CN109974311B - Solar energy leakage detection system - Google Patents
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- CN109974311B CN109974311B CN201910224710.5A CN201910224710A CN109974311B CN 109974311 B CN109974311 B CN 109974311B CN 201910224710 A CN201910224710 A CN 201910224710A CN 109974311 B CN109974311 B CN 109974311B
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- 238000001514 detection method Methods 0.000 title claims description 29
- 238000005485 electric heating Methods 0.000 claims abstract description 11
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims abstract description 9
- 238000012544 monitoring process Methods 0.000 claims description 33
- 238000009413 insulation Methods 0.000 claims description 22
- 230000008859 change Effects 0.000 claims description 15
- 238000004321 preservation Methods 0.000 claims description 13
- 238000009825 accumulation Methods 0.000 claims description 12
- 239000011159 matrix material Substances 0.000 claims description 12
- 238000012545 processing Methods 0.000 claims description 10
- 230000005540 biological transmission Effects 0.000 claims description 4
- 238000012790 confirmation Methods 0.000 claims description 4
- CLOMYZFHNHFSIQ-UHFFFAOYSA-N clonixin Chemical compound CC1=C(Cl)C=CC=C1NC1=NC=CC=C1C(O)=O CLOMYZFHNHFSIQ-UHFFFAOYSA-N 0.000 claims description 3
- 230000001186 cumulative effect Effects 0.000 claims description 3
- 239000013307 optical fiber Substances 0.000 claims description 3
- 230000001960 triggered effect Effects 0.000 claims description 2
- 230000000694 effects Effects 0.000 abstract description 2
- 238000000034 method Methods 0.000 description 16
- 238000005516 engineering process Methods 0.000 description 10
- 238000001931 thermography Methods 0.000 description 10
- 238000011897 real-time detection Methods 0.000 description 9
- 238000010438 heat treatment Methods 0.000 description 5
- 238000010586 diagram Methods 0.000 description 4
- 239000012530 fluid Substances 0.000 description 4
- 230000017525 heat dissipation Effects 0.000 description 4
- 230000008569 process Effects 0.000 description 4
- 230000002159 abnormal effect Effects 0.000 description 3
- 238000003331 infrared imaging Methods 0.000 description 2
- 230000007423 decrease Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000005265 energy consumption Methods 0.000 description 1
- 239000008236 heating water Substances 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012827 research and development Methods 0.000 description 1
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- 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
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- 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
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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 an electric heating device is arranged in the heat collector and is used for adjusting electric heating power according to the surrounding environment. The invention provides a solar system, which can adjust the electric heating power according to the surrounding environment and achieve good energy-saving and environment-friendly effects.
Description
Technical Field
The present invention relates to solar energy systems, and more particularly to a solar energy system for detecting leakage.
Background
The invention is a research and development project cooperating with Shandong building university, and is an improvement on the application range based on the Shandong building university application (2019101982039). 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.
Aiming at the problems, the invention is improved on the basis of the prior invention, and provides a solar heat collecting pipe with a new structure, which makes full use of a heat source and reduces energy consumption.
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:
the utility model provides a solar energy system, includes heat collector, hot water tank and connects the pipeline of heat collector and hot water tank, set up electric heater unit in the heat collector, its characterized in that, electric heater unit adjusts electric heating power according to the surrounding environment.
Preferably, the ambient environment includes temperature, light, season, and the like.
Preferably, the thermal imager comprises a pipeline, the pipeline is provided with a plurality of connecting points, and an insulating layer is arranged outside the connecting points.
Preferably, the thermal imager is arranged on the upright post.
Preferably, the thermal imager is arranged at the heat preservation layer and used for detecting data of the position of the heat preservation layer.
A node leakage real-time detection method of a solar system comprises the following steps:
data acquisition and monitoring: monitoring and acquiring infrared video monitoring data and visible light video monitoring data at the heat insulation layer of the solar pipeline 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 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.
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 gray scale standard deviation deltar；
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 gray scale standard deviation deltat；
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 values of the Δ μ and the Δ δ are larger than the set threshold, taking the current frame as a suspected frame, and continuing the processing of the step 6); when the values of the delta mu and the delta are 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，
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 corresponding infrared temperature field data is extracted, the temperature difference or the temperature difference change accumulation is obtained through interframe comparison, and when the temperature difference or the temperature difference change accumulation exceeds a threshold value, a node leakage alarm is triggered.
