High-precision formaldehyde removal agent with formaldehyde removal analysis detection system

Abstract

The present application belongs to the technical field of formaldehyde scavenger detection and analysis, and specifically relates to a high-precision formaldehyde removal analysis and detection system for formaldehyde scavengers, which comprises a server, a group division marker module, a plate spraying detection and analysis module, an additional influencing factor supervision and analysis module, a comparison and detection logic analysis module, and a supervision and early warning end. The present application supervises the plate spraying process before the test and evaluates the quality after spraying, and generates additional influence qualified signals or additional influence unqualified signals of the reference group or the corresponding test group through analysis when detecting the formaldehyde removal effect, thereby ensuring the environmental consistency of the reference group and each test group, significantly improving the accuracy of the test results, and determining whether to generate an invalid evaluation signal of the corresponding test group through analysis, as well as generating a low-efficiency evaluation signal or a high-efficiency evaluation signal of the corresponding test group through analysis, so that the management personnel can timely and in detail understand the test results, the test analysis is more comprehensive, and the test results are more accurate.

Description

High-precision formaldehyde removal agent formaldehyde analysis and detection system Technical Field

[0001] This invention relates to the field of formaldehyde removal agent detection and analysis technology, specifically a high-precision formaldehyde removal agent analysis and detection system. Background Technology

[0002] Currently, the main method for testing the formaldehyde removal effect of formaldehyde removers is to spray the formaldehyde remover onto the surface of the board and observe the subsequent formaldehyde release from the board to determine the formaldehyde removal effect. However, this method often fails to combine the analysis of the formaldehyde remover spraying condition with the analysis of additional influencing factors in the testing process, which is not conducive to improving the accuracy of subsequent test results. Furthermore, it is difficult to effectively analyze and evaluate the removal effect of different concentrations of formaldehyde removers, which is not conducive to the rational selection of formaldehyde remover concentrations for subsequent production.

[0003] To address the aforementioned technical shortcomings, a solution is proposed. Summary of the Invention

[0004] The purpose of this invention is to provide a high-precision formaldehyde removal analysis and detection system for formaldehyde removal agents. This system solves the problems in the prior art, which cannot combine the analysis of the formaldehyde removal agent spraying condition with the analysis of additional influencing factors in the testing process. This is not conducive to improving the accuracy of subsequent test results, and it is difficult to effectively analyze and evaluate the removal effect of different concentrations of formaldehyde removal agents, which is not conducive to the rational selection of formaldehyde removal agent concentrations for subsequent production.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A high-precision formaldehyde removal analysis and detection system for formaldehyde removal agents includes a server, a group classification and marking module, a board coating detection and analysis module, an additional influencing factor monitoring and analysis module, a comparison and detection logic analysis module, and a monitoring and early warning terminal. The group classification and marking module collects data from a reference group and several test groups. The reference group represents boards that have not been sprayed with formaldehyde removal agent, and the test groups represent boards that have been sprayed with formaldehyde removal agent. The reference group and the test groups use boards of the same specifications. The concentration of formaldehyde removal agent sprayed in different test groups is different. The test groups are sorted in ascending order of concentration, and the corresponding test group is marked as i, where i is a natural number greater than 1.

[0007] The panel spraying detection and analysis module is used to analyze the spraying status of the corresponding test group i during automatic spraying equipment spraying. If an abnormal spraying status is detected, the automatic spraying equipment is adjusted promptly. After spraying, the module marks the corresponding test area of ​​test group i as a positive spraying area or a negative spraying area. It also generates a qualified or unqualified spraying signal for test group i. The unqualified spraying signal is sent to the monitoring and early warning terminal via the server. Upon receiving the unqualified spraying signal, the monitoring personnel discard the corresponding panel as needed. The additional influencing factor monitoring and analysis module generates a qualified or unqualified additional influencing signal for the reference group or corresponding test group i during formaldehyde removal effect testing. The unqualified additional influencing signal is sent to the monitoring and early warning terminal via the server. Upon receiving the unqualified additional influencing signal, the monitoring and early warning terminal displays the signal and issues a corresponding early warning.

[0008] When testing the formaldehyde removal effect of the reference group and several experimental groups, the comparison detection logic analysis module generates a comparison coordinate system and marks the formaldehyde concentration release reference line and several formaldehyde concentration release analysis lines in the comparison coordinate system. Through analysis, it determines whether an invalid evaluation signal is generated for the corresponding experimental group i, and marks the experimental group that does not generate an invalid evaluation signal as the consideration group. Through analysis, it generates a poor evaluation signal or a high-efficiency evaluation signal for the corresponding consideration group. The invalid evaluation signal, poor evaluation signal, high-efficiency evaluation signal and the corresponding experimental group are sent to the regulatory warning terminal via the server.

[0009] Furthermore, the specific operation process of the sheet metal coating detection and analysis module includes:

[0010] Formaldehyde remover of the corresponding concentration was sprayed onto the surface of test group i using an automatic spraying device. During spraying, the spraying speed data and the straight-line distance between the nozzle and the board were collected. The spraying speed data and straight-line distance were compared with the preset spraying speed range and preset straight-line distance range. If the spraying speed data and straight-line distance were both within the corresponding preset range, the spraying condition was judged to be normal; otherwise, the spraying condition was judged to be abnormal and a corresponding spraying adjustment command was generated to make the automatic spraying device make corresponding adjustments to ensure the spraying effect and uniformity.

