Humidity interference resistance system and method for industrial and commercial environment gas detection alarm

Abstract

The invention relates to the technical field of control systems, in particular to a humidity interference resisting system and method for an industrial and commercial environment gas detection alarm. The environment humidity, the lens temperature and the environment temperature are obtained through the detection module, the lens image and the environment image are obtained in real time, the air velocity of a gas detection alarm area is obtained, the environment state category division module calculates the environment characterization value coefficient, and the environment state categories are divided according to the environment characterization value coefficient. According to the invention, fogging risks are accurately quantified through multi-parameter cooperative calculation, and the fogging risks are classified, so that the risks can be pre-judged before the lens is actually fogged, and the state of the lens is adjusted in time, so that the fogging risk of the lens is accurately determined. And the real-time performance and the accuracy of dangerous gas monitoring in industrial and commercial production environments are ensured.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of control systems, and in particular to a humidity interference resisting system and method for a gas detection alarm in an industrial and commercial environment. BACKGROUND

[0002] In industrial and commercial environments such as petroleum chemical industry, metallurgy, and warehousing, a gas detection alarm is a key device for ensuring production safety and personnel health. It needs to monitor the concentration of toxic and flammable gases in the environment in real time and trigger an alarm in time to avoid safety risks. However, such industrial and commercial scenarios are often accompanied by high humidity environments, specifically, the relative humidity of the environment frequently reaches above 70%, and in some rainy seasons or high humidity production links, the humidity can even reach above 90%, and the environmental temperature fluctuates frequently, which easily leads to water vapor in the air reaching the dew point and forming condensation.

[0003] In the prior art, the publication number CN113041747A discloses a coal mine underground infrared temperature measuring device return blowing dust removal and dehumidification device. The device is used to realize dust removal and dehumidification of the lens of the coal mine underground infrared temperature measuring device. The return blowing dust removal and dehumidification device includes a mine compressed air pipeline, a valve, a high-pressure rubber tube, a dust removal medium, a dehumidification medium, and an infrared temperature measuring device explosion-proof shell. The present application provides a coal mine underground infrared temperature measuring device return blowing dust removal and dehumidification method. The dust removal medium and the dehumidification medium are respectively embedded in the high-pressure rubber tube between the return blowing cavity and the mine compressed air pipeline, which purifies and dries the air in the blowing system. A return blowing cavity is constructed inside the coal mine underground infrared temperature measuring device explosion-proof shell, and clean and dry air passes through the return blowing cavity and blows towards the lens of the infrared temperature measuring device, thereby achieving the purpose of self-cleaning of the lens of the coal mine underground infrared temperature measuring device.

[0004] However, in the prior art, the lens fogging risk is not detected in multiple dimensions, and the lens fogging risk environment is not classified, thereby causing the problem of being unable to effectively prevent lens fogging. SUMMARY

[0005] Therefore, the present application provides a humidity interference resisting system and method for a gas detection alarm in an industrial and commercial environment to overcome the problem in the prior art that the lens fogging risk is not detected in multiple dimensions, and the lens fogging risk environment is not classified, thereby causing the problem of being unable to effectively prevent lens fogging.

[0006] In one aspect, the present application provides a humidity interference resisting system for a gas detection alarm in an industrial and commercial environment, comprising:

[0007] The detection module comprises a humidity detection unit for acquiring the ambient humidity, a temperature detection unit for acquiring the lens temperature and the ambient temperature, an image acquisition unit for acquiring the lens image and the ambient image in real time, and a flow rate detection unit for acquiring the air flow rate of the gas detection alarm area;

[0008] The environment state category division module is connected with the detection module and is configured to calculate an environment characteristic value coefficient according to the ambient humidity, the ambient humidity change rate, the ambient temperature change rate, the air flow rate of the gas detection alarm area, and the ambient image, and divide the environment state category according to the environment characteristic value coefficient;

[0009] The lens state regulation module is connected with the environment state category division module and comprises a lens state adjustment unit and a heating unit.

[0010] The lens state adjustment unit is configured to select an adjustment strategy according to the environment state category, and the adjustment strategy comprises:

[0011] adjusting the lens picture extraction frequency according to the environment characteristic value coefficient, dividing the lens image into a plurality of sub-lens images, extracting a central sub-lens image, calculating a local contrast index difference value of the central sub-lens image of adjacent lens images, and adjusting the heating unit temperature and the heating time length according to the local contrast index difference value.

