CN112325934B - Wisdom cable channel real-time supervision device - Google Patents
Wisdom cable channel real-time supervision device Download PDFInfo
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- CN112325934B CN112325934B CN202011187949.9A CN202011187949A CN112325934B CN 112325934 B CN112325934 B CN 112325934B CN 202011187949 A CN202011187949 A CN 202011187949A CN 112325934 B CN112325934 B CN 112325934B
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Abstract
The invention provides a real-time monitoring device for an intelligent cable channel, which comprises a monitoring module, a forwarding module, a processing module and a notification module, wherein the monitoring module is used for monitoring the real-time monitoring of the intelligent cable channel; the monitoring module is used for acquiring monitoring data in the cable channel and transmitting the monitoring data to the forwarding module; the forwarding module is used for receiving the monitoring data from the monitoring module and sending the monitoring data to the processing module; the processing module is used for detecting whether an abnormal condition occurs in the cable channel according to the monitoring data to obtain a detection result; and the notification module is used for sending a prompt message to related workers when the detection result is that an abnormal condition occurs in the cable channel. The cable channel real-time monitoring device has the advantages that the cable channel real-time monitoring is realized, when abnormal conditions occur in the cable channel, the prompt is timely given to relevant workers, the workers can timely find the abnormal conditions in the cable channel and timely process the abnormal conditions, and the normal operation of the cable channel is guaranteed.
Description
Technical Field
The invention relates to the field of monitoring, in particular to a real-time monitoring device for an intelligent cable channel.
Background
The cable channel refers to a channel for laying a cable, and includes a tunnel, a cable trench, and the like. In the prior art, the inspection of the cable channel is generally performed in a manual periodic inspection mode, which is not only inefficient, but also cannot find abnormal conditions in the cable channel in time.
Disclosure of Invention
In view of the above problems, an object of the present invention is to provide a real-time monitoring apparatus for smart cable channels, which includes a monitoring module, a forwarding module, a processing module and a notification module;
the monitoring module is used for acquiring monitoring data in the cable channel and transmitting the monitoring data to the forwarding module;
the forwarding module is used for receiving the monitoring data from the monitoring module and sending the monitoring data to the processing module;
the processing module is used for detecting whether an abnormal condition occurs in the cable channel according to the monitoring data to obtain a detection result;
and the notification module is used for sending a prompt message to related workers when the detection result is that an abnormal condition occurs in the cable channel.
Preferably, the monitoring data comprises temperature data, humidity data, hazardous gas concentration data, video data and location data.
Preferably, the forwarding module comprises a wireless cellular network communication unit and a fiber optic communication unit;
the wireless cellular network communication unit is used for sending monitoring data to the processing module through a cellular network; the optical fiber communication unit is used for sending the monitoring data to the processing module through an optical fiber cable.
Preferably, the monitoring module comprises a temperature and humidity monitoring unit, a gas monitoring unit, a video acquisition unit and a positioning unit;
the temperature and humidity monitoring unit is used for acquiring temperature data and humidity data in the cable channel, the gas monitoring unit is used for acquiring dangerous gas concentration data in the cable channel, the video acquiring unit is used for acquiring video data in the cable channel, and the positioning unit is used for acquiring position data of the position where the positioning unit is located.
Preferably, the hazardous gas comprises methane, hydrogen sulphide, ammonia, carbon monoxide and nitric oxide.
Preferably, the processing module comprises a numerical judgment sub-module and a video detection sub-module;
the numerical value judgment submodule is used for judging whether the temperature data, the humidity data and the dangerous gas concentration data exceed preset normal value intervals corresponding to each other, and if yes, the detection result is that an abnormal condition occurs inside the cable channel;
the video detection submodule is used for carrying out image recognition on a frame image of the video data and judging whether a preset abnormal event occurs in the frame image, if so, the detection result is that an abnormal condition occurs in the cable channel.