[0011] Furthermore, during the spraying process, the surface of test group i is divided into several detection areas, which are marked as u. Data on the amount of formaldehyde remover sprayed by the automatic spraying equipment in detection area u is collected. The spraying amount data is compared with the preset spraying amount data range. If the spraying amount data is within the preset spraying amount data range, the corresponding detection area u is marked as the positive spraying area. If the spraying amount data is not within the preset spraying amount data range, the corresponding detection area u is marked as the negative spraying area.

[0012] The ratio of the number of non-standard sprayed areas to the number of standard sprayed areas is calculated and marked as ZP1. The deviation of the spray amount data of the corresponding non-standard sprayed area from the preset spray amount data range is marked as the spray amount deviation parameter. The spray amount deviation parameters of all non-standard sprayed areas are summed and the calculation result is marked as ZP2. ZP1 and ZP2 are numerically calculated to obtain the spray non-standard coefficient. The spray non-standard coefficient is numerically compared with the preset spray non-standard coefficient threshold. If the spray non-standard coefficient exceeds the preset spray non-standard coefficient threshold, a spray non-compliance signal is generated. If the spray non-standard coefficient does not exceed the preset spray non-standard coefficient threshold, a spray compliance signal is generated.

[0013] Furthermore, the specific analysis process of the additional influencing factors regulatory analysis module includes:

[0014] During the testing process, an association analysis set was established between the reference group and all test groups. A subset in the association analysis set was labeled as the analysis object k, where k is a natural number greater than 1. Environmental performance information of the environment in which the analysis object k was located during the testing period was collected. The environmental performance information included environmental temperature data, environmental humidity data, environmental brightness data, and environmental wind speed data. The environmental temperature data, environmental humidity data, environmental brightness data, and environmental wind speed data were normalized to obtain the ring surface value.

[0015] The system collects the average and maximum dust concentration values ​​of the environment in which the analysis object k is located during the detection period, as well as the average and maximum bacterial content data of the environment in which the analysis object k is located during the detection period. The average dust concentration value, maximum dust concentration value, average bacterial content data, and maximum bacterial content data are normalized to obtain the surface cleanliness value. The surface cleanliness value and the surface cleanliness value are compared with the preset surface cleanliness threshold and the preset surface cleanliness threshold, respectively. If the surface cleanliness value does not exceed the preset surface cleanliness threshold and the surface cleanliness value does not exceed the preset surface cleanliness threshold, an additional influence qualified signal for the corresponding analysis object k is generated. Otherwise, an additional influence unqualified signal for the corresponding analysis object k is generated.

[0016] Furthermore, the methods for analyzing and obtaining environmental performance information are as follows:

[0017] Several sets of detection time points are set during the detection period, with the same time interval between adjacent sets of detection time points. Real-time temperature, real-time humidity, real-time brightness, and real-time wind speed of the environment corresponding to the analysis object k are collected at each detection time point. A temperature set is established for the real-time temperature of all detection time points corresponding to the analysis object k. Similarly, a humidity set, brightness set, and wind speed set are established. The temperature sets are summed and the average value is taken to obtain the temperature average coefficient. The difference between the maximum and minimum values ​​in the temperature set is calculated to obtain the temperature fluctuation value. The temperature average coefficient and the temperature fluctuation value are weighted and summed to obtain the temperature condition data. The temperature condition data is compared with the preset temperature condition data judgment value, and the absolute value is taken to obtain the ambient temperature data. Similarly, ambient humidity data, ambient brightness data, and ambient wind speed data are obtained.

[0018] Furthermore, the specific operation process of the comparison and detection logic analysis module includes:

[0019] A rectangular coordinate system was established with time as the X-axis and formaldehyde concentration as the Y-axis, and marked as the comparison coordinate system. The formaldehyde concentration change curve of the reference group was placed into the comparison coordinate system to form a formaldehyde concentration release reference line. The formaldehyde concentration change curves of each experimental group were also placed into the comparison coordinate system to form several sets of formaldehyde concentration release analysis lines. If the formaldehyde concentration release analysis line of the corresponding experimental group i coincides with the formaldehyde concentration release reference line or is always above the formaldehyde concentration release analysis line, it is determined that the corresponding experimental group i has no formaldehyde removal effect, and an invalid evaluation signal for the corresponding experimental group i is generated.

[0020] Otherwise, several time points are randomly collected, and reference coordinate points are marked on the formaldehyde concentration release reference line with the corresponding time points as the x-axis, and analysis coordinate points are marked on the formaldehyde concentration release analysis line. If the analysis coordinate point is below the corresponding reference coordinate point, the reference coordinate point and the corresponding analysis coordinate point are connected by a line segment to form a release difference line segment, and the length of the release difference line segment is marked as the release deviation data. All release deviation data of the corresponding experimental group i are collected, and the release deviation data are compared with the preset release deviation data threshold. If the release deviation data does not exceed the preset release deviation data threshold, the corresponding release deviation data is marked as low deviation data; otherwise, the corresponding deviation data is marked as high deviation data. If there is no high deviation data in the corresponding experimental group i, it is determined that the corresponding experimental group i has no effect on formaldehyde removal, and an invalid evaluation signal for the corresponding experimental group i is generated.