[0012] Alternatively, whether to start the heating unit is determined according to the ambient temperature and the lens temperature.

[0013] Further, the environment state category division module is configured to calculate an environment characteristic value coefficient according to the ambient humidity, the ambient humidity change rate, the ambient temperature change rate, the air flow rate of the gas detection alarm area, and the ambient image,

[0014] The ambient humidity change rate and the ambient temperature change rate within each preset time length are acquired.

[0015] The ambient image is divided into a plurality of sub-ambient image regions, and whether there is a water droplet in each sub-ambient image region is identified by using image analysis software, and a ratio of the sub-ambient image regions with water droplets to the total sub-ambient image regions is calculated.

[0016] The ratio of the ambient humidity to the preset ambient humidity threshold is recorded as the ambient humidity ratio.

[0017] The ratio of the ambient humidity change rate to the preset ambient humidity change rate threshold is recorded as the ambient humidity change rate ratio.

[0018] The ratio of the ambient temperature change rate to the preset ambient temperature change rate threshold is recorded as the ambient temperature change rate ratio.

[0019] A ratio of the preset air flow rate threshold value and the air flow rate of the gas detection alarm area is recorded as an air flow rate ratio;

[0020] A ratio of the ratio of the sub-environment image area with water droplets to the total sub-environment image area and the preset humid area ratio threshold value is recorded as a humid area ratio;

[0021] The environment humidity ratio, the environment humidity change rate ratio, the environment temperature change rate ratio, the air flow rate ratio, and the humid area ratio are weighted and summed to calculate an environment representation value coefficient.

[0022] Further, the environment state category division module is configured to divide the environment state category according to the environment representation value coefficient,

[0023] The environment representation value coefficient is compared with a preset environment representation value coefficient comparison threshold value,

[0024] If the environment representation value coefficient is less than the preset environment representation value coefficient comparison threshold value, the environment state category is divided into a weak humid category;

[0025] If the environment representation value coefficient is greater than or equal to the preset environment representation value coefficient comparison threshold value, the environment state category is divided into a strong humid category.

[0026] Further, the lens state adjustment unit is configured to select an adjustment strategy according to the environment state category, wherein,

[0027] If the environment state category is the strong humid category, the lens picture extraction frequency is adjusted according to the environment representation value coefficient, the lens image is divided into a plurality of sub-lens images, a center sub-lens image is extracted, a center sub-lens image local contrast index difference value of adjacent lens images is calculated, and the heating unit temperature and the heating time length are adjusted according to the local contrast index difference value;

[0028] If the environment state category is the weak humid category, the heating unit is adjusted according to the environment temperature and the lens temperature.

[0029] Further, the lens state adjustment unit is configured to adjust the lens picture extraction frequency according to the environment representation value coefficient, wherein the environment representation value coefficient and the lens picture extraction frequency are in a positive correlation.

[0030] Further, the lens state adjustment unit divides the lens image into a plurality of sub-lens images, extracts a center sub-lens image, calculates a center sub-image local contrast index difference value of adjacent lens images,

[0031] The sub-lens image located at the center position is selected;

[0032] The gray value of all pixels of the center sub-lens image is obtained by image analysis software;

[0033] According to the local contrast index formula, a local contrast index of a center sub-lens image is calculated;

[0034] A center sub-lens image local contrast index difference value of adjacent lens images is calculated.

[0035] Further, the lens state adjustment unit adjusts the heating unit temperature and the heating time length according to the local contrast index difference value, wherein the local contrast index difference value is positively correlated with the heating unit temperature and the heating time length.

[0036] Further, the lens state adjustment unit determines whether to start the heating unit according to the environment temperature and the lens temperature,

[0037] If the difference between the lens temperature and the environment temperature is less than a preset temperature difference comparison threshold, it is determined to start the heating unit.

[0038] Further, the lens state adjustment unit divides the lens image into a plurality of sub-lens images, wherein the areas of the sub-lens images are equal.

[0039] On the other hand, the application provides a humidity interference resistant method for a commercial and industrial environment gas detection alarm,

[0040] The environment humidity, the lens temperature and the environment temperature are obtained, the lens image and the environment image are obtained in real time, and the air flow rate in the gas detection alarm area is obtained.

[0041] According to the environment humidity, the environment humidity change rate, the environment temperature change rate, the air flow rate in the gas detection alarm area and the environment image, an environment characteristic value coefficient is calculated, and the environment state category is divided according to the environment characteristic value coefficient.

