Air duct detection system based on CAN bus big data transmission

Abstract

The invention discloses an air duct detection system based on CAN bus big data transmission, and relates to the technical field of electric data processing, and the system comprises a data analysis terminal which is used for controlling each module to carry out missing data supplement, air duct historical data classification, temperature data analysis and real-time data verification on air duct historical data. According to the method, missing data of the historical data of the air duct is supplemented, the integrity of the data in the subsequent analysis process is guaranteed, the accuracy of the analysis result can be improved, in addition, rule analysis is conducted on the historical temperature data of the air duct, the temperature reduction rule of different positions of the air duct is determined, and the accuracy of the analysis result is improved. The real-time data of the air duct is subjected to data verification according to the temperature drop rules of different positions of the air duct, whether defects exist in the air duct or not is determined, whether defects exist in the air duct or not is determined by analyzing the temperature data of the single air duct, the air duct defect analysis time is shortened, and meanwhile the defect analysis efficiency is improved. And the defects of the air duct can be repaired in time.

Description

Technical Field

[0001] This invention relates to the field of electrical data processing technology, specifically to a duct detection system based on CAN bus large data transmission. Background Technology

[0002] Air ducts are channels for air circulation, constructed using materials such as concrete, bricks, fiberglass, and galvanized steel sheets.

[0003] The existing duct data is only analyzed after all data collection is completed. However, some duct data collection cycles are too long, which leads to excessively long duct defect analysis time and makes it impossible to repair duct defects in a timely manner. Summary of the Invention

[0004] To address the aforementioned technical problems, a duct inspection system based on CAN bus large data transmission is provided. This technical solution solves the problem mentioned in the background that some duct data acquisition cycles are too long, which leads to excessively long duct defect analysis time and makes it impossible to repair duct defects in a timely manner.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A duct inspection system based on CAN bus large data transmission includes: The data analysis terminal is used to control various modules to supplement missing data, classify historical data of the air duct, analyze temperature data, and verify real-time data to determine whether there are defects inside the air duct. The data analysis terminal is also used to control data transmission and information interaction between various modules. A database system is used to store historical data of the air duct and a diagram of the equipment distribution inside the air duct. A missing data supplementation module is used to supplement the historical data of the air duct to obtain complete historical data of the air duct. A temperature drop pattern determination module is used to perform data analysis on complete historical data of the air duct to determine the temperature drop pattern at different locations in the air duct. The air duct defect verification module verifies the real-time data of the air duct based on the temperature drop pattern at different locations in the air duct to determine whether there are defects inside the air duct. An information transmitting device, which is used to send alarm information about defects inside the air duct to the outside world; The module for determining the temperature decrease pattern integrates the following internal components: The first data classification unit is used to classify and process the complete historical data of the air duct to determine the historical temperature data at different locations in the air duct. A coordinate system construction unit, which constructs a rectangular coordinate system based on the acquisition time and temperature data; The curve analysis unit is used to calculate the slope of the temperature change curve at different locations in the air duct and obtain the curve slope at different nodes. The slope analysis unit is used to perform slope analysis on the curve slopes of different nodes to determine the temperature drop pattern at different locations in the air duct. The internal integration of the air duct defect verification module includes: A data reading unit is used to read and process data from the temperature acquisition device inside the air duct to obtain real-time data of the air duct. The second data classification unit classifies the real-time temperature data of the air duct according to the installation location of the temperature acquisition equipment inside the air duct, and determines the real-time temperature data at different locations in the air duct. The data calculation unit calculates and processes the real-time temperature data of the air duct according to the temperature drop pattern at different locations in the air duct, and determines the standard temperature data at different locations in the air duct. The data comparison unit is used to judge the temperature difference value at different locations in the air duct and the set temperature difference threshold value at different locations in the air duct to determine whether there are defects inside the air duct.

[0006] Preferably, the missing data supplementation module is used to supplement the historical data of the air duct, and obtaining complete historical data of the air duct specifically includes the following steps: Determine the communication protocol of the database system, and based on the communication protocol, perform data reading and processing on the database system to obtain historical data of the air duct; Based on data type, the historical data of the air duct is classified and processed to determine different types of historical data of the air duct; Set up a heatmap, and based on the heatmap, perform missing data lookup processing on historical data of different types of air ducts to determine the location and type of missing data. Based on the missing data type, the mean of historical data for different types of air ducts is calculated to determine the supplementary data for the missing data locations; Based on the supplementary data at the missing data locations, data supplementation processing is performed on the missing data locations to obtain complete historical data of the air duct.