[0021] Furthermore, when generating invalid evaluation signals, the corresponding test group i is removed, and the remaining test groups are marked as consideration groups. The formaldehyde concentration termination value of the corresponding consideration group and the formaldehyde concentration peak value of the reference group are collected. The formaldehyde removal coefficient is calculated by the difference between the formaldehyde concentration termination value of the corresponding consideration group and the formaldehyde concentration peak value of the reference group. The formaldehyde removal amount value is calculated by the ratio between the formaldehyde removal coefficient and the formaldehyde concentration peak value of the reference group. The formaldehyde removal amount value is compared with the preset formaldehyde removal threshold. If the formaldehyde removal amount value does not exceed the preset formaldehyde removal threshold, it is determined that the formaldehyde removal effect of the corresponding consideration group is poor and an ineffective evaluation signal for the corresponding consideration group is generated.

[0022] If the formaldehyde removal value exceeds the preset formaldehyde removal threshold, the formaldehyde concentration termination time for the corresponding assessment group is collected. The formaldehyde concentration termination time is compared with the preset formaldehyde concentration termination time threshold. If the formaldehyde concentration termination time exceeds the preset formaldehyde concentration termination time threshold, the formaldehyde removal effect of the corresponding assessment group is judged to be poor, and a poor performance evaluation signal for the corresponding assessment group is generated. If the formaldehyde concentration termination time does not exceed the preset formaldehyde concentration termination time threshold, the formaldehyde removal effect of the corresponding assessment group is judged to be excellent, and a high performance evaluation signal for the corresponding assessment group is generated.

[0023] Furthermore, when generating the high-efficiency evaluation signal, all consideration groups corresponding to the high-efficiency evaluation signal are obtained. The difference between the preset formaldehyde concentration termination time threshold and the formaldehyde concentration termination time of the corresponding consideration group is calculated to obtain the final time difference value. The formaldehyde removal amount value and the final time difference value of the corresponding consideration group are numerically calculated to obtain the cleaning efficiency analysis value. All consideration groups are sorted from largest to smallest according to the cleaning efficiency analysis value, and an experimental analysis set is established according to the sorting result. The consideration group at the top is marked as the best performing object. The best performing object and the experimental analysis set are sent to the regulatory warning terminal via the server.

[0024] Compared with the prior art, the beneficial effects of the present invention are:

[0025] 1. In this invention, by judging the surface spraying status of the corresponding test group i in order to adjust the automatic spraying equipment in a timely manner, and by analyzing and generating the spraying qualified signal or spraying unqualified signal of the corresponding test group i, the pre-test board spraying process supervision and post-testing quality assessment are realized, which helps to ensure the accuracy of subsequent test results. Furthermore, when conducting formaldehyde removal effect testing, by analyzing and generating the additional influence qualified signal or additional influence unqualified signal of the reference group or the corresponding test group i, the management personnel can make timely adjustments to the corresponding environment, ensure the environmental consistency of the reference group and each test group, reduce the deviation of test results caused by environmental factors, and thus further improve the accuracy of test results.

[0026] 2. In this invention, the comparison and detection logic analysis module analyzes and determines whether an invalid evaluation signal is generated for the corresponding test group i, and marks the test group that does not generate an invalid evaluation signal as a consideration group. It also analyzes and generates a differential evaluation signal or a high-efficiency evaluation signal for the corresponding consideration group. This allows managers to understand the test results in a timely and detailed manner, making the test analysis more comprehensive and the test results more accurate. This helps managers to grasp the effect of formaldehyde removal agents of different concentrations, facilitating subsequent reasonable selection and production. Attached Figure Description

[0027] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings;

[0028] Figure 1 is an overall system block diagram of the present invention. Detailed Implementation

[0029] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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.

[0030] Example 1: As shown in Figure 1, the high-precision formaldehyde removal analysis and detection system for formaldehyde removal agents proposed in this invention includes a server, a group classification and marking module, a board coating detection and analysis module, an additional influencing factor monitoring and analysis module, a comparison detection logic analysis module, and a monitoring and early warning terminal. The server is communicatively connected to the group classification and marking module, the board coating detection and analysis module, the additional influencing factor monitoring and analysis module, the comparison detection logic analysis module, and the monitoring and early warning terminal. The group classification and marking module collects a reference group and several test groups. The reference group represents boards that have not been sprayed with formaldehyde removal agent, and the test groups represent boards that have been sprayed with formaldehyde removal agent. The concentration of formaldehyde removal agent sprayed in different test groups is different. The test groups are sorted in ascending order of concentration, and the corresponding test group is marked as i, where i is a natural number greater than 1. Preferably, the reference group and the test groups use boards of the same specifications (i.e., the material, length, width, thickness, etc. are all the same). The boards used can continuously release formaldehyde due to appropriate treatment.

