Precise air conditioner outdoor unit detection method based on video inspection technology

Abstract

The invention belongs to the field of air conditioner outdoor unit blockage detection, relates to a video detection technology, is used for solving the problem that the type of a blockage object cannot be analyzed by combining detection parameters and historical blockage data in the prior art, and particularly relates to a precise air conditioner outdoor unit detection method based on a video inspection technology. Comprising the following steps that a high-definition camera is installed on an outdoor unit of the precise air conditioner; image data in the video data are extracted at the analysis time point and marked as analysis images, the blockage coefficient of the analysis images is obtained, and whether the blockage state of the heat dissipation opening at the analysis time point meets the requirement or not is judged according to the blockage coefficient; according to the method, blockage analysis can be performed on video data regularly, an analysis image is compared with a standard image, differentiation marking is performed on pixel grids, blockage probability evaluation is performed through the number proportion of gray scale abnormal grids, and data support is provided for the blockage feature extraction and analysis process.

Description

Technical Field

[0001] The invention belongs to the field of blockage detection of air-conditioning outdoor units, and relates to video detection technology, in particular to a precision air-conditioning outdoor unit detection method based on video inspection technology. Background Art

[0002] Precision air conditioning is used to provide a specific operating environment with constant temperature and humidity for precision devices such as IT equipment to ensure the normal operation of the equipment and the safe transmission of data. Therefore, its application in data centers is particularly critical because data centers usually have a large number of electronic devices such as servers and storage devices. These devices need to run for a long time and generate a lot of heat, which needs to be cooled by precision air conditioning to ensure the normal operation of the equipment.

[0003] The outdoor unit of the precision air conditioner works in the outdoor environment for a long time. Over time, the heat dissipation ports will be blocked by dust, plants, and lint, resulting in poor heat dissipation, which will lead to reduced efficiency or even shutdown of the indoor unit. The data room environment requires constant temperature and humidity. Reduced air conditioning efficiency or shutdown will directly lead to an increase in the room environment temperature.

[0004] The precision air-conditioning outdoor unit detection method in the prior art can only detect the blockage status of the heat dissipation port of the air-conditioning outdoor unit, but cannot analyze the type of blockage by combining the detection parameters with the historical blockage data, and thus cannot count the frequency of blockage caused by different types of blockages, and perform optimization decision analysis based on the statistical results.

[0005] In view of the above technical problems, this application proposes a solution. Summary of the invention

[0006] The purpose of the present invention is to provide a precision air conditioner outdoor unit detection method based on video inspection technology, which is used to solve the problem that the existing technology cannot analyze the type of blockage by combining detection parameters with historical blockage data;

[0007] The technical problem to be solved by the present invention is: how to provide a precision air-conditioning outdoor unit detection method based on video inspection technology that can analyze the type of blockage by combining detection parameters and historical blockage data.

[0008] The purpose of the present invention can be achieved through the following technical solutions:

[0009] A precision air-conditioning outdoor unit detection method based on video inspection technology, including an outdoor unit blockage detection method and a precision air-conditioning operation detection method;

[0010] The outdoor unit blockage detection method comprises the following steps:

[0011] Step S1: Install a high-definition camera on the outdoor unit of the precision air conditioner, collect video data of the heat dissipation port of the outdoor unit through the high-definition camera, and set a number of analysis time points with equal time intervals;

[0012] Step S2: regularly perform blockage analysis on the video data: extract image data from the video data at the analysis time point and mark it as an analysis image, obtain the blockage coefficient of the analysis image, and determine whether the blockage state of the heat dissipation port at the analysis time point meets the requirements through the blockage coefficient. If the blockage state does not meet the requirements, execute step S3;

[0013] Step S3: performing blockage feature extraction analysis on the analysis image: grayscale abnormal grids that are in contact with each other in the analysis image constitute an abnormal area, the number of grayscale abnormal grids in the abnormal area is marked as the abnormal value of the abnormal area, and the abnormal area is marked as an invalid extraction area or a valid extraction area by the abnormal value; the proportion data, grayscale data and gray difference data of the effective extraction area are obtained; the characteristic parameters of the effective extraction area are constituted by the proportion data, grayscale data and gray difference data;

[0014] Step S4: Retrieve historical congestion data from the database, which includes the nature of the congestion, the type of congestion object, and the congestion parameter range corresponding to the congestion object; compare the characteristic parameters of the effective extraction area in the analysis image with the congestion parameter range in all historical congestion data and obtain the extraction type of the effective extraction area; after completing the comparison of all effective extraction areas in the analysis image, generate a congestion processing signal and send the congestion processing signal and all extraction types to the mobile phone terminal of the manager.