[0007] Preferably, the temperature drop pattern determination module is used to perform data analysis on complete historical data of the air duct, and the determination of the temperature drop pattern at different locations in the air duct specifically includes the following steps: The complete historical data of the air duct is classified and processed to determine the historical temperature data at different locations in the air duct. The historical temperature data at different locations in the air duct are calculated, analyzed, and processed to determine the temperature change curves at different locations in the air duct. The temperature change curves at different locations in the air duct are calculated and processed to determine the temperature drop pattern at different locations in the air duct.

[0008] Preferably, the step of classifying and processing the complete historical data of the air duct to determine the historical temperature data at different locations in the air duct specifically includes the following steps: The complete historical data of the air duct is read and processed to obtain the historical temperature data inside the air duct. Based on the database system, data reading and processing are performed to obtain the equipment distribution diagram inside the air duct; The location of the equipment distribution diagram inside the air duct is analyzed to determine the installation location of the temperature acquisition equipment inside the air duct. Based on the installation location of the temperature acquisition equipment inside the air duct, the historical temperature data inside the air duct is matched and processed to determine the historical temperature data at different locations in the air duct.

[0009] Preferably, the step of calculating and analyzing historical temperature data at different locations in the air duct to determine the temperature change curves at different locations in the air duct specifically includes the following steps: Based on the acquisition time, the historical temperature data at different locations in the air duct are classified and processed to obtain historical temperature data at different acquisition times. Construct a rectangular coordinate system, where the X-axis parameter of the rectangular coordinate system is the acquisition time; and the Y-axis parameter of the rectangular coordinate system is the temperature data. Historical temperature data collected at different times were plotted into a Cartesian coordinate system to obtain temperature change curves at different locations in the air duct.

[0010] Preferably, the calculation and processing of the temperature change curves at different locations in the air duct to determine the temperature decrease pattern at different locations in the air duct specifically includes the following steps: Based on the acquisition time, the slope of the temperature change curves at different locations in the air duct is calculated to obtain the slope of the curves at different nodes; wherein, the different nodes are specifically the historical temperature data corresponding to different acquisition times. The slope of the curves at different nodes is calculated by subtracting the slopes of adjacent time points to obtain the slope difference between nodes at adjacent time points. Based on the maximum value function, the slope difference of nodes at adjacent time points is sorted to obtain a set of node slope difference values; The node slope difference that appears most frequently in the set of node slope difference values ​​is set as the temperature decrease pattern at different locations in the air duct.

[0011] Preferably, the air duct defect verification module verifies the real-time data of the air duct based on the temperature drop pattern at different locations within the air duct to determine whether defects exist inside the air duct. This specifically includes the following steps: The temperature acquisition device inside the air duct reads and processes the data to obtain real-time data of the air duct; Based on temperature data, real-time data of the air duct is read and processed to obtain real-time temperature data of the air duct. Based on the installation location of the temperature acquisition equipment inside the air duct, the real-time temperature data of the air duct is classified and processed to determine the real-time temperature data at different locations in the air duct. Based on the temperature drop pattern at different locations in the air duct, the real-time temperature data of the air duct is calculated and processed to determine the standard temperature data at different locations in the air duct. Based on standard temperature data at different locations in the air duct, the real-time temperature data at different locations in the air duct are compared and analyzed to determine whether there are any defects inside the air duct.

[0012] Preferably, the step of calculating and processing the real-time temperature data of the air duct based on the temperature drop pattern at different locations in the air duct to determine the standard temperature data at different locations in the air duct specifically includes the following steps: Based on the installation location of the temperature acquisition equipment inside the air duct, the real-time temperature data at different locations in the air duct are matched and processed to determine the real-time temperature at the initial location of the air duct. Based on the initial position of the air duct, the temperature drop patterns at different positions of the air duct are sorted to determine the temperature drop patterns corresponding to different data acquisition positions in the air duct. Based on the temperature drop pattern corresponding to different data acquisition locations in the air duct, the real-time temperature at the initial location of the air duct is calculated and processed multiple times to determine the standard temperature data at different locations in the air duct.

