CN217033904U - Water quality monitoring equipment with long-term and short-term memory recurrent neural network - Google Patents
Water quality monitoring equipment with long-term and short-term memory recurrent neural network Download PDFInfo
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- CN217033904U CN217033904U CN202220752635.7U CN202220752635U CN217033904U CN 217033904 U CN217033904 U CN 217033904U CN 202220752635 U CN202220752635 U CN 202220752635U CN 217033904 U CN217033904 U CN 217033904U
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Abstract
The utility model relates to the technical field of water quality monitoring, and discloses water quality monitoring equipment with a long-term and short-term memory cyclic neural network. This water quality monitoring equipment with long short-term memory recurrent neural network, the pipeline drives connects the shell and removes about metal casing is inside, let the change of pipeline quick and convenient more, can spend a small amount of time to change the pipeline, increase the device live time, rotate hexagon socket head cap screw, hexagon socket head cap screw carries out the secondary with connecting block and metal casing and fixes, prevent that the pipeline is not hard up, when making pipeline transportation water, can avoid water to reveal, thereby increase the live time of pipeline.
Description
Technical Field
The utility model relates to the technical field of water quality monitoring, in particular to a water quality monitoring device with a long-term and short-term memory circulation neural network.
Background
The water quality monitoring is a process of monitoring and determining the types of pollutants in the water body, the concentrations and the variation trends of various pollutants, evaluating the water quality condition and effectively detecting the water quality, so that the drinking water health of people is protected, and the body safety of people can be protected.
However, the connection between the water pipe and the water quality monitoring device is used for a long time, the pipeline needs to be replaced, and when the pipeline is replaced, the pipeline is troublesome, and the pipeline needs to be detached in a large amount of time.
SUMMERY OF THE UTILITY MODEL
The present invention is directed to a water quality monitoring device with a long and short term memory recurrent neural network, so as to solve the problems mentioned in the background art.
In order to achieve the purpose, the utility model provides the following technical scheme: the utility model provides a water quality monitoring equipment with long short-term memory circulation neural network, includes check out test set and LED display screen, the door locking device is installed to the positive right-hand member of check out test set, the bottom skin weld of check out test set has fixed establishment, fixed establishment internal connection has coupling mechanism, the LED display screen is installed in the positive upper end of check out test set.
The fixing mechanism comprises a metal shell and a connecting device, a first spiral spring is installed inside the metal shell, a rubber cushion block is welded on the surface of the left side of the first spiral spring, a second spiral spring is welded on the upper end inside the metal shell, a fixing rod is welded on the upper end inside the metal shell, a polygonal clamping block is installed on the upper end inside the metal shell, and the metal shell is connected to the top surface of the connecting device.
Preferably, the connecting mechanism comprises a pipeline and a silica gel cushion block, the surface of the silica gel cushion block is provided with a connecting shell, the left side surface of the connecting shell is welded with a connecting block, and the silica gel cushion block is connected to the upper end surface of the pipeline.
Preferably, the pipeline is connected inside the connecting device, the connecting device is connected to the upper end of the water outlet device, the water outlet device is connected to the top end surface of the pipeline, the pipeline is connected to the left end of the metal shell, the metal shell is welded to the bottom end surface of the detection device, the pipeline moves inside the metal shell, meanwhile, the upper end of the pipeline moves inside the connecting device, the top end surface of the pipeline is connected with the bottom end surface of the water outlet device, and water can be transported.
Preferably, the left end of connecting block is connected with hexagon socket head cap screw, hexagon socket head cap screw connects in metal casing's left end, the connecting block is connected in the lower terminal surface of polygon fixture block, the connecting block is pegged graft inside metal casing, the connecting block is connected in the right side surface of rubber cushion, rotates hexagon socket head cap screw, and hexagon socket head cap screw carries out the secondary with metal casing and connecting block and fixes, can increase the device's live time, can avoid the pipeline not hard up simultaneously.
Preferably, the polygonal fixture blocks are connected to the bottom end surface of the second spiral spring and connected to the surface of the fixing rod, the number of the polygonal fixture blocks is two, the two polygonal fixture blocks are connected to the left end and the right end of the inside of the metal shell, the second spiral spring begins to rebound, the second spiral spring pushes the polygonal fixture blocks to move up and down inside the metal shell, and the polygonal fixture blocks are clamped into the connecting block.
Preferably, the quantity of dead lever is four, two one set of, two sets of dead lever is connected in metal casing's left end and right-hand member, two the dead lever is connected in the left end and the right-hand member of polygon fixture block, and two dead levers are connected in the left side and the right side of coil spring two, and the dead lever can let the polygon fixture block reciprocate in metal casing inside, can keep the balance of polygon fixture block simultaneously, conveniently lets the polygon fixture block remove.
Preferably, the quantity of silica gel cushion is two, two the silica gel cushion is connected in the front and the back of pipeline, the pipe connection is inside connecting the shell, connect the shell and connect inside the metal casing, the silica gel cushion can increase the pipeline and connect the frictional force between the shell to increase the live time of the device.
Preferably, the quantity of pipeline is two, two the pipeline is connected in inside left end and the right-hand member of metal casing, the pipeline is connected inside connecting device, and two pipelines can more effectual transportation water to can increase the device's live time, conveniently change the pipeline simultaneously.
