WO2023093087A1 - 基于图像识别的输煤量监测方法、装置、设备及存储介质 - Google Patents
基于图像识别的输煤量监测方法、装置、设备及存储介质 Download PDFInfo
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- G—PHYSICS
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
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Definitions
- the present application relates to the technical field of data monitoring, in particular to an image recognition-based coal delivery monitoring method, device, equipment and storage medium.
- the main purpose of this application is to provide an image recognition-based coal delivery monitoring method, device, equipment and storage medium, aiming to solve the technical problem that the coal delivery on the coal delivery belt cannot be accurately monitored in the prior art.
- the present application provides a method for monitoring coal delivery based on image recognition
- the method for monitoring coal delivery based on image recognition includes:
- the actual coal delivery volume is collected by an electronic belt scale, and the coal delivery volume is monitored according to the actual coal delivery volume and the current coal delivery volume.
- the step of collecting the current coal conveying image corresponding to the coal conveying belt, and performing image processing on the current coal conveying image, and obtaining the target coal conveying image includes:
- the region of interest is extracted from the processed current coal transportation image according to the pixel information to obtain a target coal transportation image.
- the step of demarcating the target coal conveying image according to the coal state calibration information in the historical coal conveying image, and obtaining the target image information includes:
- Target image information is determined according to the target width information and the target height information.
- the step of calibrating the target coal conveying image according to the coal block width information and the coal block height information, and obtaining target width information and target height information includes:
- the target coal conveying image is calibrated according to the angle information, the coal block width information and the coal block height information to obtain target width information and target height information.
- the step of determining target image information according to the target width information and the target height information includes:
- Target image information is determined according to the target coal block height information and the target coal block width information.
- the step of determining target image information according to the target width information and the target height information includes:
- Target image information is determined according to the target coal block width information and the target coal block height information.
- the step of collecting the actual coal delivery volume through an electronic belt scale, and monitoring the coal delivery volume according to the actual coal delivery volume and the current coal delivery volume includes:
- the actual coal delivery volume is collected through the electronic belt scale
- the coal delivery belt is controlled to stop running and an early warning is given.
- this application also proposes a coal delivery monitoring device based on image recognition, and the image recognition based coal delivery monitoring device includes:
- the image processing module is used to collect the current coal conveying image corresponding to the coal conveying belt, and perform image processing on the current coal conveying image to obtain the target coal conveying image;
- An information acquisition module configured to calibrate the target coal conveying image according to the coal state calibration information in the historical coal conveying image, to obtain target image information
- the coal delivery volume acquisition module is used to input the target image information into the preset coal delivery forecast model to obtain the current coal delivery volume;
- the coal delivery monitoring module is used to collect the actual coal delivery through the electronic belt scale, and monitor the coal delivery according to the actual coal delivery and the current coal delivery.
- the present application also proposes a coal delivery monitoring device based on image recognition, which includes: a memory, a processor, and a memory that is stored on the memory and can be
- the image recognition-based coal delivery monitoring program running on the processor is configured to implement the image recognition-based coal delivery monitoring method as described above.
- this application also proposes a storage medium, on which is stored a coal delivery monitoring program based on image recognition, and when the image recognition based coal delivery monitoring program is executed by a processor, the As mentioned above, the image recognition-based coal delivery monitoring method.
- This application collects the current coal conveying image corresponding to the coal conveying belt, and performs image processing on the current coal conveying image to obtain the target coal conveying image, and then calibrates the target coal conveying image according to the coal state calibration information in the historical coal conveying image , to obtain the target image information, and then input the target image information into the preset coal volume prediction model to obtain the current coal volume, and then collect the actual coal volume through the electronic belt scale, and according to the actual coal volume and the current coal volume Carry out coal delivery monitoring.
- This application calibrates the target coal conveying image according to the coal block state calibration information in the historical coal conveying image, obtains the target image information, and can obtain the target image information corresponding to the target coal conveying image according to the calibration result, and then input the target image information into the preset Assuming that in the coal delivery prediction model, the current coal delivery can be obtained, the current coal delivery can be obtained according to the current coal delivery images collected, and then the coal delivery on the coal delivery belt can be calculated according to the actual coal delivery and the current coal delivery. Accurate monitoring.
- Fig. 1 is the schematic structural diagram of the image recognition-based coal delivery monitoring equipment of the hardware operating environment involved in the embodiment scheme of the present application;
- Fig. 2 is the schematic flow chart of the first embodiment of the image recognition-based coal delivery monitoring method of the present application
- Fig. 3 is a schematic flow chart of the second embodiment of the image recognition-based coal delivery monitoring method of the present application.
- Fig. 4 is the schematic flow chart of the third embodiment of the image recognition-based coal delivery monitoring method of the present application.
- Fig. 5 is a structural block diagram of the first embodiment of the image recognition-based coal delivery monitoring device of the present application.
- Fig. 1 is a schematic structural diagram of the image recognition-based coal delivery monitoring equipment of the hardware operating environment involved in the embodiment of the present application.
- the coal delivery amount monitoring device based on image recognition may include: a processor 1001, such as a central processing unit (Central Processing Unit, CPU), communication bus 1002, user interface 1003, network interface 1004, memory 1005. Wherein, the communication bus 1002 is used to realize connection and communication between these components.
- the user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface.
- the network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a Wireless-Fidelity (Wi-Fi) interface).
- Wi-Fi Wireless-Fidelity
- Memory 1005 can be a high-speed random access memory (Random Access Memory, RAM), can also be a stable non-volatile memory (Non-Volatile Memory, NVM), such as disk storage.
- RAM Random Access Memory
- NVM Non-Volatile Memory
- the memory 1005 may also be a storage device independent of the aforementioned processor 1001 .
- Figure 1 does not constitute a limitation to the image recognition-based coal delivery monitoring equipment, and may include more or less components than those shown in the illustration, or combine certain components, or Different component arrangements.
- the memory 1005 as a storage medium may include an operating system, a network communication module, a user interface module, and an image recognition-based coal delivery monitoring program.
- the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with users;
- the processor 1001 and memory 1005 in the quantity monitoring equipment can be set in the coal quantity monitoring equipment based on image recognition, and the coal quantity monitoring equipment based on image recognition calls the image recognition-based coal quantity monitoring equipment stored in the memory 1005 through the processor 1001 Coal delivery monitoring program, and implement the coal delivery monitoring method based on image recognition provided by the embodiment of the present application.
- FIG. 2 is a schematic flowchart of a first embodiment of the image recognition-based coal delivery monitoring method of the present application.