[0042] According to the environment state category, an adjustment strategy is selected, which includes,

[0043] According to the environment characteristic value coefficient, the lens picture extraction frequency is adjusted, the lens image is divided into a plurality of sub-lens images, the center sub-lens image is extracted, the center sub-lens image local contrast index difference value of adjacent lens images is calculated, and the heating unit temperature and the heating time length are adjusted according to the local contrast index difference value.

[0044] Or, according to the environment temperature and the lens temperature, it is determined whether to start the heating unit.

[0045] Compared with the prior art, the present application obtains the environment humidity, the lens temperature and the environment temperature through the detection module, obtains the lens image and the environment image in real time and obtains the air flow rate of the gas detection alarm area, the environment state category division module calculates the environment representation value coefficient, the environment state category is divided according to the environment representation value coefficient, and the lens state adjustment unit selects the adjustment strategy according to the environment state category, the present application accurately quantifies the fogging risk through multi-parameter collaborative calculation, classifies the fogging risk, and thus can predict the risk before the lens actually fogs, adjusts the lens state in time, and guarantees the real-time performance and accuracy of the dangerous gas monitoring in the industrial and commercial production environment.

[0046] Especially, the environment state category division module calculates the environment representation value coefficient according to the environment humidity, the environment humidity change rate, the environment temperature change rate, the air flow rate of the gas detection alarm area and the environment image, the environment humidity is the basic inducement for the lens fogging, the higher the value is, the closer the air humidity is to the saturation state, and the water vapor is easy to condense on the lens surface to form a water film; when the environment humidity changes greatly, the sudden rise and fall of the water vapor concentration in the air will break the water vapor balance on the lens surface, even if the initial humidity does not reach a high value, the sharp fluctuation in a short time will also accelerate the attachment and aggregation of water vapor on the lens; a large change in the environment temperature will quickly change the dew point temperature of the air, if the lens temperature lags behind the change of the environment temperature due to heat conduction, the lens temperature is easy to be lower than the new dew point temperature, and thus the water vapor condensation is induced; when the air flow rate of the gas detection alarm area is too slow, the high-humidity air near the lens cannot be carried away in time, forming a local water vapor retention area, which provides a continuous condition for the formation and diffusion of fog droplets; and the water droplets in the environment are identified through the environment image, whether the air humidity is in a critical state of easy condensation is judged by observing whether there is liquid water in the environment, the fogging risk is accurately quantified through multi-parameter collaborative calculation, the risk can be predicted before the lens actually fogs, the lens state is adjusted in time, the problems of image blurring, detection accuracy reduction, false alarm and missed alarm caused by lens fogging are effectively avoided, the real-time performance and accuracy of the dangerous gas monitoring in the industrial and commercial production environment are guaranteed, the safety hidden danger is reduced, the frequency of equipment downtime maintenance caused by lens fogging is reduced, and the continuous operation efficiency of the equipment is improved.

[0047] Especially, the application divides the environment state category according to the environment characteristic value coefficient by the environment state category division module, the environment characteristic value coefficient can represent the degree of the current lens fogging to a certain extent, the difficulty of lens fogging is distinguished, corresponding methods are taken based on different environment state categories, resource waste caused by low risk over-monitoring is avoided, lens fogging caused by high risk monitoring is prevented, the optimal coping strategy is matched in time in different risk stages of lens fogging, lens fogging is ensured to be suppressed in time, the problems of gas detection image blur, data deviation and the like caused by lens fogging are significantly reduced, the accuracy and reliability of gas detection under industrial and commercial environment are improved, the equipment energy consumption and maintenance cost are optimized, and the service life of the system is prolonged.

[0048] Especially, the lens state adjustment unit divides the lens image into a plurality of sub-lens images, extracts a center sub-lens image, calculates a local contrast index difference value of the center sub-lens image of adjacent lens images, the center position of the lens is more likely to become a highlight area compared with the peripheral position, and the actual working state of the lens is more directly and sensitively reflected, the local contrast index of the center area is selected to calculate, the accuracy and pertinence of the contrast index calculation are improved, more reliable data support is provided for the lens state judgment, the local contrast index difference value of the center sub-lens image of adjacent lens images is compared, whether the lens appears a large state change is quickly captured, and then the lens adjustment action is triggered in time, the lens is ensured to be always in a clear and stable working state, the detection accuracy of the gas detection alarm is effectively avoided from being affected by the abnormal lens state, the service life of the equipment is prolonged, and the adaptability and reliability of the equipment in a high-humidity environment are improved. BRIEF DESCRIPTION OF DRAWINGS

