CN110173627B - Solar energy system - Google Patents

Solar energy system Download PDF

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CN110173627B
CN110173627B CN201910474746.9A CN201910474746A CN110173627B CN 110173627 B CN110173627 B CN 110173627B CN 201910474746 A CN201910474746 A CN 201910474746A CN 110173627 B CN110173627 B CN 110173627B
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alarm
data
threshold value
value
temperature
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CN110173627A (en
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周守军
张国正
陆万鹏
郭敏
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Shandong Jianzhu University
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Shandong Jianzhu University
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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
    • F17D—PIPE-LINE SYSTEMS; PIPE-LINES
    • F17D5/00—Protection or supervision of installations
    • F17D5/02—Preventing, monitoring, or locating loss
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24S—SOLAR HEAT COLLECTORS; SOLAR HEAT SYSTEMS
    • F24S40/00—Safety or protection arrangements of solar heat collectors; Preventing malfunction of solar heat collectors
    • F24S40/90—Arrangements for testing solar heat collectors
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/40—Solar thermal energy, e.g. solar towers

Abstract

The invention provides a solar system which comprises a heat collector, a hot water tank and a pipeline for connecting the heat collector and the hot water tank, wherein the pipeline is provided with a plurality of connecting points, and an insulating layer is arranged outside the connecting points; detecting the thermal imager at the thermal insulation layer of the connection point, and detecting data of the position of the thermal insulation layer; calculating the change of temperature deviation cumulative sum at the same time of adjacent days, and triggering a node leakage alarm when the change exceeds a threshold value; the alarm mode is temperature deviation accumulation and alarm at the same time of adjacent days, namely the temperature deviation accumulation and alarm at the same time of adjacent days are calculated, and when the value of the accumulation sum exceeds a set threshold value, the temperature deviation accumulation and alarm are triggered. This application has changed the alarm mode, adopts adjacent day moment temperature excursion to accumulate and report to the police for the result is more accurate, and the error is littleer, more is suitable for the detection of little leakage.

Description

Solar energy system
Technical Field
The present invention relates to solar energy systems, and more particularly to a solar energy system for detecting leakage.
Background
The present invention is an improvement in the scope of application based on the prior application of the present applicant. The solar energy collecting device is expanded to the field of solar energy.
The heat collecting pipe is a device for generating heat energy by utilizing solar energy. In the background art, when the solar energy is used for heating the heat collecting tube, the solar energy or the direct heating heat collecting tube or the steam is generated through secondary heat exchange, particularly the direct heating heat collecting tube, the convection heat exchange of the fluid at the upper part and the lower part of the heat collecting tube is carried out by utilizing the convection heat exchange in the heat collecting tube, but the lower part hot fluid is required to naturally convect to the upper part under the condition, and the heat exchange efficiency is low. And the leakage of the solar pipeline can directly cause the loss of a large amount of high-temperature media in the pipeline, and the environment is thermally polluted.
At present, few researches are carried out on a project of solar energy leakage detection, the project adopts a related technology of heat supply leakage detection, the heat supply leakage detection is applied to a solar energy system, and a novel solar energy system is provided. The heat source is fully utilized, and the energy consumption is reduced.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a novel solar energy system.
In order to achieve the purpose, the invention adopts the following technical scheme:
a solar energy system comprises a heat collector, a hot water tank and a pipeline for connecting the heat collector and the hot water tank, wherein the pipeline is provided with a plurality of connecting points, and the outsides of the connecting points are provided with heat insulation layers; detecting the thermal imager at the thermal insulation layer of the connection point, and detecting data of the position of the thermal insulation layer; calculating the change of temperature deviation cumulative sum at the same time of adjacent days, and triggering a node leakage alarm when the change exceeds a threshold value; the alarm mode is temperature deviation accumulation and alarm at the same time of adjacent days, namely the temperature deviation accumulation and alarm at the same time of adjacent days are calculated, and when the value of the accumulation sum exceeds a set threshold value, the temperature deviation accumulation and alarm are triggered.
Preferably, the thermal imager is arranged on the upright post.