[0013] Preferably, the step of comparing and analyzing real-time temperature data at different locations within the air duct based on standard temperature data to determine whether defects exist inside the air duct specifically includes the following steps: The temperature difference between the standard temperature data and the real-time temperature data at different locations in the air duct is calculated by subtracting the standard temperature data and the real-time temperature data at different locations in the air duct. The temperature difference at different locations in the air duct and the set temperature difference threshold at different locations in the air duct are judged and processed. If the temperature difference between different locations in the air duct is greater than or equal to the set temperature difference threshold between different locations in the air duct, there is a defect inside the air duct. If the temperature difference between different locations in the air duct is less than the set temperature difference threshold between different locations in the air duct, there are no defects inside the air duct.

[0014] Furthermore, a duct inspection method based on CAN bus large data transmission is proposed, for use with the aforementioned duct inspection system based on CAN bus large data transmission, including: S100. Based on the heat map, perform supplementary data processing on the historical data of the air duct to obtain complete historical data of the air duct. S200. Perform data analysis and processing on complete historical data of the air duct to determine the temperature drop pattern at different locations in the air duct. S300: Acquire real-time data of the air duct; S400: Based on the temperature drop pattern at different locations in the air duct, real-time data of the air duct is processed for verification to determine whether there are defects inside the air duct.

[0015] Compared with the prior art, the present invention provides a duct inspection system based on CAN bus large data transmission, which has the following advantages: This invention first supplements the missing historical data of the air duct, ensuring the integrity of the data in subsequent analysis and thus improving the accuracy of the analysis results. In addition, it performs pattern analysis on the historical temperature data of the air duct to determine the temperature drop pattern at different locations in the air duct. Subsequently, the real-time data of the air duct is verified by using the temperature drop pattern at different locations in the air duct to determine whether there are defects inside the air duct. The above method determines whether there are defects inside the air duct by analyzing the temperature data of a single air duct, shortening the analysis time of air duct defects, and at the same time, it can also repair air duct defects in a timely manner. Attached Figure Description

[0016] Figure 1 This is a structural block diagram of a duct detection system based on CAN bus large data transmission proposed in this invention; Figure 2 This is a flowchart illustrating steps S100-S400 in a duct inspection system based on CAN bus large data transmission proposed in this invention. Detailed Implementation

[0017] The following description is intended to disclose the invention and enable those skilled in the art to implement it. The preferred embodiments described below are merely examples, and other obvious variations will occur to those skilled in the art.

[0018] Reference Figure 1 As shown, a duct inspection system based on CAN bus large data transmission includes: The data analysis terminal is used to control various modules to supplement missing data, classify historical data of the air duct, analyze temperature data, and verify real-time data to determine whether there are defects inside the air duct. The data analysis terminal is also used to control data transmission and information interaction between various modules. A database system is used to store historical data of the air duct and a diagram of the equipment distribution inside the air duct. A missing data supplementation module is used to supplement the historical data of the air duct to obtain complete historical data of the air duct. A temperature drop pattern determination module is used to perform data analysis on complete historical data of the air duct to determine the temperature drop pattern at different locations in the air duct. The air duct defect verification module verifies the real-time data of the air duct based on the temperature drop pattern at different locations in the air duct to determine whether there are defects inside the air duct. An information transmitting device, which is used to send alarm information about defects inside the air duct to the outside world; The module for determining the temperature decrease pattern integrates the following internal components: The first data classification unit is used to classify and process the complete historical data of the air duct to determine the historical temperature data at different locations in the air duct. A coordinate system construction unit, which constructs a rectangular coordinate system based on the acquisition time and temperature data; The curve analysis unit is used to calculate the slope of the temperature change curve at different locations in the air duct and obtain the curve slope at different nodes. The slope analysis unit is used to perform slope analysis on the curve slopes of different nodes to determine the temperature drop pattern at different locations in the air duct. The internal integration of the air duct defect verification module includes: A data reading unit is used to read and process data from the temperature acquisition device inside the air duct to obtain real-time data of the air duct. The second data classification unit classifies the real-time temperature data of the air duct according to the installation location of the temperature acquisition equipment inside the air duct, and determines the real-time temperature data at different locations in the air duct. The data calculation unit calculates and processes the real-time temperature data of the air duct according to the temperature drop pattern at different locations in the air duct, and determines the standard temperature data at different locations in the air duct. The data comparison unit is used to judge the temperature difference value at different locations in the air duct and the set temperature difference threshold value at different locations in the air duct to determine whether there are defects inside the air duct. Those skilled in the art will understand that various types of data acquisition devices are installed inside the air duct. Some data acquisition cycles are too long. If defects appear inside the air duct and are not repaired in time, the defects may become larger. Air ducts are generally used to exhaust gas and discharge it to a specific location for harmless treatment. If defects appear in the air duct, polluted gas will leak out, thus polluting the air. Therefore, by analyzing a single data point of the air duct (i.e., the temperature data of the air duct), it is possible to determine whether there are defects inside the air duct. This not only shortens the analysis time of air duct defects but also enables timely repair of air duct defects, preventing the defects from becoming larger and leaking out and causing further air pollution.