Preferably, the sending of the prompt message to the relevant staff member includes:
sending a prompt message to related workers through a mobile phone short message and a micro message service signal; the prompting message comprises the type of the abnormal condition and the position of the abnormal condition.
Preferably, the type of the abnormal condition includes:
temperature is beyond the normal value range, humidity is beyond the normal value range, the concentration of dangerous gas is beyond the normal value range and fire occurs.
Compared with the prior art, the invention has the advantages that:
the invention realizes the real-time monitoring of the cable channel, can prompt relevant workers in time when the abnormal condition occurs in the cable channel, is favorable for the workers to find the abnormal condition in the cable channel in time and process the abnormal condition in time, and is favorable for ensuring the normal operation of the cable channel.
Drawings
The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, other drawings can be obtained on the basis of the following drawings without inventive effort.
Fig. 1 is a diagram of an exemplary embodiment of a real-time monitoring apparatus for an intelligent cable channel according to the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
The invention provides a real-time monitoring device for an intelligent cable channel, which comprises a monitoring module, a forwarding module, a processing module and a notification module, wherein the monitoring module is used for monitoring the real-time monitoring of the intelligent cable channel;
the monitoring module is used for acquiring monitoring data in the cable channel and transmitting the monitoring data to the forwarding module;
the forwarding module is used for receiving the monitoring data from the monitoring module and sending the monitoring data to the processing module;
the processing module is used for detecting whether an abnormal condition occurs in the cable channel according to the monitoring data to obtain a detection result;
and the notification module is used for sending a prompt message to related workers when the detection result is that an abnormal condition occurs in the cable channel.
In one embodiment, the processing module includes a detection submodule, a storage submodule and a management submodule, and the monitoring submodule is configured to detect whether an abnormal condition occurs inside the cable channel according to the monitoring data, so as to obtain a detection result; the storage submodule is used for storing the monitoring data and the corresponding detection result, and the management submodule is used for managing the monitoring data and the monitoring result stored in the storage submodule.
In one embodiment, the management submodule comprises an identity authentication unit, an operation unit, a log recording unit and a log query unit;
the identity verification unit is used for verifying the identity of a worker using the operation unit and giving the worker who passes the identity authentication the authority to use the operation unit;
the operation unit is used for managing the monitoring data and the monitoring results stored in the storage submodule, and the management type comprises modification and deletion of the monitoring data and the monitoring results;
the log recording unit is used for recording an operation log for managing monitoring data and monitoring results stored in the storage submodule by a worker passing identity authentication, wherein the operation log comprises the identity of the worker, the type of management and the starting and ending time of the type of management;
the log query unit is used for searching the operation working log by an administrator based on the identity of a worker, the type of management and the starting and ending time of the type of management.
In one embodiment, the monitoring data includes temperature data, humidity data, hazardous gas concentration data, video data, and location data.
In one embodiment, the forwarding module includes a wireless cellular network communication unit and a fiber optic communication unit;
the wireless cellular network communication unit is used for sending monitoring data to the processing module through a cellular network; the optical fiber communication unit is used for sending the monitoring data to the processing module through an optical fiber cable.
In one embodiment, the monitoring module comprises a temperature and humidity monitoring unit, a gas monitoring unit, a video acquisition unit and a positioning unit;
the temperature and humidity monitoring unit is used for acquiring temperature data and humidity data in the cable channel, the gas monitoring unit is used for acquiring dangerous gas concentration data in the cable channel, the video acquiring unit is used for acquiring video data in the cable channel, and the positioning unit is used for acquiring position data of the position where the positioning unit is located.
The cable channel is provided with a positioning node, the positioning node periodically broadcasts position data of the positioning node, and the positioning unit is used for receiving the position data.
In one embodiment, the hazardous gas comprises methane, hydrogen sulfide, ammonia, carbon monoxide, and nitric oxide.