[0049] Figure 1 It is a structural diagram of the humidity interference resistance system for the gas detection alarm for industrial and commercial environment of the embodiment of the application;

[0050] Figure 2 It is a lens state regulation module structure diagram of the embodiment of the application;

[0051] Figure 3 It is a logic decision diagram of the environment state category division module of the embodiment of the application for dividing the environment state category;

[0052] Figure 4 It is a step diagram of the humidity interference resistance method for the gas detection alarm for industrial and commercial environment of the embodiment of the application. DETAILED DESCRIPTION

[0053] The technical solutions of the present application will be described clearly and completely below in conjunction with the drawings. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0054] In the description of the present application, it should be noted that the orientations or positional relationships indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. are based on the orientations or positional relationships shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation on the present application. In addition, the terms "first", "second", are only for the purpose of description, and cannot be understood as indicating or implying relative importance. Among them, the terms "first position" and "second position" are two different positions, and moreover, the "above", "over" and "on" of the first feature to the second feature include the vertical direction of the first feature above and obliquely above the second feature, or only indicate that the horizontal height of the first feature is higher than that of the second feature. The "below", "under" and "under" of the first feature to the second feature include the vertical direction of the first feature below and obliquely below the second feature, or only indicate that the horizontal height of the first feature is less than that of the second feature.

[0055] In the description of the present application, it should be noted that unless otherwise explicitly specified and limited, the terms "mounting", "connection", "connection" should be understood broadly, for example, it can be fixedly connected, or it can be detachably connected, or integrally connected; it can be mechanically connected, or it can be electrically connected; it can be directly connected, or it can be indirectly connected through an intermediate medium; it can be the communication inside two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0056] The embodiments of the present application will be described in detail below, and examples of the embodiments are shown in the drawings, wherein the same or similar reference numerals represent the same or similar elements or elements with the same or similar functions throughout. The embodiments described below by referring to the drawings are exemplary and are only used to explain the present application, and cannot be understood as a limitation on the present application.

[0057] As Figures 1-3 shown, the present embodiment provides a humidity interference resistant system for a commercial and industrial environment gas detection alarm, comprising:

[0058] The detection module comprises a humidity detection unit for acquiring the ambient humidity, a temperature detection unit for acquiring the lens temperature and the ambient temperature, an image acquisition unit for acquiring the lens image and the ambient image in real time, and a flow rate detection unit for acquiring the air flow rate of the gas detection alarm area;

[0059] The environment state category division module is connected with the detection module and is configured to calculate an environment characteristic value coefficient according to the ambient humidity, the ambient humidity change rate, the ambient temperature change rate, the air flow rate of the gas detection alarm area, and the ambient image, and divide the environment state category according to the environment characteristic value coefficient;

[0060] The lens state regulation module is connected with the environment state category division module and comprises a lens state adjustment unit and a heating unit.

[0061] The lens state adjustment unit is configured to select an adjustment strategy according to the environment state category, and the adjustment strategy comprises:

[0062] adjusting the lens picture extraction frequency according to the environment characteristic value coefficient, dividing the lens image into a plurality of sub-lens images, extracting a central sub-lens image, calculating a local contrast index difference value of the central sub-lens image of adjacent lens images, and adjusting the temperature and the heating time length of the heating unit according to the local contrast index difference value;

[0063] Or, determining whether to start the heating unit according to the ambient temperature and the lens temperature.

[0064] In this embodiment, the humidity detection unit is a humidity sensor, the temperature detection unit is a plurality of temperature sensors, the image acquisition unit is a plurality of cameras, and the flow rate detection unit is a wind speed sensor.

[0065] In this embodiment, the gas detection alarm area is the area in front of the position of the gas detection alarm.

[0066] In this embodiment, the heating unit is a heating sheet.

[0067] Specifically, the environment state category division module is configured to calculate an environment characteristic value coefficient according to the ambient humidity, the ambient humidity change rate, the ambient temperature change rate, the air flow rate of the gas detection alarm area, and the ambient image,

[0068] The ambient humidity change rate and the ambient temperature change rate in each preset time length are acquired.

[0069] The ambient image is divided into a plurality of sub-ambient image regions, and whether there is a water droplet in each sub-ambient image region is identified by using image analysis software, and the ratio of the sub-ambient image regions with water droplets to the total sub-ambient image regions is calculated.

