Steam pipe network intelligent monitoring method, system and equipment based on deep learning
A deep learning and intelligent monitoring technology, applied in the field of steam pipe network, can solve problems such as burns, and achieve the effect of eliminating potential safety hazards and ensuring safety
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Embodiment 1
[0045] This embodiment implements a deep learning-based intelligent monitoring method for steam pipe networks, such as figure 1 shown, including the following steps:
[0046] S1. Carry out real-time monitoring at the steam pipe network site through the camera, collect monitoring image data, and preprocess the collected image data;
[0047] S2. Pass the preprocessed image data into the trained deep learning model;
[0048] S3. The trained deep learning model calculates the received preprocessed image data to obtain the positional relationship between the target frame and the corresponding detection area;
[0049] S4. If the target frame is within the detection area, report the event information to the control center; if the target frame is not within the detection area, detect the next image data to be detected.
[0050] Specifically, the deep learning model is a CNN model.
[0051] Further, preprocessing the image data is data enhancement, image scaling and / or normalization...
Embodiment 2
[0069] Such as Figure 4 As shown, this embodiment implements a deep learning-based steam pipeline network intelligent monitoring system, including:
[0070] The receiving data module 501 receives the image data of the steam pipe network from the camera;
[0071] A preprocessing module 502, configured to preprocess the image data of the steam pipe network;
[0072] The deep learning module 503 receives the image data from the preprocessing module, and calculates the positional relationship between the target frame and the corresponding detection area on the preprocessed image data;
[0073] The output data module 504, if the target frame is within the detection area, then report the event information to the control center.
[0074] Specifically, the deep learning model is a CNN model.
[0075] Further, calculating the positional relationship between the target frame and the corresponding detection area includes: calculating the coordinates of the center point of the target ...
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