CN113835374A - Real-time monitoring method and system for intelligent manufacturing workshop - Google Patents
Real-time monitoring method and system for intelligent manufacturing workshop Download PDFInfo
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- CN113835374A CN113835374A CN202111083201.9A CN202111083201A CN113835374A CN 113835374 A CN113835374 A CN 113835374A CN 202111083201 A CN202111083201 A CN 202111083201A CN 113835374 A CN113835374 A CN 113835374A
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Abstract
The invention is applicable to the technical field of computers, and particularly relates to a real-time monitoring method and a real-time monitoring system for an intelligent manufacturing workshop, wherein the method comprises the following steps: acquiring monitoring video information and infrared monitoring information, wherein the monitoring video information is continuously acquired video information, and the infrared monitoring information is intermittently acquired infrared images; analyzing the environmental visibility according to the monitoring video information to obtain a visibility analysis result; analyzing the abnormal condition of the environmental temperature according to the infrared monitoring information to obtain a temperature analysis result; and judging whether to send out alarm information according to the visibility analysis result and the temperature analysis result. According to the real-time monitoring method for the intelligent manufacturing workshop, provided by the embodiment of the invention, the acquired information is analyzed in real time, so that whether the conditions of abnormal visibility and abnormal temperature exist in the current workshop can be judged in real time, whether the dangerous situation exists in the workshop can be judged according to the abnormal conditions, the judgment is timely carried out, and the problem of poor timeliness of manual analysis is solved.
Description
Technical Field
The invention belongs to the technical field of computers, and particularly relates to a real-time monitoring method and a real-time monitoring system for an intelligent manufacturing workshop.
Background
Intelligent manufacturing is a man-machine integrated intelligent system composed of intelligent machines and human experts, which can perform intelligent activities such as analysis, reasoning, judgment, conception and decision making during the manufacturing process. By the cooperation of human and intelligent machine, the mental labor of human expert in the manufacturing process is enlarged, extended and partially replaced. The concept of manufacturing automation is updated, and the manufacturing automation is expanded to flexibility, intellectualization and high integration.
In current workshops, monitoring is widely used. The monitoring in the workshop can be used for monitoring the factory environment in real time so as to ensure the safety of the operation environment, and then the operation condition of the workshop can be mastered in real time by utilizing the monitoring.
However, in the existing workshop, the monitoring is mainly used for collecting the picture, and the content can be judged only by manually analyzing the picture in the later period, so that the manual judgment has hysteresis and influences the timeliness of picture content identification.
Disclosure of Invention
The embodiment of the invention aims to provide a real-time monitoring method for an intelligent manufacturing workshop, and aims to solve the problems in the third part of the background art.
The embodiment of the invention is realized as follows, and the real-time monitoring method of the intelligent manufacturing workshop comprises the following steps:
acquiring monitoring video information and infrared monitoring information, wherein the monitoring video information is continuously acquired video information, and the infrared monitoring information is intermittently acquired infrared images;
analyzing the environmental visibility according to the monitoring video information to obtain a visibility analysis result;
analyzing the abnormal condition of the environmental temperature according to the infrared monitoring information to obtain a temperature analysis result;
and judging whether to send out alarm information according to the visibility analysis result and the temperature analysis result.
Preferably, the step of analyzing the environmental visibility according to the monitored video information to obtain a visibility analysis result includes:
dividing the monitoring video information according to a preset time step length, and randomly extracting a preset number of picture frames from the monitoring video information;
identifying target identification points in each group of picture frames to obtain an identification result;
and counting the number of target identification points which can be successfully identified and are contained in the identification result, calculating the successful identification rate, and generating a visibility analysis result.
Preferably, the step of analyzing the abnormal situation of the environmental temperature according to the infrared monitoring information to obtain a temperature analysis result specifically includes:
reading each infrared image in the infrared monitoring information;
judging the infrared image according to a preset standard image, and judging whether an area with the temperature exceeding a preset temperature value exists in the infrared image;
and marking the area exceeding the preset temperature value and generating a temperature analysis result.
Preferably, the step of determining whether to send the alarm information according to the visibility analysis result and the temperature analysis result specifically includes:
inquiring a preset visibility data comparison table according to the visibility analysis result to obtain a first inquiry result;
inquiring a preset temperature data comparison table according to the temperature analysis result to obtain a second inquiry result;
and judging whether the threshold is reached at the same time according to the first query result and the second query result, and if so, sending alarm information.
