Water level detection method and apparatus, device, storage medium, and system

Abstract

The present application provides a water level detection method and apparatus, a device, a storage medium and a system. The method is applied to a respiratory humidification device which comprises a humidification tank comprising a float. The method comprises: acquiring a float position image currently captured by a camera; performing grayscale processing on the float position image to obtain current grayscale image data, wherein the current grayscale image data is a grayscale value of the humidification tank under each unit height in a grayscale image corresponding to the float position image; generating a grayscale baseline and a grayscale image curve on the basis of the current grayscale image data, wherein the grayscale image curve is a relationship curve between the current grayscale image data and a height value of the humidification tank; and determining a height value of the float on the basis of the relative positional relationship between the grayscale baseline and the grayscale image curve. The solution of the present application can detect the water level of the humidification tank in a timely manner, improving the reliability and safety of the respiratory humidification device.

Description

Water level detection method, device, equipment, storage medium and system

[0001] The present application claims priority from the Chinese patent application No. 202410451433.2 filed on April 16, 2024, and entitled "Water level detection method, device, equipment, storage medium and system", the content of which is incorporated herein by reference in its entirety. TECHNICAL FIELD

[0002] The present application relates to the technical field of water level monitoring of respiratory humidification equipment, and in particular to a water level detection method, device, equipment, storage medium and system. BACKGROUND

[0003] Respiratory humidification equipment is usually used with a gas source to provide patients with heated and humidified respiratory gas to maintain the physiological conditions necessary for the normal clearance function of the airway surface cilia system and the normal contraction and diffusion characteristics of the alveolar epithelium, and to reduce airway dryness and inflammatory symptoms. The humidification device in the respiratory humidification equipment includes a humidification tank, which is heated by a heating disc in use to promote the airflow carrying water vapor through the heated breathing pipeline to the patient end.

[0004] In practice, the humidification tank cannot be refilled in time, and the humidification tank may be dry. On the one hand, the physiological needs of the patient's respiratory tract temperature and humidity cannot be met, which may cause the respiratory tract and lungs to be too dry, and may cause physiological effects on the patient; on the other hand, the service life of the respiratory humidification equipment may be affected.

[0005] In the prior art, the water level is inferred according to the heating disc power after the temperature of the humidification tank outlet and the heating disc is obtained, the parameters required for water level detection are greatly affected by the environment, the accuracy of water level detection is poor, and the water level detection time is long, which cannot detect the water storage condition in the humidification tank in time, and the safety and reliability of the respiratory humidification equipment are poor. SUMMARY

[0006] The present application provides a water level detection method, device, equipment, storage medium and system, which aims to solve the problem of poor safety and reliability of the respiratory humidification equipment.

[0007] In a first aspect, the present application provides a water level detection method applied to a respiratory humidification device, the respiratory humidification device comprising a humidification tank, the humidification tank comprising a float, the method comprising: obtaining a float position image captured by a camera; performing grayscale processing on the float position image to obtain current grayscale image data; wherein the current grayscale image data is a grayscale value of each unit height of the humidification tank in a grayscale image corresponding to the float position image; generating a grayscale reference line and a grayscale image curve based on the current grayscale image data; wherein the grayscale image curve is a relationship curve between the current grayscale image data and the height value of the humidification tank; determining the height value of the float according to the relative position relationship between the grayscale reference line and the grayscale image curve.

[0008] In some possible implementations, before the grayscale reference line and the grayscale image curve are generated based on the current grayscale image data, the method further comprises: determining a current grayscale image parameter according to the current grayscale image data, the current grayscale image parameter comprising a minimum value and an average value of the current grayscale image data; the grayscale reference line comprises a first sub-grayscale reference line, a second sub-grayscale reference line, and a third sub-grayscale reference line; the grayscale reference line is generated based on the current grayscale image data, comprising: selecting a first threshold value, a second threshold value, and a third threshold value from a numerical interval corresponding to the minimum value and the average value of the current grayscale image data; and generating the first sub-grayscale reference line, the second sub-grayscale reference line, and the third sub-grayscale reference line by taking the first threshold value, the second threshold value, and the third threshold value as segmentation references, respectively; and the height value of the float is determined according to the relative position relationship between the grayscale reference line and the grayscale image curve, comprising: performing segmentation processing on the grayscale image curve by taking the first sub-grayscale reference line, the second sub-grayscale reference line, and the third sub-grayscale reference line as segmentation reference lines to obtain a first segment number, a second segment number, and a third segment number; wherein the segmentation processing comprises: dividing the grayscale image curve by the segmentation reference line under each segmentation reference, and counting the segment number below the segmentation reference line; determining the intersection points of the first sub-grayscale reference line, the second sub-grayscale reference line, and the third sub-grayscale reference line with the grayscale image curve, and recording the height value of the humidification tank corresponding to each intersection point; and determining the height value of the float from the height value of the humidification tank corresponding to each intersection point according to the first segment number, the second segment number, and the third segment number.

[0009] In some possible implementation manners, the determining the height value of the float according to the first number of segments, the second number of segments and the third number of segments from the height value of the wetting tank corresponding to the first intersection point comprises: if the first number of segments, the second number of segments and the third number of segments are all 1, taking the height value of the wetting tank corresponding to the first intersection point between the gray-scale image curve and the first sub-gray-scale reference line as the height value of the float; or if the first number of segments, the second number of segments and the third number of segments are not all 1, taking the height value of the wetting tank corresponding to the first intersection point between the gray-scale image curve and the second sub-gray-scale reference line as the height value of the float.

[0010] In some possible implementation manners, the first threshold value, the second threshold value and the third threshold value are selected from a numerical interval corresponding to the minimum value and the average value of the current gray-scale image data, and the selecting the first threshold value, the second threshold value and the third threshold value comprises: calculating an average value of the average value of the current gray-scale image data and the minimum value of the current gray-scale image data to obtain the first threshold value; calculating an average value of the minimum value of the current gray-scale image data and the first threshold value to obtain the second threshold value; and calculating an average value of the minimum value of the current gray-scale image data and the second threshold value to obtain the third threshold value.

[0011] In some possible implementation manners, the current gray-scale image parameters further comprise a maximum value of the current gray-scale image data; and before the generating the gray-scale reference line and the gray-scale image curve based on the current gray-scale image data, the method further comprises: judging whether the current gray-scale image parameters are all within a preset gray-scale range; if the current gray-scale image parameters are not all within the preset gray-scale range, adjusting an exposure time of the light compensation lamp according to the current gray-scale image parameters, and returning to the step of acquiring the float position image captured by the camera; and the generating the gray-scale reference line and the gray-scale image curve based on the current gray-scale image data comprises: if the current gray-scale image parameters are all within the preset gray-scale range, generating the gray-scale reference line and the gray-scale image curve based on the current gray-scale image data.

[0012] In some possible implementation manners, the adjusting the exposure time of the light compensation lamp according to the current gray-scale image parameters comprises: if the maximum value of the current gray-scale image data is less than a lower limit value of the preset gray-scale range, judging whether the exposure time of the light compensation lamp reaches an upper limit value of the exposure time; if the exposure time of the light compensation lamp reaches the upper limit value of the exposure time, keeping the exposure time of the light compensation lamp; or if the exposure time of the light compensation lamp does not reach the upper limit value of the exposure time, increasing the exposure time of the light compensation lamp; and if the minimum value of the current gray-scale image data is greater than an upper limit value of the preset gray-scale range, decreasing the exposure time of the light compensation lamp.

[0013] In some possible implementation manners, after the height value of the float is determined according to the relative position relationship between the gray reference line and the gray image curve, the method further includes: determining a current water level height value of the humidification tank according to the height value of the current float; wherein the height value of the float is a height value of the float relative to the bottom of the humidification tank; and if the current water level height value of the humidification tank is less than a warning height value, an alarm signal is output.

[0014] In some possible implementation manners, before the height value of the float is determined according to the relative position relationship between the gray reference line and the gray image curve, the method further includes: performing smoothing processing on the gray image curve to obtain a gray image curve after smoothing processing; and the height value of the float is determined according to the relative position relationship between the gray reference line and the gray image curve after smoothing processing.

[0015] In a second aspect, the present application provides a water level detection device, applied to a respiratory humidification apparatus, the respiratory humidification apparatus including a humidification tank, the humidification tank including a float, and the device including: an acquisition module configured to acquire a float position image captured by a current camera; a processing module configured to perform gray processing on the float position image to obtain current gray image data; wherein the current gray image data is a gray value of each unit height of the humidification tank in a gray image corresponding to the float position image; a generation module configured to generate a gray reference line and a gray image curve based on the current gray image data; wherein the gray image curve is a relationship curve between the current gray image data and a height value of the humidification tank; and a determination module configured to determine a height value of the float according to a relative position relationship between the gray reference line and the gray image curve.

