CN111538112A - Precipitation type detection method, system, device, computer equipment and storage medium - Google Patents
Precipitation type detection method, system, device, computer equipment and storage medium Download PDFInfo
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- CN111538112A CN111538112A CN202010377358.1A CN202010377358A CN111538112A CN 111538112 A CN111538112 A CN 111538112A CN 202010377358 A CN202010377358 A CN 202010377358A CN 111538112 A CN111538112 A CN 111538112A
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Abstract
The application relates to a precipitation type detection method, a precipitation type detection system, a precipitation type detection device, a computer device and a storage medium. The method is applied to a precipitation type detection system, and the system comprises: infrared transceiver, light-tight baffle and treater. The method comprises the following steps: controlling the infrared transceiver to emit infrared rays to the light-tight baffle according to a preset time period, wherein at least two infrared rays are emitted each time; acquiring a current distance mean value corresponding to current weather based on infrared rays emitted by an infrared transceiver; the current distance average value is the average value of the average propagation distance of each infrared ray emitted in a preset time period under the current weather; and determining the precipitation type of the current weather according to the current distance mean value and a plurality of prestored reference distance mean values. By adopting the method, the whole detection period can be shortened, the time resolution is high, the realization difficulty of the precipitation type detection method is reduced, and the detection efficiency is improved.
Description
Technical Field
The application relates to the technical field of meteorological analysis, in particular to a precipitation type detection method, a precipitation type detection system, a precipitation type detection device, computer equipment and a storage medium.
Background
Precipitation is an important cause of natural disasters such as flood disasters, landslides, debris flows and the like. In the field of meteorological analysis, when rainfall measurement research is carried out, the types of rainfall, including rain, snow, hail and the like, need to be distinguished. Different precipitation types and different mechanisms are formed, and the method has important significance for the precipitation measurement research.
In the traditional technology, the identification of the precipitation type is mainly based on a method for analyzing weather radar sweep data and a method for polarization parameters of a dual-polarization Doppler radar. However, in the two methods, data acquisition depends on large-scale equipment, the whole identification method is complex in process, long in detection and identification period and low in time resolution.
Disclosure of Invention
In view of the above, there is a need to provide a precipitation type detection method, system, apparatus, computer device and storage medium.
A precipitation type detection method is applied to a precipitation type detection system, and the precipitation type detection system comprises: the device comprises an infrared transceiver, a light-tight baffle and a processor, wherein the infrared transceiver and the light-tight baffle are oppositely arranged at a preset distance, and the processor is connected with the infrared transceiver, and the method comprises the following steps:
controlling the infrared transceiver to emit infrared rays to the light-tight baffle according to a preset time period, wherein at least two infrared rays are emitted each time;
obtaining a current distance mean value corresponding to current weather based on the infrared rays emitted by the infrared transceiver; the current distance average value is an average value of average propagation distances of the infrared rays emitted each time within a preset time period;
and determining the precipitation type of the current weather according to the current distance mean value and a plurality of prestored reference distance mean values.
In one embodiment, before determining the precipitation type of the current weather according to the current distance mean value and a plurality of pre-stored reference distance mean values, the method further includes:
acquiring a plurality of reference distance mean values corresponding to different precipitation types under the weather of the different precipitation types based on the infrared rays emitted by the infrared transceiver; wherein the precipitation types include rain, snow, and hail.
In one embodiment, the obtaining a plurality of reference distance means corresponding to different types of precipitation based on the infrared rays emitted by the infrared transceiver in the weather of different types of precipitation includes:
respectively acquiring the weather of which the precipitation types are light rain, medium rain and heavy rain, and obtaining a corresponding light rain reference distance mean value, a medium rain reference distance mean value and a heavy rain reference distance mean value based on the infrared rays emitted by the infrared transceiver;
and acquiring corresponding small snow reference distance mean value, medium snow reference distance mean value and large snow reference distance mean value based on the infrared rays emitted by the infrared transceiver under the weather conditions that the precipitation types are small snow, medium snow and large snow respectively.
In one embodiment, the determining the precipitation type of the current weather according to the current distance average and a plurality of pre-stored reference distance averages includes:
obtaining a reference error percentage between the current distance mean and the reference distance mean corresponding to each precipitation type;
comparing the reference error percentage with a preset error percentage;
and taking the precipitation type corresponding to the reference error percentage smaller than a preset error percentage as the precipitation type of the current weather.
In one embodiment, the obtaining a reference distance average corresponding to the type of precipitation based on the infrared rays emitted by the infrared transceiver under different weather conditions of the type of precipitation includes:
acquiring the transceiving time difference of each time of infrared ray transceiving operation of the infrared transceiver in a preset time period under the weather corresponding to the precipitation type to obtain the reference transceiving time difference of a preset number; the operation of receiving and sending the infrared rays is the operation of sending the infrared rays once and receiving the return of the sent infrared rays;
and obtaining a reference distance mean value corresponding to each precipitation type according to each reference transceiving time difference and the propagation speed of the infrared ray in the air.