[0019] Example 1 The missing data completion module is used to complete the historical data of the air duct. The specific steps to obtain complete historical data of the air duct are as follows: Determine the communication protocol of the database system, and based on the communication protocol, perform data reading and processing on the database system to obtain historical data of the air duct; Based on data type, the historical data of the air duct is classified and processed to determine different types of historical data of the air duct; Set up a heatmap, and based on the heatmap, perform missing data lookup processing on historical data of different types of air ducts to determine the location and type of missing data. A heatmap uses special colors or markers (such as white or gray) to represent missing data, contrasting it with the colors of normal data. By observing the color distribution of the heatmap, patterns or areas of missing data can be identified. If some areas are more evenly colored while other areas are sparsely colored, it may mean that the latter have more missing data. Based on the missing data type, the mean of historical data for different types of air ducts is calculated to determine the supplementary data for the missing data locations; Based on the supplementary data at the missing data locations, data supplementation processing is performed on the missing data locations to obtain complete historical data of the air duct; The specific calculation formula for supplementing the missing data at the specified data location is as follows: In the formula, For supplementary data; i is the number of supplementary data; For different types of air duct historical data; n is the number of different types of air duct historical data. In this embodiment, if there are missing data in the historical temperature data of the air duct, and the missing data is not supplemented before subsequent data analysis, the accuracy of the temperature drop pattern at different locations in the air duct will be reduced. Therefore, before analyzing the historical temperature data of the air duct, it is necessary to determine whether there is missing data. If there is, it should be supplemented before subsequent data analysis. If there is no missing data, subsequent data analysis can be performed directly.

[0020] Example 2 The temperature drop pattern determination module is used to analyze complete historical data of the air duct and determine the temperature drop pattern at different locations in the air duct. Specifically, it includes the following steps: The complete historical data of the air duct is classified and processed to determine the historical temperature data at different locations in the air duct. The historical temperature data at different locations in the air duct are calculated, analyzed, and processed to determine the temperature change curves at different locations in the air duct. Understandably, a duct is a long exhaust channel. To monitor a duct, monitoring equipment needs to be installed at different locations within it. Ducts are generally used to exhaust gases from the combustion of certain substances. These gases contain some energy, meaning their temperature is higher than the outside temperature. However, as the gas moves, it releases this internal energy. This means the gas temperature changes as it passes through different locations within the duct. The energy released during this movement follows a certain pattern, which is the temperature drop pattern at different locations within the duct. The temperature change curves at different locations in the air duct are calculated and processed to determine the temperature drop pattern at different locations in the air duct.

[0021] The process of classifying and processing the complete historical data of the air duct to determine the historical temperature data at different locations within the air duct includes the following steps: The complete historical data of the air duct is read and processed to obtain the historical temperature data inside the air duct. Based on the database system, data reading and processing are performed to obtain the equipment distribution diagram inside the air duct; The location of the equipment distribution diagram inside the air duct is analyzed to determine the installation location of the temperature acquisition equipment inside the air duct. Based on the installation location of the temperature acquisition equipment inside the air duct, the historical temperature data inside the air duct is matched and processed to determine the historical temperature data at different locations in the air duct.