[0031] The panel coating detection and analysis module is used to analyze the coating condition during the automatic coating equipment's spraying of the surface corresponding to test group i to determine the coating status. If abnormalities are detected, the automatic coating equipment is adjusted promptly. After coating, the module marks the corresponding detection area of ​​test group i as a positive or negative spraying area based on the analysis. It also generates a coating pass / fail signal for test group i. The non-fail signal is sent to the monitoring and early warning terminal via the server. Upon receiving the non-fail signal, the monitoring personnel discard the corresponding panel as needed. This achieves pre-test panel coating process monitoring and post-test quality assessment, which helps ensure the accuracy of subsequent test results. The specific operation process of the panel coating detection and analysis module is as follows:

[0032] Formaldehyde remover of the corresponding concentration is sprayed onto the surface of test group i using an automatic spraying device. During spraying, the spraying speed data and the straight-line distance between the nozzle and the board are collected. The spraying speed data and straight-line distance are compared with preset spraying speed range and preset straight-line distance range. If the spraying speed data and straight-line distance are both within the corresponding preset range, it indicates that the current spraying operation is standard and the spraying condition is judged to be normal. If the spraying speed data is not within the preset spraying speed range and / or the straight-line distance is not within the preset straight-line distance range, it indicates that the current spraying operation is not standard and the spraying condition is judged to be abnormal. A corresponding spraying adjustment command is generated to make the automatic spraying device make corresponding adjustments to ensure the spraying effect and spraying uniformity, thereby realizing real-time detection and accurate analysis of the spraying process.

[0033] Furthermore, during the spraying process, the surface of test group i was divided into several detection areas, labeled as u. Data on the amount of formaldehyde remover sprayed by the automatic spraying equipment in detection area u was collected. The spraying amount data was compared with the preset spraying amount data range. If the spraying amount data was within the preset spraying amount data range, the corresponding detection area u was marked as the positive spraying area. If the spraying amount data was not within the preset spraying amount data range, the corresponding detection area u was marked as the negative spraying area. The ratio of the number of negative spraying areas to the number of positive spraying areas was calculated and the ratio result was marked as ZP1. The deviation of the spraying amount data of the corresponding negative spraying area from the preset spraying amount data range was marked as the spraying amount deviation parameter. The spraying amount deviation parameters of all negative spraying areas were summed and the calculation result was marked as ZP2.

[0034] The spray variation coefficient PYi for test group i is obtained by numerically calculating ZP1 and ZP2 using the formula PYi = a1*ZP1 + a2*ZP2, where a1 and a2 are preset weighting coefficients, and a1 > a2 > 0. A larger PYi value indicates that the coated board meets the requirements, while a smaller PYi value indicates that the coated board is less suitable for the current test. The PYi value is compared with a preset threshold. If the PYi value exceeds the threshold, a spraying failure signal is generated; if the PYi value does not exceed the threshold, a spraying success signal is generated. This ensures the uniformity of the coating on the corresponding board, which is helpful for subsequent formaldehyde removal effect tests.

[0035] The Additional Influencing Factors Monitoring and Analysis module generates either a qualified or unqualified additional influence signal for the reference group or corresponding test group i during formaldehyde removal effect testing. The unqualified additional influence signal is sent to the monitoring and early warning terminal via the server. Upon receiving the unqualified additional influence signal, the monitoring and early warning terminal displays the signal and issues a corresponding warning. Upon receiving the warning, the relevant management personnel promptly adjust the corresponding environment to ensure environmental consistency between the reference group and each test group, reducing deviations in test results caused by environmental factors and thus significantly improving the accuracy of the test results. The specific analysis process of the Additional Influencing Factors Monitoring and Analysis module is as follows:

[0036] During the testing process, an association analysis set was established between the reference group and all test groups. A subset in the association analysis set was labeled as the analysis object k, where k is a natural number greater than 1. Environmental performance information of the environment where the analysis object k was located during the testing period was collected. Specifically, several sets of testing time points were set during the testing period, with the same time interval between two adjacent sets of testing time points. Real-time temperature, real-time humidity, real-time brightness, and real-time wind speed of the environment where the analysis object k was located were collected at the testing time points. A temperature set was established for the real-time temperature of all testing time points corresponding to the analysis object k. Similarly, a humidity set, a brightness set, and a wind speed set were established. The temperature sets were summed and the mean was taken to obtain the temperature average coefficient. The difference between the maximum and minimum values ​​in the temperature sets was calculated to obtain the temperature fluctuation value.

[0037] The temperature data is obtained by weighting and summing the temperature average coefficient and the temperature difference value. Specifically, the temperature average coefficient and the temperature difference value are assigned weight coefficients c1 and c2, respectively. The temperature average coefficient is multiplied by the weight coefficient c1, and the temperature difference value is multiplied by the weight coefficient c2. The sum of these two products yields the temperature data. The ambient temperature data is obtained by calculating the difference between the temperature data and a preset temperature data judgment value. This preset temperature data judgment value is pre-set by management personnel, entered into the server, and represents the optimal temperature value for temperature data determination. Similarly, ambient humidity data, ambient light data, and ambient wind speed data are obtained. It should be noted that the smaller the ambient temperature, ambient humidity, ambient light, and ambient wind speed values, the smaller the environmental deviation from the optimal test environment.