[0070] The ratio of the ambient humidity to the preset ambient humidity threshold value is denoted as the ambient humidity ratio;

[0071] The ratio of the ambient humidity change rate to the preset ambient humidity change rate threshold value is denoted as the ambient humidity change rate ratio;

[0072] The ratio of the ambient temperature change rate to the preset ambient temperature change rate threshold value is denoted as the ambient temperature change rate ratio;

[0073] The ratio of the preset air flow rate threshold value to the air flow rate of the gas detection alarm area is denoted as the air flow rate ratio;

[0074] The ratio of the ratio of the sub-environment image area with water droplets to the total sub-environment image area to the preset humid area ratio threshold value is denoted as the humid area ratio;

[0075] The ambient humidity ratio, the ambient humidity change rate ratio, the ambient temperature change rate ratio, the air flow rate ratio, and the humid area ratio are weighted and summed to calculate the ambient representation value coefficient.

[0076] In this embodiment, the preset time length is 2 min, and the image analysis software is matlab.

[0077] In this embodiment, a large number of images containing water droplets and images not containing water droplets are collected, and the positions and ranges of the water droplets are marked as training data sets.

[0078] A convolutional neural network is selected, the annotated data set is input into the model for training, and the parameters of the model are adjusted to accurately identify the water droplets.

[0079] The environment image to be detected is input into the trained model, and the model outputs whether there are water droplets in the image.

[0080] It can be understood that the ratio of the sub-environment image area with water droplets to the total sub-environment image area is calculated, if the environment image is divided into 9 sub-environment image areas, the sub-environment image area with water droplets is 3, and the ratio is 1 / 3.

[0081] In this embodiment, the preset ambient humidity threshold value is selected in the range of [65%, 75%], the preset ambient humidity change rate threshold value is selected in the range of [0.30% RH / min, 0.33% RH / min], the preset ambient temperature change rate threshold value is selected in the range of [2.5℃ / min, 3℃ / min], the preset air flow rate threshold value is selected in the range of [0.2m / s, 0.5m / s], and the preset humid area ratio threshold value is selected in the range of [10%, 15%].

[0082] In the embodiment, the weight coefficient of the ambient humidity ratio is 0.2, the weight coefficient of the ambient humidity change rate ratio is 0.2, the weight coefficient of the ambient temperature change rate ratio is 0.2, the weight coefficient of the air flow rate ratio is 0.1, and the weight coefficient of the humid area ratio is 0.3.

[0083] Specifically, the environment state category division module is configured to calculate an environment characteristic value coefficient according to the ambient humidity, the ambient humidity change rate, the ambient temperature change rate, the air flow rate of the gas detection alarm area, and an environment image. The ambient humidity is a basic inducement for lens fogging. The higher the value is, the closer the air humidity is to the saturated state, and the water vapor is easy to condense on the lens surface to form a water film. When the ambient humidity changes greatly, the sudden rise and fall of the air humidity concentration will break the water vapor balance on the lens surface. Even if the initial humidity does not reach a high value, the sharp fluctuation in a short time will also accelerate the attachment and aggregation of water vapor on the lens. A large change in the ambient temperature will quickly change the dew point temperature of the air. If the lens temperature lags behind the change of the ambient temperature due to heat conduction, the lens temperature is easy to be lower than the new dew point temperature, thereby inducing water vapor condensation. When the air flow rate of the gas detection alarm area is too slow, the high-humidity air near the lens cannot be carried away in time, forming a local water vapor retention area, which provides a continuous condition for the formation and diffusion of fog droplets. The water droplets in the environment are identified through the environment image. Whether the air humidity is in a critical state of easy condensation is judged by observing whether there is liquid water in the environment. The fogging risk is accurately quantified through multi-parameter collaborative calculation. Therefore, the risk can be predicted before the lens actually fogs, and the lens state can be adjusted in time. The problems such as image blurring, detection accuracy reduction, false alarm and missed alarm caused by lens fogging are effectively avoided. The real-time and accuracy of the monitoring of dangerous gases in industrial and commercial production environments are ensured. The safety hidden danger is reduced. The frequency of equipment downtime maintenance caused by lens fogging is reduced, and the continuous operation efficiency of the equipment is improved.

[0084] Specifically, the environment state category division module is configured to divide the environment state category according to the environment characteristic value coefficient,

[0085] The environment characteristic value coefficient is compared with a preset environment characteristic value coefficient comparison threshold,

[0086] If the environment characteristic value coefficient is less than the preset environment characteristic value coefficient comparison threshold, the environment state category is divided into a weak humid category.