[0016] In some possible implementation manners, the apparatus further includes: an extraction module configured to determine a current gray image parameter according to the current gray image data, the current gray image parameter including a minimum value and an average value of the current gray image data; the gray reference line includes a first sub-gray reference line, a second sub-gray reference line, and a third sub-gray reference line; the generation module includes: a selection unit configured to select a first threshold value, a second threshold value, and a third threshold value from a numerical interval corresponding to the minimum value and the average value of the current gray image data; and a generation unit configured to generate the first sub-gray reference line, the second sub-gray reference line, and the third sub-gray reference line by taking the first threshold value, the second threshold value, and the third threshold value as segmentation references, respectively; and the determination module includes: a segmentation processing unit configured to perform segmentation processing on the gray image curve by taking the first sub-gray reference line, the second sub-gray reference line, and the third sub-gray reference line as segmentation reference lines, to obtain a first segment number, a second segment number, and a third segment number; and a recording unit configured to determine an intersection point of the first sub-gray reference line, the second sub-gray reference line, and the third sub-gray reference line with the gray image curve, and record a height value of the wetted can corresponding to each intersection point; and a determination unit configured to determine a height value of the float from the height value of the wetted can corresponding to each intersection point according to the first segment number, the second segment number, and the third segment number.

[0017] In some possible implementation manners, the determination unit is specifically configured to: if the first segment number, the second segment number, and the third segment number are all 1, take a height value of the wetted can corresponding to a first intersection point of the gray image curve and the first sub-gray reference line as the height value of the float; or if the first segment number, the second segment number, and the third segment number are not all 1, take a height value of the wetted can corresponding to a first intersection point of the gray image curve and the second sub-gray reference line as the height value of the float.

[0018] In some possible implementation manners, the selection unit is configured to: calculate an average value of the average value of the current gray image data and the minimum value of the current gray image data to obtain the first threshold value; calculate an average value of the minimum value of the current gray image data and the first threshold value to obtain the second threshold value; and calculate an average value of the minimum value of the current gray image data and the second threshold value to obtain the third threshold value.

[0019] In some possible implementation manners, the current gray image parameters further include a maximum value of the current gray image data; the device further includes: a judging module configured to judge whether the current gray image parameters are all within a preset gray range; an adjusting module configured to, if the current gray image parameters are not all within the preset gray range, adjust an exposure time of the light compensation lamp according to the current gray image parameters, and return to performing the step of obtaining the current buoy position image captured by the camera; and the generating module is specifically configured to, if the current gray image parameters are all within the preset gray range, generate a gray reference line and a gray image curve based on the current gray image data.

[0020] In some possible implementation manners, the adjusting module is specifically configured to: if the maximum value of the current gray image data is less than a lower limit value of the preset gray range, judge whether the exposure time of the current light compensation lamp reaches an upper limit value of the exposure time, if yes, maintain the exposure time of the current light compensation lamp, or if not, increase the exposure time of the light compensation lamp; and if the minimum value of the current gray image data is greater than an upper limit value of the preset gray range, decrease the exposure time of the light compensation lamp.

[0021] In some possible implementation manners, the device further includes: an alarm module configured to determine a water level height value of the humidification tank according to a current height value of the buoy, wherein the height value of the buoy is a height value of the buoy relative to a bottom of the humidification tank; and output an alarm signal if the water level height value of the current humidification tank is less than a warning height value.

[0022] In some possible implementation manners, the device further includes: a preprocessing module configured to perform smoothing processing on the gray image curve to obtain a smoothed gray image curve; and the determining of the height value of the buoy according to the relative position relationship between the gray reference line and the gray image curve specifically includes: determining the height value of the buoy according to the relative position relationship between the gray reference line and the smoothed gray image curve.

[0023] In a third aspect, the present application provides an electronic device, including: a processor, and a memory connected with the processor in communication; the memory stores computer execution instructions; and the processor executes the computer execution instructions stored in the memory to implement the method as described above.

[0024] In a fourth aspect, the present application provides a computer readable storage medium, which stores computer execution instructions; and the computer execution instructions are executed by a processor to implement the method as described above.

[0025] In a fifth aspect, the present application provides an alarm system, comprising the water level detection method and the water level detection device.

[0026] The water level detection method, device, equipment, storage medium and system provided by the present application comprise the following steps: obtaining a floating position image captured by a camera; performing grayscale processing on the floating position image to obtain current grayscale image data; wherein the current grayscale image data is a grayscale value of each unit height of the wetting tank in a grayscale image corresponding to the floating position image; generating a grayscale reference line and a grayscale image curve based on the current grayscale image data; wherein the grayscale image curve is a relationship curve between the current grayscale image data and the height value of the wetting tank; and determining the height value of the floating object according to the relative position relationship between the grayscale reference line and the grayscale image curve. The scheme of the present application performs grayscale processing on the floating position image captured by the camera to obtain the current grayscale image data, generates the grayscale reference line and the grayscale image curve based on the grayscale image data, and determines the height value of the floating object according to the relative position relationship between the grayscale reference line and the grayscale image curve. In practice, the floating object is located at the upper water level in the wetting tank, and the height value of the floating object is the water level height value of the wetting tank. Therefore, the scheme of the present application can avoid the influence of environmental factors and does not need an indirect calculation process, so as to timely and accurately detect the water level of the wetting tank and improve the reliability and safety of the respiratory humidification equipment. BRIEF DESCRIPTION OF DRAWINGS

[0027] The accompanying drawings, which are incorporated into and form a part of the specification, illustrate one embodiment consistent with the present application and, together with the description, serve to explain the principles of the application.

[0028] FIG. 1 is a flowchart of a water level detection method according to an embodiment of the present application;

[0029] FIG. 2 is a structural diagram of a water level detection system according to an embodiment of the present application;

[0030] FIG. 3 is a flowchart of another water level detection method according to an embodiment of the present application;

[0031] FIG. 4 is a diagram of an upper water level grayscale image curve and a grayscale reference line according to an embodiment of the present application;

[0032] FIG. 5 is a diagram of a middle water level grayscale image curve and a grayscale reference line according to an embodiment of the present application;

[0033] FIG. 6 is a diagram of a lower water level grayscale image curve and a grayscale reference line according to an embodiment of the present application;

[0034] FIG. 7 is a structural diagram of a water level detection device according to an embodiment of the present application;

[0035] FIG. 8 is a structural schematic diagram of an electronic device according to an embodiment of the present application;

[0036] FIG. 9 is a schematic diagram I of determining a float height value according to an embodiment of the present application;

[0037] FIG. 10 is a schematic diagram II of determining a float height value according to an embodiment of the present application.

[0038] The above-described embodiments of the present application have been shown and described, and the following detailed description will be given. These drawings and detailed description are not intended to limit the scope of the present application in any way, but to explain the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0039] The exemplary embodiments will be described in detail herein below with reference to the drawings. In the following description, the same drawings reference numbers are used to denote like or similar elements. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of the present application as detailed in the appended claims.

[0040] It should be noted that the brief description of terms in the present application is only for the convenience of understanding the following described embodiments, and is not intended to limit the embodiments of the present application. Unless otherwise specified, these terms should be understood according to their ordinary and general meanings.

[0041] The terms "first", "second", and the like in the specification and claims of the present application and the above-described drawings are used to distinguish similar or like objects or entities, and do not necessarily mean a specific order or sequence, unless otherwise indicated. It should be understood that the terms used in this way can be interchanged as appropriate, for example, those other than the order given in the embodiment illustration or description of the present application can be implemented.

[0042] In addition, the terms "include" and "have" and any variations thereof are intended to cover but not exclusive inclusion, for example, a product or device including a series of components does not necessarily limit to those components clearly listed, but can include other components not clearly listed or inherent to these products or devices. The term "module" used in the present application refers to any known or later developed hardware, software, firmware, artificial intelligence, fuzzy logic, or a combination of hardware or / and software code capable of performing a function related to the element.

[0043] Respiratory humidification equipment is usually used with an air source to provide patients with heated and humidified respiratory gas to maintain the physiological conditions necessary for the normal clearance function of the airway surface cilia system and the normal contraction and diffusion characteristics of the alveolar epithelium, and to reduce airway dryness and inflammatory symptoms. The humidification device in the respiratory humidification equipment includes a humidification tank, which, in use, is heated by a heating plate to promote the airflow carrying water vapor through the heated breathing pipeline to the patient end.

[0044] In practice, the humidification tank cannot be refilled in time, and the humidification tank may be dry. On the one hand, the physiological needs of the patient's respiratory tract temperature and humidity cannot be met, which may cause the respiratory tract and lungs to be too dry, and may have physiological effects on the patient; on the other hand, the humidification tank is a consumable, with an average service life of 1-2 weeks, and if it is frequently dry, it may affect the service life of the respiratory humidification equipment.

[0045] In the prior art, the water level is inferred according to the heating plate power after the temperature of the humidification tank outlet and the heating plate is obtained, the parameters required for water level detection are greatly affected by the environment, and the accuracy of water level detection is poor; and the water level is inferred indirectly by measuring the temperature, the time length of water level detection is long, the water storage condition in the humidification tank cannot be detected in time, and actual measurement shows that when the humidification tank is short of water, the equipment still runs for a period of time before alarming, and the safety and reliability of the respiratory humidification equipment are poor.

[0046] The technical content provided in the present application aims to solve the above technical problems in the related art. In the embodiments of the present application, the position image of the float taken by the camera is subjected to grayscale processing to obtain current grayscale image data, and a grayscale reference line and a grayscale image curve are generated based on the grayscale image data, and the height value of the float can be determined according to the relative position relationship between the grayscale reference line and the grayscale image curve. In practice, the float is located at the upper water level in the humidification tank, and the height value of the float is the water level height value of the humidification tank. Therefore, the scheme of the present application can avoid the influence of environmental factors and does not need an indirect inference process, so that the water level of the humidification tank can be detected in time and accurately, and the reliability and safety of the respiratory humidification equipment are improved.