A typing detection system, the system comprising:
the device comprises an infrared transceiver, a light-tight baffle and a processor; the infrared transceiver and the light-tight baffle are oppositely arranged at a preset distance, the infrared transceiver is used for emitting infrared rays and receiving the reflected infrared rays, and the light-tight baffle is used for reflecting the infrared rays;
the processor is used for controlling the infrared transceiver to emit infrared rays to the light-tight baffle according to a preset time period, and at least two infrared rays are emitted each time; acquiring a current distance average value corresponding to current weather based on the infrared rays emitted by the infrared transceiver; the current distance average value is the average value of the average propagation distance of the infrared ray emitted each time in a preset time period under the current weather; and determining the precipitation type of the current weather according to the current distance mean value and a plurality of prestored reference distance mean values.
In one embodiment, the system further comprises:
the bottomless light-transmitting container is positioned between the infrared transceiver and the light-tight baffle, and the diameter of the bottomless light-transmitting container is equal to the preset distance;
the string bag, with bottomless printing opacity container's inner wall connection for accept by bottomless printing opacity container's top falls into hail in the bottomless printing opacity container, infrared transceiver's high position is located the string bag with between the top of bottomless printing opacity container.
A precipitation type detection device is applied to a precipitation type detection system, and the precipitation type detection system comprises: infrared transceiver, light-tight baffle and treater, infrared transceiver with light-tight baffle interval preset distance sets up relatively, the treater with infrared transceiver connects, the device includes:
the infrared control module is used for controlling the infrared transceiver to emit infrared rays to the light-tight baffle according to a preset time period, and at least two infrared rays are emitted each time;
the first acquisition module is used for acquiring a current distance average value corresponding to current weather based on the infrared rays emitted by the infrared transceiver; the current distance average value is the average value of the average propagation distance of the infrared ray emitted each time in a preset time period under the current weather;
and the weather classification module is used for determining the precipitation type of the current weather according to the current distance mean value and a plurality of pre-stored reference distance mean values.
A computer device for use in a precipitation type detection system, the precipitation type detection system comprising: the computer equipment comprises a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to realize the following steps:
controlling the infrared transceiver to emit infrared rays to the light-tight baffle according to a preset time period, wherein at least two infrared rays are emitted each time;
acquiring a current distance average value corresponding to current weather based on the infrared rays emitted by the infrared transceiver; the current distance average value is the average value of the average propagation distance of the infrared ray emitted each time in a preset time period under the current weather;
and determining the precipitation type of the current weather according to the current distance mean value and a plurality of prestored reference distance mean values.
A computer readable storage medium for use in a precipitation type detection system, the precipitation type detection system comprising: the infrared transceiver and the light-tight baffle are oppositely arranged at a preset distance, the processor is connected with the infrared transceiver, a computer program is stored on the computer readable storage medium, and when the computer program is executed by the processor, the following steps are realized:
controlling the infrared transceiver to emit infrared rays to the light-tight baffle according to a preset time period, wherein at least two infrared rays are emitted each time;
acquiring a current distance average value corresponding to current weather based on the infrared rays emitted by the infrared transceiver; the current distance average value is the average value of the average propagation distance of the infrared ray emitted each time in a preset time period under the current weather;
and determining the precipitation type of the current weather according to the current distance mean value and a plurality of prestored reference distance mean values.
The precipitation type detection method, the precipitation type detection system, the precipitation type detection device, the computer equipment and the storage medium are applied to the precipitation type detection system, and the precipitation type detection system comprises: infrared transceiver, light-tight baffle and treater. The method comprises the following steps: the processor controls the infrared transceiver to emit infrared rays to the light-tight baffle according to a preset time period, and at least two infrared rays are emitted each time; acquiring a current distance average value corresponding to the current weather based on the infrared rays emitted by the infrared transceiver; and determining the precipitation type of the current weather according to the current distance mean value and a plurality of prestored reference distance mean values. The method comprises the steps of obtaining a current distance mean value under current weather by utilizing an infrared ray ranging principle, matching the current distance mean value with reference distance mean values corresponding to different precipitation types to obtain the precipitation types of the current weather, wherein the whole method is based on the infrared ranging principle, the whole detection process period is short, the time resolution ratio is high, the method can be realized by the simple and small precipitation type detection system, the realization difficulty of the precipitation type detection method is reduced, and the detection efficiency is improved.
Drawings
FIG. 1 is a schematic diagram of an embodiment of a precipitation type detection system;
FIG. 2 is a schematic flow diagram of a precipitation type detection method according to an embodiment;
FIG. 3 is a schematic flow chart of a precipitation type detection method according to another embodiment;
FIG. 4 is a schematic flow chart illustrating a process for obtaining a plurality of reference distance means according to one embodiment;
FIG. 5 is a schematic flow diagram illustrating the determination of the type of precipitation for the current weather in one embodiment;
FIG. 6 is a schematic diagram of another embodiment of a precipitation type detection system;
FIG. 7 is a block diagram of an embodiment of a precipitation type detection device;
FIG. 8 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The precipitation type detection method provided by the application can be applied to a precipitation type detection system shown in fig. 1. Precipitation type detection system 100 includes: an infrared transceiver 101, an opaque baffle 102, and a processor 103. The infrared transceiver 101 and the opaque baffle 102 are oppositely arranged at a preset distance, and the processor 103 is connected with the infrared transceiver 101. When the precipitation type detection system 100 detects the precipitation type, the processor 103 controls the infrared transceiver 101 to emit infrared rays to the opaque baffle 102 according to a preset time period, and at least two infrared rays are emitted each time. The infrared rays hit rain, snow, hail or the opaque baffle 102 and then are reflected back to the infrared transceiver 101; the infrared transceiver 101 receives the reflected infrared radiation. The processor 103 obtains a current distance average value corresponding to the current weather based on the infrared rays emitted by the infrared transceiver, and determines the precipitation type of the current weather according to the current distance average value and a plurality of pre-stored reference distance average values; wherein the precipitation types include rain, snow, and hail.