[0087] If the environment characteristic value coefficient is greater than or equal to the preset environment characteristic value coefficient comparison threshold, the environment state category is divided into a strong humid category.

[0088] In the embodiment, the preset environment characteristic value coefficient comparison threshold is selected in the range of [0.9, 1.1].

[0089] Specifically, the application divides the environment state category according to the environment characteristic value coefficient by the environment state category division module, the environment characteristic value coefficient can to some extent represent the degree of current lens fogging, the difficulty of lens fogging is distinguished, corresponding methods are taken based on different environment state categories, resource waste caused by low risk over-monitoring is avoided, lens fogging caused by high risk monitoring deficiency is prevented, optimal coping strategies are matched in time in different risk stages of lens fogging, lens fogging is ensured to be suppressed in time, problems such as blurred gas detection image and data deviation caused by lens fogging are significantly reduced, the accuracy and reliability of gas detection under industrial and commercial environment are improved, equipment energy consumption and maintenance cost are optimized, and system service life is prolonged.

[0090] Specifically, the lens state adjustment unit is used to select an adjustment strategy according to the environment state category.

[0091] If the environment state category is the strong humidity category, the lens picture extraction frequency is adjusted according to the environment characteristic value coefficient, the lens image is divided into a plurality of sub-lens images, the center sub-lens image is extracted, the local contrast index difference value of the center sub-lens image of the adjacent lens image is calculated, and the heating unit temperature and the heating time length are adjusted according to the local contrast index difference value.

[0092] If the environment state category is the weak humidity category, the heating unit is adjusted according to the environment temperature and the lens temperature.

[0093] Specifically, the lens state adjustment unit is used to adjust the lens picture extraction frequency according to the environment characteristic value coefficient, and the environment characteristic value coefficient and the lens picture extraction frequency are in a positive correlation relationship.

[0094] It can be understood that the larger the environment characteristic value coefficient is, the higher the possibility of lens fogging of the gas detection alarm is, so the extraction frequency of the lens picture should be increased to discover the lens change in time.

[0095] Specifically, the lens state adjustment unit divides the lens image into a plurality of sub-lens images, extracts the center sub-lens image, calculates the local contrast index difference value of the center sub-image of the adjacent lens image,

[0096] The sub-lens image located at the center position is selected.

[0097] The gray value of all pixels of the center sub-lens image is obtained by the image analysis software.

[0098] The local contrast index of the center sub-lens image is calculated according to the local contrast index formula.

[0099] The local contrast index difference value of the center sub-image of the adjacent lens image is calculated.

[0100] It can be understood that when the total number of sub-lens images is odd (such as 3*3, 5*5), the center position is the sub-lens image in the middle, for example, “in a 3*3 sub-lens image matrix, the center sub-lens image in the 2nd row and the 2nd column is extracted”.

[0101] When the total number of sub-lens images is even (such as 2*2, 4*4), the center position is a plurality of sub-lens images, for example, “in a 4*4 sub-lens image matrix, a 2*2 sub-image block composed of the 2nd-3rd row and the 2nd-3rd column is extracted as the sub-lens image of the center region”.

[0102] In this embodiment, the local contrast index formula is the maximum gray value of the target region divided by the average gray value of the background region.

[0103] Specifically, the lens state adjustment unit divides the lens image into a plurality of sub-lens images, extracts the center sub-lens image, and calculates the local contrast index difference of the center sub-lens images of adjacent lens images. The lens center position is more likely to become a highlight area than the surrounding position, and the reflection of the actual working state of the lens is more direct and sensitive. Selecting the center region to calculate the local contrast index can improve the accuracy and relevance of the contrast index calculation, and provide more reliable data support for lens state judgment. By comparing the local contrast index difference of the center sub-lens images of adjacent lens images, whether the lens has a large state change can be quickly captured, and then the lens adjustment action is triggered in time to ensure that the lens is always in a clear and stable working state. Effectively avoid the influence of abnormal lens state on the detection accuracy of the gas detection alarm, prolong the service life of the equipment, and improve the adaptability and reliability of the equipment in a high-humidity environment.

[0104] Specifically, the lens state adjustment unit adjusts the heating unit temperature and the heating time according to the local contrast index difference, wherein the local contrast index difference and the heating unit temperature and the heating time are in a positive correlation.

[0105] Specifically, the lens state adjustment unit determines whether to start the heating unit according to the ambient temperature and the lens temperature,

[0106] If the difference between the lens temperature and the ambient temperature is less than the preset temperature difference comparison threshold, it is determined to start the heating unit.