[0047] The technical scheme of the present application and the technical scheme of the present application will be described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes can not be described again in some embodiments. In the description of the present application, unless otherwise explicitly specified and limited, each term should be understood in a broad sense within the art. The embodiments of the present application will be described below with reference to the accompanying drawings.

[0048] Embodiment One

[0049] Fig. 1 is a flowchart of a water level detection method according to an embodiment of the present application. The water level detection method is applied to a respiratory humidification device, and the respiratory humidification device includes a humidification tank, and the humidification tank includes a float. As shown in Fig. 1, the water level detection method includes the following steps:

[0050] Step 101: obtaining a float position image captured by a camera;

[0051] Step 102: performing a grayscale processing on the float position image to obtain current grayscale image data, wherein the current grayscale image data is a grayscale value of each unit height of the humidification tank in a grayscale image corresponding to the float position image;

[0052] Step 103: generating a grayscale reference line and a grayscale image curve based on the current grayscale image data, wherein the grayscale image curve is a relationship curve between the current grayscale image data and the height of the humidification tank;

[0053] Step 104: determining the height of the float according to the relative position relationship between the grayscale reference line and the grayscale image curve.

[0054] In practical applications, the water level detection method can be implemented by a water level detection device. The water level detection device can be implemented in various ways, such as a computer program, for example, an application software, or a chip. The water level detection device can also be implemented as a medium storing a computer program, such as a U disk, a cloud disk, or an entity device integrated or installed with a computer program, such as a server.

[0055] For example, the water level detection device can be a microcontroller unit (MCU). Fig. 2 is a structural diagram of a water level detection system according to an embodiment of the present application. As shown in Fig. 2, the water level detection system includes a microcontroller unit 20, a camera 21, a fill light 22, and a humidification tank 23. The humidification tank 23 includes a float 231. The camera 21 is arranged at a side of the humidification tank 23, and the camera 21 is used to capture a float position image. The fill light 22 is used to provide auxiliary light for the camera 21 to capture a suitable float position image in a weak light condition. The float 231 is located at an upper water level in the humidification tank 23, and the height of the float 231 is the height of the float 231 relative to the bottom of the humidification tank 23. Therefore, the water level of the humidification tank 23 can be determined by the height of the float 231.

[0056] Specifically, the step 101 obtains the current float position image captured by the camera. For example, the camera captures the float position image in real time, and the water level detection device obtains the current float position image captured by the camera in real time. For another example, the camera can capture the float position image periodically, and the water level detection device can set the capture period according to actual needs. When the capture time comes, the water level detection device controls the camera to capture the float position image, and the water level detection device obtains the current float position image captured by the camera.

[0057] Optionally, for the respiratory humidification device with manual water adding, in order to save the cost of water level detection, the water level detection is not performed when the water level in the humidification tank is high, or a larger capture period is set. For example, after the humidification tank is added with water, the water level detection device sets the starting time of water level detection according to the power of the current respiratory humidification device. For example, when the power of the respiratory humidification device is large, the starting time of water level detection is set to be earlier; when the power of the respiratory humidification device is small, the starting time of water level detection is set to be later.

[0058] In the embodiment, the step 102 is the process of converting the float position image into a corresponding gray image. The gray image is an image with only one sample color for each pixel, and the gray image is usually displayed as gray between black and white. The gray image has many levels of color depth between black and white, and the gray image is usually obtained by measuring the brightness of each pixel in a single electromagnetic spectrum such as visible light. The gray image used for display is usually saved by using an 8-bit nonlinear scale for each sample pixel, so that there are 256 levels of gray (if 16 bits are used, there are 65536 levels). The gray image occupies less memory than the float position image, and can improve the speed of water level detection. After the float position image is converted into a corresponding gray image, the gray image can increase the contrast in vision, highlight the target area, and more accurately and quickly determine the position of the float.

[0059] Further, after the float position image is converted into a corresponding gray image, each pixel includes a gray value. In the embodiment, the unit height of the humidification tank includes at least one row of pixels, and the unit height of the humidification tank can be set according to actual needs. The gray values of all pixels in the unit height of the humidification tank are close, and the average value of the gray values of all pixels in the unit height of the humidification tank can be used as the gray value in the unit height of the humidification tank.

[0060] Specifically, the gray scale reference line is generated according to the gray scale image data in step 103, and the gray scale reference line is used as a standard to judge the size of the gray scale value on the gray scale image curve. In practice, the water in the humidification tank is colorless, and the gray scale value of the float in the gray scale image is greater than the gray scale value of other positions in the gray scale image. Therefore, the gray scale value on the part of the gray scale image curve below the gray scale reference line is the gray scale value corresponding to the float part in the float position image.

[0061] Further, the height value of the float is determined according to the relative position relationship between the gray scale reference line and the gray scale image curve in step 104. Specifically, a rectangular coordinate system is established, the horizontal coordinate is the height value of the humidification tank, and the vertical coordinate is the gray scale value. The part of the gray scale image curve below the gray scale reference line is obtained, and the two ends of the part of the gray scale image curve below the gray scale reference line both intersect with the gray scale reference line. The height value of the humidification tank corresponding to the first intersection point is taken as the height value of the float. It can be understood that the gray scale reference line and the gray scale image curve are generated based on the current gray scale image data, and the height value of the float can be quickly obtained based on the relative position of the gray scale reference line and the gray scale image curve.

[0062] In the embodiment, the float position image obtained by the camera is subjected to gray scale processing to obtain the current gray scale image data, and the gray scale reference line and the gray scale image curve are generated based on the gray scale image data. According to the relative position relationship between the gray scale reference line and the gray scale image curve, the height value of the float can be determined. In practice, the float is located at the upper water level in the humidification tank, and the height value of the float is the water level height value of the humidification tank. Therefore, the scheme of the present application can avoid the influence of environmental factors and does not need indirect calculation process, so that the water level of the humidification tank can be timely and accurately detected, and the reliability and safety of the respiratory humidification equipment are improved.

[0063] According to the above description, the gray scale value on the part of the gray scale image curve below the gray scale reference line is the gray scale value corresponding to the float part in the float position image. In practical application, the float may have a part under water and another part above water. In the embodiment, the height value of the float is equal to the water level height value of the humidification tank. Further, in order to more accurately detect the water level of the humidification tank, a plurality of sub-gray scale reference lines are set, and the height value of the float is determined according to the relative position relationship between the gray scale image curve and the plurality of gray scale reference lines. On the basis of the above embodiment, in one possible implementation manner, FIG. 3 is a flowchart of another water level detection method provided by the first embodiment of the present application, as shown in FIG. 3, before step 103, the method further includes:

[0064] Step 301: determining the current gray scale image parameters according to the current gray scale image data, the current gray scale image parameters including the minimum value and the average value of the current gray scale image data;

[0065] The gray scale reference line comprises a first sub-gray scale reference line, a second sub-gray scale reference line and a third sub-gray scale reference line; the step 103 comprises:

[0066] Step 302: generating a gray scale image curve based on the current gray scale image data;

[0067] Step 303: selecting a first threshold value, a second threshold value and a third threshold value from a numerical interval corresponding to the minimum value and the average value of the current gray scale image data;

[0068] Step 304: generating a first sub-gray scale reference line, a second sub-gray scale reference line and a third sub-gray scale reference line respectively by taking the first threshold value, the second threshold value and the third threshold value as the segmentation reference respectively;

[0069] The step 104 comprises:

[0070] Step 305: segmenting the gray scale image curve by taking the first sub-gray scale reference line, the second sub-gray scale reference line and the third sub-gray scale reference line as the segmentation reference line respectively to obtain a first segment number, a second segment number and a third segment number; wherein the segmentation processing comprises: under each segmentation reference, the gray scale image curve is divided by the segmentation reference line, and the segment number located below the segmentation reference line is counted;

[0071] Step 306: determining the intersection points of the first sub-gray scale reference line, the second sub-gray scale reference line and the third sub-gray scale reference line and the gray scale image curve respectively, and recording the height value of the wetting tank corresponding to each intersection point;

[0072] Step 307: determining the height value of the float from the height value of the wetting tank corresponding to each intersection point according to the first segment number, the second segment number and the third segment number.

[0073] It can be understood that step 301 determines the minimum value and the average value of the current gray image data according to the current gray image data. Among them, the minimum value of the current gray image data can be obtained by direct lookup. For example, the water level detection device stores a computer program for looking up the minimum value, and the minimum value of the current gray image data is obtained by calling the computer program from the current gray image data. For another example, the water level detection device includes a minimum value lookup module, and the minimum value of the current gray image data output by the minimum value lookup module can be obtained by inputting the current gray image data into the minimum value lookup module. Among them, the minimum value of the current gray image data can be calculated. For example, the water level detection device stores a computer program for calculating the minimum value, and the average value of the current gray image data is calculated by calling the computer program. For another example, the water level detection device includes an average value calculation module, and the average value of the current gray image data output by the average value calculation module can be obtained by inputting the current gray image data into the average value calculation module.

[0074] In combination with the above description, the current gray image data floating position image corresponds to the gray value of each unit height of the wetting tank in the gray image. Specifically, in step 302, the gray image curve is generated based on the current gray image data. For example, the height value of the wetting tank is taken as the abscissa, the gray value is taken as the ordinate, a rectangular coordinate system is established, and the current gray image data is fitted to generate a gray image curve.