Preferably, the following two alarm modes are specifically included:
and calculating the difference D between the current temperature field matrix P and the previous frame temperature field matrix Q as P-Q, and triggering temperature difference alarm when the value of D exceeds a set threshold value.
2) Temperature difference accumulation alarm
Sequentially calculating a current temperature field matrix PiWith the temperature field matrix Q of the previous framei-1Difference D ofi＝Pi-Qi-1And for n frames of temperature difference DiPerforming arithmetic cumulative summation
And when the value of Y exceeds a set threshold value, triggering a temperature difference accumulation alarm.
Preferably, a primary alarm, a secondary alarm and a tertiary alarm are set according to the size of the D value.
Preferably, a primary alarm, a secondary alarm and a tertiary alarm are set according to the size of the Y value.
The invention has the following advantages:
1) the novel solar system is provided, the electric heating power is adjusted according to the surrounding environment by arranging the electric heater, and good energy-saving and environment-friendly effects can be achieved.
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 shows a solar energy system of the present invention.
Figure 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 flowchart of an infrared temperature alarm algorithm in the real-time connection point leakage detection method based on infrared thermal imaging technology according to the present invention;
fig. 8 shows a general algorithm flow chart of the connection point leakage real-time detection method based on the infrared thermal imaging technology of the present invention.
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 the solar system of the present invention.
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 system comprises a data acquisition and monitoring subsystem, a data acquisition and monitoring subsystem and a data transmission subsystem, wherein 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 gray scale standard deviation deltar；
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 gray scale standard deviation deltat；
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 values of the delta mu and the delta are larger than a set threshold, taking the current frame as a suspected frame, and continuing to confirm the subsequent suspected frame; and (3) when the values of the delta mu and the delta are 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 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，
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 two alarm modes:
temperature difference alarm
And calculating the difference D between the current temperature field matrix P and the previous frame temperature field matrix Q as P-Q, and triggering temperature difference alarm when the value of D exceeds a set threshold value. And setting a first-level alarm, a second-level alarm and a third-level alarm according to the value of the D.
Temperature difference accumulation alarm
Sequentially calculating a current temperature field matrix PiWith the temperature field matrix Q of the previous framei-1Difference D ofi＝Pi-Qi-1And for n frames of temperature difference DiPerforming arithmetic cumulative summation
And when the value of Y exceeds a set threshold value, triggering a temperature difference accumulation alarm. And setting a first-level alarm, a second-level alarm and a third-level alarm according to the Y value.
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 leakage detection system comprises a heat collector, a hot water tank and a pipeline connecting the heat collector and the hot water tank, wherein an electric heating device is arranged in the heat collector, and the solar energy leakage detection system is characterized in that the electric heating device adjusts electric heating power according to the surrounding environment;
the system comprises a pipeline, wherein the pipeline is provided with a plurality of connecting points, an insulating layer is arranged outside the connecting points, and a thermal imager is arranged at least one connecting point;
the system comprises the following steps:
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: 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 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 frame R;
1) calculating the average value mu of the gray scale of each reference frame according to the following formularAnd gray scale standard deviation deltar；
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 gray scale standard deviation deltat；
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 values of the Δ μ and the Δ δ are larger than the set threshold, taking the current frame as a suspected frame, and continuing the processing of the step 5); when the values of the delta mu and the delta are 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 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，
If S isiIf the value of (1) is greater than the set threshold value, the current frame is considered not to pass the detection of the integrity of the heat insulation layer, the frame is discarded, and the step 3) is returned to continue the next frameThe treatment of (1);
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 system of claim 1, wherein for image frames meeting the thermal insulation layer integrity detection, corresponding infrared temperature field data is extracted, the temperature difference or the accumulation of temperature difference changes is obtained through inter-frame comparison, and when the temperature difference or the temperature difference changes exceed a threshold value, a node leakage alarm is triggered.
3. The system of claim 2, comprising in particular the following two alarm modes:
1) temperature difference alarm
And calculating the difference D between the current temperature field matrix P and the previous frame temperature field matrix Q as P-Q, and triggering temperature difference alarm when the value of D exceeds a set threshold value.
2) Temperature difference accumulation alarm
Sequentially calculating a current temperature field matrix PiWith the temperature field matrix Q of the previous framei-1Difference D ofi＝Pi-Qi-1And for n frames of temperature difference DiPerforming arithmetic cumulative summation
And when the value of Y exceeds a set threshold value, triggering a temperature difference accumulation alarm.
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