2 In the case of 6 points arranged inside the heat dissipation holes shown, the Nav_lim value is preferably 3, and can preferably be 2 or 4.

[0075] The production process of an aluminum electrolysis cell is essentially a process of converting electrical energy into chemical energy. During the production of the aluminum electrolysis cell, the temperatures of the electrolyte and the molten aluminum are not the same, but rather there exists a certain temperature gradient. Correspondingly, the temperature reflected at different heights of the heat dissipation holes is also different. Therefore, in step S21, the average value of all effective temperature signals is calculated. Before the first step, there is also the following step:

[0076] Correct the effective temperature signal.

[0077] The following explanation uses the thermocouple measuring point arrangement shown in the figure to further illustrate the correction steps:

[0078] Using thermocouple 3, located at the center of the heat dissipation hole, as the reference measuring point, the deviation between other thermocouple measuring points and this reference measuring point is determined based on daily production experience of the aluminum electrolysis cell or numerical simulation results of the heat dissipation hole temperature distribution. For example, if daily production experience of the aluminum electrolysis cell indicates that the temperature difference between the electrolyte level and the bottom of the aluminum liquid does not exceed 10℃, and daily temperature monitoring signals of the heat dissipation hole indicate that the temperature difference between the temperature signal around the heat dissipation hole and the temperature signal at the center does not exceed 10℃, then the deviation ε between other thermocouple measuring points and the reference measuring point can be selected as 10℃. That is, subtract 10℃ from the temperature signals of thermocouple measuring points 1 and 2, and add 10℃ to the temperature signals of thermocouple measuring points 4, 5, and 6. (Note: The value of ε can be different for different measuring point positions).

[0079] Each valid temperature signal is corrected, and the corrected temperature signal T is used as the basis for the correction. tc Calculate the average value of the effective temperature signal Then, the temperature signal T is calculated. tc Average value of effective temperature signal The deviation. If the temperature signal T tc Average value of effective temperature signal The absolute value of the difference is greater than the threshold T dif If the sum of the two values ​​is less than or equal to the deviation ε, the temperature signal is considered invalid, triggering a fault alarm indication for that temperature signal measurement channel. The invalid temperature signal is then discarded, and the average value of the valid temperature signals is recalculated. The calculation and subsequent processes continue until the average value of all temperature signal data and the effective temperature signal is reached. The deviations are all at the threshold T dif + Deviation ε within. Threshold T dif The temperature can be determined based on experience and statistical analysis of historical temperature data of heat dissipation holes during the daily operation of aluminum electrolysis cells; for example, 60℃ can be taken.

[0080] Step S22, the step of processing the effective temperature signal, includes:

[0081] Valid temperature signals with a deviation greater than the second set value are marked as invalid.

[0082] The effective temperature signal at the previous moment is used to replace the effective temperature signal with a deviation greater than the second set value. Further implementation details of this step can be found in step S1132.

[0083] S3. Based on the validity check results of step S2, verify the temperature deviation between the heat dissipation holes, and issue a fault alarm signal if the temperature deviation between the heat dissipation holes is abnormal. The purpose of the validity check between the heat dissipation holes is to monitor possible temperature measurement faults of the heat dissipation holes and to promptly detect abnormal temperature deviations between the heat dissipation holes. Typical fault causes include faults induced by electromagnetic interference in the signal acquisition module. Figure 5 As shown, step S3 specifically includes:

[0084] Select each heat dissipation hole that is not marked as a faulty heat dissipation hole, and determine whether the heat dissipation holes adjacent to it are marked as faulty heat dissipation holes. If all the heat dissipation holes adjacent to it have been marked as faulty heat dissipation holes, then do not perform validity verification on the current heat dissipation hole.

[0085] If at least one adjacent heat dissipation hole is not marked as faulty, then calculate the average value of the effective temperature signal of the selected heat dissipation hole and the average value of the effective temperature signals of the adjacent heat dissipation holes. If the temperature deviation exceeds a third preset threshold, it is determined that the temperature difference between the heat dissipation holes is abnormal, and a fault signal is issued. The third preset threshold can be determined based on statistical analysis of historical temperature data of the heat dissipation holes during the daily operation of the aluminum electrolysis cell. Preferably, 40°C can be selected as the third preset threshold.

[0086] Before step S3, the following is also included:

[0087] If the operator's settings information is obtained, the temperature deviation verification between the heat dissipation holes is stopped. Specifically, during the daily production process of the aluminum electrolysis cell, if the cell is undergoing operations such as anode raising, aluminum tapping, or feeding, the electrolyte and molten aluminum in the cell are in a relatively unstable physical state, and the temperature deviation between the heat dissipation holes is irregular. Therefore, the effectiveness verification process between the heat dissipation holes is not very meaningful during these periods. The operating status of the aluminum electrolysis cell can be obtained by the cell control machine or by the operator's settings.