Preferably, the data acquisition and monitoring step: monitoring and acquiring infrared video monitoring data and visible light video monitoring data at the connecting point by using a thermal imager;
a data transmission step: the system is communicated with a data acquisition and monitoring subsystem, and transmits infrared video data and visible light video data of a monitoring point to a server through optical fibers;
and (3) detecting the integrity of the heat insulation layer: judging the integrity of the heat insulation layer according to the visible light video data transmitted to the server;
a leakage confirmation step: and extracting corresponding infrared temperature field data of the image frames meeting the heat preservation integrity detection, calculating the temperature deviation accumulation sum of the adjacent days and the same time for the image frames meeting the heat preservation integrity detection, and triggering the temperature deviation accumulation sum to give an alarm when the value of the accumulation sum exceeds a set threshold value.
Preferably, in the leakage confirmation step, the alarm mode adopts the temperature offset accumulation and alarm at the same time of adjacent days, namely, the temperature monitoring data of the heat preservation layer at the connecting point of each day is set to select a calculation time every 2h from a zero point, the 12 calculation times are counted, then the data at the same time of the adjacent days form 12 groups of stable time data sequences, and the temperature offset accumulation and C of the data sequences at the same time of the adjacent days are calculatediWhen C is presentiWhen the value of (b) exceeds a set threshold value h, triggering temperature deviation accumulation and alarming, and the specific steps are as follows:
1) according to the heat preservation temperature monitoring data sequence x at the same time of adjacent daysiWhere i is 1,2, … n, the mean value of which is calculated
Figure BDA0002081857650000021
And variance
Figure BDA0002081857650000022
Normalizing a data sequence to yi＝(xi-μ0)/σ0；
2) The CUSUM cumulative sum parameter k is empirically chosen to be 1.376, and then the offset cumulative sum is calculated
Figure BDA0002081857650000023
Wherein the content of the first and second substances,
Figure BDA0002081857650000024
3) judgment of
Figure BDA0002081857650000025
Whether the value is greater than a set alarm threshold value h or not, if a certain value is greater than the set alarm threshold value h
Figure BDA0002081857650000026
The temperature deviation is accumulated and exceeds a threshold value at the moment, and an alarm is given;
4) and (4) performing manual intervention, namely performing alarm, accumulating and resetting temperature data offset, and restarting the next round of calculation and detection.
Preferably, the detection of the integrity of the insulating layer comprises the following steps:
defining a standard image frame of a heat insulation layer in the visible light video data under various working conditions of each monitoring point, and calling the standard image frame as a reference frame R;
1) calculating the average value mu of the gray scale of each reference frame according to the following formularAnd standard deviation of gray scaler；
Figure BDA0002081857650000027
Where M, N are image resolutions, IijRepresenting the gray value at the corresponding coordinate
2) One frame in the visible light monitoring video is taken, and the gray average value mu of the current image frame T is calculatedtAnd standard deviation of gray scalet；
3) Calculating the gray average value difference delta mu and the gray standard difference delta between the current image frame T and the corresponding reference image frame R;
4) when the value of the delta mu is larger than the set threshold value, taking the current frame as a suspected frame, and continuing the processing of the step 6); when the value of delta mu is smaller than the set threshold value, the current frame is a normal heat preservation layer frame, and the processing of the step 4) is continued;
5) for the suspected frame, the sum S of the absolute values of the number differences of the gray level pixels of each level of the current image frame T and the corresponding reference image frame R is continuously calculatedi，
Figure BDA0002081857650000028
If S isiWhen the value of the threshold value is larger than the set threshold value, the current frame is considered not to pass the heat insulation layer integrity detection, the frame is discarded, and the step 3) is returned to continue the processing of the next frame;
6) and if the image frames in the specified continuous time do not pass the integrity detection of the heat insulation layer, triggering an integrity abnormity alarm and informing a manager to carry out manual treatment.
Preferably, for the image frames meeting the heat preservation layer integrity detection, the accumulated sum of temperature deviation of the adjacent days and the same time is calculated, and when the accumulated sum of temperature deviation exceeds a threshold value, a node leakage alarm is triggered.
Preferably, a primary alarm, a secondary alarm and a tertiary alarm are set according to the size of the threshold h.