[0015] Furthermore, in step S2, the analysis image is enlarged into a pixel grid image and grayscale transformation is performed, a standard image taken when the heat dissipation outlet of the outdoor unit is in a standard state without being blocked is retrieved, the standard image is also enlarged into a pixel grid image and grayscale transformation is performed, and the analysis image and the standard image are compared and analyzed: the absolute value of the difference between the grayscale value of the pixel grid at the same position in the analysis image and the grayscale value in the standard image is marked as the gray outlier value of the corresponding pixel grid, the gray outlier threshold of the pixel grid is retrieved, and the pixel grid whose gray outlier value is not less than the gray outlier threshold is marked as a gray outlier grid; the ratio of the number of gray outlier grids in the analysis image to the total number of pixel grids is marked as the blockage coefficient of the analysis image.

[0016] Furthermore, the specific process of determining whether the blockage state of the heat dissipation port at the analysis time point meets the requirements includes: comparing the blockage coefficient with a preset blockage threshold value: if the blockage coefficient is less than the blockage threshold value, it is determined that the blockage state of the heat dissipation port at the analysis time point meets the requirements, and step one is executed at the next analysis time point; if the blockage coefficient is greater than or equal to the blockage threshold value, it is determined that the blockage state of the heat dissipation port at the analysis time point does not meet the requirements.

[0017] Furthermore, in step S3, the specific process of marking the abnormal area as an invalid extraction area or a valid extraction area includes: comparing the abnormal value with a preset abnormal threshold: if the abnormal value is less than the abnormal threshold, the corresponding abnormal area is marked as an invalid extraction area; if the abnormal value is greater than or equal to the abnormal threshold, the corresponding abnormal area is marked as a valid extraction area.

[0018] Furthermore, in step S3, the process of acquiring the proportion data includes: generating a rectangular area that completely contains the effective extraction area in the analysis area, marking the ratio of the outlier value of the effective extraction area to the number of pixel grids in the rectangular area as the proportion data; the grayscale data is the average value of the grayscale values ​​of all grayscale outlier grids in the effective extraction area; the gray difference data HC is the difference between the maximum grayscale value and the minimum grayscale value of all grayscale outlier grids in the effective extraction area.

[0019] Furthermore, in step S4, the process of obtaining the extraction type of the effective extraction area includes: if all characteristic parameters of the effective extraction area in the analysis image correspond to the congestion parameter range corresponding to the congestion in the historical congestion data, then the type of congestion in the corresponding historical congestion data is marked as the extraction type of the effective extraction area.

[0020] Furthermore, the precision air conditioning operation detection method comprises the following steps:

[0021] Step Q1: When the precision air conditioner is turned on, the setting data of the precision air conditioner is obtained, and the setting data includes a set temperature value, a set humidity value, and a set wind speed value. L1 minutes after the precision air conditioner is turned on, the temperature deviation value WC, the humidity deviation value SC, and the wind speed deviation value FC of the precision air conditioner are obtained and numerical calculation is performed to obtain the detection coefficient JC of the precision air conditioner; the detection coefficient JC is compared with the preset detection threshold value JCmax: if the detection coefficient JC is less than the detection threshold value JCmax, it is determined that the operating state of the precision air conditioner meets the requirements; if the detection coefficient JC is greater than or equal to the detection threshold value JCmax, it is determined that the operating state of the precision air conditioner does not meet the requirements, and an abnormal operation signal is generated and sent to the mobile phone terminal of the administrator;

[0022] Step Q2: Perform periodic detection and analysis on the blocking state of the outdoor unit: generate a detection cycle, obtain the number of times the management personnel receive the blocking processing signal within the detection cycle and mark it as a processing value, and compare the processing value with a preset processing threshold: if the processing value is less than the processing threshold, it is determined that the overall blocking state of the outdoor unit within the detection cycle meets the requirements; if the processing value is greater than or equal to the processing threshold, it is determined that the overall blocking state of the outdoor unit within the detection cycle does not meet the requirements; execute step Q3;