[0075] Specifically, in step 303, the first threshold, the second threshold and the third threshold are selected from the numerical interval corresponding to the minimum value and the average value of the current gray image data. In practice, the first threshold, the second threshold and the third threshold can be three values selected from the above numerical interval, or can be selected according to a pre-specified rule, which is not limited here. Optionally, in one example, the above step 303 includes:

[0076] The average value of the minimum value of the current gray image data and the average value of the current gray image data is calculated to obtain the first threshold;

[0077] The average value of the minimum value of the current gray image data and the first threshold is calculated to obtain the second threshold;

[0078] The average value of the minimum value of the current gray image data and the second threshold is calculated to obtain the third threshold.

[0079] For example, the average value of the current gray scale image data is 50, and the minimum value of the current gray scale image data is 40; the average value of the average value 50 of the current gray scale image data and the minimum value 40 of the current gray scale image data is calculated to obtain a first threshold value of 45; the average value of the first threshold value 45 and the minimum value 40 of the current gray scale image is calculated to obtain a second threshold value of 42.5; and the average value of the second threshold value 42.5 and the minimum value 40 of the current gray scale image is calculated to obtain a third threshold value of 41.25.

[0080] In the embodiment, in order to more accurately detect the water level of the humidification tank, three sub-gray scale reference lines are set, and the height value of the float is determined according to the relative position relationship between the gray scale image curve and the multiple gray scale reference lines. In a rectangular coordinate system with the height value of the humidification tank as the abscissa and the gray scale value as the ordinate, the three sub-gray scale reference lines are three straight lines parallel to the abscissa. The ordinate values corresponding to the three sub-gray scale reference lines are the first threshold value, the second threshold value and the third threshold value respectively. Specifically, in step 304, the first threshold value, the second threshold value and the third threshold value are respectively taken as the segmentation reference to generate the first sub-gray scale reference line, the second sub-gray scale reference line and the third sub-gray scale reference line, including: generating the first sub-gray scale reference line, the second sub-gray scale reference line and the third sub-gray scale reference line with the ordinate being the first threshold value, the second threshold value and the third threshold value respectively and being parallel to the abscissa.

[0081] It should be noted that the number of sub-gray scale reference lines can be set according to actual needs and current gray scale image data. In the embodiment, three sub-gray scale reference lines are set only as an example, and the number of sub-gray scale reference lines is not specifically limited.

[0082] Next, how to determine the height value of the float according to the first sub-gray scale reference line, the second sub-gray scale reference line and the third sub-gray scale reference line and the gray scale image curve will be described with reference to FIG. 4, FIG. 5 and FIG. 6. FIG. 4 is a schematic diagram of the upper water level gray scale image curve and the gray scale reference line provided by the first embodiment of the application; FIG. 5 is a schematic diagram of the middle water level gray scale image curve and the gray scale reference line provided by the first embodiment of the application; and FIG. 6 is a schematic diagram of the lower water level gray scale image curve and the gray scale reference line provided by the first embodiment of the application.

[0083] Specifically, the first sub-gray reference line, the second sub-gray reference line and the third sub-gray reference line are respectively taken as the segmentation reference line to segment the gray image curve in step 305, and the first segment number, the second segment number and the third segment number are obtained. It can be understood that the first segment number C1 is obtained by taking the first sub-gray reference line as the segmentation reference line to segment the gray image curve and counting the segment number below the first sub-gray reference line. Similarly, the second segment number C2 is obtained by taking the second sub-gray reference line as the segmentation reference line to segment the gray image curve and counting the segment number below the second sub-gray reference line. The third segment number C3 is obtained by taking the third sub-gray reference line as the segmentation reference line to segment the gray image curve and counting the segment number below the third sub-gray reference line.

[0084] For example, the first threshold value is T1, the second threshold value is T2, and the third threshold value is T3, T1>T2>T3, and the order of the three sub-gray reference lines from top to bottom is the first sub-gray reference line, the second sub-gray reference line and the third sub-gray reference line. As shown in FIG. 4, the first sub-gray reference line is taken as the segmentation reference line to segment the gray image, and the first segment number C1 is 2. The second sub-gray reference line is taken as the segmentation reference line to segment the gray image, and the second segment number C2 is 2. The third sub-gray reference line is taken as the segmentation reference line to segment the gray image, and the third segment number C3 is 2. As shown in FIG. 5, the first sub-gray reference line is taken as the segmentation reference line to segment the gray image, and the first segment number C1 is 1. The second sub-gray reference line is taken as the segmentation reference line to segment the gray image, and the second segment number C2 is 1. The third sub-gray reference line is taken as the segmentation reference line to segment the gray image, and the third segment number C3 is 1. As shown in FIG. 6, the first sub-gray reference line is taken as the segmentation reference line to segment the gray image, and the first segment number C1 is 1. The second sub-gray reference line is taken as the segmentation reference line to segment the gray image, and the second segment number C2 is 1. The third sub-gray reference line is taken as the segmentation reference line to segment the gray image, and the third segment number C3 is 1.

[0085] In practical application, the first sub-gray reference line, the second sub-gray reference line and the third sub-gray reference line are all used to determine the height value of the float. It can be understood that there are multiple intersection points between the first sub-gray reference line, the second sub-gray reference line, the third sub-gray reference line and the gray image curve, and each intersection point corresponds to a height value of a wetting tank. The height values of the wetting tanks corresponding to the multiple intersection points include the height value of the float. Therefore, after the intersection points between the first sub-gray reference line, the second sub-gray reference line and the third sub-gray reference line and the gray image curve are determined in step 306, the height value of the wetting tank corresponding to each intersection point is recorded.

[0086] Further, the height value of the float is determined from the height values of the wetting tanks corresponding to the intersection points. Specifically, the height value of the float is determined from the height values of the wetting tanks corresponding to the intersection points according to the first segment number, the second segment number and the third segment number in step 307.

[0087] As an example, in one example, step 307 comprises:

[0088] If the first segment number, the second segment number and the third segment number are all 1, the height value of the wetting tank corresponding to the first intersection point of the gray scale image curve and the first sub-gray scale reference line is taken as the height value of the float; otherwise, the height value of the wetting tank corresponding to the first intersection point of the gray scale image curve and the second sub-gray scale reference line is taken as the height value of the float.

[0089] Specifically, the specific process of determining the height value of the float from the height values of the wetting tanks corresponding to the intersection points according to the first segment number, the second segment number and the third segment number is exemplarily explained in combination with FIG. 4, FIG. 5 and FIG. 6. For FIG. 4, the first segment number C1, the second segment number C2 and the third segment number C3 are all 2, the height value of the wetting tank corresponding to the first intersection point A of the gray scale image curve and the second sub-gray scale reference line is taken as the height value of the float, as shown in FIG. 4, the height value of the wetting tank corresponding to point A is 573, then the height value of the float is 573, and the water level height value of the wetting tank is 573. For FIG. 5, the first segment number C1 is 1, the second segment number C2 and the third segment number C3 are both 1, the height value of the wetting tank corresponding to the first intersection point B of the gray scale image curve and the second sub-gray scale reference line is taken as the height value of the float, as shown in FIG. 5, the height value of the wetting tank corresponding to point B is 545, then the height value of the float is 545, and the water level height value of the wetting tank is 545. For FIG. 6, the first segment number C1, the second segment number C2 and the third segment number C3 are all 1, the height value of the wetting tank corresponding to the first intersection point C of the gray scale image curve and the first sub-gray scale reference line is taken as the height value of the float, as shown in FIG. 4, the height value of the wetting tank corresponding to point C is 396, then the height value of the float is 396, and the water level height value of the wetting tank is 396.

[0090] In this embodiment, first, the camera captures the position of the float image to be processed gray, get the current gray image data; then, according to the current gray image data to determine the current gray image parameters; then, according to the current gray image data to generate gray image curve, and according to the gray image parameters to generate the first sub gray reference curve, the second sub gray reference line and the third sub gray reference line; finally, according to the relative position relationship of the first sub gray reference curve, the second sub gray reference line, the third sub gray reference line and the gray image curve, the height value of the float is determined. In practice, the float is located at the upper water level of the humidification tank, and the height value of the float is the water level height value of the humidification tank, so the scheme of the application can avoid the influence of environmental factors and does not need indirect calculation process, so as to detect the water level of the humidification tank in time and accurately, improve the reliability and safety of the respiratory humidification equipment. Further, in this embodiment, three sub gray reference lines are set, which can detect the water level of the humidification tank more accurately and improve the accuracy of water level detection.

[0091] In combination with the above description, the present application is to process the float position image captured by the camera to realize water level detection. In practical application, when the light is dark, the float position image captured by the camera does not meet the demand of water level detection. In order to further improve the accuracy of water level detection, it can be judged whether the current float position image meets the demand of water level detection, if it meets, the above water level detection steps can be executed to realize water level detection; if it does not meet, the fill light can be turned on until the current float position image meets the demand of water level detection. As an example, in a possible embodiment, the current gray image parameters further include the maximum value of the current gray image data; before the step 103, the method further includes:

[0092] judging whether the current gray image parameters are all located in the pre-set gray range;

[0093] if the current gray image parameters are not all located in the pre-set gray range, adjusting the exposure time of the fill light according to the current gray image parameters, and returning to execute the step of obtaining the float position image captured by the camera;

[0094] the step 103 specifically includes:

[0095] if the current gray image parameters are all located in the pre-set gray range, generating a gray reference line and a gray image curve based on the current gray image data.