- the image recognition-based coal delivery monitoring method includes the following steps:
- Step S10 collecting the current coal conveying image corresponding to the coal conveying belt, and performing image processing on the current coal conveying image to obtain the target coal conveying image;
- execution subject of this embodiment can be the above-mentioned image recognition-based coal delivery monitoring equipment with functions of image processing, network communication, and program operation, or other equipment that can realize the same or similar functions. There is no specific limitation on this example.
- the current coal conveying image refers to the image corresponding to the coal conveying belt collected at the current moment, and the current coal conveying image needs to include a complete coal conveying belt and coal blocks transported on the coal conveying belt.
- the image processing refers to processing the current coal conveying image to obtain an image containing only the coal conveying belt and the coal blocks transported on the coal conveying belt.
- the step S10 includes: collecting the current coal conveying image corresponding to the coal conveying belt, performing preprocessing on the current coal conveying image, and obtaining the processed coal conveying image The current coal transportation image; obtain the pixel information corresponding to all pixels in the processed current coal transportation image; extract the region of interest from the processed current coal transportation image according to the pixel information, and obtain the target coal transportation image.
- image preprocessing is required before image analysis (feature extraction, segmentation, matching and recognition, etc.).
- the main purpose of image preprocessing is to eliminate irrelevant information in the image, restore useful real information, enhance the detectability of relevant information, and simplify data to the greatest extent, thereby improving the reliability of feature extraction, image segmentation, matching and recognition.
- the image preprocessing can include denoising the current coal transportation image, which can reduce the noise of the current coal transportation image, and can also include other preprocessing operations on the current coal transportation image, which is not discussed in this embodiment. Make specific restrictions.
- a more accurate target coal transportation image can be obtained by preprocessing the current coal transportation image, and then extracting the region of interest from the processed current coal transportation image.
- the region of interest can be extracted according to the pixel information corresponding to all pixels in the processed current coal transportation image.
- the pixel information refers to the pixel coordinate values of all pixels, that is, the current position.
- the specific method of extracting the region of interest can be to pre-set the pixel range of the region of interest according to the actual situation, and then extract all the pixels in the pixel range in the current coal transportation image after processing, according to the extracted
- the target coal conveying image can be obtained by all the pixels reached.
- Step S20 Calibrate the target coal transportation image according to the coal state calibration information in the historical coal transportation image to obtain target image information
- the coal state calibration information refers to the proportion information corresponding to the coal state in the historical coal transportation image and the coal state in the actual situation, for example: the height of the coal block in the historical coal transportation image and the actual situation
- the ratio between the heights of the coal blocks, the ratio between the width of the coal blocks in the historical coal transportation image and the width of the coal blocks in the actual situation, and other calibration information can also be included, which is not specifically limited in this embodiment .
- calibration refers to labeling the corresponding relationship between the coal state in the target coal transportation image and the coal state in the actual situation
- target image information refers to the coal state information in the target coal transportation image. It can include coal block height information, width information, etc. in the target coal transportation image.
- Step S30 Input the target image information into the preset coal delivery prediction model to obtain the current coal delivery;
- the preset coal delivery forecast model refers to a pre-set model that can be used to predict the coal delivery.
- the image information of historical coal delivery images can be used as a preset sample for training.
- Step S40 collecting the actual coal delivery volume through the electronic belt scale, and monitoring the coal delivery volume according to the actual coal delivery volume and the current coal delivery volume.
- the step S40 includes: collecting the actual coal delivery volume through an electronic belt scale; when the difference between the actual coal delivery volume and the current coal delivery volume does not meet the preset condition, control The coal conveyor belt stops running and an early warning is given.
- the electronic belt scale refers to an automatic weighing instrument that continuously weighs the bulk materials on the coal conveyor belt without subdividing the quality or interrupting the movement of the coal conveyor belt.
- preset conditions are preset conditions, which can be set according to actual conditions, and are not specifically limited in this embodiment.
- the above preset conditions can be set to a range.
- the difference between the actual coal delivery volume and the current coal delivery volume exceeds the above range, it means that there is an error in the actual coal delivery volume or the current coal delivery volume.
- a Early warning notify the management personnel to test the electronic belt scale to detect whether the electronic belt scale is abnormal, so as to avoid overweight coal transport corresponding to the coal transport belt and damage the coal transport belt.
- the current coal conveying image corresponding to the coal conveying belt is collected, and image processing is performed on the current coal conveying image to obtain the target coal conveying image, and then the target coal conveying image is processed according to the coal state calibration information in the historical coal conveying image Calibrate to obtain the target image information, and then input the target image information into the preset coal delivery forecast model to obtain the current coal delivery volume, and then collect the actual coal delivery volume through the electronic belt scale, and based on the actual coal delivery volume and the current coal delivery volume The amount of coal transported is monitored.
- the target coal transportation image is calibrated according to the coal state calibration information in the historical coal transportation image to obtain the target image information, and the target image information corresponding to the target coal transportation image can be obtained according to the calibration result, and then the target image information is input into
- the current coal delivery can be obtained, and the current coal delivery can be obtained according to the current coal delivery image collected, and then the coal delivery on the coal delivery belt can be calculated according to the actual coal delivery and the current coal delivery for precise monitoring.
- FIG. 3 is a schematic flow chart of the second embodiment of the image recognition-based coal delivery monitoring method of the present application.
- the step S20 includes:
- Step S201 Obtain historical coal transportation images within a preset time period, and perform image processing on the historical coal transportation images to obtain processed historical coal transportation images;
- the preset time period is a preset time period, which can be set according to the actual situation, and the angle of the camera when acquiring the historical coal transportation image is the same as the camera angle when collecting the current coal transportation image.
- the image processing process in this embodiment is the same as the image processing process in the above-mentioned first embodiment.
- the coal conveying belt and the coal conveying belt on the coal conveying belt can be obtained.
- Step S202 Obtain the coal block width information and coal block height information in the processed historical coal transportation image
- coal block width information refers to the width of the coal block in the processed historical coal conveying image, that is, the width on the coal conveying belt
- coal block height information refers to the coal block in the processed historical coal conveying image.
- the height of the coal block that is, the height on the coal conveyor belt.
- an image can be taken above the coal conveyor belt and processed to obtain the width information of the coal block, and an image can be taken on the front of the coal conveyor belt and processed to obtain the height information of the coal block.
- Step S203 Calibrate the target coal delivery image according to the coal block width information and the coal block height information, and obtain target width information and target height information;
- the target width information refers to the coal block width information in the actual situation corresponding to the target coal transportation image
- the target height information refers to the coal block height information in the actual situation corresponding to the target coal transportation image
- Step S204 Determine target image information according to the target width information and the target height information.
- target image information may include target width information and target height information.
- the step S204 includes: classifying the target width information through preset width classification rules to obtain different categories of target width information; acquiring the different categories Target height information corresponding to each target width information in the target width information; Determine the target coal block height information according to the target height information; Obtain the target coal block width information corresponding to each target width information in the different types of target width information; Target image information is determined according to the target coal block height information and the target coal block width information.