[0088] The temperature measurement validity verification method in this embodiment verifies the validity of the cell shell temperature measurement to ensure that the read temperature data can accurately reflect the state of the electrolytic cell shell, enabling real-time prediction and early warning of the health status of the aluminum electrolytic cell, ensuring the stable operation of aluminum electrolysis production, preventing dangerous accidents such as cell leakage, and extending the working life of the electrolytic cell.

[0089] Example 2

[0090] The present invention also provides a temperature measurement validity verification system, including a temperature measurement sensor and a computer device. The temperature measurement sensor is arranged on an aluminum electrolysis cell to acquire temperature information. The computer device includes a processor and a memory. The memory stores at least one instruction, at least one program, code set or instruction set. The at least one instruction, at least one program, code set or instruction set is loaded and executed by the processor to implement the aforementioned temperature measurement validity verification method.

[0091] The processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0092] The memory can be used to store the computer program or module. The processor implements various functions of the charging pile identification method by running or executing the computer program or module stored in the memory and calling the data stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application required for a function, etc.; the data storage area may store data created based on the use of the mobile phone, etc. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0093] Example 3

[0094] This embodiment provides a method for reconstructing temperature distribution cloud maps, such as... Figure 6 As shown, the steps include:

[0095] A. Divide the temperature measurement area into several coarse grids, and then divide each coarse grid into several fine grids. For example, in this embodiment, the temperature measurement area is divided into a 5×5 coarse grid, and each coarse grid is further subdivided into a 20×10 fine grid, resulting in a total of 80×40 grid points. Figure 7 As shown.

[0096] B. Assign values ​​to the grid nodes of the coarse network using the temperature measurement validity verification method obtained in Example 1; such as... Figure 7 As shown in the figure, the bolded nodes are the corresponding... Figure 1 Arrange thermocouple nodes and assign values ​​to 5×5 grid nodes based on temperature measurement data. Real-time and historical temperature information for 6 measurement points, after verification of single heat dissipation hole effectiveness, is known.

[0097] C. Use linear interpolation to solve for the temperature values ​​of the grid nodes in the coarse network, such as:

[0098] For nodes where thermocouple measuring points are located, if the thermocouple temperature signal is valid, the temperature of the node is the real-time temperature signal of the corresponding thermocouple; if the thermocouple data is invalid, the valid value of the previous moment is taken.

[0099] For nodes at the four corners, it is approximately considered that the temperature is equal to the temperature collected by the measuring point of the adjacent thermocouple in the previous time interval. For example, for the top left node T(0,0), it is approximately considered that the temperature signal is equal to the temperature signal collected by the thermocouple at node (20,10) in the previous time interval. If the temperature signal of the adjacent thermocouple is invalid, the valid value of the adjacent thermocouple in the previous moment is taken as the temperature signal.

[0100] For other nodes, the temperature of that node is obtained by linear interpolation based on the known temperature signals of the surrounding nodes. For example, for nodes (20, 0), (40, 0), (60, 0), and (40, 10), the temperature can be solved using the following system of equations:

[0101] T(20,0)=1 / 3(T(0,0)+T(20,10)+T(40,0))

[0102] T(40,0)=1 / 3(T(20,0)+T(40,10)+T(60,0))

[0103] T(60,0)=1 / 3(T(40,0)+T(60,10)+T(80,0))

[0104] T(40,10)=1 / 4(T(20,10)+T(40,0)+T(60,10)+T(40,20)

[0105] D. Based on the temperature values ​​of the grid nodes in each coarse mesh, the temperature of the grid nodes in the fine mesh is obtained by two-dimensional interpolation using the shape function interpolation method; for example... Figure 8 As shown, assume that the temperature at point 1 is T1, the temperature at point 2 is T2, the temperature at point 3 is T3, and the temperature at point 4 is T4. The shape function of the four-node linear element is as follows:

[0106] N1 = 1 / 4 (1-ξ)(1-η)

[0107] N2 = 1 / 4 (1 + ξ)(1 - η)

[0108] N3 = 1 / 4 (1 + ξ)(1 + η)

[0109] N4 = 1 / 4(1-ξ)(1+η)

[0110] Temperature at any point (ξ, η):

[0111] T(ξ, η)=N1×T1+N2×T2+N3×T3+N4×T4 (-1≤ξ≤1,-1≤η≤1)

[0112] Where (ξ, η) are relative coordinate points, converted to real coordinate points:

[0113] x=(X1-X4) / 2×η+(X4+X1) / 2

[0114] y=(Y3-Y4) / 2×ξ+(Y3+Y4) / 2

[0115] T(x, y) = T(ξ, η)

[0116] Based on this, the temperature T(x, y) at any point can be obtained.

[0117] E. A temperature distribution cloud map is constructed using the temperature of the grid nodes in a fine mesh. The figure shows an example of the reconstructed temperature distribution cloud map effect of the heat dissipation hole of an A20 electrolytic cell. Figure 9 In the diagram, the darker the color, the higher the temperature.