The invention has the following advantages:
1) the invention provides a novel solar system for intelligently detecting leakage, which monitors the change of an infrared temperature field of a node heat-insulating layer of the solar system in real time through a thermal infrared imager, and determines a node leakage accident by monitoring the abnormity of the heat-insulating layer at first and then adopting the temperature offset accumulation and alarm at the same time on adjacent days according to the temperature jump of the temperature field and the change of the temperature offset accumulation sum in an alarm mode, and alarms and informs a manager. Compared with the leakage detection method applied in the prior art, the method changes an alarm mode, adopts temperature deviation accumulation and alarm at the same time on adjacent days, enables the result to be more accurate, has smaller error and is more suitable for the detection of small leakage.
2) The invention provides a new idea for monitoring leakage by detecting the temperature change at the heat-insulating layer, and the novel idea is simple in structure and low in cost.
3) In order to ensure the reliability and accuracy of the method, the invention utilizes the visible light data monitored at the nodes to process the abnormal condition (damage or shielding) of the heat-insulating layer of the monitoring nodes, thereby avoiding the generation of false alarm.
Description of the drawings:
FIG. 1 illustrates a solar energy system of the present invention;
FIG. 2 shows a schematic view of a preferred embodiment of the collector of the present invention;
FIG. 3 shows a functional block diagram of a connection point leak real-time detection system based on infrared thermal imaging technology;
FIG. 4 shows a schematic engineering implementation diagram of a connection point leakage real-time detection system based on an infrared thermal imaging technology;
FIG. 5 is a flow chart illustrating an implementation of the connection point leakage real-time detection method based on the infrared thermal imaging technology;
FIG. 6 is a flowchart of an insulation layer integrity checking algorithm in the real-time connection point leakage detection method based on the infrared thermal imaging technology;
FIG. 7 is a flow chart of the current temperature difference alarm and 24-hour temperature deviation accumulation alarm algorithm in the real-time detection method for the leakage of the connection point based on the infrared thermal imaging technology;
FIG. 8 is a flowchart illustrating the algorithm of the present temperature difference alarm and the total 24 hour temperature offset accumulation alarm in the real-time connection point leakage detection method based on the infrared thermal imaging technology according to the present invention;
FIG. 9 is a flowchart of an adjacent-day-simultaneous-time temperature offset accumulation and alarm algorithm in the method for real-time detection of node leakage in a solar system based on infrared thermal imaging technology according to the present invention;
FIG. 10 is a flowchart of an algorithm for accumulating temperature offsets and alarming at the same time of adjacent days in the method for real-time detecting node leakage of a solar system based on infrared thermal imaging technology according to the present invention;
FIG. 11 is a flow chart of an alarm algorithm used in cooperation with a plurality of alarm modes in the real-time detection method for node leakage of a solar energy system based on an infrared thermal imaging technology;
fig. 12 shows a general algorithm flowchart used in cooperation with a plurality of alarm modes of the real-time detection method for node leakage of a solar system based on infrared thermal imaging technology.
Detailed Description
The present invention will now be described in further detail with reference to the accompanying drawings. The drawings are simplified schematic views illustrating the basic structure of the present invention only in a schematic manner, and thus show only the constitution related to the present invention,
fig. 1 discloses a solar energy system, which comprises a solar heat collector 5 and a heat utilization device 4, wherein a pipeline is connected between the heat collector and a hot water tank, the solar heat collector absorbs solar energy, heats fluid flowing through, and then the fluid enters the heat utilization device for utilization.
Preferably, an electric heating device is arranged in the heat collector, and the electric heating device is characterized in that the electric heating power is adjusted according to the surrounding environment.
Preferably, the ambient environment includes ambient temperature, light, season, and the like. For example, if the light becomes weak, the heating power increases, the temperature decreases, and the heating power increases in winter.
As shown in fig. 2, a trough solar collector 5 using heat pipes is disclosed, the collector includes a reflector 1 and a heat collecting pipe 2, the heat collecting pipe 2 is located at a focal position of the reflector 1, and the reflector 1 reflects solar energy to the heat collecting pipe 2 for heating water in the heat collecting pipe 2.
As preferred, the heat collector is still including setting up the heat pipe in thermal-collecting tube 2, as shown in fig. 2, the heat pipe sets up inside thermal-collecting tube 2, the heat pipe includes collection case 6 and heat dissipation end 3, collection case 6 sets up the bottom at thermal-collecting tube 2, heat dissipation end 3 and collection case 6 intercommunication, heat dissipation end 3 begins upwards to extend from collection case 6 upper portion wall, heat dissipation end 3 is many, the bottom of collection case 6 is connected on thermal-collecting tube 2's inner wall.