Preferably, the monitoring video information and the infrared monitoring information both include collected time information.
Preferably, the method further comprises judging whether the highest threshold value is reached according to the first query result and/or the second query result, and if so, sending out alarm information.
Preferably, the temperature analysis result marks an area exceeding a preset temperature value.
Another object of an embodiment of the present invention is to provide a real-time monitoring system for an intelligent manufacturing plant, including:
the information acquisition module is used for acquiring monitoring video information and infrared monitoring information, wherein the monitoring video information is continuously acquired video information, and the infrared monitoring information is intermittently acquired infrared images;
the visibility analysis module is used for analyzing the environmental visibility according to the monitoring video information to obtain a visibility analysis result;
the temperature analysis module is used for analyzing the abnormal condition of the environmental temperature according to the infrared monitoring information to obtain a temperature analysis result;
and the alarm judging module is used for judging whether to send out alarm information according to the visibility analysis result and the temperature analysis result.
Preferably, the visibility analysis module includes:
the frame extracting unit is used for dividing the monitoring video information according to a preset time step length and randomly extracting a preset number of frame frames from the monitoring video information;
the picture identification unit is used for identifying the target identification points in each group of picture frames to obtain an identification result;
and the data counting unit is used for counting the number of the target identification points which can be successfully identified and are contained in the identification result, calculating the successful identification rate and generating a visibility analysis result.
Preferably, the temperature analysis module includes:
the data reading unit is used for reading each infrared image in the infrared monitoring information;
the over-temperature area judging unit is used for judging the infrared image according to a preset standard image and judging whether an area with the temperature exceeding a preset temperature value exists in the infrared image or not;
and the result generation unit is used for marking the area exceeding the preset temperature value and generating a temperature analysis result.
According to the real-time monitoring method for the intelligent manufacturing workshop, provided by the embodiment of the invention, the acquired information is analyzed in real time, so that whether the conditions of abnormal visibility and abnormal temperature exist in the current workshop can be judged in real time, whether the dangerous situation exists in the workshop can be judged according to the abnormal conditions, the judgment is timely carried out, and the problem of poor timeliness of manual analysis is solved.
Drawings
FIG. 1 is a flow chart of a method for real-time monitoring of an intelligent manufacturing plant according to an embodiment of the present invention;
fig. 2 is a flowchart illustrating steps of analyzing environmental visibility according to monitored video information and obtaining a visibility analysis result according to an embodiment of the present invention;
FIG. 3 is a flowchart illustrating steps for analyzing an abnormal ambient temperature condition according to infrared monitoring information and obtaining a temperature analysis result according to an embodiment of the present invention;
fig. 4 is a flowchart illustrating a step of determining whether to issue an alarm message according to a visibility analysis result and a temperature analysis result according to an embodiment of the present invention;
FIG. 5 is an architecture diagram of a real-time monitoring system for an intelligent manufacturing plant according to an embodiment of the present invention;
fig. 6 is an architecture diagram of a visibility analysis module provided in an embodiment of the present invention;
fig. 7 is a schematic diagram of a temperature analysis module according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention 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 invention and are not intended to limit the invention.
It will be understood that, as used herein, the terms "first," "second," and the like may be used herein to describe various elements, but these elements are not limited by these terms unless otherwise specified. These terms are only used to distinguish one element from another. For example, a first xx script may be referred to as a second xx script, and similarly, a second xx script may be referred to as a first xx script, without departing from the scope of the present application.
In current workshops, monitoring is widely used. The monitoring in the workshop can be used for monitoring the factory environment in real time so as to ensure the safety of the operation environment, and then the operation condition of the workshop can be mastered in real time by utilizing the monitoring. However, in the existing workshop, the monitoring is mainly used for collecting the picture, and the content can be judged only by manually analyzing the picture in the later period, so that the manual judgment has hysteresis and influences the timeliness of picture content identification.
According to the invention, the acquired information is analyzed in real time, so that whether the conditions of abnormal visibility and abnormal temperature exist in the current workshop can be judged in real time, whether the dangerous situation exists in the workshop can be judged according to the abnormal conditions, the judgment is timely and correspondingly carried out, and the problem of poor timeliness of manual analysis is solved.
As shown in fig. 1, a flowchart of a real-time monitoring method for an intelligent manufacturing plant according to an embodiment of the present invention is provided, where the method includes:
s100, acquiring monitoring video information and infrared monitoring information, wherein the monitoring video information is continuously acquired video information, and the infrared monitoring information is intermittently acquired infrared images.