[0023] Step Q3: Count the extraction types received by the management personnel during the detection period, mark the number of extraction types whose blockage properties are human-influenced as the habitual warning value, mark the number of extraction types whose blockage properties are naturally-influenced as the monitoring warning value, and compare the habitual warning value with the monitoring warning value: if the habitual warning value is less than the monitoring warning value, a natural monitoring signal is generated and sent to the management personnel's mobile phone terminal; if the habitual warning value is greater than the monitoring warning value, a habitual supervision signal is generated and sent to the management personnel's mobile phone terminal; if the habitual warning value is equal to the monitoring warning value, a merger optimization signal is generated and sent to the management personnel's mobile phone terminal.

[0024] Further, in step Q1, the process of obtaining the temperature deviation value WC, the humidity deviation value SC and the wind speed deviation value FC includes: obtaining indoor environmental data, the indoor environmental data including the indoor temperature value, the indoor humidity value and the operating wind speed value; marking the absolute value of the difference between the indoor temperature value and the set temperature value as the temperature deviation value WC, marking the absolute value of the difference between the indoor humidity value and the set humidity value as the humidity deviation value SC, and marking the absolute value of the difference between the operating wind speed value and the set wind speed value as the wind speed deviation value FC.

[0025] Furthermore, a computer storage medium stores a computer program, which, when executed by a processor, implements a precision air-conditioning outdoor unit detection method based on video inspection technology.

[0026] Furthermore, a computer device includes: a processor and a memory; the memory stores a computer program, and the processor executes the computer program stored in the memory, so that the computer device executes a precision air-conditioning outdoor unit detection method based on video inspection technology.

[0027] The present invention has the following beneficial effects:

[0028] 1. Regularly analyze the congestion of video data, compare the analysis image with the standard image and mark the pixel grid differently. The congestion probability is evaluated by the proportion of grayscale abnormal grids. When the congestion status does not meet the requirements, the analysis image is divided into regions by constructing abnormal regions, providing data support for the congestion feature extraction and analysis process.

[0029] 2. Through the blockage feature extraction analysis of the analysis image, multiple features of the effective extraction area are quantitatively fed back according to the extracted feature parameters, and then the feature parameters are compared with the blockage parameter range in the historical blockage data. The extraction type is marked according to the comparison result. The extraction type is the type of blockage corresponding to the effective extraction area. The management personnel can directly carry the corresponding processing tools and adopt the corresponding processing methods to clean up the blockage, thereby improving the efficiency of blockage processing;

[0030] 3. The various parameters of the precision air conditioner during operation are counted and calculated to obtain the detection coefficient. The detection coefficient is used to provide feedback on the operating status of the precision air conditioner and to handle abnormalities in a timely manner;

[0031] 4. Perform periodic detection and analysis on the blockage status of the outdoor unit, and mark the habitual warning value and the monitoring warning value according to the blockage properties of the historical blockage data corresponding to the different extraction types obtained by statistics, so as to generate targeted optimization processing signals based on the comparison results of the habitual warning value and the monitoring warning value, thereby reducing the probability of subsequent blockage of the heat dissipation outlet of the outdoor unit. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0033] Figure 1 This is a flow chart of a method according to Embodiment 1 of the present invention;

[0034] Figure 2 This is a flow chart of the method of Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0035] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0036] A precision air-conditioning outdoor unit detection method based on video inspection technology includes an outdoor unit blockage detection method and a precision air-conditioning operation detection method.

[0037] Embodiment 1: Figure 1 As shown, the outdoor unit blockage detection method includes the following steps:

[0038] Step S1: Install a high-definition camera on the outdoor unit of the precision air conditioner, and collect video data from the heat dissipation port of the outdoor unit through the high-definition camera. The high-definition camera is installed near the heat dissipation port of the outdoor unit and has night vision, waterproof, dustproof, thermal imaging and other functions to ensure that clear video images can be obtained in various environments; set a number of analysis time points with equal time intervals;