The connecting pipeline (comprising a heat collector hot water inlet pipe and a hot water return pipe) is provided with a plurality of connecting points, the outside of each connecting point is provided with a heat insulation layer, and a thermal imager is arranged at least one connecting point.
Preferably, as shown in fig. 2, the thermal imager is disposed at the thermal insulation layer, and detects data of the position of the thermal insulation layer. The thermal imager is arranged on the upright post.
The invention provides a novel solar pipeline system for intelligently detecting leakage.
The method of detection will be described in detail below.
Fig. 3 shows a schematic block diagram of a connection point leakage real-time detection system based on infrared thermal imaging technology.
As shown in fig. 3, the solar pipeline node leakage real-time detection system based on the infrared thermal imaging technology of the present invention includes:
the data acquisition and monitoring subsystem is used for acquiring and transmitting infrared video monitoring data and visible light video monitoring data at a connecting point (preferably an insulating layer) in real time;
the data transmission subsystem is used for communicating with the data acquisition and monitoring subsystem and transmitting the infrared video data and the visible light video data of the monitoring point to the server;
and the heat-insulating layer integrity detection subsystem judges whether the monitored point (preferably the heat-insulating layer) has damage and is shielded by utilizing the monitored visible light data, sends the data frames passing the integrity detection into the data processing and alarm subsystem, directly discards the data frames not passing the integrity detection, triggers the heat-insulating layer integrity abnormity alarm if the image frames in the specified continuous time do not pass the heat-insulating layer integrity detection, and informs a manager of manual processing.
And the infrared data processing and alarming subsystem acquires the temperature change jump or the accumulated trend of the temperature change by utilizing the monitored temperature field data of the infrared imaging through interframe comparison, and triggers the node leakage alarm when the temperature change jump or the accumulated trend of the temperature change exceeds a threshold value.
Fig. 4 shows an engineering implementation diagram of a solar system connection node leakage real-time detection system based on an infrared thermal imaging technology.
Engineering practice data show that: in the case of leakage of the solar system, the vast majority of the leakage occurs at the connection points. As shown in fig. 4, the infrared thermal image monitor is placed near the connection point (thermal insulation layer), the change information of the infrared temperature field at the monitoring point is transmitted to the server in real time through the optical fiber, and the server automatically monitors the occurrence of leakage in real time through the change of the temperature field and informs the manager.
Preferably, the invention also provides a connection point leakage real-time detection method based on the infrared thermal imaging technology. Fig. 5 shows a flow chart of an implementation of the connection point leakage real-time detection method based on the infrared thermal imaging technology, as shown in fig. 5, specifically including the following steps:
1) and extracting a frame of visible light image from the data transmitted from the monitoring point to the server, and carrying out heat preservation layer integrity detection according to the frame of visible light image. The infrared temperature field imaging is very easily influenced by surrounding objects or environments, abnormal conditions such as the absence and shielding of the insulating layer can be eliminated through the integrity check of the insulating layer, and the accuracy of infrared temperature field data transmitted back to the server from a monitoring point is ensured. The specific method of insulation integrity check will be described in detail later.
2) Directly discarding the data frame which does not pass the detection, and taking the next frame of visible light data;
3) and for the data frame passing the detection, extracting the infrared temperature field data corresponding to the frame, and determining whether the leakage condition occurs or not through threshold judgment. If yes, triggering a leakage alarm to inform relevant management personnel to process, otherwise, directly returning to the step 1) to continuously process the next frame data in the monitoring video. The specific method of infrared temperature field data threshold detection alarm will be explained in detail later.
The method for detecting the integrity of the insulating layer will be described in detail in this embodiment.