In current intelligent manufacturing workshops, such as flour production workshops, a large amount of dust exists in the workshops, and the flour has small particle size, so the flour is easily suspended in the air, and the flour can be fully contacted with the air due to flammability of the flour and can be suspended in the air, so when the concentration of the dust exceeds a certain value, dust explosion is very easy to occur, and two necessary conditions of the dust explosion are that the concentration of the dust reaches a certain value, and open fire or high temperature occurs in the environment, so the dust is rapidly combusted, and the explosion phenomenon is extremely dangerous; and in the intelligent manufacturing workshop, a plurality of cameras are arranged, so that the cameras can be utilized to monitor the dust explosion conditions to ensure the production safety.
In the step, monitoring video information and infrared monitoring information are obtained, wherein the monitoring video information is continuously acquired video information, the infrared monitoring information is intermittently acquired infrared images, monitoring is set in an intelligent manufacturing workshop, the intelligent manufacturing workshop is monitored in real time by monitoring, so that the continuous video information, namely the monitoring video information, is obtained, an infrared camera is set in the intelligent manufacturing workshop, the infrared camera can sense the temperature of each position in the intelligent manufacturing workshop, and the infrared image acquisition can be carried out on the intelligent manufacturing workshop in an intermittent acquisition mode and is carried out once every a period of time as the temperature rises; the monitoring video information and the infrared monitoring information both comprise collected time information.
And S200, analyzing the environmental visibility according to the monitoring video information to obtain a visibility analysis result.
In this step, according to monitoring video information analysis environment visibility, at the very beginning, indoor dust concentration is not high, only at ventilation system trouble or the in-process that the leakage appears, indoor dust concentration just can rise to the required concentration of explosion, and the concentration of dust rises and also can cause the influence to indoor visibility, consequently through detecting indoor visibility, just can backward judge the dust concentration information in the current intelligent manufacturing shop, namely obtain the visibility analysis result.
And S300, analyzing the abnormal condition of the environmental temperature according to the infrared monitoring information to obtain a temperature analysis result.
In the step, the abnormal situation of the environmental temperature is analyzed according to the infrared monitoring information, and the infrared images are collected intermittently and contain the temperature situations of various places, so that the specific temperature situation of each position and the heating speed of each position can be judged according to the continuous infrared images, and the temperature change in the future time can be reasonably predicted according to the current temperature and the heating speed, so that the temperature analysis result is obtained.
And S400, judging whether alarm information is sent out or not according to the visibility analysis result and the temperature analysis result.
In this step, judge according to visibility analysis result and temperature analysis result, the appearance of dust explosion, its two main requirements all need satisfy, consequently when a set of at most in two main conditions reaches the numerical value, the condition of dust explosion still can not appear, and temperature and dust concentration in the intelligent manufacturing workshop exceed and all reach the required condition of dust explosion that appears, then send alarm information to remind relevant personnel to handle, thereby play the effect of in time reporting to the police.
As shown in fig. 2, as a preferred embodiment of the present invention, the step of analyzing the environmental visibility according to the monitored video information to obtain a visibility analysis result specifically includes:
s201, dividing the monitoring video information according to a preset time step, and randomly extracting a preset number of picture frames from the monitoring video information.
In this step, the monitoring video information is divided according to a preset time step, because the monitoring video information is a continuous video, the processing is difficult, the monitoring video information is divided into short videos of a segment, the divided time step can be selected according to the data processing capability, after the short videos of a segment are obtained, picture frames are randomly extracted from each short video, the number of the picture frames is selected according to the length of the short videos and the frame rate, the larger the length of the short videos is, the larger the number of the extracted picture frames is, and the larger the frame rate of the short videos is, the larger the number of the extracted picture frames is.
S202, identifying the target identification points in each group of picture frames to obtain an identification result.
In this step, the target identification points in each group of picture frames are identified, target detection points are set at key positions of the intelligent manufacturing workshop, specifically, the monitoring area of each monitoring device is limited, so that the target identification points can be set in the monitoring area of the monitoring device, the target identification points can be printed mark points or fixed objects in the monitoring area, and when the picture frames are identified, the target identification points in the picture are identified, and then the identification result is obtained.
And S203, counting the number of target identification points which can be successfully identified and are contained in the identification result, calculating the successful identification rate, and generating a visibility analysis result.