- the preset width classification rules are pre-set rules for classification according to width, which can be set according to the width of the coal conveying belt, for example: the target width information is 1 cm ⁇ 2 cm as the first category, 2 cm to 3 cm is the second category, and other ranges can also be set, which is not specifically limited in this embodiment.
- target height information there is corresponding target height information, and for all target height information acquired in the same category, average value processing can be performed to obtain target coal block height information.
- the target coal block width information can be determined according to each target width information in different types of target width information, and specifically, average value processing can be performed on each target width information.
- the target image information can be determined according to the target coal block height information and the target coal block width information, and different types of target image information are also different.
- the step S204 includes: classifying the target height information by preset height classification rules to obtain different categories of target height information; acquiring the different categories The target width information corresponding to each target height information in the target height information; determine the target coal block width information according to the target width information; obtain the target coal block height information corresponding to each target height information in the different types of target height information; Target image information is determined according to the target coal block width information and the target coal block height information.
- the target width information is classified according to the preset width classification rules or the target height information is classified according to the preset height classification rules, and the target coal block width information and target coal block height information are obtained according to the classification results, so that accurate Target image information.
- the processed historical coal transportation images are obtained, and then the coal block width information in the processed historical coal transportation images is obtained and coal block height information, and then calibrate the target coal conveying image according to the coal block width information and coal block height information, obtain target width information and target height information, and then determine target image information according to target width information and target height information.
- the target coal conveying image is calibrated according to the coal block width information and the coal block height information, and the target width information and target height information are obtained, and then the target image information is determined according to the target width information and target height information.
- the coal block width information and coal block height information are used to calibrate the target coal transportation image, and the target width information and target height information are obtained according to the calibration results, so that the target image information can be more accurate.
- FIG. 4 is a schematic flowchart of a third embodiment of an image recognition-based coal delivery monitoring method of the present application.
- the step S203 includes:
- Step S2031 Obtain the actual width information and actual height information corresponding to the historical coal transportation image
- Step S2032 Obtain the shooting center point position information corresponding to the historical coal handling image, and determine the angle information of each area in the historical coal handling image according to the center point position information;
- the historical coal transportation image can be divided into regions according to the actual situation, the smaller the region, the more accurate it is, and then the angle information between each region and the shooting center point can be obtained, and different calibration methods can be set for different angle information.
- Step S2033 Calibrate the target coal conveying image according to the angle information, the coal block width information, and the coal block height information to obtain target width information and target height information.
- the proportion of the target coal conveying image set for different angle information and the actual scene should be different, so the target coal conveying image can be calibrated according to the angle information, coal block width information and coal block height information, Obtain target width information and target height information.
- the actual width information and the actual height information corresponding to the historical coal transportation image are obtained, and then the shooting center point position information corresponding to the historical coal transportation image is obtained, and the angle information of each area in the historical coal transportation image is determined according to the center point position information.
- the target coal transportation image is calibrated to obtain the target width information and target height information.
- the angle information of each region in the historical coal transportation image is determined according to the position information of the center point, and then the target coal transportation image is calibrated according to the angle information, coal block width information and coal block height information, which can be based on the position of the shooting center point.
- the target coal conveying image is calibrated, so that the target width information and target height information can be accurately obtained, so as to accurately monitor the coal conveying amount on the coal conveying belt.
- the embodiment of the present application also proposes a storage medium, on which is stored an image recognition-based coal delivery monitoring program, and when the image recognition-based coal delivery monitoring program is executed by a processor, the above-mentioned The coal delivery monitoring method based on image recognition described above.
- Fig. 5 is a structural block diagram of the first embodiment of the image recognition-based coal delivery monitoring device of the present application.
- the image recognition-based coal delivery monitoring device proposed in the embodiment of the present application includes:
- the image processing module 10 is used to collect the current coal conveying image corresponding to the coal conveying belt, and perform image processing on the current coal conveying image to obtain the target coal conveying image;
- the information acquisition module 20 is used to calibrate the target coal conveying image according to the coal state calibration information in the historical coal conveying image, and obtain the target image information;
- the coal delivery volume acquisition module 30 is used to input the target image information into the preset coal delivery forecast model to obtain the current coal delivery volume;
- the coal delivery monitoring module 40 is used to collect the actual coal delivery through the electronic belt scale, and monitor the coal delivery according to the actual coal delivery and the current coal delivery.
- the current coal conveying image corresponding to the coal conveying belt is collected, and image processing is performed on the current coal conveying image to obtain the target coal conveying image, and then the target coal conveying image is processed according to the coal state calibration information in the historical coal conveying image Calibrate to obtain the target image information, and then input the target image information into the preset coal delivery forecast model to obtain the current coal delivery volume, and then collect the actual coal delivery volume through the electronic belt scale, and based on the actual coal delivery volume and the current coal delivery volume The amount of coal transported is monitored.
- the target coal transportation image is calibrated according to the coal state calibration information in the historical coal transportation image to obtain the target image information, and the target image information corresponding to the target coal transportation image can be obtained according to the calibration result, and then the target image information is input into
- the current coal delivery can be obtained, and the current coal delivery can be obtained according to the current coal delivery image collected, and then the coal delivery on the coal delivery belt can be calculated according to the actual coal delivery and the current coal delivery for precise monitoring.
- the image processing module 10 is also used to collect the current coal conveying image corresponding to the coal conveying belt, perform preprocessing on the current coal conveying image, and obtain the processed current coal conveying image; obtain the The pixel information corresponding to all pixels in the processed current coal transportation image; extracting the region of interest from the processed current coal transportation image according to the pixel information to obtain a target coal transportation image.
- the information acquisition module 20 is also used to obtain historical coal transportation images within a preset time period, and perform image processing on the historical coal transportation images to obtain processed historical coal transportation images; obtain the processed The coal block width information and coal block height information in the last historical coal transport image; according to the coal block width information and the coal block height information, the target coal transport image is calibrated to obtain target width information and target height information ; Determine target image information according to the target width information and the target height information.
- the information acquisition module 20 is also used to obtain the actual width information and actual height information corresponding to the historical coal transportation image; obtain the photographing center point position information corresponding to the historical coal transportation image, according to the center point
- the position information determines the angle information of each area in the historical coal transportation image; according to the angle information, the coal block width information and the coal block height information, the target coal transportation image is calibrated to obtain the target width information and Target height information.
- the information acquisition module 20 is also used to classify the target width information by preset width classification rules to obtain different types of target width information; acquire each target width information in the different types of target width information Corresponding target height information; determine the target coal block height information according to the target height information; obtain the target coal block width information corresponding to each target width information in the different types of target width information; according to the target coal block height information and The target coal block width information determines the target image information.