[0039] Step S2: Regularly perform blockage analysis on the video data: extract image data from the video data at the analysis time point and mark it as an analysis image, enlarge the analysis image into a pixel grid image and perform grayscale transformation, call a standard image taken when the heat dissipation outlet of the outdoor unit is not blocked in a standard state, and similarly enlarge the standard image into a pixel grid image and perform grayscale transformation, compare and analyze the analysis image with the standard image: mark the absolute value of the difference between the grayscale value of the pixel grid at the same position in the analysis image and the grayscale value in the standard image as the gray outlier value of the corresponding pixel grid, call the gray outlier threshold of the pixel grid, and mark the pixel grid with a gray outlier value not less than the gray outlier threshold as a gray outlier grid; compare the number of gray outlier grids in the analysis image with the number of gray outlier grids in the image The ratio of the total number of pixel grids is marked as the blocking coefficient of the analysis image, and the blocking coefficient is compared with the preset blocking threshold: if the blocking coefficient is less than the blocking threshold, it is determined that the blocking state of the heat dissipation port at the analysis time point meets the requirements, and step 1 is executed at the next analysis time point; if the blocking coefficient is greater than or equal to the blocking threshold, it is determined that the blocking state of the heat dissipation port at the analysis time point does not meet the requirements, and step S3 is executed; the analysis image is compared with the standard image and the pixel grids are differentially marked, the blocking probability is evaluated by the proportion of the number of grayscale abnormal grids, and when the blocking state does not meet the requirements, the analysis image is divided into regions by constructing abnormal regions, providing data support for the blockage feature extraction and analysis process;

[0040] Step S3: Perform blockage feature extraction analysis on the analysis image: grayscale abnormal grids that touch each other in the analysis image constitute an abnormal area, mark the number of grayscale abnormal grids in the abnormal area as the abnormal value of the abnormal area, and compare the abnormal value with the preset abnormal threshold: if the abnormal value is less than the abnormal threshold, mark the corresponding abnormal area as an invalid extraction area; if the abnormal value is greater than or equal to the abnormal threshold, mark the corresponding abnormal area as a valid extraction area; obtain the proportion data, grayscale data and gray difference data of the valid extraction area, and the process of obtaining the proportion data includes: generating a rectangular area that completely contains the valid extraction area in the analysis area, marking the ratio of the abnormal value of the valid extraction area to the number of pixel grids in the rectangular area as the proportion data; the grayscale data is the average grayscale value of all grayscale abnormal grids in the valid extraction area; the gray difference data HC is the difference between the maximum grayscale value and the minimum grayscale value of all grayscale abnormal grids in the valid extraction area; the characteristic parameters of the valid extraction area are formed by the proportion data, grayscale data and gray difference data;

[0041] Step S4: Retrieve historical congestion data from the database, the historical congestion data includes congestion properties, types of obstructions, and congestion parameter ranges corresponding to the obstructions; congestion properties include human impact and natural impact; types of obstructions include dust, plants, lint, waste paper, cigarette butts, etc.; congestion properties correspond to types of obstructions, for example, the congestion properties of historical congestion data with types of dust, plants, and lint are all natural impacts; the congestion properties of historical congestion data with types of waste paper and cigarette butts are all human impacts; the congestion parameter ranges corresponding to the congestion include proportion ranges, grayscale ranges, and gray difference ranges; compare the feature parameters of the effective extraction area in the analysis image with the congestion parameter ranges in all historical congestion data: if all feature parameters of the effective extraction area in the analysis image correspond to the congestion parameter ranges corresponding to the congestion in the historical congestion data, then mark the congestion type in the corresponding historical congestion data as the extraction type of the effective extraction area; after completing the comparison of all effective extraction areas in the analysis image, generate a congestion processing signal and send the congestion processing signal and all extraction types to the mobile phone terminal of the manager;

[0042] Based on the extracted characteristic parameters, multiple features of the effective extraction area are quantitatively fed back, and then the characteristic parameters are compared with the congestion parameter range in the historical congestion data. The extraction type is marked according to the comparison result. The extraction type is the type of blockage corresponding to the effective extraction area. The management personnel can directly carry the corresponding processing tools and adopt the corresponding processing methods to clean up the blockage, thereby improving the efficiency of congestion processing.