In the step, the number of the successfully identified target identification points contained in the identification result is counted, in the process of identifying the target identification points, due to the influence of dust, part of the target identification points cannot be identified, so that the concentration of the dust can be judged according to the probability that the target identification points are successfully identified, the total number of the target identification points is firstly calculated, then the successful identification rate is calculated according to the number of the successfully identified target identification points, and the visibility analysis result is generated.
As shown in fig. 3, as a preferred embodiment of the present invention, the step of analyzing the abnormal environment temperature condition according to the infrared monitoring information to obtain the temperature analysis result specifically includes:
s301, reading each infrared image in the infrared monitoring information.
In the step, each infrared image in the infrared monitoring information is read, the number of the infrared images is small because the infrared images are collected intermittently, each infrared image can be processed, and if the collection interval time is short, an excerpt mode can be adopted to select one infrared image at intervals.
S302, judging the infrared image according to a preset standard image, and judging whether an area with temperature exceeding a preset temperature value exists in the infrared image.
In this step, the infrared image is judged according to the preset standard image, and the temperature in the infrared image is represented by color, so that the temperature of each region can be judged according to the color distribution in the infrared image, and whether the region with the temperature exceeding the preset temperature value exists in the infrared image is judged.
S303, marking the area exceeding the preset temperature value and generating a temperature analysis result.
In the step, marking the area with the temperature value exceeding the preset temperature value, which indicates that the risk of overtemperature exists in the current area, and if the temperature is not regulated, the situation of dust explosion or fire is easily caused; and marking the area exceeding the preset temperature value according to the temperature analysis result.
As shown in fig. 4, as a preferred embodiment of the present invention, the step of determining whether to send out the alarm information according to the visibility analysis result and the temperature analysis result specifically includes:
s401, inquiring a preset visibility data comparison table according to the visibility analysis result to obtain a first inquiry result.
In this step, a preset visibility data comparison table is queried according to the visibility analysis result, and a numerical value of dust concentration corresponding to each visibility is recorded in the visibility data comparison table, that is, the dust concentration in the room can be reversely deduced according to the visibility analysis result, so that a first query result is obtained.
S402, inquiring a preset temperature data comparison table according to the temperature analysis result to obtain a second inquiry result.
In this step, a preset temperature data comparison table is queried according to the temperature analysis result, and similarly, a temperature value corresponding to each color is recorded in the temperature data comparison table, so that the temperature of each area in the room can be inferred according to the color, and a second query result is obtained.
And S403, judging whether the threshold is reached simultaneously according to the first query result and the second query result, and if so, sending alarm information.
In the step, whether the threshold is reached simultaneously is judged according to the first query result and the second query result, if the indoor dust concentration and the indoor temperature reach the threshold, the dust explosion is probably caused, and the dust explosion needs to be processed immediately, namely, an alarm message is sent out to inform related personnel of evacuating.
In the step, whether the maximum threshold value is reached is judged according to the first query result and/or the second query result, if yes, alarm information is sent, when the temperature exceeds the maximum threshold value, a fire hazard is possible, and therefore processing is needed, and when the dust concentration is too high, even if the indoor temperature is not enough to ignite, the high concentration can affect visibility and health of workers, and therefore the alarm information is sent to inform relevant personnel of processing.
As shown in fig. 5, a real-time monitoring system for an intelligent manufacturing plant according to an embodiment of the present invention is characterized in that the system includes:
the information acquiring module 100 is configured to acquire monitoring video information and infrared monitoring information, where the monitoring video information is continuously acquired video information, and the infrared monitoring information is an intermittently acquired infrared image.
In the system, an information acquisition module 100 acquires monitoring video information and infrared monitoring information, wherein the monitoring video information is continuously acquired video information, the infrared monitoring information is intermittently acquired infrared images, monitoring is arranged in an intelligent manufacturing workshop, the intelligent manufacturing workshop is monitored in real time by monitoring, so that the continuous video information, namely the monitoring video information, is obtained, an infrared camera is arranged in the intelligent manufacturing workshop, the infrared camera can sense the temperature of each position in the intelligent manufacturing workshop, and the temperature rises in a time-consuming manner, so that the infrared image acquisition can be carried out on the intelligent manufacturing workshop in an intermittent acquisition mode and is carried out once every a period of time; the monitoring video information and the infrared monitoring information both comprise collected time information.
And the visibility analysis module 200 is configured to analyze the environmental visibility according to the monitoring video information to obtain a visibility analysis result.