[0096] The gray scale range can be pre-set according to actual water level detection requirements. It can be understood that the current gray scale image parameters are all within the pre-set gray scale range, indicating that the current float position image meets the water level detection requirements. Specifically, a gray scale reference line and a gray scale image curve are generated based on the current gray scale image data, and the height value of the float is determined according to the relative position relationship between the gray scale reference line and the gray scale image curve.

[0097] Correspondingly, if the current gray scale image parameters are not all within the pre-set gray scale range, it indicates that the current float position image meets the water level detection requirements. Specifically, the light compensation lamp is turned on, the exposure time of the light compensation lamp is adjusted according to the current gray scale image parameters, the camera re-shoots the float position image, until the current float position image meets the water level detection requirements, and then the subsequent water level detection steps are performed according to the float position image re-shot by the camera, to realize accurate water level detection.

[0098] In this embodiment, before generating the gray scale reference line and the gray scale image curve based on the current gray scale image data, it is determined whether the current gray scale image parameters are all within the pre-set gray scale range. If the current gray scale image parameters are not all within the pre-set gray scale range, the exposure time of the light compensation lamp is adjusted according to the current gray scale image parameters, thereby improving the accuracy of water level detection and further improving the reliability and safety of the respiratory humidification device.

[0099] Further, as an example, in one possible implementation, the above-mentioned adjustment of the exposure time of the light compensation lamp according to the current gray scale image parameters includes:

[0100] If the maximum value of the current gray scale image data is less than the lower limit value of the pre-set gray scale range, it is determined whether the exposure time of the current light compensation lamp reaches the upper limit value of the exposure time. If so, the exposure time of the current light compensation lamp is maintained, otherwise, the exposure time of the light compensation lamp is increased.

[0101] If the minimum value of the current gray scale image data is greater than the upper limit value of the pre-set gray scale range, the exposure time of the light compensation lamp is reduced.

[0102] It can be understood that the maximum value of the gray scale image data is greater than the minimum value and the average value. Therefore, the maximum value of the current gray scale image data being less than the lower limit value of the pre-set gray scale range indicates that the current gray scale image parameters are all less than the lower limit value of the pre-set gray scale range, and the minimum value of the current gray scale image data being greater than the upper limit value of the pre-set gray scale range indicates that the current gray scale image parameters are all greater than the upper limit value of the pre-set gray scale range.

[0103] In actual application, in order to ensure the service life of the light supplement lamp, an upper limit value of the exposure time of the light supplement lamp is set, and the reliability of the water level detection is improved. The way of increasing the exposure time of the light supplement lamp is not limited, for example, an increasing mechanism can be set, and the exposure time is increased by a fixed value each time; for another example, the exposure time is determined according to the difference between the maximum value and the lower limit value of the gray scale range, and the greater the difference, the longer the exposure time is increased. The way of reducing the exposure time of the light supplement lamp is also not limited, for example, a reducing mechanism can be set, and the exposure time is reduced by a fixed value each time; for another example, the exposure time is determined according to the difference between the minimum value and the upper limit value of the gray scale range, and the greater the difference, the longer the exposure time is reduced.

[0104] In the embodiment, the exposure time of the light supplement lamp is adjusted according to the current gray scale image parameter, so that the position image of the float captured by the camera meets the requirements, the accuracy of the water level detection is improved, and the reliability and safety of the respiratory humidification device are improved.

[0105] Further, in order to ensure the safety and reliability of the respiratory humidification device, when the water level height value of the humidification tank is small, an alarm signal can be outputted so that the user can handle it in time. As an example, in a possible embodiment, after the step 104, the method further comprises:

[0106] determining the current water level height value of the humidification tank according to the current height value of the float; wherein the height value of the float is the height value of the float relative to the bottom of the humidification tank;

[0107] if the current water level height value of the humidification tank is less than the early warning height value, outputting an alarm signal.

[0108] The early warning height value can be set according to actual needs, when the safety requirement is high, the early warning height value can be set to a large value; when the safety requirement is low, the early warning height value can be set to a small value. It should be noted that since the alarm signal is outputted, it needs a certain reaction time to handle afterwards, therefore the early warning height value is greater than 0.

[0109] In the embodiment, after determining the current water level height value of the humidification tank, when the current water level height value of the humidification tank is less than the early warning height value, an alarm signal is outputted, and the reliability and safety of the respiratory humidification device are improved.

[0110] In addition, in one example, after determining the current water level height value of the humidification tank according to the current height value of the float, if the current water level height value of the humidification tank is greater than the highest water level value, an alarm signal is outputted.

[0111] Specifically, for the automatic water adding respiratory humidification device, the maximum water level of the humidification tank is generally set, and when the water level of the humidification tank reaches the maximum water level, the water adding is stopped. In practice, the automatic water adding device may be abnormal, and the water adding is not stopped when the water level of the humidification tank reaches the maximum water level. It can be understood that the water level detection method provided in the present application can realize the water level detection of the humidification tank, and output an alarm signal when the water level height value of the humidification tank is greater than the maximum water level value, thereby improving the reliability and safety of the respiratory humidification device.

[0112] In practice, in order to further improve the accuracy of water level detection and thereby improve the reliability and safety of the respiratory humidification device, the current gray image data can be preprocessed to suppress the noise of the gray image. As an example, the gray image curve can be preprocessed to filter out relatively sharp burrs. Optionally, in a possible implementation, before the step 104, the method further includes:

[0113] smoothing the gray image curve to obtain a smoothed gray image curve;

[0114] The step 104 specifically includes:

[0115] determining the height value of the float according to the relative position relationship between the gray reference line and the smoothed gray image curve.

[0116] The smoothing processing includes mean filtering, median filtering, Gaussian filtering, etc. In the present embodiment, after obtaining the gray reference line and the gray image curve, the gray image curve is smoothed, and the height value of the float is determined according to the relative position relationship between the gray reference line and the smoothed gray image curve, thereby improving the accuracy of water level detection and further improving the reliability and safety of the respiratory humidification device.

[0117] The water level detection method provided in the embodiment comprises the following steps: obtaining a floating position image captured by a camera; performing gray scale processing on the floating position image to obtain current gray scale image data; wherein the current gray scale image data is a gray scale value of each unit height of the wetting tank in a gray scale image corresponding to the floating position image; generating a gray scale reference line and a gray scale image curve based on the current gray scale image data; wherein the gray scale image curve is a relationship curve of the current gray scale image data and the height value of the wetting tank; and determining the height value of the floating object according to the relative position relationship between the gray scale reference line and the gray scale image curve. In the embodiment, the floating position image captured by the camera is subjected to gray scale processing to obtain the current gray scale image data, and the gray scale reference line and the gray scale image curve are generated based on the gray scale image data, and the height value of the floating object can be determined according to the relative position relationship between the gray scale reference line and the gray scale image curve. In practice, the floating object is located at the upper water level in the wetting tank, and the height value of the floating object is the water level height value of the wetting tank. Therefore, the scheme of the application can avoid the influence of environmental factors and does not need an indirect calculation process, so that the water level of the wetting tank can be detected in time and accurately, and the reliability and safety of the respiratory humidification device are improved.

[0118] In some embodiments, the light supplement lamp is arranged above the wetting tank, and the camera is arranged at the side of the wetting tank. When the light is weak or the light supplement lamp is turned on, a shadow is generated between the floating object and the bottom of the wetting tank, and the longitudinal width of the shadow is theoretically greater than the longitudinal width of the floating object.

[0119] In some embodiments, the step 307 comprises:

[0120] If the third paragraph number is 2, the part between the first and second intersection points of the third sub-gray scale reference line and the gray scale image curve is regarded as the first paragraph, the absolute value of the difference in the abscissa corresponding to the first and second intersection points is the width of the first paragraph, and the part between the third and fourth intersection points of the third sub-gray scale reference line and the gray scale image curve is regarded as the second paragraph, the absolute value of the difference in the abscissa corresponding to the third and fourth intersection points is the width of the second paragraph;

[0121] If the first paragraph contains the minimum gray scale value of the entire gray scale image curve, and the width of the first paragraph is less than the width of the second paragraph, the height value of the wetting tank corresponding to the first intersection point of the gray scale image curve and the third sub-gray scale reference line is taken as the height value of the floating object;

[0122] If the second paragraph contains the minimum gray scale value of the entire gray scale curve, and the width of the second paragraph is less than the width of the first paragraph, the height value of the wetting tank corresponding to the third intersection point of the gray scale image curve and the third sub-gray scale reference line is taken as the height value of the floating object;

[0123] In other cases, the height value of the wetting tank corresponding to the first intersection point of the gray image curve and the third sub-gray reference line is taken as the height value of the float.

[0124] Specifically, the specific process of determining the height value of the float from the height value of the wetting tank corresponding to each intersection point according to the first paragraph number, the second paragraph number and the third paragraph number is exemplarily described in combination with FIG. 9 and FIG. 10.

[0125] For FIG. 9, the first paragraph number C1, the second paragraph number C2 and the third paragraph number C3 are all 2, the two paragraphs below the third sub-gray reference line both contain the minimum gray value 8 of the entire gray curve, and the width of the first paragraph is less than the width of the second paragraph. The height value of the wetting tank corresponding to the first intersection point A of the gray image curve and the third sub-gray reference line is taken as the height value of the float. As shown in FIG. 9, the height value of the wetting tank corresponding to the point A is 206, so the height value of the float is 206, and the water level height value of the wetting tank is 206.