In one embodiment, the processing module comprises a numerical judgment sub-module and a video detection sub-module;
the numerical value judgment submodule is used for judging whether the temperature data, the humidity data and the dangerous gas concentration data exceed preset normal value intervals corresponding to each other, and if yes, the detection result is that an abnormal condition occurs inside the cable channel;
the video detection submodule is used for carrying out image recognition on a frame image of the video data and judging whether a preset abnormal event occurs in the frame image, if so, the detection result is that an abnormal condition occurs in the cable channel.
The abnormal events include the entrance of animals in the cable channel and the occurrence of fire in the cable channel.
In one embodiment, sending a prompt message to the associated staff member includes:
sending a prompt message to related workers through a mobile phone short message and a micro message service signal; the prompting message comprises the type of the abnormal condition and the position of the abnormal condition.
In one embodiment, the type of abnormal condition includes:
temperature is beyond the normal value range, humidity is beyond the normal value range, the concentration of dangerous gas is beyond the normal value range and fire occurs.
In one embodiment, the image recognition of the frame image of the video data to determine whether a preset abnormal event occurs in the frame image includes:
extracting frame images from the video data by adopting a fixed time period, recording the serial number of the extracted frame images in the video data as t, calculating the defect index of all the frame images with the serial number range of [ t-a, t + a ], wherein a represents a preset interval parameter, and selecting the frame image with the minimum defect index for further identification;
the defect index is calculated as follows:
in the formula, qidxjDenotes a number range of [ t-a, t + a ]]qxU indicates the sequence number range [ t-a, t + a ] as the defect index of the jth frame image of all the frame images]Set of all frame images of, biRepresenting the variance of the gray values, c, of the frame image i in qxUiRepresenting the variance, d, of the noise estimate of frame image i in qxUiRepresenting the peak signal-to-noise ratio, b, of frame image i in qxUjRepresenting the gray value standard deviation of the jth frame image of all the frame images, cjStandard deviation of noise estimation representing jth frame image of all frame images, djRepresenting the peak signal-to-noise ratio of the jth frame image of all frame images, baveDenotes a number range of [ t-a, t + a ]]C mean of the variance of the gray values of all the frame images, caveDenotes a number range of [ t-a, t + a ]]Of all frame images, daveDenotes a number range of [ t-a, t + a ]]Is measured as the average of the peak signal-to-noise ratios of all frame images.
Due to the transmission reason or the reason of a video shooting machine, frame images in video data sometimes have defects, if the frame images with the defects are directly subjected to image recognition, misjudgment results are easily obtained, and the method screens the frame images needing image recognition, is favorable for selecting high-quality frame images, and improves the accuracy of subsequent abnormal event recognition. Specifically, when calculating the defect index, consideration is given to gray scale values, variance of noise estimation, peak signal-to-noise ratio and the like, which is beneficial to selecting a frame image with higher quality, wherein the variance of noise estimation is smaller, and the peak signal-to-noise ratio is larger.
In one embodiment, the frame image with the minimum defect index is selected for further identification, and the method comprises the following steps:
carrying out graying processing on the frame image with the minimum defect index to obtain a grayscale image;
carrying out noise reduction processing on the gray level image to obtain a noise reduction image;
extracting a foreground object from the noise-reduced image to obtain a foreground image;
and extracting feature data contained in the foreground image, and identifying whether a preset abnormal event occurs in the foreground image according to the feature data.