Due to different degrees of transmission of infrared rays by rain, snow and hail, the emitted infrared rays are reflected back to different degrees. Wherein, the relation of the transmission degree of rain, snow and hail to infrared ray is as follows: rain > hail > snow, i.e. rain, less reflection, more transmission, snow, more reflection, less transmission, hail, reflection, transmission conditions are centered relative to rain and snow. The different degrees of transmission lead to different degrees of reflection, which differ to such an extent that the distance measured from the infrared radiation differs. Less reflection, more transmission, greater measured distance; more reflection and less transmission the measured distance is smaller. Consequently, usable rain of this application, snow, hail are different to infrared ray's transmission degree, and then under the meteorological weather of corresponding precipitation type, adopt the distance that infrared ranging surveyed to be different, realize the discernment of different precipitation types to distinguish three kinds of precipitation types of rain, snow, hail.
In one embodiment, as shown in fig. 2, a method for detecting a type of precipitation is provided, which is illustrated by applying the method to the precipitation type detection system in fig. 1, and includes the following steps:
s210, controlling the infrared transceiver to emit at least two infrared rays to the light-tight baffle according to a preset time period, wherein at least two infrared rays are emitted each time.
Specifically, the processor 103 controls the infrared transceiver 101 to continuously emit infrared rays to the opaque baffle 102 for a preset time period, for example, 30s, and at least two infrared rays are emitted each time.
And S220, acquiring the current distance average value corresponding to the current weather based on the infrared rays emitted by the infrared transceiver.
And the current distance average value is the average value of the average propagation distance of the infrared ray emitted every time in a preset time period under the current weather.
The infrared ray emitted from the infrared transceiver 101 toward the opaque baffle 102 encounters an obstacle such as dust, rain, snow, hail, or the opaque baffle 102The infrared ray is reflected by the obstacle, and the infrared transceiver 101 receives the reflected infrared ray. The propagation speed of light in vacuum can reach 3 x 108m/s, is reduced in the air, but the difference is not too large, so that, in practical applications, the infrared transceiver 101 has received all the infrared rays returned by the last emitted infrared ray when the next emitted infrared ray is emitted.
Specifically, the processor 103 obtains a time difference between each time of transmitting and receiving the infrared ray by the infrared transceiver 101 under the current weather, and obtains an average propagation distance of each time of transmitting the infrared ray according to the time difference and a propagation speed of the infrared ray. The processor 103 controls the infrared transceiver 101 to transmit the infrared rays for a preset number of times within a preset time period, and obtains the average propagation distances of the preset number which is the same as the preset number of times. In the preset time period, the processor 103 calculates an average value of the average propagation distances of the preset number, that is, a current distance average value of the current weather. For example, under the current weather, the processor 103 controls the infrared transceiver 101 to emit the infrared rays once every 30s, 5 pieces of the infrared rays are emitted each time, 5 propagation distances corresponding to the 5 pieces of the infrared rays are obtained by calculation according to a time difference between each emission and each reception of the infrared rays and a propagation speed of the infrared rays, an average propagation distance of the 5 propagation distances is obtained by calculation according to a speed distance formula, a preset number of 120 average propagation distances are obtained within 1 hour of a preset time period, and an average value of the 120 average propagation distances is calculated to be used as a current distance average value of the current weather.
And S230, determining the precipitation type of the current weather according to the current distance mean value and a plurality of pre-stored reference distance mean values.
Wherein each of the reference distance means corresponds to one of the precipitation types. The types of precipitation include rain, snow, and hail. The reference distance average value is an average value of average propagation distances of the infrared rays emitted each time in the preset time period under each precipitation type weather.
Specifically, the processor 103 matches the obtained current distance average value with a plurality of pre-stored reference distance average values. And if the current distance average value is equal to one of the reference distance average values, the matching is successful. The processor 103 uses the precipitation type corresponding to the reference distance mean value successfully matched with the current distance mean value as the precipitation type of the current weather. For example, the processor 103 matches the current distance average value with a plurality of pre-stored reference distance average values, and if the current distance average value is successfully matched with the reference distance average value corresponding to the precipitation type of snow, the precipitation type of the current weather is snow.