[0126] For FIG. 10, the first paragraph number C1 and the second paragraph number C2 are both 2, and the third paragraph number C3 is 1. The height value of the wetting tank corresponding to the first intersection point B of the gray image curve and the third sub-gray reference line is taken as the height value of the float. As shown in FIG. 10, the height value of the wetting tank corresponding to the point B is 594, so the height value of the float is 594, and the water level height value of the wetting tank is 594.

[0127] Embodiment Two

[0128] FIG. 7 is a structural schematic diagram of a water level detection device provided by the embodiment two of the present application, which is applied to a respiratory humidification device. The respiratory humidification device includes a wetting tank, and the wetting tank includes a float. As shown in FIG. 7, the device includes:

[0129] The acquisition module 71 is configured to acquire a float position image captured by a current camera;

[0130] The processing module 72 is configured to perform gray processing on the float position image to obtain current gray image data. The current gray image data is the gray value of each unit height of the wetting tank in the gray image corresponding to the float position image.

[0131] The generation module 73 is configured to generate a gray reference line and a gray image curve based on the current gray image data. The gray image curve is a relationship curve of the current gray image data and the height value of the wetting tank.

[0132] The determination module 74 is configured to determine the height value of the float according to the relative position relationship between the gray reference line and the gray image curve.

[0133] Specifically, the acquisition module 71 acquires the current buoy position image captured by the camera. For example, the camera captures the buoy position image in real time, and the acquisition module 71 acquires the current buoy position image captured by the camera in real time. For another example, the camera can capture the buoy position image periodically, and the acquisition module 71 can set the capture period according to actual needs. When the capture time comes, the water level detection device controls the camera to capture the buoy position image, and the acquisition module 71 acquires the current buoy position image captured by the camera.

[0134] Optionally, for the artificial water adding respiratory humidification device, in order to save the cost of water level detection, the water level detection is not performed when the water level in the humidification tank is high, or a larger capture period is set. For example, after the humidification tank is added with water, the water level detection device sets the start time of the water level detection according to the current power of the respiratory humidification device. For example, when the power of the respiratory humidification device is large, the start time of the water level detection is set to be earlier; when the power of the respiratory humidification device is small, the start time of the water level detection is set to be later.

[0135] In this embodiment, the grayscale processing refers to the process of converting the buoy position image into a corresponding grayscale image. The grayscale image occupies less memory than the buoy position image, which can improve the speed of water level detection. After the processing module 72 converts the buoy position image into a corresponding grayscale image, the grayscale image can increase the contrast in vision, highlight the target area, and more accurately and quickly determine the position of the buoy.

[0136] Further, after the processing module 72 converts the buoy position image into a corresponding grayscale image, each pixel includes a grayscale value. In this embodiment, the unit height of the humidification tank includes at least one row of pixels, and the unit height of the humidification tank can be set according to actual needs. The grayscale values of all pixels in the unit height of the humidification tank are close, and the processing module 72 can take the average value of the grayscale values of all pixels in the unit height of the humidification tank as the grayscale value in the unit height of the humidification tank.

[0137] Specifically, the grayscale reference line is generated according to the grayscale image data, and the grayscale reference line serves as a standard to judge the size of the grayscale value on the grayscale image curve. In practice, the water in the humidification tank is colorless, and the grayscale value of the buoy in the grayscale image is greater than the grayscale value of other positions in the grayscale image. Therefore, the grayscale value on the part of the grayscale image curve below the grayscale reference line is the grayscale value corresponding to the buoy part in the buoy position image.

[0138] Further, the determining module 74 determines the height value of the float according to the relative position relationship between the gray reference line and the gray image curve. Specifically, a rectangular coordinate system is established, the horizontal coordinate is the height value of the humidification tank, and the vertical coordinate is the gray value. The part of the gray image curve below the gray reference line is obtained, both ends of the part of the gray image curve intersect with the gray reference line, and the height value of the humidification tank corresponding to the first intersection point is taken as the height value of the float. It can be understood that the gray reference line and the gray image curve are generated based on the current gray image data, and the height value of the float can be quickly obtained based on the relative position of the gray reference line and the gray image curve.

[0139] In the embodiment, the processing module 72 performs gray processing on the float position image captured by the camera to obtain the current gray image data. The generating module 73 generates the gray reference line and the gray image curve based on the gray image data. The determining module 74 can determine the height value of the float according to the relative position relationship between the gray reference line and the gray image curve. In practice, the float is located at the upper water level in the humidification tank, and the height value of the float is the water level height value of the humidification tank. Therefore, the scheme of the application can avoid the influence of environmental factors and does not need indirect calculation process, so as to timely and accurately detect the water level of the humidification tank and improve the reliability and safety of the respiratory humidification device.

[0140] On the basis of the above-mentioned embodiments, in a possible implementation manner, the device further includes:

[0141] The extracting module is configured to determine the current gray image parameters according to the current gray image data, and the current gray image parameters include the minimum value and the average value of the current gray image data.

[0142] The gray reference line includes a first sub-gray reference line, a second sub-gray reference line, and a third sub-gray reference line. The generating module 73 includes:

[0143] The selecting unit is configured to select the first threshold value, the second threshold value, and the third threshold value from the numerical interval corresponding to the minimum value and the average value of the current gray image data.

[0144] The generating unit is configured to generate the first sub-gray reference line, the second sub-gray reference line, and the third sub-gray reference line by taking the first threshold value, the second threshold value, and the third threshold value as the segmentation reference respectively.

[0145] The determining module 74 includes:

[0146] The segmentation processing unit is configured to perform segmentation processing on the gray image curve with the first sub-gray reference line, the second sub-gray reference line, and the third sub-gray reference line as the segmentation reference lines respectively, to obtain the first segment number, the second segment number, and the third segment number; wherein the segmentation processing comprises: under each segmentation reference, the gray image curve is divided by the segmentation reference line, and the segment number below the segmentation reference line is counted;

[0147] The recording unit is configured to determine the intersection points of the first sub-gray reference line, the second sub-gray reference line, and the third sub-gray reference line with the gray image curve respectively, and record the height value of the wetting tank corresponding to each intersection point;

[0148] The determination unit is configured to determine the height value of the float from the height value of the wetting tank corresponding to each intersection point according to the first segment number, the second segment number, and the third segment number.

[0149] It can be understood that the extraction module determines the minimum value and the average value of the current gray image data according to the current gray image data. The minimum value of the current gray image data can be obtained by direct lookup. The average value of the current gray image data can be calculated.

[0150] In combination with the above description, the gray value of each unit height of the wetting tank in the gray image corresponding to the current gray image data float position image. Specifically, when the generation module 73 generates the gray image curve based on the current gray image data, it is specifically configured to: take the height value of the wetting tank as the abscissa, take the gray value as the ordinate, establish a rectangular coordinate system, and fit the current gray image data to generate a gray image curve.

[0151] Specifically, the first threshold, the second threshold, and the third threshold are selected by the selection unit from the numerical interval corresponding to the minimum value and the average value of the current gray image data. In practice, the first threshold, the second threshold, and the third threshold can be any three values selected in the above numerical interval, or can be selected according to a pre-specified rule, which is not limited here. Optionally, in one example, the selection unit is configured to:

[0152] Calculate the average value of the average value of the current gray image data and the minimum value of the current gray image data to obtain the first threshold;

[0153] Calculate the average value of the minimum value of the current gray image data and the first threshold to obtain the second threshold;

[0154] Calculate the average value of the minimum value of the current gray image data and the second threshold to obtain the third threshold.

[0155] In this embodiment, in order to more accurately detect the water level of the humidification tank, three sub-gray reference lines are set, and the height value of the float is determined according to the relative position relationship between the gray image curve and the multiple gray reference lines. In the rectangular coordinate system with the height value of the humidification tank as the horizontal coordinate and the gray value as the vertical coordinate, the three sub-gray reference lines are three straight lines parallel to the horizontal coordinate axis. The vertical coordinate values corresponding to the three sub-gray reference lines are the first threshold value, the second threshold value and the third threshold value. Specifically, the generating unit is specifically configured to generate the first sub-gray reference line, the second sub-gray reference line and the third sub-gray reference line with the vertical coordinates of the first threshold value, the second threshold value and the third threshold value respectively, and parallel to the horizontal coordinate axis.

[0156] It should be noted that the number of sub-gray reference lines can be set according to actual needs and current gray image data. In this embodiment, three sub-gray reference lines are set only as an example, and the number of sub-gray reference lines is not specifically limited.

[0157] Specifically, the segmented processing unit takes the first sub-gray reference line, the second sub-gray reference line and the third sub-gray reference line as the segmentation reference line to perform segmentation processing on the gray image curve, and obtains the first segment number, the second segment number and the third segment number. It can be understood that the first segment number C1 is obtained by taking the first sub-gray reference line as the segmentation reference line to perform segmentation processing on the gray image curve and counting the segment number below the first sub-gray reference line. Similarly, the second segment number C2 is obtained by taking the second sub-gray reference line as the segmentation reference line to perform segmentation processing on the gray image curve and counting the segment number below the second sub-gray reference line. The third segment number C3 is obtained by taking the third sub-gray reference line as the segmentation reference line to perform segmentation processing on the gray image curve and counting the segment number below the third sub-gray reference line.