[0022] The specific steps involved in calculating and analyzing historical temperature data at different locations within the air duct to determine the temperature change curves at those locations include the following: Based on the acquisition time, the historical temperature data at different locations in the air duct are classified and processed to obtain historical temperature data at different acquisition times. Construct a rectangular coordinate system, where the X-axis parameter of the rectangular coordinate system is the acquisition time; and the Y-axis parameter of the rectangular coordinate system is the temperature data. Historical temperature data collected at different times were plotted into a Cartesian coordinate system to obtain temperature change curves at different locations in the air duct.

[0023] The calculation and processing of temperature change curves at different locations in the air duct to determine the temperature drop pattern at different locations in the air duct specifically includes the following steps: Based on the acquisition time, the slope of the temperature change curves at different locations in the air duct is calculated to obtain the slope of the curves at different nodes; wherein, the different nodes are specifically the historical temperature data corresponding to different acquisition times. The slope of the curves at different nodes is calculated by subtracting the slopes of adjacent time points to obtain the slope difference between nodes at adjacent time points. Based on the maximum value function, the slope difference of nodes at adjacent time points is sorted to obtain a set of node slope difference values; The node slope difference that appears most frequently in the set of node slope difference values ​​is set as the temperature decrease pattern at different locations in the air duct; It is understandable that, since the length of the air duct is fixed, the energy released by the gas when it moves a certain distance follows a certain pattern. However, with prolonged use, the performance of the air duct will decline, and thus the gas release capacity will also change to some extent. But this change follows a certain pattern. Therefore, by analyzing the slope of the curve, the temperature drop pattern at different locations in the air duct can be determined.

[0024] Example 2 The air duct defect verification module verifies real-time data from the air duct based on the temperature drop patterns at different locations within the air duct to determine whether defects exist inside the air duct. Specifically, this includes the following steps: The temperature acquisition device inside the air duct reads and processes the data to obtain real-time data of the air duct; Based on temperature data, real-time data of the air duct is read and processed to obtain real-time temperature data of the air duct. Based on the installation location of the temperature acquisition equipment inside the air duct, the real-time temperature data of the air duct is classified and processed to determine the real-time temperature data at different locations in the air duct. Based on the temperature drop pattern at different locations in the air duct, the real-time temperature data of the air duct is calculated and processed to determine the standard temperature data at different locations in the air duct. Based on standard temperature data at different locations in the air duct, the real-time temperature data at different locations in the air duct are compared and analyzed to determine whether there are any defects inside the air duct.

[0025] The process of calculating and processing real-time temperature data of the air duct based on the temperature drop pattern at different locations within the air duct to determine the standard temperature data for different locations specifically includes the following steps: Based on the installation location of the temperature acquisition equipment inside the air duct, the real-time temperature data at different locations in the air duct are matched and processed to determine the real-time temperature at the initial location of the air duct. Based on the initial position of the air duct, the temperature drop patterns at different positions of the air duct are sorted to determine the temperature drop patterns corresponding to different data acquisition positions in the air duct. Based on the temperature drop pattern corresponding to different data acquisition locations in the air duct, the real-time temperature at the initial location of the air duct is calculated and processed multiple times to determine the standard temperature data at different locations in the air duct. For example, the real-time temperature at the initial position of the air duct is 60℃ (i.e., gas temperature). The distance between the first data acquisition position (initial position) and the second data acquisition position of the air duct is 5 meters. During the movement of the gas within these 5 meters, the temperature will drop by 4℃ (i.e., the temperature drop pattern at different positions of the air duct). Therefore, the temperature data at the second data acquisition position should be 56℃. Thus, based on the temperature drop pattern at different positions of the air duct, the standard temperature data at different positions of the air duct can be calculated. When the temperature collected at the second data acquisition position of the air duct is 50℃, it indicates that the gas is dropping too fast, which means that some gas has escaped, and that there is a defect in this section of the air duct.