[0043] Embodiment 2: Figure 2 As shown, the precision air conditioning operation detection method includes the following steps:

[0044] Step Q1: When the precision air conditioner is turned on, the setting data of the precision air conditioner is obtained. The setting data includes the set temperature value, the set humidity value and the set wind speed value. The indoor environment data is obtained L1 minutes after the precision air conditioner is turned on. L1 is a numerical constant. The specific value of L1 is set by the management personnel. The indoor environment data includes the indoor temperature value, the indoor humidity value and the operating wind speed value. The absolute value of the difference between the indoor temperature value and the set temperature value is marked as the temperature deviation value WC, the absolute value of the difference between the indoor humidity value and the set humidity value is marked as the humidity deviation value SC, and the absolute value of the difference between the operating wind speed value and the set wind speed value is marked as the wind speed deviation value FC. The formula JC=m1*WC+m2*SC+m3*FC is used to obtain The detection coefficient JC of the precision air conditioner, where m1, m2 and m3 are all proportional coefficients, and m3>m2>m1>1; compare the detection coefficient JC with the preset detection threshold JCmax: if the detection coefficient JC is less than the detection threshold JCmax, it is determined that the operating state of the precision air conditioner meets the requirements; if the detection coefficient JC is greater than or equal to the detection threshold JCmax, it is determined that the operating state of the precision air conditioner does not meet the requirements, and an abnormal operation signal is generated and sent to the mobile phone terminal of the manager; the various parameters of the precision air conditioner during operation are counted and calculated to obtain the detection coefficient, and the operating state of the precision air conditioner is fed back through the detection coefficient, and timely processing is performed when the operating state is abnormal;

[0045] Step Q2: Perform periodic detection and analysis on the blocking state of the outdoor unit: generate a detection cycle, obtain the number of times the management personnel receive the blocking processing signal within the detection cycle and mark it as a processing value, and compare the processing value with a preset processing threshold: if the processing value is less than the processing threshold, it is determined that the overall blocking state of the outdoor unit within the detection cycle meets the requirements; if the processing value is greater than or equal to the processing threshold, it is determined that the overall blocking state of the outdoor unit within the detection cycle does not meet the requirements; execute step Q3;

[0046] Step Q3: Count the extraction types received by the management personnel during the detection period, mark the number of extraction types with human-influenced blocking properties as the habitual warning value, mark the number of extraction types with natural-influenced blocking properties as the monitoring warning value, and compare the habitual warning value with the monitoring warning value: if the habitual warning value is less than the monitoring warning value, generate a natural monitoring signal and send the natural monitoring signal to the management personnel's mobile phone terminal; if the habitual warning value is greater than the monitoring warning value, generate a habitual supervision signal and send the habitual supervision signal to the management personnel's mobile phone terminal; if the habitual warning value is equal to the monitoring warning value, generate a merger optimization signal and send the merger optimization signal to the management personnel's mobile phone terminal; perform periodic detection and analysis on the blocking status of the outdoor unit, mark the habitual warning value and the monitoring warning value according to the blocking properties of the historical blocking data corresponding to different extraction types obtained by statistics, and generate targeted optimization processing signals according to the comparison results of the habitual warning value and the monitoring warning value to reduce the subsequent blocking probability of the heat dissipation outlet of the outdoor unit.

[0047] A precision air-conditioning outdoor unit detection method based on video inspection technology is as follows: when working, a high-definition camera is installed on the outdoor unit of the precision air-conditioning, and video data of the heat dissipation port of the outdoor unit is collected through the high-definition camera, and several analysis time points with equal time intervals are set; image data in the video data is extracted at the analysis time point and marked as an analysis image, and the blocking coefficient of the analysis image is obtained, and whether the blocking state of the heat dissipation port at the analysis time point meets the requirements is judged by the blocking coefficient. When the blocking state does not meet the requirements, an abnormal area is formed by the grayscale abnormal grids that touch each other in the analysis image, and the abnormal area is marked as an invalid extraction area or a valid extraction area by the abnormal value; the characteristic parameters of the effective extraction area are formed by the proportion data, grayscale data and gray difference data; the characteristic parameters of the effective extraction area in the analysis image are compared with the blocking parameter range in all historical blocking data to obtain the extraction type of the effective extraction area; the blocking processing signal and all extraction types are sent to the mobile phone terminal of the manager.