[0158] In actual application, the first sub-gray reference line, the second sub-gray reference line and the third sub-gray reference line are all used to determine the height value of the float. It can be understood that there are multiple intersection points between the first sub-gray reference line, the second sub-gray reference line, the third sub-gray reference line and the gray image curve, and each intersection point corresponds to a height value of the humidification tank. The height values of the humidification tank corresponding to the multiple intersection points include the height value of the float. Therefore, after the recording unit determines the intersection points between the first sub-gray reference line, the second sub-gray reference line, the third sub-gray reference line and the gray image curve, the height value of the humidification tank corresponding to each intersection point is recorded.

[0159] Further, the height value of the float needs to be determined from the height values of the humidification tank corresponding to the multiple intersection points. Specifically, the determining unit determines the height value of the float from the height values of the humidification tank corresponding to each intersection point according to the first segment number, the second segment number and the third segment number.

[0160] As an example, in one example, the determination unit is specifically configured to:

[0161] If the first paragraph number, the second paragraph number and the third paragraph number are all 1, the height value of the wetting tank corresponding to the first intersection point of the gray image curve and the first sub-gray reference line is taken as the height value of the float; otherwise, the height value of the wetting tank corresponding to the first intersection point of the gray image curve and the second sub-gray reference line is taken as the height value of the float.

[0162] In the embodiment, first, the processing module 72 performs gray processing on the float position image captured by the camera to obtain current gray image data; then, the extraction module determines current gray image parameters according to the current gray image data; then, the generation module 73 generates a gray image curve according to the current gray image data, and generates a first sub-gray reference curve, a second sub-gray reference line and a third sub-gray reference line according to the gray image parameters; finally, the determination module 74 determines the height value of the float according to the relative positional relationship between the first sub-gray reference curve, the second sub-gray reference line, the third sub-gray reference line and the gray image curve. In practice, the float is located at the upper water level in the wetting tank, and the height value of the float is the water level height value of the wetting tank. Therefore, the scheme of the application can avoid the influence of environmental factors and does not need indirect calculation process, so as to timely and accurately detect the water level of the wetting tank, and improve the reliability and safety of the respiratory humidification equipment. Further, in the embodiment, three sub-gray reference lines are set, which can more accurately detect the water level of the wetting tank and improve the accuracy of water level detection.

[0163] As an example, in one possible implementation, the current gray image parameters further include a maximum value of the current gray image data; the device further includes:

[0164] The determination module is configured to determine whether the current gray image parameters are all located within the pre-set gray range;

[0165] The adjustment module is configured to, if the current gray image parameters are not all located within the pre-set gray range, adjust the exposure time of the light compensation lamp according to the current gray image parameters, and return to execute the step of obtaining the float position image captured by the camera;

[0166] The generation module 73 is specifically configured to:

[0167] If the current gray image parameters are all located within the pre-set gray range, generate a gray reference line and a gray image curve based on the current gray image data.

[0168] The gray scale range can be pre-set according to actual water level detection requirements. It can be understood that the current gray scale image parameters are all within the pre-set gray scale range, indicating that the current float position image meets the water level detection requirements. Specifically, the generation module 73 generates a gray scale reference line and a gray scale image curve based on the current gray scale image data, and the determination module 74 determines the height value of the float according to the relative position relationship between the gray scale reference line and the gray scale image curve.

[0169] Correspondingly, if the current gray scale image parameters are not all within the pre-set gray scale range, it indicates that the current float position image meets the water level detection requirements. Specifically, the light compensation lamp is turned on, the adjustment module adjusts the exposure time of the light compensation lamp according to the current gray scale image parameters, the camera re-shoots the float position image, until the current float position image meets the water level detection requirements, and then the subsequent water level detection steps are performed according to the float position image re-shot by the camera, to realize accurate water level detection.

[0170] In this embodiment, before generating the gray scale reference line and the gray scale image curve based on the current gray scale image data, it is determined whether the current gray scale image parameters are all within the pre-set gray scale range. If the current gray scale image parameters are not all within the pre-set gray scale range, the exposure time of the light compensation lamp is adjusted according to the current gray scale image parameters, which improves the accuracy of water level detection and further improves the reliability and safety of the respiratory humidification device.

[0171] Further, as an example, in one possible implementation, the above-mentioned adjustment module is specifically configured to:

[0172] If the maximum value of the current gray scale image data is less than the lower limit value of the pre-set gray scale range, it is determined whether the exposure time of the current light compensation lamp reaches the upper limit value of the exposure time. If so, the exposure time of the current light compensation lamp is maintained, otherwise, the exposure time of the light compensation lamp is increased.

[0173] If the minimum value of the current gray scale image data is greater than the upper limit value of the pre-set gray scale range, the exposure time of the light compensation lamp is reduced.

[0174] It can be understood that the maximum value of the gray scale image data is greater than the minimum value and the average value. Therefore, the maximum value of the current gray scale image data being less than the lower limit value of the pre-set gray scale range indicates that the current gray scale image parameters are all less than the lower limit value of the pre-set gray scale range, and the minimum value of the current gray scale image data being greater than the upper limit value of the pre-set gray scale range indicates that the current gray scale image parameters are all greater than the upper limit value of the pre-set gray scale range.

[0175] In practical applications, in order to ensure the service life of the light supplement lamp, an upper limit value of the exposure time of the light supplement lamp is set, and the reliability of the water level detection is improved. The way of increasing the exposure time of the light supplement lamp is not limited, for example, an increasing mechanism can be set, and the exposure time is increased by a fixed value each time; for another example, the exposure time is determined according to the difference between the maximum value and the lower limit value of the gray scale range, and the greater the difference, the longer the exposure time is increased. The way of reducing the exposure time of the light supplement lamp is also not limited, for example, a reducing mechanism can be set, and the exposure time is reduced by a fixed value each time; for another example, the exposure time is determined according to the difference between the minimum value and the upper limit value of the gray scale range, and the greater the difference, the longer the exposure time is reduced.

[0176] In the embodiment, the exposure time of the light supplement lamp is adjusted according to the current gray scale image parameter, so that the position image of the float captured by the camera meets the requirements, the accuracy of the water level detection is improved, and the reliability and safety of the respiratory humidification device are improved.

[0177] Further, in order to ensure the safety and reliability of the respiratory humidification device, when the water level height value of the humidification tank is small, an alarm signal can be outputted so that the user can handle it in time. As an example, in a possible implementation, the device further comprises an alarm module configured to:

[0178] determine the current water level height value of the humidification tank according to the current height value of the float, wherein the height value of the float is the height value of the float relative to the bottom of the humidification tank;

[0179] if the current water level height value of the humidification tank is less than the warning height value, output an alarm signal.

[0180] The warning height value can be set according to actual needs, when the safety requirement is high, the warning height value can be set to a large value; when the safety requirement is low, the warning height value can be set to a small value. It should be noted that since the alarm signal is outputted, the user needs a certain reaction time to handle it afterwards, therefore the warning height value is greater than 0.

[0181] In the embodiment, after determining the current water level height value of the humidification tank, if the current water level height value of the humidification tank is less than the warning height value, an alarm signal is outputted, and the reliability and safety of the respiratory humidification device are improved.

[0182] In addition, in one example, the alarm module is further configured to output an alarm signal if the current water level height value of the humidification tank is greater than the maximum water level value.

[0183] Specifically, for the automatic water adding respiratory humidification device, the highest water level of the humidification tank is generally set, and the water adding is stopped when the water level of the humidification tank reaches the highest water level. In practice, the automatic water adding device may be abnormal, and the water adding is not stopped when the water level of the humidification tank reaches the highest water level. It can be understood that the water level detection method provided in the application can realize the water level detection of the humidification tank, and output an alarm signal when the water level height value of the humidification tank is greater than the highest water level value, thereby improving the reliability and safety of the respiratory humidification device.

[0184] Optionally, in a possible implementation, the device further includes a preprocessing module configured to:

[0185] The gray scale image curve is smoothed to obtain a smoothed gray scale image curve;

[0186] According to the relative position relationship between the gray scale reference line and the gray scale image curve, the height value of the float is determined, and specifically includes:

[0187] According to the relative position relationship between the gray scale reference line and the smoothed gray scale image curve, the height value of the float is determined.

[0188] The smoothing processing includes mean filtering, median filtering, Gaussian filtering, etc. In the embodiment, after the gray scale reference line and the gray scale image curve are obtained, the gray scale image curve is smoothed, and according to the relative position relationship between the gray scale reference line and the smoothed gray scale image curve, the height value of the float is determined, thereby improving the accuracy of the water level detection, and further improving the reliability and safety of the respiratory humidification device.

[0189] The water level detection device provided in the embodiment includes an acquisition module configured to acquire a float position image captured by a camera; a processing module configured to perform grayscale processing on the float position image to obtain current grayscale image data; wherein the current grayscale image data is a grayscale value of each unit height of the wetting tank in a grayscale image corresponding to the float position image; a generation module configured to generate a grayscale reference line and a grayscale image curve based on the current grayscale image data; wherein the grayscale image curve is a relationship curve of the current grayscale image data and the height value of the wetting tank; and a determination module configured to determine the height value of the float according to a relative position relationship between the grayscale reference line and the grayscale image curve. In the embodiment, the float position image captured by the camera is subjected to grayscale processing to obtain the current grayscale image data, and the grayscale reference line and the grayscale image curve are generated based on the grayscale image data, and the height value of the float can be determined according to the relative position relationship between the grayscale reference line and the grayscale image curve. In practice, the float is located at the upper water level in the wetting tank, and the height value of the float is the water level height value of the wetting tank. Therefore, the scheme of the application can avoid the influence of environmental factors and does not need an indirect calculation process, so that the water level of the wetting tank can be detected in time and accurately, and the reliability and safety of the respiratory humidification device are improved.