Infrared imaging data easily receives external environment influence, and the heat preservation integrality detects the damage that can get rid of the heat preservation, shelters from the abnormal conditions such as, guarantees follow-up infrared temperature field distribution that can accurately acquire the monitoring point department (preferably heat preservation). The detection of the integrity of the insulating layer is divided into two steps of suspected frame search and suspected frame confirmation by utilizing visible light data transmitted from a monitoring point to a server. The steps of suspected frame search are as follows:
1) defining a standard image frame of a heat insulation layer in the visible light video data of each monitoring point under various working conditions, wherein the standard image frame is called as a reference frame R;
2) calculating the average value mu of the gray scale of each reference frame according to the following formularAnd standard deviation of gray scaler；
Figure BDA0002081857650000061
Where M, N are image resolutions, IijRepresenting the gray value at the corresponding coordinate
3) One frame in the visible light monitoring video is taken, and the gray average value mu of the current image frame T is calculatedtAnd standard deviation of gray scalet；
4) Calculating the gray average value difference delta mu and the gray standard difference delta between the current image frame T and the corresponding reference image frame R;
5) when the value of the delta mu is larger than a set threshold value, taking the current frame as a suspected frame, and continuing to confirm the subsequent suspected frame; and (3) when the value of the delta mu is smaller than the set threshold value, the current frame is a normal heat preservation layer frame, and the processing of the step (3) is continued.
The steps of suspected frame confirmation are as follows:
1) for suspected frames, the current frame is continuously calculatedSum S of absolute values of differences of gray level pixels of each level of the image frame T and the corresponding reference image frame Ri，
Figure BDA0002081857650000062
If S isiWhen the value of the infrared data frame is larger than the set threshold value, the current frame is considered not to pass the detection of the integrity of the heat insulation layer, the infrared data frame corresponding to the current frame is discarded, and the suspected frame searching step 3) is returned;
2) and if the image frames in the continuous time do not pass the integrity detection of the heat insulation layer, triggering an integrity abnormity alarm and informing a manager to manually process the abnormity at the heat insulation layer.
Preferably, the infrared data processing and alarming method comprises the following steps: .
And extracting corresponding infrared temperature field data of the image frames meeting the heat preservation layer integrity detection, obtaining the temperature difference or the accumulation of temperature difference change through interframe comparison, and triggering a node leakage alarm when the temperature difference or the temperature difference change exceeds a threshold value. The method specifically comprises the following three alarm modes:
the method specifically comprises the following three alarm modes:
1) current temperature difference alarm
Calculating the current temperature field matrix T according to a set time interval (preferably 5min)iWith the temperature field matrix T of the previous framei-1Δ T ═ Ti-Ti-1And when the value of delta T exceeds a set threshold value, triggering a temperature difference alarm. And setting a first-level alarm, a second-level alarm and a third-level alarm according to the magnitude of the delta T value so as to realize rapid detection of the solar tube burst.
2)24 hour temperature offset accumulation and alarm
And calculating the change of the accumulated sum of the continuously monitored temperature offsets of the image frames meeting the integrity detection of the heat insulation layer within 24 hours, and triggering the node leakage alarm when the change exceeds a threshold value. The method specifically comprises the following steps:
① according to the heat preservation temperature monitoring data sequence x with 24 hours set time intervaliWhere i is 1,2, … n, the mean value of which is calculated
Figure BDA0002081857650000071
And variance
Figure BDA0002081857650000072
Normalizing a data sequence to yi＝(xi-μ0)/σ0。
② the CUSUM cumulative sum parameter k is 1.35, the value of h is set to different values according to three-level alarm, then the offset cumulative sum is calculated
Figure BDA0002081857650000073
Wherein the content of the first and second substances,
Figure BDA0002081857650000074
③ judgment
Figure BDA0002081857650000075
Whether the threshold value is larger than a set three-level alarm threshold value h or not, if a certain threshold value is larger than the set three-level alarm threshold value h
Figure BDA0002081857650000076
The temperature offset is considered to accumulate at that time and exceed the threshold and an alarm is issued. After the alarm occurs, the first-level alarm time is 15min, the second-level alarm time is 30min and the third-level alarm is kept in an alarm state unless manual intervention is performed.
Fourthly, the third-level alarm is subjected to artificial intervention prognosis, temperature data deviation accumulation and zero clearing, and calculation and detection are restarted.
And fifthly, starting from 0 to 24 hours every day, completing the detection task of the day, accumulating and automatically resetting, and simultaneously re-entering the detection and calculation of the next day.
When in use
Figure BDA0002081857650000079
When the value of (b) exceeds a set threshold value h, temperature offset accumulation and alarm are triggered. Preferably, according to the threshold h1The first-level alarm, the second-level alarm and the third-level alarm are set.