[0038] The ambient temperature data WP1, ambient humidity data WP2, ambient brightness data WP3, and ambient wind speed data WP4 are normalized and calculated using the formula HWk = ru1*WP1 + ru2*WP2 + ru3*WP3 + ru4*WP4 to obtain the loop table value HWk. Here, ru1, ru2, ru3, and ru4 are preset weighting coefficients, and all values ​​of ru1, ru2, ru3, and ru4 are greater than zero. The smaller the loop table value HWk, the better the environmental conditions of the corresponding analysis object k, the less adjustment is needed, and the more it helps ensure the accuracy of the experimental results.

[0039] The average and maximum dust concentration values ​​of the environment in which the analyte k was located during the detection period were collected, as well as the average and maximum bacterial content data of the environment in which the analyte k was located during the detection period. The surface cleanliness value JWk was obtained by normalizing the average dust concentration value PH1, the maximum dust concentration value PH2, the average bacterial content data PH3, and the maximum bacterial content data PH4 using the formula JWk=(ep1*PH1+ep2*PH2) / 2+(ep3*PH3+ep4*PH4) / 2. Among them, ep1, ep2, ep3, and ep4 are preset weighting coefficients, and the values ​​of ep1, ep2, ep3, and ep4 are all greater than zero. Furthermore, the smaller the surface cleanliness value JWk, the cleaner the environment in which the analyte k is located, which is more conducive to ensuring the accuracy of the test results.

[0040] The ring surface value and clean surface value are compared with the preset ring surface threshold and preset clean surface threshold respectively. If the ring surface value of the corresponding analysis object k does not exceed the preset ring surface threshold and the clean surface value does not exceed the preset clean surface threshold, it indicates that the environmental conditions of the corresponding analysis object k are good and the influence of additional influencing factors on the accuracy of the test results is small. In this case, an additional influence qualified signal for the corresponding analysis object k is generated. If the ring surface value of the corresponding analysis object k exceeds the preset ring surface threshold and / or the clean surface value exceeds the preset clean surface threshold, it indicates that the environmental conditions of the corresponding analysis object k are poor and the influence of additional influencing factors on the accuracy of the test results is large. In this case, an additional influence unqualified signal for the corresponding analysis object k is generated.

[0041] When testing the formaldehyde removal effect of the reference group and several experimental groups, the comparison and detection logic analysis module generates a comparison coordinate system and marks the formaldehyde concentration release reference line and several sets of formaldehyde concentration release analysis lines in the comparison coordinate system. Analysis is used to determine whether an invalid evaluation signal is generated for the corresponding experimental group i, and experimental groups that do not generate invalid evaluation signals are marked as consideration groups. Further analysis generates poor or high efficiency evaluation signals for the corresponding consideration groups. The invalid, poor, and high efficiency evaluation signals, along with their corresponding experimental groups, are sent to the monitoring and early warning terminal via the server. This allows managers to promptly and thoroughly understand the test results, making the test analysis more comprehensive and the results more accurate. This helps managers understand the effectiveness of formaldehyde removers at different concentrations, facilitating subsequent rational selection and production. The specific operation process of the comparison and detection logic analysis module is as follows:

[0042] A rectangular coordinate system was established with time as the X-axis and formaldehyde concentration as the Y-axis, and marked as the comparison coordinate system. The formaldehyde concentration change curve of the reference group was placed into the comparison coordinate system to form a formaldehyde concentration release reference line. The formaldehyde concentration change curves of each experimental group were also placed into the comparison coordinate system to form several sets of formaldehyde concentration release analysis lines. If the formaldehyde concentration release analysis line of the corresponding experimental group i coincides with the formaldehyde concentration release reference line or is always above the formaldehyde concentration release analysis line, it indicates that the formaldehyde release state of the corresponding experimental group i is basically the same as that of the reference group. Therefore, it is judged that the corresponding experimental group i has no formaldehyde removal effect, and an invalid evaluation signal for the corresponding experimental group i is generated.

[0043] Otherwise, several time points are randomly collected, and reference coordinate points are marked on the formaldehyde concentration release reference line with the corresponding time points as the x-axis, and analysis coordinate points are marked on the formaldehyde concentration release analysis line. If the analysis coordinate point is below the corresponding reference coordinate point, the reference coordinate point and the corresponding analysis coordinate point are connected by a line segment to form a release difference line segment. The length of the release difference line segment is marked as the release deviation data. The larger the value of the corresponding release deviation data, the better the formaldehyde removal effect at the corresponding time point. All release deviation data of the corresponding experimental group i are collected, and the release deviation data is compared with the preset release deviation data threshold. If the release deviation data does not exceed the preset release deviation data threshold, the corresponding release deviation data is marked as low deviation data. If the release deviation data exceeds the preset release deviation data threshold, the corresponding deviation data is marked as high deviation data. If there is no high deviation data in the corresponding experimental group i, it indicates that the formaldehyde release state of the corresponding experimental group i is basically the same as that of the reference group. Therefore, it is judged that the corresponding experimental group i has no formaldehyde removal effect, and an invalid evaluation signal for the corresponding experimental group i is generated.