- the information acquisition module 20 is also used to classify the target height information through preset height classification rules to obtain different types of target height information; to obtain each target height information in the different types of target height information Corresponding target width information; determine the target coal block width information according to the target width information; obtain the target coal block height information corresponding to each target height information in the different types of target height information; according to the target coal block width information and The target coal block height information determines the target image information.
- the coal delivery monitoring module 40 is also used to collect the actual coal delivery through the electronic belt scale; when the difference between the actual coal delivery and the current coal delivery does not meet the preset condition, control The coal conveyor belt stops running and an early warning is given.
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Abstract
本申请涉及数据监测技术领域，公开了一种基于图像识别的输煤量监测方法、装置、设备及存储介质。本申请通过采集输煤皮带对应的当前输煤图像，并对当前输煤图像进行图像处理，获得目标输煤图像，然后根据历史输煤图像中的煤块状态标定信息对目标输煤图像进行标定，获得目标图像信息，然后将目标图像信息输入至预设输煤量预测模型中，获得当前输煤量，再通过电子皮带秤采集实际输煤量，并根据实际输煤量和当前输煤量进行输煤量监测。
Description
本申请要求于2021年11月29日申请的、申请号为202111438870.3的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
本申请涉及数据监测技术领域，尤其涉及一种基于图像识别的输煤量监测方法、装置、设备及存储介质。
近年来，随着我国煤炭工业的飞速发展，煤炭的利用率越来越高。燃料是发电企业的主要生产原料，其成本占发电企业总成本的70％左右，燃料管理水平的高低直接影响发电企业燃料成本控制和经营效益。在遵循经济掺烧的原则的情况下，为了提高掺配效率、严格按照参配指令精确掺配各种煤种量，需要准确测量皮带当前输煤量。大部分的发电厂一般采用皮带秤来计量输煤量，但是当皮带秤出现异常状况时，这种测量方式可能会造成较大误差。
上述内容仅用于辅助理解本申请的技术方案，并不代表承认上述内容是现有技术。
本申请的主要目的在于提供了一种基于图像识别的输煤量监测方法、装置、设备及存储介质，旨在解决现有技术中无法精确监测输煤皮带上的输煤量的技术问题。
为实现上述目的，本申请提供了一种基于图像识别的输煤量监测方法，所述基于图像识别的输煤量监测方法包括：
采集输煤皮带对应的当前输煤图像，并对所述当前输煤图像进行图像处理，获得目标输煤图像；
根据历史输煤图像中的煤块状态标定信息对所述目标输煤图像进行标定，获得目标图像信息；
将所述目标图像信息输入至预设输煤量预测模型中，获得当前输煤量；
通过电子皮带秤采集实际输煤量，并根据所述实际输煤量和所述当前输煤量进行输煤量监测。
在一实施例中，所述采集输煤皮带对应的当前输煤图像，并对所述当前输煤图像进行图像处理，获得目标输煤图像的步骤包括：
采集输煤皮带对应的当前输煤图像，对所述当前输煤图像进行预处理，获得处理后的当前输煤图像；
获取所述处理后的当前输煤图像中的所有像素点对应的像素信息；
根据所述像素信息对所述处理后的当前输煤图像进行感兴趣区域提取，获得目标输煤图像。
在一实施例中，所述根据历史输煤图像中的煤块状态标定信息对所述目标输煤图像进行标定，获得目标图像信息的步骤包括：
获取预设时间段内的历史输煤图像，并对所述历史输煤图像进行图像处理，获得处理后的历史输煤图像；
获取所述处理后的历史输煤图像中的煤块宽度信息和煤块高度信息；
根据所述煤块宽度信息和所述煤块高度信息对所述目标输煤图像进行标定，获得目标宽度信息和目标高度信息；
根据所述目标宽度信息和所述目标高度信息确定目标图像信息。
在一实施例中，所述根据所述煤块宽度信息和所述煤块高度信息对所述目标输煤图像进行标定，获得目标宽度信息和目标高度信息的步骤包括：
获取所述历史输煤图像对应的实际宽度信息和实际高度信息；
获取所述历史输煤图像对应的拍摄中心点位置信息，根据所述中心点位置信息确定所述历史输煤图像中各个区域的角度信息；
根据所述角度信息、所述煤块宽度信息以及所述煤块高度信息对所述目标输煤图像进行标定，获得目标宽度信息和目标高度信息。
在一实施例中，所述根据所述目标宽度信息和所述目标高度信息确定目标图像信息的步骤包括：
通过预设宽度分类规则对所述目标宽度信息进行分类，获得不同类别的目标宽度信息；
获取所述不同类别的目标宽度信息中各目标宽度信息对应的目标高度信息；
根据所述目标高度信息确定目标煤块高度信息；
获取所述不同类别的目标宽度信息中各目标宽度信息对应的目标煤块宽度信息；
根据所述目标煤块高度信息和所述目标煤块宽度信息确定目标图像信息。
在一实施例中，所述根据所述目标宽度信息和所述目标高度信息确定目标图像信息的步骤包括：