[0118] This embodiment allows for a direct view of the temperature distribution cloud map in the temperature measurement zone, enabling monitoring of the electrolytic cell shell.

[0119] It should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This way of describing the specification is only for clarity. Those skilled in the art should regard the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

[0120] The technical principles of the present invention have been described above with reference to specific embodiments. These descriptions are merely for explaining the principles of the invention and should not be construed as limiting the scope of protection of the invention in any way. Based on this explanation, those skilled in the art can readily conceive of other specific embodiments of the invention without inventive effort, and these embodiments will all fall within the scope of protection of the present invention.

Claims

1. A method for verifying the validity of temperature measurements, characterized in that, Including the following steps: S1. Verify the validity of the temperature signal at a single measurement point, and process any temperature signals that do not meet the requirements: For each temperature signal at a single measurement point, an out-of-limit judgment is performed. If the temperature signal exceeds the limit, the temperature signal is processed; if the temperature signal does not exceed the limit, the stability of the temperature signal is judged. If the temperature signal is unstable, the temperature signal is processed. S2. Based on the validity check results of step S1, the validity of the temperature signal in a single heat dissipation hole is verified. Temperature signals that do not meet the requirements are processed: If the number of valid temperature signals at a single measurement point in the same heat dissipation hole is less than the minimum valid temperature signal limit, the heat dissipation hole is marked as a faulty heat dissipation hole, and a heat dissipation hole fault alarm signal is issued; If the number of valid temperature signals at a single measurement point is greater than or equal to the minimum valid temperature signal limit, the average value of all valid temperature signals is calculated, and the deviation between a single valid temperature signal and the average value is calculated. If the deviation is greater than the second set value, the valid temperature signal is processed. Before the step of calculating the average value of all valid temperature signals, the method further includes: Correct the effective temperature signal; S3. Based on the validity test results of step S2, verify the temperature deviation between the heat dissipation holes, and issue a fault alarm signal if the temperature deviation between the heat dissipation holes is abnormal.

2. The method for verifying the validity of temperature measurement according to claim 1, characterized in that, It also includes steps for determining when the temperature signal exceeds limits: Set an out-of-limit range; when the temperature signal is outside the out-of-limit range, the temperature signal is judged as out of limit.

3. The method for verifying the validity of temperature measurement according to claim 1, characterized in that, It also includes steps for determining the stability of the temperature signal: Calculate the absolute value between the real-time measured temperature signal and the average value of the measured temperature signal. If the absolute value exceeds the first set value, the temperature signal is judged to be unstable.

4. The method for verifying the validity of temperature measurement according to claim 1, characterized in that, The steps for processing the temperature signal include: Temperature signals that are deemed to be out of range or unstable will be marked as invalid. The effective temperature signal at the previous moment or the temperature signal obtained by real-time measurement is used to replace the temperature signal that is judged to be out of limit or unstable. Issue a fault alarm signal.

5. The method for verifying the validity of temperature measurement according to claim 1, characterized in that, The step of processing the effective temperature signal includes: Valid temperature signals with a deviation greater than the second set value are marked as invalid. The effective temperature signal at the previous moment is used to replace the effective temperature signal with a deviation greater than the second set value.

6. The method for verifying the validity of temperature measurement according to claim 1, characterized in that, Step S3 includes: Select each heat dissipation hole that is not marked as a faulty heat dissipation hole, and determine whether the heat dissipation holes adjacent to it are marked as faulty heat dissipation holes. If not, the average temperature deviation between the selected heat dissipation hole effective temperature signal and the average temperature deviation between the adjacent heat dissipation hole effective temperature signals is calculated. If the temperature deviation is greater than the third set threshold, it is determined that the temperature difference deviation between the heat dissipation holes is abnormal and a fault signal is issued.

7. A temperature measurement validity verification system, characterized in that, include: Temperature measurement sensors are installed on the aluminum electrolysis cell to acquire temperature information; A computer device connected to the temperature measurement sensor to acquire the temperature information, the computer device including a processor and a memory, the memory storing at least one instruction, the at least one instruction being loaded and executed by the processor to implement the temperature measurement validity verification method as described in any one of claims 1 to 6.

8. A method for reconstructing a temperature distribution cloud map, characterized in that, Including the following steps: The temperature measurement area is divided into several coarse grids, and each coarse grid is further divided into several fine grids. The temperature information obtained by the temperature measurement validity verification method as described in any one of claims 1 to 6 is used to assign values ​​to the grid nodes of the coarse network; Determine the temperature values ​​of the grid nodes in a coarse mesh. The temperature of the fine mesh nodes is obtained by solving for the temperature value of each coarse mesh node. A temperature distribution cloud map is constructed using the temperature of the grid nodes in the fine mesh.

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