[0026] The process of comparing and analyzing real-time temperature data at different locations within the air duct based on standard temperature data to determine whether defects exist inside the air duct includes the following steps: The temperature difference between the standard temperature data and the real-time temperature data at different locations in the air duct is calculated by subtracting the standard temperature data and the real-time temperature data at different locations in the air duct. The temperature difference at different locations in the air duct and the set temperature difference threshold at different locations in the air duct are judged and processed. If the temperature difference between different locations in the air duct is greater than or equal to the set temperature difference threshold between different locations in the air duct, there is a defect inside the air duct. If the temperature difference between different locations in the air duct is less than the set temperature difference threshold between different locations in the air duct, there are no defects inside the air duct. It is understandable that when a defect occurs at a certain location in the air duct, some gas will escape into the external environment along this defect. When some gas escapes into the external environment, the gas volume inside the air duct will decrease. When the gas volume decreases, the energy released by the gas will decrease, and the temperature inside the air duct will not rise as much, thus falling below the standard value. Therefore, by analyzing the temperature drop patterns at different locations in the air duct, real-time data of the air duct can be verified to determine whether there are defects inside the air duct.

[0027] Reference Figure 2 As shown, a duct inspection method based on CAN bus large data transmission is used in a duct inspection system based on CAN bus large data transmission as described above, comprising: S100. Based on the heat map, perform supplementary data processing on the historical data of the air duct to obtain complete historical data of the air duct. S200. Perform data analysis and processing on complete historical data of the air duct to determine the temperature drop pattern at different locations in the air duct. S300: Acquire real-time data of the air duct; S400: Based on the temperature drop pattern at different locations in the air duct, real-time data of the air duct is processed for verification to determine whether there are defects inside the air duct.

[0028] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention. The scope of protection claimed by the appended claims and their equivalents is defined.

Claims

1. A duct inspection system based on CAN bus large data transmission, characterized in that, include: The data analysis terminal is used to control various modules to supplement missing data, classify historical data of the air duct, analyze temperature data, and verify real-time data to determine whether there are defects inside the air duct. The data analysis terminal is also used to control data transmission and information interaction between various modules. A database system is used to store historical data of the air duct and a diagram of the equipment distribution inside the air duct. A missing data supplementation module is used to supplement the historical data of the air duct to obtain complete historical data of the air duct. A temperature drop pattern determination module is used to perform data analysis on complete historical data of the air duct to determine the temperature drop pattern at different locations in the air duct. The air duct defect verification module verifies the real-time data of the air duct based on the temperature drop pattern at different locations in the air duct to determine whether there are defects inside the air duct. An information transmitting device is used to send alarm information about defects inside the air duct to the outside world.

2. The duct inspection system based on CAN bus large data transmission according to claim 1, characterized in that, The missing data supplementation module is used to supplement the historical data of the air duct. The specific steps to obtain complete historical data of the air duct are as follows: Determine the communication protocol of the database system, and based on the communication protocol, perform data reading and processing on the database system to obtain historical data of the air duct; Based on data type, the historical data of the air duct is classified and processed to determine different types of historical data of the air duct; Set up a heatmap, and based on the heatmap, perform missing data lookup processing on historical data of different types of air ducts to determine the location and type of missing data. Based on the missing data type, the mean of historical data for different types of air ducts is calculated to determine the supplementary data for the missing data locations; Based on the supplementary data at the missing data locations, data supplementation processing is performed on the missing data locations to obtain complete historical data of the air duct.

3. The duct inspection system based on CAN bus large data transmission according to claim 1, characterized in that, The temperature drop pattern determination module is used to analyze complete historical data of the air duct and determine the temperature drop pattern at different locations in the air duct, specifically including the following steps: The complete historical data of the air duct is classified and processed to determine the historical temperature data at different locations in the air duct. The historical temperature data at different locations in the air duct are calculated, analyzed, and processed to determine the temperature change curves at different locations in the air duct. The temperature change curves at different locations in the air duct are calculated and processed to determine the temperature drop pattern at different locations in the air duct.

4. The air duct detection system based on CAN bus large data transmission according to claim 3, characterized in that, The process of classifying and processing the complete historical data of the air duct to determine the historical temperature data at different locations within the air duct specifically includes the following steps: The complete historical data of the air duct is read and processed to obtain the historical temperature data inside the air duct. Based on the database system, data reading and processing are performed to obtain the equipment distribution diagram inside the air duct; The location of the equipment distribution diagram inside the air duct is analyzed to determine the installation location of the temperature acquisition equipment inside the air duct. Based on the installation location of the temperature acquisition equipment inside the air duct, the historical temperature data inside the air duct is matched and processed to determine the historical temperature data at different locations in the air duct.