In this system, visibility analysis module 200 is according to monitoring video information analysis environment visibility, at the very beginning, indoor dust concentration is not high, only at ventilation system trouble or the in-process that leaks appear, indoor dust concentration just can rise to the required concentration of explosion, and the concentration of dust rises and also can cause the influence to indoor visibility, consequently through detecting indoor visibility, just can reverse judge the dust concentration information in the current intelligent manufacturing shop, namely obtain the visibility analysis result.
And the temperature analysis module 300 is configured to analyze an abnormal environment temperature condition according to the infrared monitoring information to obtain a temperature analysis result.
In the system, the temperature analysis module 300 analyzes the abnormal situation of the environmental temperature according to the infrared monitoring information, and since the infrared images are intermittently acquired and include the temperature situations of various places, the specific temperature situation of each place and the temperature rise speed of each place can be judged according to the continuous infrared images, and the temperature change in the future time can be reasonably predicted according to the current temperature and the temperature rise speed, so as to obtain the temperature analysis result.
And an alarm judging module 400, configured to judge whether to send alarm information according to the visibility analysis result and the temperature analysis result.
In this system, alarm judgment module 400 judges according to visibility analysis result and temperature analysis result, the appearance of dust explosion, its two main requirements all need satisfy, consequently when a set of at most in two main conditions reaches the numerical value, the condition of dust explosion still can not appear, and temperature and dust concentration in the intelligent manufacturing workshop exceed when all reaching the required condition of dust explosion that appears, then send alarm information, handle with reminding relevant personnel, thereby play the effect of timely warning.
As shown in fig. 6, as a preferred embodiment of the present invention, the visibility analyzing module includes:
the frame extracting unit 201 is configured to divide the monitoring video information according to a preset time step, and randomly extract a preset number of frame frames from the monitoring video information.
In this module, the frame extracting unit 201 divides the monitoring video information according to a preset time step, because the monitoring video information is a continuous video, it is difficult to process, and the monitoring video information is divided into a segment of short video, the divided time step can be selected according to the capability of data processing, after a segment of short video is obtained, the frame frames are randomly extracted from each short video, the number of the frame frames is selected according to the length of the short video and the frame rate, the larger the length of the short video is, the larger the number of the extracted frame frames is, and the larger the frame rate of the short video is, the larger the number of the extracted frame frames is.
And the picture identification unit 202 is used for identifying the target identification point in each group of picture frames to obtain an identification result.
In this module, the image recognition unit 202 recognizes the target recognition point in each group of image frames, and sets a target detection point at a key position of the intelligent manufacturing shop, specifically, the monitoring area of each monitoring device is limited, so that the target recognition point can be set in the monitoring area of the monitoring device, and the target recognition point can be a printed mark point or a fixed object in the monitoring area.
And the data counting unit 203 is used for counting the number of the target identification points which can be successfully identified and are contained in the identification result, calculating the successful identification rate and generating a visibility analysis result.
In this module, the data statistics unit 203 counts the number of successfully recognized target recognition points included in the recognition result, and in the process of recognizing the target recognition points, due to the influence of dust, part of the target recognition points cannot be recognized, so that the concentration of the dust can be determined according to the probability that the target recognition points are successfully recognized, the total number of the target recognition points is first calculated, and then the successful recognition rate is calculated according to the number of the successfully recognized target recognition points, so as to generate the visibility analysis result.
As shown in fig. 7, as a preferred embodiment of the present invention, the temperature analysis module includes:
and a data reading unit 301, configured to read each infrared image in the infrared monitoring information.
In this module, the data reading unit 301 reads each infrared image in the infrared monitoring information, and since the infrared images are intermittently collected, the number of the infrared images is small, each infrared image can be processed, and if the collection interval time is short, an alternate mode can be adopted, and one infrared image is selected at intervals.
The over-temperature area determining unit 302 is configured to determine the infrared image according to a preset standard image, and determine whether an area with a temperature exceeding a preset temperature value exists in the infrared image.
In this module, the over-temperature region determining unit 302 determines the infrared image according to a preset standard image, and in the infrared image, the temperature is represented by a color, so that the temperature of each region can be determined according to the color distribution in the infrared image, and thus, whether a region with a temperature exceeding a preset temperature value exists in the infrared image is determined.
A result generating unit 303 for marking a region exceeding a preset temperature value and generating a temperature analysis result.