[0048] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

[0049] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula close to the real value. The coefficients in the formula are set by technicians in this field according to the actual situation; for example: formula JC = m1*WC+m2*SC+m3*FC; technicians in this field collect multiple groups of sample data and set corresponding detection coefficients for each group of sample data; substitute the set detection coefficients and the collected sample data into the formula, any three formulas constitute a three-variable linear equation group, screen the calculated coefficients and take the average, and obtain the values ​​of m1, m2 and m3 as 3.27, 2.86 and 2.14 respectively;

[0050] The size of the coefficient is to quantify each parameter to obtain a specific value for subsequent comparison. The size of the coefficient depends on the amount of sample data and the preliminary setting of the corresponding detection coefficient for each set of sample data by technical personnel in this field; as long as it does not affect the proportional relationship between the parameter and the quantized value, such as the detection coefficient is proportional to the value of the temperature deviation value.

[0051] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0052] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A precision air conditioner outdoor unit detection method based on video inspection technology, characterized in that: Including outdoor unit blockage detection method and precision air conditioning operation detection method; The outdoor unit blockage detection method comprises the following steps: Step S1: Install a high-definition camera on the outdoor unit of the precision air conditioner, collect video data of the heat dissipation port of the outdoor unit through the high-definition camera, and set a number of analysis time points with equal time intervals; Step S2: regularly perform blockage analysis on the video data: extract image data from the video data at the analysis time point and mark it as an analysis image, obtain the blockage coefficient of the analysis image, and determine whether the blockage state of the heat dissipation port at the analysis time point meets the requirements through the blockage coefficient. If the blockage state does not meet the requirements, execute step S3; Step S3: performing blockage feature extraction analysis on the analysis image: grayscale abnormal grids that are in contact with each other in the analysis image constitute an abnormal area, the number of grayscale abnormal grids in the abnormal area is marked as the abnormal value of the abnormal area, and the abnormal area is marked as an invalid extraction area or a valid extraction area by the abnormal value; the proportion data, grayscale data and gray difference data of the effective extraction area are obtained; the characteristic parameters of the effective extraction area are constituted by the proportion data, grayscale data and gray difference data; Step S4: Retrieve historical congestion data from the database, which includes the nature of the congestion, the type of congestion object, and the congestion parameter range corresponding to the congestion object; compare the characteristic parameters of the effective extraction area in the analysis image with the congestion parameter range in all historical congestion data and obtain the extraction type of the effective extraction area; after completing the comparison of all effective extraction areas in the analysis image, generate a congestion processing signal and send the congestion processing signal and all extraction types to the mobile phone terminal of the manager.

2. The method for detecting a precision air conditioner outdoor unit based on video inspection technology according to claim 1 is characterized in that: In step S2, the analysis image is enlarged into a pixel grid image and grayscale transformation is performed, a standard image taken when the heat dissipation outlet of the outdoor unit is not blocked in a standard state is retrieved, and the standard image is also enlarged into a pixel grid image and grayscale transformation is performed, and the analysis image and the standard image are compared and analyzed: the absolute value of the difference between the grayscale value of the pixel grid at the same position in the analysis image and the grayscale value in the standard image is marked as the gray outlier value of the corresponding pixel grid, the gray outlier threshold of the pixel grid is retrieved, and the pixel grid whose gray outlier value is not less than the gray outlier threshold is marked as a gray outlier grid; the ratio of the number of gray outlier grids in the analysis image to the total number of pixel grids is marked as the blockage coefficient of the analysis image.

3. The method for detecting outdoor units of precision air conditioners based on video inspection technology according to claim 2 is characterized in that: The specific process of determining whether the blocking state of the heat dissipation port at the analysis time point meets the requirements includes: comparing the blocking coefficient with a preset blocking threshold value: if the blocking coefficient is less than the blocking threshold value, it is determined that the blocking state of the heat dissipation port at the analysis time point meets the requirements, and step one is executed at the next analysis time point; if the blocking coefficient is greater than or equal to the blocking threshold value, it is determined that the blocking state of the heat dissipation port at the analysis time point does not meet the requirements.

4. The method for detecting a precision air conditioner outdoor unit based on video inspection technology according to claim 3 is characterized in that: In step S3, the specific process of marking the abnormal area as an invalid extraction area or a valid extraction area includes: comparing the abnormal value with the preset abnormal threshold: if the abnormal value is less than the abnormal threshold, the corresponding abnormal area is marked as an invalid extraction area; if the abnormal value is greater than or equal to the abnormal threshold, the corresponding abnormal area is marked as a valid extraction area.