3) Temperature difference accumulation and alarm at the same time of adjacent days
And calculating the change of the temperature deviation cumulative sum of the adjacent days of the image frames meeting the heat preservation layer integrity detection, and triggering the node leakage alarm when the change exceeds a threshold value. Preferably, the method specifically comprises the following steps:
① according to the heat preservation temperature monitoring data sequence x at the same time (2h group, 12 groups in total) of adjacent daysiWhere i is 1,2, … n, the mean value of which is calculated
Figure BDA0002081857650000077
And variance
Figure BDA0002081857650000078
Normalizing a data sequence to yi＝(xi-μ0)/σ0。
② according to the experience, CUSUM cumulative sum parameter k is 1.376, the value of h is set to different values according to three-level alarm, then the offset cumulative sum is calculated
Figure BDA0002081857650000081
Wherein the content of the first and second substances,
Figure BDA0002081857650000082
③ judgment
Figure BDA0002081857650000083
Whether the threshold value is larger than a set three-level alarm threshold value h or not, if a certain threshold value is larger than the set three-level alarm threshold value h
Figure BDA0002081857650000084
The temperature offset is considered to accumulate at that time and exceed the threshold and an alarm is issued. After the alarm occurs, the first-level alarm time is 15min, the second-level alarm time is 30min and the third-level alarm is kept in an alarm state unless manual intervention is performed.
Fourthly, the third-level alarm is subjected to manual intervention, temperature data deviation accumulation and zero clearing, and the next round of calculation detection is restarted.
When in use
Figure BDA0002081857650000085
Value of (A) exceedsAnd when the set threshold h is exceeded, triggering temperature deviation accumulation and alarming. Preferably, according to the threshold h2The first-level alarm, the second-level alarm and the third-level alarm are set.
Preferably, the three alarm modes can be used in combination or independently.
Compared with the current temperature difference alarm in the background technology, the invention adopts a new alarm mode, and adopts the 24-hour temperature deviation accumulation and alarm and the adjacent day moment temperature deviation accumulation and alarm modes to further improve the accuracy of alarm and reduce errors.
Although the present invention has been described with reference to the preferred embodiments, it is not limited thereto. Various changes and modifications may be effected therein by one skilled in the art without departing from the spirit and scope of the invention as defined in the appended claims.
Application case
The thermal imager is arranged on an upright post with the height of 3.5 meters, is powered by a civil alternating current power supply and is connected with a server through an optical fiber. The vertical distance between the thermal imager and the solar heat-insulating layer is 3 meters, the horizontal distance is 1.5 meters, and the monitoring angle is about 30 degrees below the oblique direction. The surveillance video resolution was 384 × 288 and the frame rate was 12 frames/sec.
Other parameter settings for the thermal imager are shown in the following table:
parameter item Value range
Temperature range -20℃---150℃
Emissivity 0.81
Reflection temperature 5℃
Atmospheric temperature 10℃
Relative humidity 0.33
Transmittance of light 0.80
The thresholds used for the manhole cover integrity check are shown in the following table:
parameter item Threshold value
Mean difference in gray level Δ μ 30
Difference of gray scale standard deviation Δ δ 15
Sum of absolute values of difference of number of pixels per gradation level Si 5500
The temperature difference alarm threshold is shown in the following table:
alarm level Threshold value
First-level alarm 5
Two-stage alarm 8
Three-level alarm 12
The 24 hour temperature excursion accumulation and alarm thresholds are shown in the following table:
alarm level Threshold value h
First-level alarm 5
Two-stage alarm 10
Three-level alarm 15
The temperature offset accumulation and alarm thresholds for the same time of day on adjacent days are shown in the following table:
alarm level Threshold value h
First-level alarm 4
Two-stage alarm 8
Three-level alarm 12
Although the present invention has been described with reference to the preferred embodiments, it is not limited thereto. Various changes and modifications may be effected therein by one skilled in the art without departing from the spirit and scope of the invention as defined in the appended claims.