[0107] In this embodiment, the preset temperature difference comparison threshold is selected in the range of [3℃, 6℃].

[0108] Specifically, the lens state adjustment unit divides the lens image into a plurality of sub-lens images, wherein the area of each sub-lens image is equal.

[0109] Please refer to Figure 4A humidity interference resisting method for a gas detection alarm in a commercial environment,

[0110] Step S1, obtaining the environmental humidity, obtaining the lens temperature and the environmental temperature, obtaining the lens image and the environmental image in real time, and obtaining the air flow rate in the area of the gas detection alarm;

[0111] Step S2, calculating the environmental characteristic value coefficient according to the environmental humidity, the environmental humidity change rate, the environmental temperature change rate, the air flow rate in the area of the gas detection alarm, and the environmental image, and dividing the environmental state category according to the environmental characteristic value coefficient;

[0112] Step S3, selecting the adjustment strategy according to the environmental state category, including,

[0113] adjusting the lens picture extraction frequency according to the environmental characteristic value coefficient, dividing the lens image into a plurality of sub-lens images, extracting the center sub-lens image, calculating the center sub-lens image local contrast index difference value of the adjacent lens image, and adjusting the heating unit temperature and the heating time length according to the local contrast index difference value;

[0114] or, judging whether to start the heating unit according to the environmental temperature and the lens temperature.

[0115] The modules involved in the embodiments of the present application can be implemented in the form of software or in the form of hardware. The described modules can also be arranged in the processor.

[0116] The flowcharts and block diagrams in the drawings illustrate the possible implementation architecture, function and operation of the apparatus, method and computer program product according to various embodiments of the present application. In this regard, each block in the flowchart or block diagram can represent a module, a program segment, or a part of code containing one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions noted in the blocks can occur in different order than that noted in the drawings. For example, two blocks represented in succession can actually be executed substantially in parallel, and sometimes they can be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and the combination of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based device that performs the specified function or operation, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0117] Obviously, the above embodiments of the present application are merely example for clearly explaining the present application, and are not intended to limit the embodiments of the present application. Based on the above description, other different forms of changes or variations can be made by those skilled in the art. Here, it is not necessary and also impossible to enumerate all the embodiments. Any modification, equivalent replacement and improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the claims of the present application.

Claims

1. A humidity interference resistant system for a commercial and industrial environment gas detection alarm, characterized in that, The application comprises: a detection module, including a humidity detection unit for obtaining ambient humidity, a temperature detection unit for obtaining lens temperature and ambient temperature, an image acquisition unit for obtaining lens images and ambient images in real time, and a flow rate detection unit for obtaining air flow rate in the gas detection alarm area; an ambient state category division module connected with the detection module, for calculating an ambient representation value coefficient according to ambient humidity, ambient humidity change rate, ambient temperature change rate, air flow rate in the gas detection alarm area, and ambient images, and dividing ambient state categories according to the ambient representation value coefficient; a lens state regulation module connected with the ambient state category division module, including a lens state adjustment unit and a heating unit; the lens state adjustment unit is used to select an adjustment strategy according to the ambient state category, including, adjusting lens picture extraction frequency according to the ambient representation value coefficient, dividing lens images into a plurality of sub-lens images, extracting central sub-lens images, calculating the local contrast index difference value of the central sub-lens images of adjacent lens images, and adjusting the temperature and heating time of the heating unit according to the local contrast index difference value; or, judging whether to start the heating unit according to the ambient temperature and the lens temperature.

2. The humidity interference resistant system for commercial and industrial environment gas detection alarms of claim 1, wherein, The ambient state category division module is used to calculate an ambient representation value coefficient according to ambient humidity, ambient humidity change rate, ambient temperature change rate, air flow rate in the gas detection alarm area, and ambient images, obtaining ambient humidity change rate and ambient temperature change rate within each preset time period; dividing ambient images into a plurality of sub-ambient image regions, identifying whether there are water droplets in each sub-ambient image region through image analysis software, and calculating the ratio of the sub-ambient image regions with water droplets to the total sub-ambient image regions; obtaining the ratio of ambient humidity to a preset ambient humidity threshold value, which is recorded as ambient humidity ratio; obtaining the ratio of ambient humidity change rate to a preset ambient humidity change rate threshold value, which is recorded as ambient humidity change rate ratio; obtaining the ratio of ambient temperature change rate to a preset ambient temperature change rate threshold value, which is recorded as ambient temperature change rate ratio; obtaining the ratio of a preset air flow rate threshold value to the air flow rate in the gas detection alarm area, which is recorded as air flow rate ratio; obtaining the ratio of the sub-ambient image regions with water droplets to the total sub-ambient image regions, which is recorded as humid region ratio; weighting and summing ambient humidity ratio, ambient humidity change rate ratio, ambient temperature change rate ratio, air flow rate ratio, and humid region ratio to calculate the ambient representation value coefficient.