5. The method for detecting outdoor units of precision air conditioners based on video inspection technology according to claim 4 is characterized in that: In step S3, the process of acquiring the proportion data includes: generating a rectangular area that completely contains the effective extraction area in the analysis area, marking the ratio of the outlier value of the effective extraction area to the number of pixel grids in the rectangular area as the proportion data; the grayscale data is the average value of the grayscale values ​​of all grayscale outlier grids in the effective extraction area; the gray difference data HC is the difference between the maximum grayscale value and the minimum grayscale value of all grayscale outlier grids in the effective extraction area.

6. The method for detecting outdoor units of precision air conditioners based on video inspection technology according to claim 5 is characterized in that: In step S4, the process of obtaining the extraction type of the effective extraction area includes: if all characteristic parameters of the effective extraction area in the analysis image correspond to the congestion parameter range corresponding to the congestion in the historical congestion data, then the type of congestion in the corresponding historical congestion data is marked as the extraction type of the effective extraction area.

7. The method for detecting outdoor units of precision air conditioners based on video inspection technology according to claim 6 is characterized in that: The precision air conditioning operation detection method comprises the following steps: Step Q1: When the precision air conditioner is turned on, the setting data of the precision air conditioner is obtained, and the setting data includes a set temperature value, a set humidity value, and a set wind speed value. L1 minutes after the precision air conditioner is turned on, the temperature deviation value WC, the humidity deviation value SC, and the wind speed deviation value FC of the precision air conditioner are obtained and numerical calculation is performed to obtain the detection coefficient JC of the precision air conditioner; the detection coefficient JC is compared with the preset detection threshold value JCmax: if the detection coefficient JC is less than the detection threshold value JCmax, it is determined that the operating state of the precision air conditioner meets the requirements; if the detection coefficient JC is greater than or equal to the detection threshold value JCmax, it is determined that the operating state of the precision air conditioner does not meet the requirements, and an abnormal operation signal is generated and sent to the mobile phone terminal of the administrator; Step Q2: Perform periodic detection and analysis on the blocking state of the outdoor unit: generate a detection cycle, obtain the number of times the management personnel receive the blocking processing signal within the detection cycle and mark it as a processing value, and compare the processing value with a preset processing threshold: if the processing value is less than the processing threshold, it is determined that the overall blocking state of the outdoor unit within the detection cycle meets the requirements; if the processing value is greater than or equal to the processing threshold, it is determined that the overall blocking state of the outdoor unit within the detection cycle does not meet the requirements; execute step Q3; Step Q3: Count the extraction types received by the management personnel during the detection period, mark the number of extraction types whose blockage properties are human-influenced as the habitual warning value, mark the number of extraction types whose blockage properties are naturally-influenced as the monitoring warning value, and compare the habitual warning value with the monitoring warning value: if the habitual warning value is less than the monitoring warning value, a natural monitoring signal is generated and sent to the management personnel's mobile phone terminal; if the habitual warning value is greater than the monitoring warning value, a habitual supervision signal is generated and sent to the management personnel's mobile phone terminal; if the habitual warning value is equal to the monitoring warning value, a merger optimization signal is generated and sent to the management personnel's mobile phone terminal.

8. The method for detecting outdoor units of precision air conditioners based on video inspection technology according to claim 7 is characterized in that: In step Q1, the process of obtaining the temperature deviation value WC, the humidity deviation value SC and the wind speed deviation value FC includes: obtaining indoor environmental data, the indoor environmental data including the indoor temperature value, the indoor humidity value and the operating wind speed value; marking the absolute value of the difference between the indoor temperature value and the set temperature value as the temperature deviation value WC, marking the absolute value of the difference between the indoor humidity value and the set humidity value as the humidity deviation value SC, and marking the absolute value of the difference between the operating wind speed value and the set wind speed value as the wind speed deviation value FC.

9. A computer storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the precision air-conditioning outdoor unit detection method based on video inspection technology described in any one of claims 1 to 8 is implemented.

10. A computer device, characterized in that: include: Processor and memory; The memory stores a computer program, and the processor executes the computer program stored in the memory so that the computer device executes the precision air-conditioning outdoor unit detection method based on video inspection technology as described in any one of claims 1-8.

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