[0044] When generating an invalid evaluation signal, the corresponding test group i is removed, and the remaining test groups are marked as the consideration group. The formaldehyde concentration termination value of the corresponding consideration group and the formaldehyde concentration peak value of the reference group are collected. The formaldehyde concentration termination value is the final stable release concentration value. For example, if the formaldehyde concentration termination value of the corresponding consideration group is 0, it indicates that the corresponding consideration group can completely remove formaldehyde and the formaldehyde removal effect is excellent. The formaldehyde removal coefficient is calculated by the difference between the formaldehyde concentration termination value of the corresponding consideration group and the formaldehyde concentration peak value of the reference group. The formaldehyde removal amount value is calculated by the ratio of the formaldehyde removal coefficient to the formaldehyde concentration peak value of the reference group. The formaldehyde removal amount value is compared with the preset formaldehyde removal threshold. If the formaldehyde removal amount value does not exceed the preset formaldehyde removal threshold, it is judged that the formaldehyde removal effect of the corresponding consideration group is poor and a poor evaluation signal for the corresponding consideration group is generated.

[0045] If the formaldehyde removal value exceeds the preset formaldehyde removal threshold, the formaldehyde concentration termination time for the corresponding assessment group is collected. The larger the formaldehyde concentration termination time, the slower the formaldehyde removal efficiency of the corresponding assessment group. The formaldehyde concentration termination time is compared with the preset formaldehyde concentration termination time threshold. If the formaldehyde concentration termination time exceeds the preset formaldehyde concentration termination time threshold, the formaldehyde removal effect of the corresponding assessment group is judged to be poor, and a poor performance evaluation signal is generated for the corresponding assessment group. If the formaldehyde concentration termination time does not exceed the preset formaldehyde concentration termination time threshold, the formaldehyde removal effect of the corresponding assessment group is judged to be excellent, and a high performance evaluation signal is generated for the corresponding assessment group.

[0046] Example 2: The difference between this example and Example 1 is that, when generating the high-efficiency evaluation signal, all consideration groups corresponding to the high-efficiency evaluation signal are obtained. The difference between the preset formaldehyde concentration termination time threshold and the formaldehyde concentration termination time of the corresponding consideration group is calculated to obtain the final time difference value FR. The formaldehyde removal amount value QL and the final time difference value FR of the corresponding consideration group are numerically calculated using the formula QX=(sd1*QL+sd2*FR) / (sd1+sd2) to obtain the purification efficiency analysis value QX, where sd1 and sd2 are preset weight systems. The order is sd1 > sd2 > 1. Furthermore, the larger the value of the formaldehyde removal efficiency analysis value QX, the better the formaldehyde removal effect and efficiency of the corresponding consideration group. All consideration groups are sorted from largest to smallest according to the formaldehyde removal efficiency analysis value, and an experimental analysis set is established based on the sorting results. The consideration group at the top is marked as the best performing group. The best performing group and the experimental analysis set are sent to the monitoring and early warning terminal via the server. The monitoring and early warning terminal displays the corresponding information, which helps the relevant managers select the appropriate formaldehyde removal agent concentration.

[0047] The working principle of this invention is as follows: During use, the panel spraying detection and analysis module judges the surface spraying condition of the corresponding test group i. When an abnormal spraying condition is detected, the automatic spraying equipment is adjusted promptly. After spraying, the corresponding detection area on the surface of test group i is marked as a positive spraying area or an abnormal spraying area through analysis. Furthermore, a qualified or unqualified spraying signal for test group i is generated through analysis. When an unqualified spraying signal is generated, the corresponding panel is discarded as needed. This achieves pre-test panel spraying process monitoring and post-test quality assessment, which helps ensure the accuracy of subsequent test results. The additional influencing factor monitoring and analysis module, when testing the formaldehyde removal effect, analyzes and generates additional influencing factors for the reference group or the corresponding test group i. The system generates non-compliant signals or additional signals that affect the test results, enabling managers to make timely adjustments to the environment, ensuring consistency between the reference group and each test group, reducing deviations in test results caused by environmental factors, and further improving the accuracy of test results. The comparison and detection logic analysis module analyzes and determines whether an invalid evaluation signal is generated for the corresponding test group i, and marks test groups that do not generate invalid evaluation signals as consideration groups. It also analyzes and generates differential or high-efficiency evaluation signals for the corresponding consideration groups, allowing managers to understand the test results in a timely and detailed manner. The test analysis is more comprehensive, and the test results are more accurate, helping managers to grasp the effectiveness of formaldehyde removal agents at different concentrations, facilitating subsequent rational selection and production.