通过预设高度分类规则对所述目标高度信息进行分类，获得不同类别的目标高度信息；
获取所述不同类别的目标高度信息中各目标高度信息对应的目标宽度信息；
根据所述目标宽度信息确定目标煤块宽度信息；
获取所述不同类别的目标高度信息中各目标高度信息对应的目标煤块高度信息；
根据所述目标煤块宽度信息和所述目标煤块高度信息确定目标图像信息。
在一实施例中，所述通过电子皮带秤采集实际输煤量，并根据所述实际输煤量和所述当前输煤量进行输煤量监测的步骤包括：
通过电子皮带秤采集实际输煤量；
在所述实际输煤量和所述当前输煤量的差值不满足预设条件时，控制所述输煤皮带停止运行，并进行预警。
此外，为实现上述目的，本申请还提出一种基于图像识别的输煤量监测装置，所述基于图像识别的输煤量监测装置包括：
图像处理模块，用于采集输煤皮带对应的当前输煤图像，并对所述当前输煤图像进行图像处理，获得目标输煤图像；
信息获取模块，用于根据历史输煤图像中的煤块状态标定信息对所述目标输煤图像进行标定，获得目标图像信息；
输煤量获取模块，用于将所述目标图像信息输入至预设输煤量预测模型中，获得当前输煤量；
输煤量监测模块，用于通过电子皮带秤采集实际输煤量，并根据所述实际输煤量和所述当前输煤量进行输煤量监测。
此外，为实现上述目的，本申请还提出一种基于图像识别的输煤量监测设备，所述基于图像识别的输煤量监测设备包括：存储器、处理器及存储在所述存储器上并可在所述处理器上运行的基于图像识别的输煤量监测程序，所述基于图像识别的输煤量监测程序配置为实现如上文所述的基于图像识别的输煤量监测方法。
此外，为实现上述目的，本申请还提出一种存储介质，所述存储介质上存储有基于图像识别的输煤量监测程序，所述基于图像识别的输煤量监测程序被处理器执行时实现如上文所述的基于图像识别的输煤量监测方法。
本申请通过采集输煤皮带对应的当前输煤图像，并对当前输煤图像进行图像处理，获得目标输煤图像，然后根据历史输煤图像中的煤块状态标定信息对目标输煤图像进行标定，获得目标图像信息，然后将目标图像信息输入至预设输煤量预测模型中，获得当前输煤量，再通过电子皮带秤采集实际输煤量，并根据实际输煤量和当前输煤量进行输煤量监测。本申请根据历史输煤图像中的煤块状态标定信息对目标输煤图像进行标定，获得目标图像信息，能够根据标定结果得到目标输煤图像对应的目标图像信息，然后将目标图像信息输入至预设输煤量预测模型中，获得当前输煤量，能够根据采集到的当前输煤图像得到当前输煤量，再根据实际输煤量和当前输煤量对输煤皮带上的输煤量进行精确监测。
图1是本申请实施例方案涉及的硬件运行环境的基于图像识别的输煤量监测设备的结构示意图；
图2为本申请基于图像识别的输煤量监测方法第一实施例的流程示意图；
图3为本申请基于图像识别的输煤量监测方法第二实施例的流程示意图；
图4为本申请基于图像识别的输煤量监测方法第三实施例的流程示意图；
图5为本申请基于图像识别的输煤量监测装置第一实施例的结构框图。
本申请目的的实现、功能特点及优点将结合实施例，参照附图做进一步说明。
应当理解，此处所描述的具体实施例仅用以解释本申请，并不用于限定本申请。
参照图1，图1为本申请实施例方案涉及的硬件运行环境的基于图像识别的输煤量监测设备结构示意图。
如图1所示，该基于图像识别的输煤量监测设备可以包括：处理器1001，例如中央处理器（Central
Processing Unit，CPU），通信总线1002、用户接口1003，网络接口1004，存储器1005。其中，通信总线1002用于实现这些组件之间的连接通信。用户接口1003可以包括显示屏（Display）、输入单元比如键盘（Keyboard），可选用户接口1003还可以包括标准的有线接口、无线接口。网络接口1004可选的可以包括标准的有线接口、无线接口（如无线保真（Wireless-Fidelity，Wi-Fi）接口）。存储器1005可以是高速的随机存取存储器（Random
Access Memory，RAM），也可以是稳定的非易失性存储器（Non-Volatile
Memory，NVM），例如磁盘存储器。存储器1005可选的还可以是独立于前述处理器1001的存储装置。
本领域技术人员可以理解，图1中示出的结构并不构成对基于图像识别的输煤量监测设备的限定，可以包括比图示更多或更少的部件，或者组合某些部件，或者不同的部件布置。
如图1所示，作为一种存储介质的存储器1005中可以包括操作系统、网络通信模块、用户接口模块以及基于图像识别的输煤量监测程序。
在图1所示的基于图像识别的输煤量监测设备中，网络接口1004主要用于与网络服务器进行数据通信；用户接口1003主要用于与用户进行数据交互；本申请基于图像识别的输煤量监测设备中的处理器1001、存储器1005可以设置在基于图像识别的输煤量监测设备中，所述基于图像识别的输煤量监测设备通过处理器1001调用存储器1005中存储的基于图像识别的输煤量监测程序，并执行本申请实施例提供的基于图像识别的输煤量监测方法。
本申请实施例提供了一种基于图像识别的输煤量监测方法，参照图2，图2为本申请基于图像识别的输煤量监测方法第一实施例的流程示意图。
本实施例中，所述基于图像识别的输煤量监测方法包括以下步骤：
步骤S10：采集输煤皮带对应的当前输煤图像，并对所述当前输煤图像进行图像处理，获得目标输煤图像；
需要说明的是，本实施例的执行主体可以是上述具有图像处理、网络通信以及程序运行功能的基于图像识别的输煤量监测设备，也可以是能够实现相同或相似功能的其他设备，本实施例对此不做具体限制。
可理解的是，当前输煤图像是指在当前时刻采集到的输煤皮带对应的图像，该当前输煤图像需要包含完整的输煤皮带和输煤皮带上运输的煤块。
应理解的是，图像处理是指对当前输煤图像进行处理，获得仅包含输煤皮带和输煤皮带上运输的煤块的图像。
进一步地，为了获得准确的目标输煤图像，在本实施例中，所述步骤S10包括：采集输煤皮带对应的当前输煤图像，对所述当前输煤图像进行预处理，获得处理后的当前输煤图像；获取所述处理后的当前输煤图像中的所有像素点对应的像素信息；根据所述像素信息对所述处理后的当前输煤图像进行感兴趣区域提取，获得目标输煤图像。
需要说明的是，在图像分析中，图像质量的好坏直接影响识别算法的设计与效果的精度，因此在图像分析（特征提取、分割、匹配和识别等）前，需要进行预处理。图像预处理的主要目的是消除图像中无关的信息，恢复有用的真实信息，增强有关信息的可检测性、最大限度地简化数据，从而改进特征提取、图像分割、匹配和识别的可靠性。在本实施例中，图像预处理可包括对当前输煤图像进行去噪，可减少当前输煤图像的噪声，还可包括其他对当前输煤图像进行预处理的操作，本实施例对此不做具体限制。