In this embodiment, the above precipitation type detection method is applied to a precipitation type detection system, and the precipitation type detection system includes: infrared transceiver, light-tight baffle and treater. When the rainfall type detection system detects the rainfall type, the processor controls the infrared transceiver to emit infrared rays to the light-tight baffle according to a preset time period; acquiring a current distance average value corresponding to the current weather based on the infrared rays emitted by the infrared transceiver; and determining the precipitation type of the current weather according to the current distance mean value and a plurality of pre-stored reference distance mean values, wherein each reference distance mean value corresponds to one precipitation type. The method comprises the steps of distinguishing and identifying different precipitation types by utilizing different influence degrees of the different precipitation types on infrared distance measurement, obtaining a current distance mean value under current weather by adopting an infrared ray distance measurement principle, and matching the current distance mean value with reference distance mean values corresponding to the different precipitation types to obtain the precipitation types of the current weather. The whole method is based on the infrared distance measurement principle, the whole detection process is short in period and high in time resolution, and can be realized through the simple and small precipitation type detection system, the realization difficulty of the precipitation type detection method is reduced, and the detection efficiency is improved.
In an embodiment, with reference to fig. 1, before the determining, at S230, a precipitation type of the current weather according to the current distance mean and a plurality of reference distance means, further includes:
and acquiring a plurality of reference distance mean values corresponding to different precipitation types based on the infrared rays emitted by the infrared transceiver under the weather conditions of the different precipitation types.
The rainfall type comprises rain, snow and hail, and the correspondingly obtained reference distance mean value comprises a rain reference distance mean value, a snow reference distance mean value and a hail reference distance mean value.
Further, the precipitation types further include light rain, medium rain, heavy rain, light snow, medium snow and university, and as shown in fig. 3, the obtaining of the plurality of reference distance averages corresponding to different precipitation types specifically includes the following steps:
and S310, respectively obtaining the corresponding small rain reference distance mean value, medium rain reference distance mean value and heavy rain reference distance mean value based on the infrared rays emitted by the infrared transceiver under the weather conditions that the types of the precipitation are small rain, medium rain and heavy rain.
And S320, respectively obtaining the weather of which the precipitation types are small snow, medium snow and large snow, and obtaining the corresponding small snow reference distance mean value, medium snow reference distance mean value and large snow reference distance mean value based on the infrared rays emitted by the infrared transceiver.
Specifically, the processor 103 obtains a plurality of reference distance averages in different weather conditions of known precipitation type in advance before determining the precipitation type of the current weather condition. The precipitation type may include: light rain, medium rain, heavy rain, light snow, medium snow, heavy snow, and hail. The plurality of reference distance means includes reference distance means of the precipitation type corresponding to the weather, which are obtained by the processor 103 under the weather with the precipitation type of light rain, medium rain, heavy rain, light snow, medium snow, heavy snow and hail, including light rain reference distance means, medium rain reference distance means, heavy rain reference distance means, light snow reference distance means, medium snow reference distance means, heavy snow reference distance means, and hail reference distance means.
In this embodiment, the processor obtains reference distance mean values in the meteorology of different precipitation types in advance, makes a reference standard for obtaining the precipitation type corresponding to the current meteorology through subsequent comparison with the current distance mean value, and further divides the precipitation type into light rain, medium rain, heavy rain, light snow, medium snow, heavy snow and hail, so that while the precipitation type detection diversity is improved, the reference distance mean value in the subdivided precipitation type is obtained, and therefore the detection precision of the precipitation type is improved when the precipitation type of the current meteorology is determined through subsequent comparison with the current distance mean value.
In one embodiment, as shown in fig. 4 in conjunction with fig. 1, the following method may be used to obtain a plurality of reference distance averages for different precipitation types under the weather conditions:
and S410, acquiring the transceiving time difference of the infrared transceiver in each time of transceiving infrared rays in a preset time period under the weather corresponding to the precipitation type, and acquiring the reference transceiving time difference of a preset number.
Wherein the operation of receiving and transmitting infrared rays is an operation of transmitting infrared rays once and receiving the return of the transmitted infrared rays.
Specifically, the processor 103 obtains an average value of the transceiving time differences of the infrared transceiver 101 during each operation of transceiving infrared rays within a preset time period under each weather of the precipitation type, so as to obtain a preset number of reference transceiving time differences. For example, the processor 103 controls the infrared transceiver 101 to emit 5 infrared rays each time, and the infrared transceiver 101 obtains 5 transceiving time differences corresponding to the 5 infrared rays reflected back, and calculates an average value of the 5 transceiving time differences as the reference transceiving time difference. And the preset time period and the preset number are the same as the current distance average value. For example, the processor 103 obtains the current distance average values of 120 in preset number at a preset time interval of 30s for a preset time period of 1 hour, and then the processor 103 also obtains the reference transceiving time differences of 120 in preset number at a preset time interval of 30s for a preset time period of 1 hour for the infrared transceiver 101 in each weather of the precipitation type.
And S420, obtaining a reference distance mean value corresponding to each precipitation type according to each reference transceiving time difference and the propagation speed of the infrared ray in the air.