In one embodiment, performing noise reduction processing on the grayscale image to obtain a noise-reduced image includes:
performing wavelet decomposition on the gray level image to obtain a wavelet image of a high frequency part and a wavelet image of a low frequency part;
the wavelet image of the high frequency part is subjected to the following threshold processing:
in the formula (a) ag(x, y) and fg(x, y) respectively representing the wavelet coefficient image of the high-frequency part after thresholding and the wavelet coefficient image of the high-frequency part before thresholding, (x, y) representing the coordinates of the pixel points in the wavelet image of the high-frequency part, g ∈ {1,2,3}, g representing the number of the wavelet coefficient image of the high-frequency part, th1And th2F, fh, fU (g), numU, f (g), f (h) and f (g) are all preset judgment thresholds, fh represents a sign function, fU (g) represents a set of all pixel points of the wavelet coefficient image of the high-frequency part with the number of g, numU represents the total number of the pixel points in fU (g), and fkRepresenting the pixel value of pixel k in fU (g), fuavePixels representing all pixel points in fU (g)Mean value of values, g1And g2All are preset adjusting parameters;
the wavelet image of the low frequency part is processed as follows:
and smoothing the wavelet image of the low-frequency part by using the following functions to obtain a processed wavelet image of the low-frequency part:
in the formula, ag (x, y) represents the processed wavelet image of the low-frequency part, and x and y respectively represent the abscissa and the ordinate of a pixel point in the wavelet image of the low-frequency part; sig denotes smoothing parameters;
mixing ag (x, y) and afgAnd (x, y) reconstructing to obtain a noise-reduced image.
The threshold processing is carried out after the wavelet decomposition is carried out on the gray level image, which is beneficial to inhibiting the noise of the image while retaining the detail information of the image. When the wavelet image of the high-frequency part is processed, a mode of self-adaptive function selection is adopted, and different functions are self-adaptively selected for processing the wavelet images of different high-frequency parts, so that the pertinence and the accuracy of threshold processing are improved. When the wavelet image of the low-frequency part is processed, the adopted smoothing parameters have adaptivity, and compared with the smoothing parameters with fixed numerical values, the noise reduction effect is undoubtedly more accurate.
In one embodiment, the value of the smoothing parameter sig is determined as follows:
initializing the value of sig to be 2, smoothing the wavelet image of the low-frequency part by using the function to obtain a processed wavelet image ag2(x, y), calculating ag2(x, y) two-dimensional entropy, noted esw2Using maximum entropy threshold segmentation algorithm to pair ag2(x, y) is calculated to find the division threshold fgt2Judgment esw2And fgt2If the absolute value of the difference between the two is greater than the set absolute value threshold abth, the value of sig is updated, where sig' denotes the value of sig for the value of sig 2-blTaking the updated value of the smoothing parameter sig, wherein bl represents the updating step length, and if not, determining the final value of the smoothing parameter sig to be 2;
smoothing the wavelet image of the low frequency part by using the function when sig is 2-bl, and calculating the wavelet image ag of the low frequency part after processing2-bl(x, y) two-dimensional entropy esw2-blUsing maximum entropy threshold segmentation algorithm to pair ag2-bl(x, y) is calculated to find the division threshold fgt2-blJudgment esw2-blAnd fgt2-blWhether the absolute value of the difference is larger than a set absolute value threshold abth or not is judged, if yes, bl is subtracted from the value of sig' to obtain an updated value of the smoothing parameter sig; if not, determining the final value of the smoothing parameter sig as 2-bl,
and by analogy, continuously updating the value of sig by using the updating step bl until the absolute value between the two-dimensional entropy of the wavelet image of the low-frequency part after processing and the segmentation threshold obtained by calculating the wavelet image by using the maximum entropy threshold segmentation algorithm is smaller than a set absolute value threshold abth when the wavelet image of the low-frequency part is subjected to smoothing processing by using the value of sig, and taking the value of sig at the moment as the final value of sig.
By comparing the two-dimensional entropy of the smoothed image with the segmentation threshold of the maximum entropy threshold segmentation algorithm, the smoothing parameters are continuously adjusted, so that correct adjustment parameters can be selected, and the adaptivity of the smoothing function is enhanced.
In one embodiment, extracting a foreground object from the noise-reduced image to obtain a foreground image includes:
and extracting the foreground object of the noise reduction image by using an Otsu method to obtain a foreground image.
In one embodiment, identifying whether a preset abnormal event occurs in a foreground image according to the feature data includes:
and matching the characteristic data with a pre-stored characteristic data template of the abnormal event, and if the matching is successful, judging that the preset abnormal event occurs in the foreground image.
While embodiments of the invention have been shown and described, it will be understood by those skilled in the art that: various changes, modifications, substitutions and alterations can be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.