本实施例通过对当前输煤图像进行预处理，然后对处理后的当前输煤图像进行感兴趣区域提取，能够得到较为精准的目标输煤图像。
在具体实现中，可根据处理后的当前输煤图像中的所有像素点对应的像素信息进行感兴趣区域提取，像素信息是指所有像素点的像素坐标值，也就是像素点在处理后的当前输煤图像中的位置，具体感兴趣区域提取的方法可以是根据实际情况预先设置感兴趣区域的像素范围，然后提取处理后的当前输煤图像中处于该像素范围内的所有像素点，根据提取到的所有像素点即可获得目标输煤图像。
步骤S20：根据历史输煤图像中的煤块状态标定信息对所述目标输煤图像进行标定，获得目标图像信息；
需要说明的是，煤块状态标定信息是指历史输煤图像中的煤块状态与实际情况中的煤块状态对应的比例信息，例如：历史输煤图像中的煤块的高度与实际情况中的煤块的高度之间的比例、历史输煤图像中的煤块的宽度与实际情况中的煤块的宽度之间的比例，还可包括其他标定信息，本实施例对此不做具体限制。
可理解的是，标定是指对目标输煤图像中的煤块状态与实际情况中的煤块状态之间的对应关系进行标注，目标图像信息是指目标输煤图像中的煤块状态信息，可包括目标输煤图像中的煤块高度信息、宽度信息等。
步骤S30：将所述目标图像信息输入至预设输煤量预测模型中，获得当前输煤量；
需要说明的是，预设输煤量预测模型是指预先设置的可用于预测输煤量的模型，具体可将历史输煤图像的图像信息作为预设样本进行训练得到。
步骤S40：通过电子皮带秤采集实际输煤量，并根据所述实际输煤量和所述当前输煤量进行输煤量监测。
进一步地，在本实施例中，所述步骤S40包括：通过电子皮带秤采集实际输煤量；在所述实际输煤量和所述当前输煤量的差值不满足预设条件时，控制所述输煤皮带停止运行，并进行预警。
需要说明的是，电子皮带秤是指无需对质量细分或者中断输煤皮带的运动，而对输煤皮带上的散装物料进行连续称量的自动衡器，通过电子皮带秤可采集当前时刻的输煤皮带对应的实际输煤量。
可理解的是，预设条件为预先设置的条件，具体可根据实际情况自行设置，本实施例对此不做具体限制。
在具体实现中，上述预设条件可设置为一个范围，在实际输煤量和当前输煤量的差值超出上述范围时，说明实际输煤量或者当前输煤量存在误差，此时需要发出预警，通知管理人员对电子皮带秤进行检测，检测电子皮带秤是否异常，避免在输煤皮带对应的输煤量超重，损坏输煤皮带。
本实施例通过采集输煤皮带对应的当前输煤图像，并对当前输煤图像进行图像处理，获得目标输煤图像，然后根据历史输煤图像中的煤块状态标定信息对目标输煤图像进行标定，获得目标图像信息，然后将目标图像信息输入至预设输煤量预测模型中，获得当前输煤量，再通过电子皮带秤采集实际输煤量，并根据实际输煤量和当前输煤量进行输煤量监测。本实施例根据历史输煤图像中的煤块状态标定信息对目标输煤图像进行标定，获得目标图像信息，能够根据标定结果得到目标输煤图像对应的目标图像信息，然后将目标图像信息输入至预设输煤量预测模型中，获得当前输煤量，能够根据采集到的当前输煤图像得到当前输煤量，再根据实际输煤量和当前输煤量对输煤皮带上的输煤量进行精确监测。
参考图3，图3为本申请基于图像识别的输煤量监测方法第二实施例的流程示意图。
基于上述第一实施例，在本实施例中，所述步骤S20包括：
步骤S201：获取预设时间段内的历史输煤图像，并对所述历史输煤图像进行图像处理，获得处理后的历史输煤图像；
需要说明的是，预设时间段为预先设置的时间段，具体可根据实际情况自行设置，并且获取历史输煤图像时摄像头的角度与采集当前输煤图像时的摄像头角度相同。
应理解的是，本实施例中的图像处理过程与上述第一实施例中的图像处理过程相同，在对历史输煤图像进行图像处理后，可以得到包含输煤皮带和输煤皮带上的煤块的图像，即处理后的历史输煤图像。
步骤S202：获取所述处理后的历史输煤图像中的煤块宽度信息和煤块高度信息；
需要说明的是，煤块宽度信息是指处理后的历史输煤图像中的煤块的宽度，也就是在输煤皮带上的宽度，煤块高度信息是指处理后的历史输煤图像中的煤块的高度，也就是在输煤皮带上的高度。
在具体实现中，可在输煤皮带上方拍摄图像并进行图像处理，获得煤块宽度信息，在输煤皮带正面拍摄图像并进行图像处理，获得煤块高度信息。
步骤S203：根据所述煤块宽度信息和所述煤块高度信息对所述目标输煤图像进行标定，获得目标宽度信息和目标高度信息；
需要说明的是，目标宽度信息是指目标输煤图像对应的实际情况中的煤块宽度信息，目标高度信息是指目标输煤图像对应的实际情况中的煤块高度信息。
步骤S204：根据所述目标宽度信息和所述目标高度信息确定目标图像信息。
应理解的是，目标图像信息可包括目标宽度信息和目标高度信息。
进一步地，为了精确确定目标图像信息，在本实施例中，所述步骤S204包括：通过预设宽度分类规则对所述目标宽度信息进行分类，获得不同类别的目标宽度信息；获取所述不同类别的目标宽度信息中各目标宽度信息对应的目标高度信息；根据所述目标高度信息确定目标煤块高度信息；获取所述不同类别的目标宽度信息中各目标宽度信息对应的目标煤块宽度信息；根据所述目标煤块高度信息和所述目标煤块宽度信息确定目标图像信息。
需要说明的是，预设宽度分类规则为预先设置的根据宽度进行分类的规则，可根据输煤皮带的宽度进行设置，例如：目标宽度信息为1厘米~2厘米为第一类别，目标宽度信息为2厘米~3厘米为第二类别，还可设置为其他的范围，本实施例对此不做具体限制。
可理解的是，对于每一个目标宽度信息，都存在对应的目标高度信息，对于同一类别获取到的所有目标高度信息，可以进行平均值处理，获得目标煤块高度信息。
在具体实现中，目标煤块宽度信息可以根据不同类别的目标宽度信息中各目标宽度信息进行确定，具体可对各目标宽度信息进行平均值处理。目标图像信息可根据目标煤块高度信息和目标煤块宽度信息进行确定，不同类别的目标图像信息也不相同。
同理，为了精确确定目标图像信息，在本实施例中，所述步骤S204包括：通过预设高度分类规则对所述目标高度信息进行分类，获得不同类别的目标高度信息；获取所述不同类别的目标高度信息中各目标高度信息对应的目标宽度信息；根据所述目标宽度信息确定目标煤块宽度信息；获取所述不同类别的目标高度信息中各目标高度信息对应的目标煤块高度信息；根据所述目标煤块宽度信息和所述目标煤块高度信息确定目标图像信息。
可理解的是，本实施例中确定目标图像信息的方法与上述方法一致，本实施例对此不过多赘述。