[0048] The above formulas are all dimensionless numerical calculations. These formulas are derived from software simulations using collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to actual conditions. The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. The preferred embodiments do not exhaustively describe all details, nor do they limit the invention to specific implementations. These embodiments are selected and specifically described in this specification to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A high-precision formaldehyde removal agent formaldehyde analysis and detection system, characterized in that, The system includes a server, a group classification and marking module, a board coating detection and analysis module, an additional influencing factor monitoring and analysis module, a comparison and detection logic analysis module, and a monitoring and early warning terminal. The group classification and marking module collects data on a reference group and several test groups. The reference group represents boards without formaldehyde removal agent, while the test groups represent boards with formaldehyde removal agent coating. Both the reference and test groups use boards of the same specifications, but the concentration of formaldehyde removal agent used in different test groups varies. The test groups are sorted in ascending order of concentration and marked as i, where i is a natural number greater than 1. The board coating detection and analysis module analyzes the coating status during automatic coating equipment spraying the surface of test group i to determine the coating condition. If an abnormal coating status is detected, the automatic coating equipment is adjusted promptly. After coating, the module analyzes and marks the corresponding detection area of ​​test group i as a positive or negative spraying area, and generates a coating pass or fail signal for test group i. The failure signal is then sent to the server. At the regulatory early warning end, when regulatory personnel receive a signal indicating substandard spraying, they will discard the corresponding board material as needed. The additional influencing factor regulatory analysis module, during formaldehyde removal effect testing, generates an additional influence pass signal or an additional influence fail signal for the reference group or corresponding test group i. The additional influence fail signal is sent to the regulatory early warning end via the server. Upon receiving the additional influence fail signal, the regulatory early warning end displays the signal and issues a corresponding warning. During formaldehyde removal effect testing of the reference group and several test groups, the comparison detection logic analysis module generates a comparison coordinate system and marks formaldehyde concentration release reference lines and several sets of formaldehyde concentration release analysis lines in the comparison coordinate system. Analysis determines whether an invalid evaluation signal for the corresponding test group i is generated, and test groups that do not generate invalid evaluation signals are marked as consideration groups. Analysis also generates a poor or high efficiency evaluation signal for the corresponding consideration group. The invalid evaluation signal, poor evaluation signal, high efficiency evaluation signal, and the corresponding test group are sent to the regulatory early warning end via the server. The specific analysis process of the additional influencing factors regulatory analysis module includes: during the testing process, establishing an association analysis set between the reference group and all test groups, marking the subset in the association analysis set as the analysis object k, where k is a natural number greater than 1; collecting environmental performance information of the environment where the analysis object k is located during the testing period, including environmental temperature data, environmental humidity data, environmental brightness data, and environmental wind speed data, and normalizing the environmental temperature data, environmental humidity data, environmental brightness data, and environmental wind speed data to obtain the environmental table value; The system collects the average and maximum dust concentration values ​​of the environment in which the analysis object k is located during the detection period, as well as the average and maximum bacterial content data of the environment in which the analysis object k is located during the detection period. The average dust concentration value, maximum dust concentration value, average bacterial content data, and maximum bacterial content data are normalized to obtain the surface cleanliness value. The surface cleanliness value and the environmental surface cleanliness value are compared with the preset surface cleanliness threshold and the preset surface cleanliness threshold, respectively. If the surface cleanliness value does not exceed the preset surface cleanliness threshold and the surface cleanliness value does not exceed the preset surface cleanliness threshold, an additional impact qualified signal for the corresponding analysis object k is generated; otherwise, an additional impact unqualified signal for the corresponding analysis object k is generated. The method for analyzing and obtaining environmental performance information is as follows: During the detection period... Several sets of detection time points are set, with the same time interval between adjacent sets. Real-time temperature, humidity, brightness, and wind speed of the environment corresponding to the analysis object k are collected at each detection time point. A temperature set is established for the real-time temperature of all detection time points corresponding to the analysis object k. Similarly, humidity, brightness, and wind speed sets are established. The temperature sets are summed and the average value is taken to obtain the temperature average coefficient. The difference between the maximum and minimum values ​​in the temperature set is calculated to obtain the temperature fluctuation value. The temperature average coefficient and the temperature fluctuation value are weighted and summed to obtain the temperature condition data. The temperature condition data is compared with the preset temperature condition data judgment value, and the absolute value is taken to obtain the ambient temperature data. Similarly, ambient humidity, ambient brightness, and ambient wind speed data are obtained.