Claims (5)
1. A real-time monitoring device for an intelligent cable channel is characterized by comprising a monitoring module, a forwarding module, a processing module and a notification module;
the monitoring module is used for acquiring monitoring data in the cable channel and transmitting the monitoring data to the forwarding module;
the forwarding module is used for receiving the monitoring data from the monitoring module and sending the monitoring data to the processing module;
the processing module is used for detecting whether an abnormal condition occurs in the cable channel according to the monitoring data to obtain a detection result;
the notification module is used for sending a prompt message to related workers when the detection result is that an abnormal condition occurs in the cable channel;
the monitoring data comprises temperature data, humidity data, dangerous gas concentration data, video data and position data;
the monitoring module comprises a temperature and humidity monitoring unit, a gas monitoring unit, a video acquisition unit and a positioning unit;
the temperature and humidity monitoring unit is used for acquiring temperature data and humidity data in the cable channel, the gas monitoring unit is used for acquiring concentration data of hazardous gas in the cable channel, the video acquiring unit is used for acquiring video data in the cable channel, and the positioning unit is used for acquiring position data of the position where the positioning unit is located;
the processing module comprises a numerical value judgment sub-module and a video detection sub-module;
the numerical value judgment submodule is used for judging whether the temperature data, the humidity data and the dangerous gas concentration data exceed preset normal value intervals corresponding to each other, and if yes, the detection result is that an abnormal condition occurs inside the cable channel;
the video detection submodule is used for carrying out image recognition on a frame image of the video data and judging whether a preset abnormal event occurs in the frame image, if so, the detection result is that an abnormal condition occurs in the cable channel;
performing image recognition on a frame image of the video data, and judging whether a preset abnormal event occurs in the frame image, including:
extracting frame images from the video data by adopting a fixed time period, recording the serial number of the extracted frame images in the video data as t, calculating the defect index of all the frame images with the serial number range of [ t-a, t + a ], wherein a represents a preset interval parameter, and selecting the frame image with the minimum defect index for further identification;
the defect index is calculated as follows:
in the formula, qidxjDenotes a number range of [ t-a, t + a ]]qxU indicates the sequence number range [ t-a, t + a ] as the defect index of the jth frame image of all the frame images]Set of all frame images of, biRepresenting the variance of the gray values, c, of the frame image i in qxUiRepresenting the variance, d, of the noise estimate of frame image i in qxUiRepresenting the peak signal-to-noise ratio, b, of frame image i in qxUjRepresenting the gray value standard deviation of the jth frame image of all the frame images, cjStandard deviation of noise estimation representing jth frame image of all frame images, djRepresenting the peak signal-to-noise ratio of the jth frame image of all frame images, baveDenotes a number range of [ t-a, t + a ]]C mean of the variance of the gray values of all the frame images, caveDenotes a number range of [ t-a, t + a ]]Of all frame images, daveDenotes a number range of [ t-a, t + a ]]Is measured as the average of the peak signal-to-noise ratios of all frame images.
2. The real-time monitoring device for intelligent cable channel as claimed in claim 1, wherein said forwarding module comprises a wireless cellular network communication unit and a fiber optic communication unit;
the wireless cellular network communication unit is used for sending monitoring data to the processing module through a cellular network; the optical fiber communication unit is used for sending the monitoring data to the processing module through an optical fiber cable.
3. The device as claimed in claim 1, wherein the hazardous gas includes methane, hydrogen sulfide, ammonia, carbon monoxide and nitric oxide.
4. The device of claim 1, wherein the sending of the prompt message to the associated staff member comprises:
sending a prompt message to related workers through a mobile phone short message and a micro message service signal; the prompting message comprises the type of the abnormal condition and the position of the abnormal condition.
5. The device according to claim 4, wherein the type of the abnormal condition comprises:
temperature is beyond the normal value range, humidity is beyond the normal value range, the concentration of dangerous gas is beyond the normal value range and fire occurs.
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