本实施例根据预设宽度分类规则对目标宽度信息进行分类或者根据预设高度分类规则对目标高度信息进行分类，根据分类结果得到目标煤块宽度信息和目标煤块高度信息，从而能够获得精确的目标图像信息。
本实施例通过获取预设时间段内的历史输煤图像，并对历史输煤图像进行图像处理，获得处理后的历史输煤图像，然后获取处理后的历史输煤图像中的煤块宽度信息和煤块高度信息，然后根据煤块宽度信息和煤块高度信息对目标输煤图像进行标定，获得目标宽度信息和目标高度信息，再根据目标宽度信息和目标高度信息确定目标图像信息。本实施例根据煤块宽度信息和煤块高度信息对目标输煤图像进行标定，获得目标宽度信息和目标高度信息，再根据目标宽度信息和目标高度信息确定目标图像信息，能够根据历史输煤图像的煤块宽度信息和煤块高度信息对目标输煤图像进行标定，根据标定结果得到目标宽度信息和目标高度信息，从而能够使目标图像信息更加精确。
参考图4，图4为本申请基于图像识别的输煤量监测方法第三实施例的流程示意图。
基于上述各实施例，在本实施例中，所述步骤S203包括：
步骤S2031：获取所述历史输煤图像对应的实际宽度信息和实际高度信息；
步骤S2032：获取所述历史输煤图像对应的拍摄中心点位置信息，根据所述中心点位置信息确定所述历史输煤图像中各个区域的角度信息；
可理解的是，对于获取到的历史输煤图像，存在拍摄中心点，距离拍摄中心点越远，拍摄出来的图片上的煤块看起来越小，但是实际情况中煤块的大小是不变的。
在具体实现中，可根据实际情况对历史输煤图像划分区域，区域越小越精确，然后获取各个区域与拍摄中心点之间的角度信息，对于不同的角度信息可设置不同标定方法。
步骤S2033：根据所述角度信息、所述煤块宽度信息以及所述煤块高度信息对所述目标输煤图像进行标定，获得目标宽度信息和目标高度信息。
应理解的是，对于不同的角度信息设置的目标输煤图像与实际场景中的比例应该也不相同，因此可根据角度信息、煤块宽度信息以及煤块高度信息对目标输煤图像进行标定，获得目标宽度信息和目标高度信息。
本实施例通过获取历史输煤图像对应的实际宽度信息和实际高度信息，然后获取历史输煤图像对应的拍摄中心点位置信息，根据中心点位置信息确定历史输煤图像中各个区域的角度信息，再根据角度信息、煤块宽度信息以及煤块高度信息对目标输煤图像进行标定，获得目标宽度信息和目标高度信息。本实施例根据中心点位置信息确定历史输煤图像中各个区域的角度信息，再根据角度信息、煤块宽度信息以及煤块高度信息对目标输煤图像进行标定，能够根据拍摄中心点的位置对目标输煤图像进行标定，从而能够精确获得目标宽度信息和目标高度信息，以对输煤皮带上的输煤量进行精确监测。
此外，本申请实施例还提出一种存储介质，所述存储介质上存储有基于图像识别的输煤量监测程序，所述基于图像识别的输煤量监测程序被处理器执行时实现如上文所述的基于图像识别的输煤量监测方法。
参照图5，图5为本申请基于图像识别的输煤量监测装置第一实施例的结构框图。
如图5所示，本申请实施例提出的基于图像识别的输煤量监测装置包括：
图像处理模块10，用于采集输煤皮带对应的当前输煤图像，并对所述当前输煤图像进行图像处理，获得目标输煤图像；
信息获取模块20，用于根据历史输煤图像中的煤块状态标定信息对所述目标输煤图像进行标定，获得目标图像信息；
输煤量获取模块30，用于将所述目标图像信息输入至预设输煤量预测模型中，获得当前输煤量；
输煤量监测模块40，用于通过电子皮带秤采集实际输煤量，并根据所述实际输煤量和所述当前输煤量进行输煤量监测。
本实施例通过采集输煤皮带对应的当前输煤图像，并对当前输煤图像进行图像处理，获得目标输煤图像，然后根据历史输煤图像中的煤块状态标定信息对目标输煤图像进行标定，获得目标图像信息，然后将目标图像信息输入至预设输煤量预测模型中，获得当前输煤量，再通过电子皮带秤采集实际输煤量，并根据实际输煤量和当前输煤量进行输煤量监测。本实施例根据历史输煤图像中的煤块状态标定信息对目标输煤图像进行标定，获得目标图像信息，能够根据标定结果得到目标输煤图像对应的目标图像信息，然后将目标图像信息输入至预设输煤量预测模型中，获得当前输煤量，能够根据采集到的当前输煤图像得到当前输煤量，再根据实际输煤量和当前输煤量对输煤皮带上的输煤量进行精确监测。
基于本申请上述基于图像识别的输煤量监测装置第一实施例，提出本申请基于图像识别的输煤量监测装置的第二实施例。
在本实施例中，所述图像处理模块10，还用于采集输煤皮带对应的当前输煤图像，对所述当前输煤图像进行预处理，获得处理后的当前输煤图像；获取所述处理后的当前输煤图像中的所有像素点对应的像素信息；根据所述像素信息对所述处理后的当前输煤图像进行感兴趣区域提取，获得目标输煤图像。
进一步地，所述信息获取模块20，还用于获取预设时间段内的历史输煤图像，并对所述历史输煤图像进行图像处理，获得处理后的历史输煤图像；获取所述处理后的历史输煤图像中的煤块宽度信息和煤块高度信息；根据所述煤块宽度信息和所述煤块高度信息对所述目标输煤图像进行标定，获得目标宽度信息和目标高度信息；根据所述目标宽度信息和所述目标高度信息确定目标图像信息。
进一步地，所述信息获取模块20，还用于获取所述历史输煤图像对应的实际宽度信息和实际高度信息；获取所述历史输煤图像对应的拍摄中心点位置信息，根据所述中心点位置信息确定所述历史输煤图像中各个区域的角度信息；根据所述角度信息、所述煤块宽度信息以及所述煤块高度信息对所述目标输煤图像进行标定，获得目标宽度信息和目标高度信息。
进一步地，所述信息获取模块20，还用于通过预设宽度分类规则对所述目标宽度信息进行分类，获得不同类别的目标宽度信息；获取所述不同类别的目标宽度信息中各目标宽度信息对应的目标高度信息；根据所述目标高度信息确定目标煤块高度信息；获取所述不同类别的目标宽度信息中各目标宽度信息对应的目标煤块宽度信息；根据所述目标煤块高度信息和所述目标煤块宽度信息确定目标图像信息。
进一步地，所述信息获取模块20，还用于通过预设高度分类规则对所述目标高度信息进行分类，获得不同类别的目标高度信息；获取所述不同类别的目标高度信息中各目标高度信息对应的目标宽度信息；根据所述目标宽度信息确定目标煤块宽度信息；获取所述不同类别的目标高度信息中各目标高度信息对应的目标煤块高度信息；根据所述目标煤块宽度信息和所述目标煤块高度信息确定目标图像信息。
进一步地，所述输煤量监测模块40，还用于通过电子皮带秤采集实际输煤量；在所述实际输煤量和所述当前输煤量的差值不满足预设条件时，控制所述输煤皮带停止运行，并进行预警。
本申请基于图像识别的输煤量监测装置的其他实施例或具体实现方式可参照上述各方法实施例，此处不再赘述。