Specifically, the processor 103 brings each reference transceiving time difference and the propagation speed of the infrared ray in the air into a speed-time formula of speed × time — distance, so as to obtain the average propagation distances of the preset number corresponding to each precipitation type. Taking the preset number of 120 as an example, the average propagation distance of 120 small rains corresponding to small rains, the average propagation distance of 120 medium rains corresponding to medium rains, the average propagation distance of 120 large rains corresponding to large rains, the average propagation distance of 120 small snows corresponding to small snows, the average propagation distance of 120 medium snows corresponding to medium snows, the average propagation distance of 120 large snows corresponding to large snows, and the average propagation distance of hail corresponding to hail are obtained. The processor 103 controls the infrared transceiver 101 to emit infrared red rays to the opaque baffle 102 every 30 seconds, and the execution program for obtaining each propagation distance is specifically as follows:
said processor 103 is adapted to determine said preset number (120) and said average propagation distance (d)1～d120) And acquiring the average value of the average propagation distances corresponding to each precipitation type, namely a reference distance average value M.
Wherein the reference distance mean M reference distance mean satisfies the following equation:
in this embodiment, the reflection degree that the treater is utilizing rain, snow, hail to lead to infrared ray's transmission degree is different, and it is also different that the distance that corresponding adoption infrared ranging obtained is just different to on the basis that comes different precipitation types, further according to the size degree of precipitation to infrared ray's reflection degree is different, and the distance that leads to infrared ranging to obtain is further different, comes with the precipitation type differentiation with different size degrees, with this detection to different precipitation types of realization to further improve and detect the precision, realize the detection to the different precipitation degrees of different precipitation types.
In one embodiment, as shown in fig. 5, the determining, at S230, a precipitation type of the current weather according to the current distance mean and a plurality of pre-stored reference distance means includes:
s510, obtaining a reference error percentage between the current distance mean value and the reference distance mean value corresponding to each precipitation weather.
And S520, comparing the reference error percentage with a preset error percentage. S530, acquiring the precipitation type corresponding to the reference error percentage smaller than a preset error percentage as the precipitation type of the current weather.
Specifically, the processor 103 compares a reference error percentage between the obtained current distance mean and the reference distance mean corresponding to each precipitation type with a preset error percentage, and takes the precipitation type corresponding to the reference error percentage smaller than the preset error percentage as the precipitation type of the current weather. For example, if the reference error percentage between the obtained current distance average and the reference distance average corresponding to the heavy snow is 3% and is less than the preset error percentage by 5%, the type of precipitation of the current weather is the heavy snow.
In this embodiment, the processor performs matching comparison between the current distance mean value and the reference distance mean value corresponding to each precipitation type based on a preset error percentage, and uses the precipitation type corresponding to the reference distance mean value within the preset error percentage range as the precipitation type of the current weather. Therefore, the success rate of the matching comparison is improved, and the effective detection of the whole system on the precipitation type of the current weather is improved.
It should be understood that although the various steps in the flow charts of fig. 2-5 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 2-5 may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed in turn or alternately with other steps or at least some of the other steps.
In one embodiment, as shown in fig. 1, there is provided a precipitation type detection system, the system comprising: an infrared transceiver 101, an opaque baffle 102, and a processor 103.
The infrared transceiver 101 and the opaque baffle 102 are oppositely disposed at a predetermined distance d. The infrared transceiver 101 is configured to emit infrared rays and receive the reflected infrared rays, and the opaque baffle 102 is configured to reflect the infrared rays.
The processor 103 is configured to control the infrared transceiver 101 to emit infrared rays to the light-tight baffle 102 according to a preset time period, where at least two infrared rays are emitted each time; acquiring a current distance average value corresponding to current weather based on the infrared rays emitted by the infrared transceiver; the current distance average value is the average value of the average propagation distance of the infrared ray emitted each time in a preset time period under the current weather; and determining the precipitation type of the current weather according to the current distance mean value and a plurality of prestored reference distance mean values.
Specifically, the specific process of detecting the type of precipitation by the precipitation type detection system is the above precipitation type detection method, and is not described herein again.
In this embodiment, the preset distance d is 10cm to 80cm, and the opaque baffle 102 is a black baffle. The processor 103 is an Arduino single chip microcomputer.
In one embodiment, as shown in fig. 6, the system further comprises:
a bottomless transparent container 104 located between the infrared transceiver 101 and the opaque baffle 102, wherein the diameter of the bottomless transparent container 104 is equal to the preset distance d.
The net bag 105 is connected with the inner wall of the bottomless transparent container 104, and the height position of the infrared transceiver 601 is located between the net bag 105 and the top of the bottomless transparent container 105.
The net bag 105 is used for receiving hail falling into the bottomless transparent container 104 from the top of the bottomless transparent container 104, so that the hail is prevented from being heavy and rapidly passing through the bottomless transparent container 104, and detection errors caused by infrared ray reflection are avoided, and the detection accuracy is improved.
In this embodiment, the bottomless transparent container 104 is a hollow cylinder made of polymethyl methacrylate, and the net bag 105 is a mesh-shaped woven fabric made of polyamide, and can be connected to the inner wall of the bottomless transparent container 104 through hot melting.