5. The air duct detection system based on CAN bus large data transmission according to claim 3, characterized in that, The process of calculating and analyzing historical temperature data at different locations in the air duct to determine the temperature change curves at different locations in the air duct specifically includes the following steps: Based on the acquisition time, the historical temperature data at different locations in the air duct are classified and processed to obtain historical temperature data at different acquisition times. Construct a rectangular coordinate system, where the X-axis parameter of the rectangular coordinate system is the acquisition time; and the Y-axis parameter of the rectangular coordinate system is the temperature data. Historical temperature data collected at different times were plotted into a Cartesian coordinate system to obtain temperature change curves at different locations in the air duct.

6. The air duct detection system based on CAN bus large data transmission according to claim 3, characterized in that, The calculation and processing of temperature change curves at different locations in the air duct to determine the temperature drop pattern at different locations in the air duct specifically includes the following steps: Based on the acquisition time, the slope of the temperature change curves at different locations in the air duct is calculated to obtain the slope of the curves at different nodes; wherein, the different nodes are specifically the historical temperature data corresponding to different acquisition times. The slope of the curves at different nodes is calculated by subtracting the slopes of adjacent time points to obtain the slope difference between nodes at adjacent time points. Based on the maximum value function, the slope difference of nodes at adjacent time points is sorted to obtain a set of node slope difference values; The node slope difference that appears most frequently in the set of node slope difference values ​​is set as the temperature decrease pattern at different locations in the air duct.

7. The duct inspection system based on CAN bus large data transmission according to claim 1, characterized in that, The air duct defect verification module verifies the real-time data of the air duct based on the temperature drop pattern at different locations within the air duct to determine whether defects exist inside the air duct. Specifically, this includes the following steps: The temperature acquisition device inside the air duct reads and processes the data to obtain real-time data of the air duct; Based on temperature data, real-time data of the air duct is read and processed to obtain real-time temperature data of the air duct. Based on the installation location of the temperature acquisition equipment inside the air duct, the real-time temperature data of the air duct is classified and processed to determine the real-time temperature data at different locations in the air duct. Based on the temperature drop pattern at different locations in the air duct, the real-time temperature data of the air duct is calculated and processed to determine the standard temperature data at different locations in the air duct. Based on standard temperature data at different locations in the air duct, the real-time temperature data at different locations in the air duct are compared and analyzed to determine whether there are any defects inside the air duct.

8. The duct inspection system based on CAN bus large data transmission according to claim 7, characterized in that, The process of calculating and processing real-time temperature data of the air duct based on the temperature drop pattern at different locations within the air duct to determine the standard temperature data for different locations specifically includes the following steps: Based on the installation location of the temperature acquisition equipment inside the air duct, the real-time temperature data at different locations in the air duct are matched and processed to determine the real-time temperature at the initial location of the air duct. Based on the initial position of the air duct, the temperature drop patterns at different positions of the air duct are sorted to determine the temperature drop patterns corresponding to different data acquisition positions in the air duct. Based on the temperature drop pattern corresponding to different data acquisition locations in the air duct, the real-time temperature at the initial location of the air duct is calculated and processed multiple times to determine the standard temperature data at different locations in the air duct.

9. A duct inspection system based on CAN bus large data transmission according to claim 7, characterized in that, The process of comparing and analyzing real-time temperature data at different locations within the air duct based on standard temperature data to determine whether defects exist inside the air duct includes the following steps: The temperature difference between the standard temperature data and the real-time temperature data at different locations in the air duct is calculated by subtracting the standard temperature data and the real-time temperature data at different locations in the air duct. The temperature difference at different locations in the air duct and the set temperature difference threshold at different locations in the air duct are judged and processed. If the temperature difference between different locations in the air duct is greater than or equal to the set temperature difference threshold between different locations in the air duct, there is a defect inside the air duct. If the temperature difference between different locations in the air duct is less than the set temperature difference threshold between different locations in the air duct, there are no defects inside the air duct.

Images