2. The high-precision formaldehyde removal agent formaldehyde analysis and detection system according to claim 1, characterized in that, The specific operation process of the board coating detection and analysis module includes: spraying a formaldehyde remover of the corresponding concentration onto the surface of the corresponding test group i using an automatic spraying device; collecting the spraying speed data and the straight-line distance between the nozzle and the board during spraying; comparing the spraying speed data and straight-line distance with preset spraying speed ranges and preset straight-line distance ranges; if both are within the corresponding preset ranges, the spraying condition is judged to be normal; otherwise, the spraying condition is judged to be abnormal and a corresponding spraying adjustment command is generated to make the automatic spraying device adjust accordingly to ensure the spraying effect and uniformity; and after spraying is completed, the surface of test group i is divided into several detection areas, marked as u, and the amount of formaldehyde remover sprayed by the automatic spraying device in detection area u is collected, and the spraying amount data is compared with the preset spraying amount. The data range is compared numerically. If the spray volume data is within the preset spray volume data range, the corresponding detection area u is marked as the positive spray area. If the spray volume data is not within the preset spray volume data range, the corresponding detection area u is marked as the negative spray area. The ratio of the number of negative spray areas to the number of positive spray areas is calculated and the ratio result is marked as ZP1. The deviation of the spray volume data of the corresponding negative spray area from the preset spray volume data range is marked as the spray volume deviation parameter. The spray volume deviation parameters of all negative spray areas are summed and the calculation result is marked as ZP2. ZP1 and ZP2 are numerically calculated to obtain the negative spray coefficient. The negative spray coefficient is numerically compared with the preset negative spray coefficient threshold. If the negative spray coefficient exceeds the preset negative spray coefficient threshold, a negative spray signal is generated. If the negative spray coefficient does not exceed the preset negative spray coefficient threshold, a positive spray signal is generated.

3. The high-precision formaldehyde removal agent formaldehyde analysis and detection system according to claim 1, characterized in that, The specific operation process of the comparison and detection logic analysis module includes: establishing a rectangular coordinate system with time as the X-axis and formaldehyde concentration as the Y-axis, and marking it as the comparison coordinate system; placing the formaldehyde concentration change curve of the reference group into the comparison coordinate system to form a formaldehyde concentration release reference line; and placing the formaldehyde concentration change curves of each test group into the comparison coordinate system to form several sets of formaldehyde concentration release analysis lines; if the formaldehyde concentration release analysis line of the corresponding test group i coincides with the formaldehyde concentration release reference line or is always above the formaldehyde concentration release analysis line, it is determined that the corresponding test group i has no formaldehyde removal effect, and an invalid evaluation signal for the corresponding test group i is generated; otherwise, several time points are randomly collected, and the reference coordinates are marked on the formaldehyde concentration release reference line with the corresponding time points as the x-axis. The analysis coordinates are marked on the formaldehyde concentration release analysis line. If the analysis coordinate is below the corresponding reference coordinate, the reference coordinate and the corresponding analysis coordinate are connected by a line segment to form a release difference line segment. The length of the release difference line segment is marked as the release deviation data. All release deviation data for the corresponding test group i are collected and compared with the preset release deviation data threshold. If the release deviation data does not exceed the preset release deviation data threshold, the corresponding release deviation data is marked as low deviation data. Otherwise, the corresponding deviation data is marked as high deviation data. If there is no high deviation data in the corresponding test group i, it is determined that the corresponding test group i has no effect on formaldehyde removal and an invalid evaluation signal for the corresponding test group i is generated.

4. The high-precision formaldehyde removal agent formaldehyde analysis and detection system according to claim 3, characterized in that, When an invalid evaluation signal is generated, the corresponding test group i is removed, and the remaining test groups are marked as the consideration group. The formaldehyde concentration termination value of the corresponding consideration group and the formaldehyde concentration peak value of the reference group are collected. The formaldehyde removal coefficient is calculated by the difference between the formaldehyde concentration termination value of the corresponding consideration group and the formaldehyde concentration peak value of the reference group. The formaldehyde removal amount value is calculated by the ratio of the formaldehyde removal coefficient to the formaldehyde concentration peak value of the reference group. The formaldehyde removal amount value is compared with the preset formaldehyde removal threshold. If the formaldehyde removal amount value does not exceed the preset formaldehyde removal threshold, the formaldehyde removal effect of the corresponding consideration group is judged to be poor. A differential evaluation signal is generated for the corresponding assessment group. If the formaldehyde removal value exceeds the preset formaldehyde removal threshold, the formaldehyde concentration termination time for the corresponding assessment group is collected. The formaldehyde concentration termination time is compared with the preset formaldehyde concentration termination time threshold. If the formaldehyde concentration termination time exceeds the preset formaldehyde concentration termination time threshold, the formaldehyde removal effect of the corresponding assessment group is judged to be poor and a differential evaluation signal for the corresponding assessment group is generated. If the formaldehyde concentration termination time does not exceed the preset formaldehyde concentration termination time threshold, the formaldehyde removal effect of the corresponding assessment group is judged to be excellent and a high-efficiency evaluation signal for the corresponding assessment group is generated.

5. The high-precision formaldehyde removal agent formaldehyde analysis and detection system according to claim 4, characterized in that, When generating a high-efficiency evaluation signal, all consideration groups corresponding to the high-efficiency evaluation signal are obtained. The difference between the preset formaldehyde concentration termination time threshold and the formaldehyde concentration termination time of the corresponding consideration group is calculated to obtain the final time difference value. The formaldehyde removal amount value and the final time difference value of the corresponding consideration group are numerically calculated to obtain the cleaning efficiency analysis value. All consideration groups are sorted from largest to smallest according to the cleaning efficiency analysis value, and an experimental analysis set is established according to the sorting results. The consideration group at the top is marked as the best performing object. The best performing object and the experimental analysis set are sent to the regulatory warning terminal via the server.

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