需要说明的是，在本文中，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、物品或者系统不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者系统所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括该要素的过程、方法、物品或者系统中还存在另外的相同要素。
上述本申请实施例序号仅仅为了描述，不代表实施例的优劣。
通过以上的实施方式的描述，本领域的技术人员可以清楚地了解到上述实施例方法可借助软件加必需的通用硬件平台的方式来实现，当然也可以通过硬件，但很多情况下前者是更佳的实施方式。基于这样的理解，本申请的技术方案本质上或者说对现有技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质（如只读存储器/随机存取存储器、磁碟、光盘）中，包括若干指令用以使得一台终端设备(可以是手机，计算机，服务器，或者网络设备等)执行本申请各个实施例所述的方法。
以上仅为本申请的优选实施例，并非因此限制本申请的专利范围，凡是利用本申请说明书及附图内容所作的等效结构或等效流程变换，或直接或间接运用在其他相关的技术领域，均同理包括在本申请的专利保护范围内。
Claims (10)
- 一种基于图像识别的输煤量监测方法，其中，所述基于图像识别的输煤量监测方法包括：采集输煤皮带对应的当前输煤图像，并对所述当前输煤图像进行图像处理，获得目标输煤图像；根据历史输煤图像中的煤块状态标定信息对所述目标输煤图像进行标定，获得目标图像信息；将所述目标图像信息输入至预设输煤量预测模型中，获得当前输煤量；以及通过电子皮带秤采集实际输煤量，并根据所述实际输煤量和所述当前输煤量进行输煤量监测。
- 如权利要求1所述的基于图像识别的输煤量监测方法，其中，所述采集输煤皮带对应的当前输煤图像，并对所述当前输煤图像进行图像处理，获得目标输煤图像的步骤包括：采集输煤皮带对应的当前输煤图像，对所述当前输煤图像进行预处理，获得处理后的当前输煤图像；获取所述处理后的当前输煤图像中的所有像素点对应的像素信息；以及根据所述像素信息对所述处理后的当前输煤图像进行感兴趣区域提取，获得目标输煤图像。
- 如权利要求1所述的基于图像识别的输煤量监测方法，其中，所述根据历史输煤图像中的煤块状态标定信息对所述目标输煤图像进行标定，获得目标图像信息的步骤包括：获取预设时间段内的历史输煤图像，并对所述历史输煤图像进行图像处理，获得处理后的历史输煤图像；获取所述处理后的历史输煤图像中的煤块宽度信息和煤块高度信息；根据所述煤块宽度信息和所述煤块高度信息对所述目标输煤图像进行标定，获得目标宽度信息和目标高度信息；以及根据所述目标宽度信息和所述目标高度信息确定目标图像信息。
- 如权利要求3所述的基于图像识别的输煤量监测方法，其中，所述根据所述煤块宽度信息和所述煤块高度信息对所述目标输煤图像进行标定，获得目标宽度信息和目标高度信息的步骤包括：获取所述历史输煤图像对应的实际宽度信息和实际高度信息；获取所述历史输煤图像对应的拍摄中心点位置信息，根据所述中心点位置信息确定所述历史输煤图像中各个区域的角度信息；以及根据所述角度信息、所述煤块宽度信息以及所述煤块高度信息对所述目标输煤图像进行标定，获得目标宽度信息和目标高度信息。
- 如权利要求3所述的基于图像识别的输煤量监测方法，其中，所述根据所述目标宽度信息和所述目标高度信息确定目标图像信息的步骤包括：通过预设宽度分类规则对所述目标宽度信息进行分类，获得不同类别的目标宽度信息；获取所述不同类别的目标宽度信息中各目标宽度信息对应的目标高度信息；根据所述目标高度信息确定目标煤块高度信息；获取所述不同类别的目标宽度信息中各目标宽度信息对应的目标煤块宽度信息；以及根据所述目标煤块高度信息和所述目标煤块宽度信息确定目标图像信息。
- 如权利要求3所述的基于图像识别的输煤量监测方法，其中，所述根据所述目标宽度信息和所述目标高度信息确定目标图像信息的步骤包括：通过预设高度分类规则对所述目标高度信息进行分类，获得不同类别的目标高度信息；获取所述不同类别的目标高度信息中各目标高度信息对应的目标宽度信息；根据所述目标宽度信息确定目标煤块宽度信息；获取所述不同类别的目标高度信息中各目标高度信息对应的目标煤块高度信息；以及根据所述目标煤块宽度信息和所述目标煤块高度信息确定目标图像信息。
- 如权利要求1~6中任一项所述基于图像识别的输煤量监测方法，其中，所述通过电子皮带秤采集实际输煤量，并根据所述实际输煤量和所述当前输煤量进行输煤量监测的步骤包括：通过电子皮带秤采集实际输煤量；以及在所述实际输煤量和所述当前输煤量的差值不满足预设条件时，控制所述输煤皮带停止运行，并进行预警。
- 一种基于图像识别的输煤量监测装置，其中，所述基于图像识别的输煤量监测装置包括：图像处理模块，用于采集输煤皮带对应的当前输煤图像，并对所述当前输煤图像进行图像处理，获得目标输煤图像；信息获取模块，用于根据历史输煤图像中的煤块状态标定信息对所述目标输煤图像进行标定，获得目标图像信息；输煤量获取模块，用于将所述目标图像信息输入至预设输煤量预测模型中，获得当前输煤量；以及输煤量监测模块，用于通过电子皮带秤采集实际输煤量，并根据所述实际输煤量和所述当前输煤量进行输煤量监测。
- 一种基于图像识别的输煤量监测设备，其中，所述基于图像识别的输煤量监测设备包括：存储器、处理器及存储在所述存储器上并可在所述处理器上运行的基于图像识别的输煤量监测程序，所述基于图像识别的输煤量监测程序配置为实现如权利要求1至7中任一项所述的基于图像识别的输煤量监测方法。
- 一种存储介质，其中，所述存储介质上存储有基于图像识别的输煤量监测程序，所述基于图像识别的输煤量监测程序被处理器执行时实现如权利要求1至7中任一项所述的基于图像识别的输煤量监测方法。
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| CN114529824B (zh) * | 2022-04-24 | 2022-06-28 | 江苏科比泰智能科技有限公司 | 一种基于图像识别的胶带传输机皮带监测系统及方法 |
| CN116692395A (zh) * | 2023-05-29 | 2023-09-05 | 华能巢湖发电有限责任公司 | 一种皮带输煤机输料计量方法及系统 |
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