In one embodiment, as shown in fig. 7, there is provided a precipitation type detection apparatus for use in the precipitation type detection system of fig. 1, the apparatus comprising: infrared control module 710, first acquisition module 720 and precipitation classification module 730, wherein:
the infrared control module 710 is configured to control the infrared transceiver to emit infrared rays to the opaque baffle according to a preset time period, where at least two infrared rays are emitted each time;
the first obtaining module 720 is configured to obtain a current distance average corresponding to the current weather based on the infrared rays emitted by the infrared transceiver; the current distance average value is the average value of the average propagation distance of the infrared ray emitted each time in a preset time period under the current weather;
the precipitation classification module 730 is configured to determine the precipitation type of the current weather according to the current distance mean and a plurality of pre-stored reference distance means.
In one embodiment, the apparatus further comprises:
the second acquisition module is used for acquiring a plurality of reference distance mean values corresponding to different precipitation types based on the infrared rays emitted by the infrared transceiver under the meteorology of the different precipitation types; wherein the precipitation types include rain, snow, and hail.
In one embodiment, the second obtaining module is further configured to:
respectively acquiring the weather of which the precipitation types are light rain, medium rain and heavy rain, and obtaining a corresponding light rain reference distance mean value, a medium rain reference distance mean value and a heavy rain reference distance mean value based on the infrared rays emitted by the infrared transceiver;
and acquiring corresponding small snow reference distance mean value, medium snow reference distance mean value and large snow reference distance mean value based on the infrared rays emitted by the infrared transceiver under the weather conditions that the precipitation types are small snow, medium snow and large snow respectively.
In one embodiment, the precipitation classification module 730 includes:
an error obtaining unit, configured to obtain a reference error percentage between the current distance mean and the reference distance mean corresponding to each precipitation type;
the error comparison unit is used for comparing the reference error percentage with a preset error percentage;
and the type acquisition unit is used for taking the precipitation type corresponding to the reference error percentage smaller than a preset error percentage as the precipitation type of the current weather.
In one embodiment, the second obtaining module includes:
the time difference acquisition unit is used for acquiring the transceiving time difference of the infrared transceiver in each infrared ray transceiving operation within a preset time period under the weather corresponding to the precipitation type to obtain the reference transceiving time difference of the preset number; the operation of receiving and sending the infrared rays is the operation of sending the infrared rays once and receiving the return of the sent infrared rays;
and the distance acquisition unit is used for obtaining a reference distance average value corresponding to each precipitation type according to each reference transceiving time difference and the propagation speed of the infrared ray in the air.
For specific limitations of the precipitation type detection device, reference may be made to the above limitations of the precipitation type detection method, which are not described herein again. The modules in the precipitation type detection device can be wholly or partially realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as shown in fig. 8. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless communication can be realized through WIFI, an operator network, NFC (near field communication) or other technologies. The computer program is executed by a processor to implement a precipitation type detection method. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
Those skilled in the art will appreciate that the architecture shown in fig. 8 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, there is provided a computer device for use in a precipitation type detection system, the precipitation type detection system comprising: the computer equipment comprises a memory and a processor, wherein a computer program is stored in the memory, and the processor realizes the following steps when executing the computer program:
controlling the infrared transceiver to emit infrared rays to the light-tight baffle according to a preset time period, wherein at least two infrared rays are emitted each time;
acquiring a current distance average value corresponding to current weather based on the infrared rays emitted by the infrared transceiver; the current distance average value is the average value of the average propagation distance of the infrared ray emitted each time in a preset time period under the current weather;
and determining the precipitation type of the current weather according to the current distance mean value and a plurality of prestored reference distance mean values.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
acquiring a plurality of reference distance mean values corresponding to different precipitation types under the weather of the different precipitation types based on the infrared rays emitted by the infrared transceiver; wherein the precipitation types include rain, snow, and hail.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
respectively acquiring the weather of which the precipitation types are light rain, medium rain and heavy rain, and obtaining a corresponding light rain reference distance mean value, a medium rain reference distance mean value and a heavy rain reference distance mean value based on the infrared rays emitted by the infrared transceiver;
and acquiring corresponding small snow reference distance mean value, medium snow reference distance mean value and large snow reference distance mean value based on the infrared rays emitted by the infrared transceiver under the weather conditions that the precipitation types are small snow, medium snow and large snow respectively.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
obtaining a reference error percentage between the current distance mean and the reference distance mean corresponding to each precipitation type;
comparing the reference error percentage with a preset error percentage;
and taking the precipitation type corresponding to the reference error percentage smaller than a preset error percentage as the precipitation type of the current weather.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
acquiring the transceiving time difference of each time of infrared ray transceiving operation of the infrared transceiver in a preset time period under the weather corresponding to the precipitation type to obtain the reference transceiving time difference of a preset number; the operation of receiving and sending the infrared rays is the operation of sending the infrared rays once and receiving the return of the sent infrared rays;
obtaining a reference distance mean value corresponding to each precipitation type according to each reference transceiving time difference and the propagation speed of the infrared ray in the air;
and obtaining the reference distance mean value corresponding to each precipitation type based on the preset number and the reference distance mean value.