3. The humidity interference resistant system for commercial and industrial environment gas detection alarms of claim 2, wherein, The ambient state category division module is used to divide ambient state categories according to the ambient representation value coefficient, comparing the ambient representation value coefficient with a preset ambient representation value coefficient comparison threshold value, if the ambient representation value coefficient is less than the preset ambient representation value coefficient comparison threshold value, the ambient state category is divided into a weak humid category; if the ambient representation value coefficient is greater than or equal to the preset ambient representation value coefficient comparison threshold value, the ambient state category is divided into a strong humid category.

4. The humidity interference resistant system for commercial and industrial environment gas detection alarms of claim 3, wherein, The lens state adjustment unit is used to select an adjustment strategy according to the ambient state category, wherein, If the environment state category is the strong humidity category, the lens picture extraction frequency is adjusted according to the environment representation value coefficient, the lens image is divided into a plurality of sub-lens images, the central sub-lens image is extracted, the local contrast index difference of the central sub-lens image of adjacent lens images is calculated, and the heating unit temperature and the heating duration are adjusted according to the local contrast index difference. If the environment state category is the weak humidity category, the heating unit is adjusted according to the environment temperature and the lens temperature.

5. The humidity interference resistant system for commercial and industrial environment gas detection alarms of claim 1, wherein, The lens state adjustment unit is used to adjust the lens picture extraction frequency according to the environment representation value coefficient, wherein the environment representation value coefficient and the lens picture extraction frequency are in a positive correlation.

6. The humidity interference resistant system for commercial and industrial environment gas detection alarms of claim 1, wherein, The lens state adjustment unit divides the lens image into a plurality of sub-lens images, extracts the central sub-lens image, calculates the local contrast index difference of the central sub-image of adjacent lens images, The central sub-lens image is selected at the center position. The gray value of all pixels of the central sub-lens image is obtained through image analysis software. The local contrast index of the central sub-lens image is calculated according to the local contrast index formula. The local contrast index difference of the central sub-image of adjacent lens images is calculated.

7. The humidity interference resistant system for commercial and industrial environment gas detection alarms of claim 6, wherein, The lens state adjustment unit adjusts the heating unit temperature and the heating duration according to the local contrast index difference, wherein the local contrast index difference and the heating unit temperature and the heating duration are in a positive correlation.

8. The humidity interference resistant system for commercial and industrial environment gas detection alarms of claim 1, wherein, The lens state adjustment unit determines whether to start the heating unit according to the environment temperature and the lens temperature, If the difference between the lens temperature and the environment temperature is less than the preset temperature difference comparison threshold, it is determined to start the heating unit.

9. The humidity interference resistant system for commercial and industrial environment gas detection alarms of claim 1, wherein, The lens state adjustment unit divides the lens image into a plurality of sub-lens images, wherein the area of each sub-lens image is equal.

10. A method of resisting humidity interference for a gas detection alarm in a commercial environment, characterized in that, The humidity interference resistant system for the gas detection alarm for industrial and commercial environment according to any one of claims 1-9, the humidity interference resistant method for the gas detection alarm for industrial and commercial environment comprises: Obtain the environment humidity, obtain the lens temperature and the environment temperature, obtain the lens image and the environment image in real time, and obtain the air flow rate in the area of the gas detection alarm; Calculate the environment representation value coefficient according to the environment humidity, the environment humidity change rate, the environment temperature change rate, the air flow rate in the area of the gas detection alarm, and the environment image, and divide the environment state category according to the environment representation value coefficient; Select the adjustment strategy according to the environment state category, including, Adjust the lens picture extraction frequency according to the environment representation value coefficient, divide the lens image into a plurality of sub-lens images, extract the central sub-lens image, calculate the local contrast index difference of the central sub-lens image of adjacent lens images, and adjust the heating unit temperature and the heating duration according to the local contrast index difference. Or, determine whether to start the heating unit according to the environment temperature and the lens temperature.

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