In the module, the result generation unit 303 marks an area exceeding a preset temperature value, which indicates that the current area has a risk of over-temperature, and if the area is not regulated, the situation of dust explosion or fire is easily caused; and marking the area exceeding the preset temperature value according to the temperature analysis result.
It should be understood that, although the steps in the flowcharts of the embodiments of the present invention are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence 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 a portion of the steps in various embodiments may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.
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 a computer program, which can be stored in a non-volatile computer-readable storage medium, and can include the processes of the embodiments of the methods described above when the program is executed. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within 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 invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (10)
1. A method for real-time monitoring of an intelligent manufacturing plant, the method comprising:
acquiring monitoring video information and infrared monitoring information, wherein the monitoring video information is continuously acquired video information, and the infrared monitoring information is intermittently acquired infrared images;
analyzing the environmental visibility according to the monitoring video information to obtain a visibility analysis result;
analyzing the abnormal condition of the environmental temperature according to the infrared monitoring information to obtain a temperature analysis result;
and judging whether to send out alarm information according to the visibility analysis result and the temperature analysis result.
2. The real-time monitoring method for the intelligent manufacturing plant according to claim 1, wherein the step of analyzing the environmental visibility according to the monitoring video information to obtain the visibility analysis result specifically comprises:
dividing the monitoring video information according to a preset time step length, and randomly extracting a preset number of picture frames from the monitoring video information;
identifying target identification points in each group of picture frames to obtain an identification result;
and counting the number of target identification points which can be successfully identified and are contained in the identification result, calculating the successful identification rate, and generating a visibility analysis result.
3. The real-time monitoring method for the intelligent manufacturing workshop according to claim 1, wherein the step of analyzing the abnormal situation of the environmental temperature according to the infrared monitoring information to obtain the temperature analysis result specifically comprises:
reading each infrared image in the infrared monitoring information;
judging the infrared image according to a preset standard image, and judging whether an area with the temperature exceeding a preset temperature value exists in the infrared image;
and marking the area exceeding the preset temperature value and generating a temperature analysis result.
4. The real-time monitoring method for the intelligent manufacturing plant according to claim 1, wherein the step of judging whether to send out the alarm information according to the visibility analysis result and the temperature analysis result specifically comprises:
inquiring a preset visibility data comparison table according to the visibility analysis result to obtain a first inquiry result;
inquiring a preset temperature data comparison table according to the temperature analysis result to obtain a second inquiry result;
and judging whether the threshold is reached at the same time according to the first query result and the second query result, and if so, sending alarm information.
5. The method according to claim 1, wherein the monitoring video information and the infrared monitoring information each comprise collected time information.
6. The real-time monitoring method for the intelligent manufacturing plant according to claim 4, further comprising judging whether a highest threshold value is reached according to the first query result and/or the second query result, and if so, sending an alarm message.
7. The real-time monitoring method for an intelligent manufacturing plant according to claim 1, wherein the temperature analysis result marks an area exceeding a preset temperature value.
8. Real-time monitoring system in intelligent manufacturing shop characterized in that, the system includes:
the information acquisition module is used for acquiring monitoring video information and infrared monitoring information, wherein the monitoring video information is continuously acquired video information, and the infrared monitoring information is intermittently acquired infrared images;
the visibility analysis module is used for analyzing the environmental visibility according to the monitoring video information to obtain a visibility analysis result;
the temperature analysis module is used for analyzing the abnormal condition of the environmental temperature according to the infrared monitoring information to obtain a temperature analysis result;
and the alarm judging module is used for judging whether to send out alarm information according to the visibility analysis result and the temperature analysis result.
9. The real-time monitoring system for an intelligent manufacturing plant according to claim 8, wherein the visibility analysis module comprises:
the frame extracting unit is used for dividing the monitoring video information according to a preset time step length and randomly extracting a preset number of frame frames from the monitoring video information;
the picture identification unit is used for identifying the target identification points in each group of picture frames to obtain an identification result;
and the data counting unit is used for counting the number of the target identification points which can be successfully identified and are contained in the identification result, calculating the successful identification rate and generating a visibility analysis result.
10. The real-time monitoring system for an intelligent manufacturing plant according to claim 8, wherein the temperature analysis module comprises:
the data reading unit is used for reading each infrared image in the infrared monitoring information;
the over-temperature area judging unit is used for judging the infrared image according to a preset standard image and judging whether an area with the temperature exceeding a preset temperature value exists in the infrared image or not;
and the result generation unit is used for marking the area exceeding the preset temperature value and generating a temperature analysis result.
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