In one embodiment, there is provided a computer readable storage medium for use in a precipitation type detection system, the precipitation type detection system comprising: the infrared transceiver and the light-tight baffle are oppositely arranged at a preset distance, the processor is connected with the infrared transceiver, a computer program is stored on the computer readable storage medium, and when the computer program is executed by the processor, the following steps are realized:
controlling the infrared transceiver to emit infrared rays to the light-tight baffle according to a preset time period, wherein at least two infrared rays are emitted each time;
acquiring a current distance average value corresponding to current weather based on the infrared rays emitted by the infrared transceiver; the current distance average value is the average value of the average propagation distance of the infrared ray emitted each time in a preset time period under the current weather;
and determining the precipitation type of the current weather according to the current distance mean value and a plurality of prestored reference distance mean values.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring a plurality of reference distance mean values corresponding to different precipitation types under the weather of the different precipitation types based on the infrared rays emitted by the infrared transceiver; wherein the precipitation types include rain, snow, and hail.
In one embodiment, the computer program when executed by the processor further performs the steps of:
respectively acquiring the weather of which the precipitation types are light rain, medium rain and heavy rain, and obtaining a corresponding light rain reference distance mean value, a medium rain reference distance mean value and a heavy rain reference distance mean value based on the infrared rays emitted by the infrared transceiver;
and acquiring corresponding small snow reference distance mean value, medium snow reference distance mean value and large snow reference distance mean value based on the infrared rays emitted by the infrared transceiver under the weather conditions that the precipitation types are small snow, medium snow and large snow respectively.
In one embodiment, the computer program when executed by the processor further performs the steps of:
obtaining a reference error percentage between the current distance mean and the reference distance mean corresponding to each precipitation type;
comparing the reference error percentage with a preset error percentage;
and taking the precipitation type corresponding to the reference error percentage smaller than a preset error percentage as the precipitation type of the current weather.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring the transceiving time difference of each time of infrared ray transceiving operation of the infrared transceiver in a preset time period under the weather corresponding to the precipitation type to obtain the reference transceiving time difference of a preset number; the operation of receiving and sending the infrared rays is the operation of sending the infrared rays once and receiving the return of the sent infrared rays;
obtaining a reference distance mean value corresponding to each precipitation type according to each reference transceiving time difference and the propagation speed of the infrared ray in the air;
and obtaining the reference distance mean value corresponding to each precipitation type based on the preset number and the reference distance mean value.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database or other medium used in the embodiments provided herein can include at least one of non-volatile and volatile memory. Non-volatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical storage, or the like. Volatile Memory can include Random Access Memory (RAM) or external cache Memory. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A precipitation type detection method is applied to a precipitation type detection system, and the precipitation type detection system comprises: the device comprises an infrared transceiver, a light-tight baffle and a processor, wherein the infrared transceiver and the light-tight baffle are oppositely arranged at a preset distance, and the processor is connected with the infrared transceiver, and the method comprises the following steps:
controlling the infrared transceiver to emit infrared rays to the light-tight baffle according to a preset time period, wherein at least two infrared rays are emitted each time;
obtaining a current distance mean value corresponding to current weather based on the infrared rays emitted by the infrared transceiver; the current distance average value is the average value of the average propagation distance of the infrared ray emitted each time in a preset time period under the current weather;
and determining the precipitation type of the current weather according to the current distance mean value and a plurality of prestored reference distance mean values.
2. The method of claim 1, wherein before determining the precipitation type of the current weather from the current distance average and a pre-stored reference distance average, further comprising:
acquiring a plurality of reference distance mean values corresponding to different precipitation types based on infrared rays emitted by the infrared transceiver under the weather conditions of the different precipitation types; wherein the precipitation types include rain, snow, and hail.
3. The method of claim 2, wherein said obtaining a plurality of said reference distance means corresponding to different types of said precipitation based on infrared radiation emitted by said infrared transceiver under different weather conditions of said types of precipitation comprises:
respectively acquiring the weather of which the precipitation types are light rain, medium rain and heavy rain, and obtaining a corresponding light rain reference distance mean value, a medium rain reference distance mean value and a heavy rain reference distance mean value based on the infrared rays emitted by the infrared transceiver;
and acquiring corresponding small snow reference distance mean value, medium snow reference distance mean value and large snow reference distance mean value based on the infrared rays emitted by the infrared transceiver under the weather conditions that the precipitation types are small snow, medium snow and large snow respectively.
4. The method of claim 1, wherein said determining the type of precipitation of the current weather from the current distance mean and a plurality of pre-stored reference distance means comprises:
obtaining a reference error percentage between the current distance mean and the reference distance mean corresponding to each precipitation type;
comparing the reference error percentage with a preset error percentage;
and taking the precipitation type corresponding to the reference error percentage smaller than a preset error percentage as the precipitation type of the current weather.
5. The method of claim 2, wherein said obtaining a reference distance average for different types of precipitation based on infrared radiation emitted by said infrared transceiver under different weather conditions comprises:
acquiring the transceiving time difference of each time of infrared ray transceiving operation of the infrared transceiver in a preset time period under the weather corresponding to the precipitation type to obtain the reference transceiving time difference of a preset number; the operation of receiving and sending the infrared rays is the operation of sending the infrared rays once and receiving the return of the sent infrared rays;
and obtaining a reference distance mean value corresponding to each precipitation type according to each reference transceiving time difference and the propagation speed of the infrared ray in the air.