Claims (3)

1. A solar energy system leakage detection method is characterized in that a thermal imager is arranged at least one connecting point; the thermal imager is arranged at the heat insulation layer of the connection point and used for detecting data of the position of the heat insulation layer; calculating the change of temperature deviation cumulative sum at the same time of adjacent days, and triggering a node leakage alarm when the change exceeds a threshold value; the alarm mode is temperature deviation accumulation and alarm at the same time of adjacent days, namely the temperature deviation accumulation and alarm at the same time of adjacent days are calculated, and when the value of the accumulation sum exceeds a set threshold value, the temperature deviation accumulation and alarm are triggered;
the leak detection method includes the steps of:
data acquisition and monitoring: monitoring and acquiring infrared video monitoring data and visible light video monitoring data at the connecting point by using a thermal imager;
a data transmission step: the system is communicated with a data acquisition and monitoring subsystem, and transmits infrared video data and visible light video data of a monitoring point to a server through optical fibers;
and (3) detecting the integrity of the heat insulation layer: judging the integrity of the heat insulation layer according to the visible light video data transmitted to the server;
a leakage confirmation step: extracting corresponding infrared temperature field data of the image frames meeting the heat preservation layer integrity detection, calculating the temperature deviation accumulation sum of the image frames meeting the heat preservation layer integrity detection at the same time on adjacent days, and triggering the temperature deviation accumulation sum to alarm when the value of the accumulation sum exceeds a set threshold value;
in the leakage confirmation step, the alarm mode adopts the temperature offset accumulation and alarm at the same time of adjacent days, namely the temperature monitoring data of the heat preservation layer at the connecting point of each day is set to select a calculation time every 2h from a zero point, 12 times are counted, then the data at the same time of the adjacent days form 12 groups of stable time data sequences, and the temperature offset accumulation sum C of the data sequences at the same time of the adjacent days is calculatediWhen C is presentiWhen the value of (b) exceeds a set threshold value h, triggering temperature deviation accumulation and alarming, and the specific steps are as follows:
1) according to the heat preservation temperature monitoring data sequence x at the same time of adjacent daysiWhere i is 1,2, … n, the mean value of which is calculated
Figure FDA0002609837950000011
And variance
Figure FDA0002609837950000012
Normalizing a data sequence to yi＝(xi-μ0)/σ0；
2) The CUSUM cumulative sum parameter k is empirically chosen to be 1.35, and then the offset cumulative sum is calculated
Figure FDA0002609837950000013
Wherein the content of the first and second substances,
Figure FDA0002609837950000014
3) judgment of
Figure FDA0002609837950000015
Whether the value is greater than a set alarm threshold value h or not, if a certain value is greater than the set alarm threshold value h
Figure FDA0002609837950000016
The temperature deviation is accumulated and exceeds a threshold value at the moment, and an alarm is given;
4) the alarm is subjected to manual intervention, temperature data is subjected to deviation accumulation and zero clearing, and the next round of calculation detection is restarted;
the detection of the integrity of the heat-insulating layer comprises the following steps:
defining a standard image frame of a heat insulation layer in the visible light video data under various working conditions of each monitoring point, and calling the standard image frame as a reference image frame R;
1) calculating the average value mu of the gray scale of each reference image frame according to the following formularAnd standard deviation of gray scaler；
Figure FDA0002609837950000021
Where M, N are image resolutions, IijRepresenting the gray value at the corresponding coordinate
2) One frame in the visible light monitoring video is taken, and the gray average value mu of the current image frame T is calculatedtAnd standard deviation of gray scalet；
3) Calculating the gray average value difference delta mu and the gray standard difference delta between the current image frame T and the corresponding reference image frame R;
4) when the value of the delta mu is larger than the set threshold value, taking the current frame as a suspected frame, and continuing the processing of the step 5); when the value of delta mu is smaller than the set threshold value, the current frame is a normal heat preservation layer frame, and the processing of the step 2) is continued;
5) for the suspected frame, the current image frame T and the corresponding reference are continuously calculatedSum S of absolute values of difference of number of gray pixels of each level of image frame Ri，
Figure FDA0002609837950000022
If S isiWhen the value of the threshold value is larger than the set threshold value, the current frame is considered not to pass the heat insulation layer integrity detection, the frame is discarded, and the step 2) is returned to continue the processing of the next frame;
6) and if the image frames in the specified continuous time do not pass the integrity detection of the heat insulation layer, triggering an integrity abnormity alarm and informing a manager to carry out manual treatment.
2. The detection method according to claim 1, wherein for the image frames meeting the detection of the integrity of the heat insulation layer, the change of the cumulative sum of the temperature shifts of the image frames at the same time of the adjacent day is calculated, and when the change exceeds a threshold value, a node leakage alarm is triggered.
3. The detection method according to claim 2, wherein the primary alarm, the secondary alarm and the tertiary alarm are set according to the magnitude of the threshold h.
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