[0190] Embodiment three

[0191] FIG. 8 is a structural schematic diagram of an electronic device provided in the embodiment three of the application. As shown in FIG. 8, the electronic device includes:

[0192] A processor 81, and the host device further includes a memory 82; and can further include a communication interface 83 and a bus 84. The processor 81, the memory 82, and the communication interface 83 can complete communication with each other through the bus 84. The communication interface 83 can be used for information transmission. The processor 81 can call logical instructions in the memory 82 to execute the method of the above-mentioned embodiment.

[0193] In addition, the logical instructions in the memory 82 described above can be implemented in the form of a software function unit and sold or used as an independent product, which can be stored in a computer readable storage medium.

[0194] The memory 82 as a computer readable storage medium can be used to store software programs, computer executable programs, such as program instructions / modules corresponding to the method in the embodiment of the application. The processor 81 executes the functions and data processing by running the software programs, instructions and modules stored in the memory 82, that is, implements the method in the above-mentioned method embodiment.

[0195] The memory 82 can include a program storage area and a data storage area, wherein the program storage area can store an operating system, application programs required by at least one function; the data storage area can store data created according to the use of the terminal device, etc. In addition, the memory 82 can include a high-speed random access memory, and can also include a nonvolatile memory.

[0196] The embodiments of the present application further provide a computer readable storage medium, wherein the computer readable storage medium stores computer execution instructions, and the computer execution instructions are executed by a processor to implement the method in any of the embodiments. For example, the computer readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0197] In the exemplary embodiments, a computer program product is also provided, which includes a computer program, and the computer program is executed by a processor to implement the above method.

[0198] The embodiments of the present application further provide an alarm system, which includes the above water level detection method and water level detection device.

[0199] Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. The specification and examples given are exemplary only and the true scope and spirit of the application are indicated by the following claims. It will be appreciated by those skilled in the art that changes could be made to the application described and illustrated herein without departing from the essential scope of the application. It is intended that all such changes fall within the scope of the application. It is therefore intended that the true scope of the present application be determined by the following claims.

[0200] It should be understood that the application is not limited to the precise construction that has been described above and illustrated in the accompanying drawings, and that various modifications and changes can be made by those skilled in the art without departing from the scope of the application. The scope of the application should only be limited by the appended claims.

Claims

1. A water level detecting method characterized by comprising: Applied to a respiratory humidification device, the respiratory humidification device comprising a humidification tank, the method comprising: obtaining a float position image captured by a current camera; graying the float position image to obtain current gray image data; wherein the current gray image data is the gray value of each unit height of the humidification tank in the gray image corresponding to the float position image; generating a gray reference line and a gray image curve based on the current gray image data; wherein the gray image curve is a relationship curve of the current gray image data and the height value of the humidification tank; the gray reference line comprises a first sub-gray reference line, a second sub-gray reference line and a third sub-gray reference line; determining the height value of the float according to the relative position relationship between the gray reference line and the gray image curve; wherein, according to the relative position relationship between the gray reference line and the gray image curve, the height value of the float is determined, comprising: respectively taking the first sub-gray reference line, the second sub-gray reference line and the third sub-gray reference line as the segmented reference line, and segmenting the gray image curve to obtain the first segment number, the second segment number and the third segment number; wherein the segmenting comprises: under each segment reference, the gray image curve is divided by the segment reference line, and the segment number below the segment reference line is counted; determining the intersection of the first sub-gray reference line, the second sub-gray reference line and the third sub-gray reference line and the gray image curve respectively, and recording the height value of the humidification tank corresponding to each intersection point; determining the height value of the float from the height value of the humidification tank corresponding to each intersection point according to the first segment number, the second segment number and the third segment number.

2. The method of claim 1, wherein, Before the gray reference line and the gray image curve are generated based on the current gray image data, the method further comprises: determining the current gray image parameter according to the current gray image data, the current gray image parameter comprising the minimum value and the average value of the current gray image data; the gray reference line is generated based on the current gray image data, comprising: selecting the first threshold, the second threshold and the third threshold from the numerical interval corresponding to the minimum value and the average value of the current gray image data; respectively taking the first threshold, the second threshold and the third threshold as the segmented reference to generate the first sub-gray reference line, the second sub-gray reference line and the third sub-gray reference line.

3. The method of claim 1, wherein, the height value of the float is determined from the height value of the humidification tank corresponding to each intersection point according to the first segment number, the second segment number and the third segment number, comprising: If the first segment number, the second segment number and the third segment number are all 1, the height value of the wetting tank corresponding to the first intersection point of the gray image curve and the first sub-gray reference line is taken as the height value of the float; otherwise, the height value of the wetting tank corresponding to the first intersection point of the gray image curve and the second sub-gray reference line is taken as the height value of the float.

4. The method of claim 2, wherein, The first threshold value, the second threshold value and the third threshold value are obtained from a numerical interval corresponding to the minimum value and the average value of the current gray image data, including: The average value of the minimum value of the current gray image data and the average value of the current gray image data is calculated to obtain the first threshold value; The average value of the minimum value of the current gray image data and the first threshold value is calculated to obtain the second threshold value; The average value of the minimum value of the current gray image data and the second threshold value is calculated to obtain the third threshold value.

5. The method of claim 2, wherein, The current gray image parameters further include the maximum value of the current gray image data; before the gray reference line and the gray image curve are generated based on the current gray image data, the method further includes: It is judged whether the current gray image parameters are all located in a pre-set gray range; If the current gray image parameters are not all located in the pre-set gray range, the exposure time of the light supplement lamp is adjusted according to the current gray image parameters, and the step of obtaining the current camera shooting float position image is returned to execute; The gray reference line and the gray image curve are generated based on the current gray image data, specifically including: If the current gray image parameters are all located in the pre-set gray range, the gray reference line and the gray image curve are generated based on the current gray image data.

6. The method of claim 5, wherein, The exposure time of the light supplement lamp is adjusted according to the current gray image parameters, including: If the maximum value of the current gray image data is less than the lower limit value of the pre-set gray range, it is judged whether the current exposure time of the light supplement lamp reaches the upper limit value of the exposure time, if yes, the current exposure time of the light supplement lamp is maintained, otherwise, the exposure time of the light supplement lamp is increased; If the minimum value of the current gray image data is greater than the upper limit value of the pre-set gray range, the exposure time of the light supplement lamp is reduced.

7. The method according to any one of claims 1 to 6, characterized in that, After the height value of the float is determined according to the relative position relationship between the gray reference line and the gray image curve, the method further includes: The water level height value of the current wetting tank is determined according to the height value of the current float; wherein the height value of the float is the height value of the float relative to the bottom of the wetting tank; If the water level height value of the current wetting tank is less than the early warning height value, an alarm signal is output.

8. The method according to any one of claims 1 to 6, characterized in that, Before the height value of the float is determined according to the relative position relationship between the gray reference line and the gray image curve, the method further includes: The gray image curve is smoothed to obtain a smoothed gray image curve; The height value of the float is determined according to the relative position relationship between the gray reference line and the gray image curve, and specifically includes: The height value of the float is determined according to the relative position relationship between the gray reference line and the gray image curve.

9. A water level detecting device characterized by comprising: The device is applied to a respiratory humidification device, and the respiratory humidification device includes a humidification tank, and the humidification tank includes a float. The acquisition module is configured to acquire a float position image captured by a current camera; The processing module is configured to perform gray processing on the float position image to obtain current gray image data; wherein the current gray image data is a gray value of each unit height of the humidification tank in a gray image corresponding to the float position image; The generation module is configured to generate a gray reference line and a gray image curve based on the current gray image data; wherein the gray image curve is a relationship curve of the current gray image data and the height value of the humidification tank; and the gray reference line includes a first sub-gray reference line, a second sub-gray reference line, and a third sub-gray reference line. The determination module is configured to determine the height value of the float according to the relative position relationship between the gray reference line and the gray image curve; wherein the determination module is specifically configured to: perform segmented processing on the gray image curve by taking the first sub-gray reference line, the second sub-gray reference line, and the third sub-gray reference line as segmented reference lines to obtain a first segment number, a second segment number, and a third segment number; wherein the segmented processing includes: under each segmented reference line, the gray image curve is divided by the segmented reference line, and the segment number below the segmented reference line is counted; the intersection points of the first sub-gray reference line, the second sub-gray reference line, and the third sub-gray reference line and the gray image curve are determined, and the height value of the humidification tank corresponding to each intersection point is recorded; and the height value of the float is determined from the height value of the humidification tank corresponding to each intersection point according to the first segment number, the second segment number, and the third segment number.

10. An electronic device, comprising: It includes: A processor and a memory connected in communication with the processor; The memory stores computer execution instructions; The processor executes the computer execution instructions stored in the memory to implement the method of any one of claims 1-8.

11. A computer readable storage medium, characterized in that, The computer readable storage medium stores computer execution instructions, and the computer execution instructions are executed by the processor to implement the method of any one of claims 1-8.

12. An alarm system characterized by It includes: The water level detection method of any one of claims 1-8 and the water level detection device of claim 9.

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