6. A precipitation type detection system, the system comprising:
the device comprises an infrared transceiver, a light-tight baffle and a processor; the infrared transceiver and the light-tight baffle are oppositely arranged at a preset distance, the infrared transceiver is used for emitting infrared rays and receiving the reflected infrared rays, and the light-tight baffle is used for reflecting the infrared rays;
the processor is used for controlling the infrared transceiver to emit infrared rays to the light-tight baffle according to a preset time period, and at least two infrared rays are emitted each time; acquiring a current distance average value corresponding to current weather based on the infrared rays emitted by the infrared transceiver; the current distance average value is the average value of the average propagation distance of the infrared ray emitted each time in a preset time period under the current weather; and determining the precipitation type of the current weather according to the current distance mean value and a plurality of prestored reference distance mean values.
7. The system of claim 6, further comprising:
the bottomless light-transmitting container is positioned between the infrared transceiver and the light-tight baffle, and the diameter of the bottomless light-transmitting container is equal to the preset distance;
the string bag, with bottomless printing opacity container's inner wall connection for accept by bottomless printing opacity container's top falls into hail in the bottomless printing opacity container, infrared transceiver's high position is located the string bag with between the top of bottomless printing opacity container.
8. A precipitation type detection device, characterized in that, be applied to precipitation type detecting system, precipitation type detecting system includes: infrared transceiver, light-tight baffle and treater, infrared transceiver with light-tight baffle interval preset distance sets up relatively, the treater with infrared transceiver connects, the device includes:
the infrared control module is used for controlling the infrared transceiver to emit infrared rays to the light-tight baffle according to a preset time period, and at least two infrared rays are emitted each time;
the first acquisition module is used for acquiring a current distance average value corresponding to current weather based on the infrared rays emitted by the infrared transceiver; the current distance average value is the average value of the average propagation distance of the infrared ray emitted each time in a preset time period under the current weather;
and the weather classification module is used for determining the precipitation type of the current weather according to the current distance mean value and a plurality of pre-stored reference distance mean values.
9. A computer device comprising a memory and a processor, the memory storing a computer program, wherein the processor implements the steps of the method of any one of claims 1 to 5 when executing the computer program.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 5.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111983729A (en) * | 2020-08-20 | 2020-11-24 | 上海眼控科技股份有限公司 | Weather phenomenon determination method, weather phenomenon determination device, computer equipment and medium |
| CN115356013A (en) * | 2022-08-15 | 2022-11-18 | 桂林师范高等专科学校 | Reflow soldering temperature curve abnormity detection method |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201392306Y (en) * | 2009-04-16 | 2010-01-27 | 北京华创风云科技有限责任公司 | Laser raindrop spectrum analyzing and measuring device |
| CN106405685A (en) * | 2016-08-26 | 2017-02-15 | 无锡信大气象传感网科技有限公司 | Rainfall induction sensor |
| JP2017219383A (en) * | 2016-06-06 | 2017-12-14 | パイオニア株式会社 | Distance measurement device and distance measurement method |
| CN109541616A (en) * | 2018-10-09 | 2019-03-29 | 天津大学 | BP neural network rain, snow, greasy weather gas pulse laser distance measurement method |
| CN110082842A (en) * | 2019-05-24 | 2019-08-02 | 北京敏视达雷达有限公司 | A kind of precipitation estimation method and device |
| TW202001292A (en) * | 2018-06-15 | 2020-01-01 | 國立高雄科技大學 | Internet of Things rainfall monitoring system and monitoring method thereof capable of monitoring rainfall through ultrasonic detection waves |
-
2020
- 2020-05-07 CN CN202010377358.1A patent/CN111538112A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201392306Y (en) * | 2009-04-16 | 2010-01-27 | 北京华创风云科技有限责任公司 | Laser raindrop spectrum analyzing and measuring device |
| JP2017219383A (en) * | 2016-06-06 | 2017-12-14 | パイオニア株式会社 | Distance measurement device and distance measurement method |
| CN106405685A (en) * | 2016-08-26 | 2017-02-15 | 无锡信大气象传感网科技有限公司 | Rainfall induction sensor |
| TW202001292A (en) * | 2018-06-15 | 2020-01-01 | 國立高雄科技大學 | Internet of Things rainfall monitoring system and monitoring method thereof capable of monitoring rainfall through ultrasonic detection waves |
| CN109541616A (en) * | 2018-10-09 | 2019-03-29 | 天津大学 | BP neural network rain, snow, greasy weather gas pulse laser distance measurement method |
| CN110082842A (en) * | 2019-05-24 | 2019-08-02 | 北京敏视达雷达有限公司 | A kind of precipitation estimation method and device |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111983729A (en) * | 2020-08-20 | 2020-11-24 | 上海眼控科技股份有限公司 | Weather phenomenon determination method, weather phenomenon determination device, computer equipment and medium |
| CN115356013A (en) * | 2022-08-15 | 2022-11-18 | 桂林师范高等专科学校 | Reflow soldering temperature curve abnormity detection method |
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