Compared with the prior art, the utility model has the beneficial effects that:
1. this water quality monitoring equipment with long short-term memory cyclic neural network, the pipeline drives and connects the shell and remove about metal casing is inside, lets the change of pipeline more quick and convenient, can spend a small amount of time to change the pipeline, increases the device live time.
2. This water quality monitoring equipment with long short-term memory recurrent neural network rotates hexagon socket head cap screw, and hexagon socket head cap screw is fixed connecting block and metal casing, prevents that the pipeline is not hard up for when pipeline transportation water, can avoid water to reveal.
Drawings
FIG. 1 is a schematic front view of the structure of the present invention;
FIG. 2 is a schematic view of the front view of the internal structure of the present invention;
FIG. 3 is a schematic view of the structural coupling mechanism of the present invention taken from the top view of the internal structure;
FIG. 4 is a schematic view of the internal structure of the fixing mechanism of the present invention;
fig. 5 is a partially enlarged view of the structure at a in fig. 4 according to the present invention.
In the figure: 1. a detection device; 2. an LED display screen; 3. a fixing mechanism; 301. a metal housing; 302. a first coil spring; 303. a connecting device; 304. a water outlet device; 305. a fixing rod; 306. a rubber cushion block; 307. a polygonal fixture block; 308. a second spiral spring; 4. a connecting mechanism; 401. a pipeline; 402. a silica gel cushion block; 403. a connecting housing; 404. connecting blocks; 5. provided is a door lock device.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
Referring to fig. 1-5, the present invention provides a technical solution: the utility model provides a water quality monitoring equipment with long short-term memory recurrent neural network, includes check out test set 1 and LED display screen 2, and door locking device 5 is installed to the positive right-hand member of check out test set 1, and the bottom skin weld of check out test set 1 has fixed establishment 3, and the inside swing joint of fixed establishment 3 has coupling mechanism 4, and LED display screen 2 is installed in the positive upper end of check out test set 1.
The fixing mechanism 3 comprises a metal shell 301 and a connecting device 303, a first coil spring 302 is installed inside the metal shell 301, a rubber cushion block 306 is welded on the left side surface of the first coil spring 302, a second coil spring 308 is welded on the upper end inside the metal shell 301, a polygonal fixture block 307 is fixedly connected to the bottom end surface of the second coil spring 308, the polygonal fixture block 307 is movably connected to the surface of the fixing rod 305, the number of the polygonal fixture blocks 307 is two, the two polygonal fixture blocks 307 are movably connected to the left end and the right end inside the metal shell 301, the second coil spring 308 starts to rebound, the polygonal fixture block 307 is pushed by the second coil spring 308 to move up and down inside the metal shell 301, the polygonal fixture block 307 is clamped into the connecting block 404, the fixing rod 305 is welded on the upper end inside the metal shell 301, the polygonal fixture block 307 is installed on the upper end inside the metal shell 301, and the metal shell 301 is fixedly connected to the top end surface of the connecting device 303, the number of the fixing rods 305 is four, two fixing rods 305 are one set, two sets of fixing rods 305 are connected to the left end and the right end of the metal casing 301, the two fixing rods 305 are movably connected to the left end and the right end of the polygonal clamping block 307, the two fixing rods 305 are fixedly connected to the left side and the right side of the second coil spring 308, the fixing rods 305 can enable the polygonal clamping block 307 to move up and down in the metal casing 301, meanwhile, the balance of the polygonal clamping block 307 can be kept, and the polygonal clamping block 307 can be moved conveniently.
The connecting mechanism 4 comprises a pipeline 401 and a silica gel cushion block 402, the pipeline 401 is movably connected inside the connecting device 303, the connecting device 303 is fixedly connected to the upper end of the water outlet device 304, the water outlet device 304 is movably connected to the top end surface of the pipeline 401, the pipeline 401 is movably connected to the left end of the metal shell 301, the metal shell 301 is welded to the bottom end surface of the detection device 1, the pipeline 401 moves inside the metal shell 301, meanwhile, the upper end of the pipeline 401 moves inside the connecting device 303, so that the top end surface of the pipeline 401 is connected with the bottom end surface of the water outlet device 304, water can be transported, the connecting shell 403 is mounted on the surface of the silica gel cushion block 402, the connecting block 404 is welded on the left side surface of the connecting shell 403, the left end of the connecting block 404 is movably connected with an inner hexagon bolt, the inner hexagon bolt is movably connected to the left end of the metal shell 301, the connecting block 404 is movably connected to the lower end surface of the polygon 307, the connecting block 404 is inserted into the metal shell 301, the connecting block 404 is movably connected to the right side surface of the rubber cushion block 306, the inner hexagon bolts are rotated to secondarily fix the metal shell 301 and the connecting block 404, the service life of the device can be prolonged, meanwhile, looseness of the pipeline 401 can be avoided, the silica gel cushion blocks 402 are movably connected to the upper end surface of the pipeline 401, the number of the silica gel cushion blocks 402 is two, the two silica gel cushion blocks 402 are movably connected to the front surface and the back surface of the pipeline 401, the pipeline 401 is movably connected into the connecting shell 403, the connecting shell 403 is movably connected into the metal shell 301, the silica gel cushion blocks 402 can increase friction force between the pipeline 401 and the connecting shell 403, so that the service life of the device is prolonged, the number of the pipelines 401 is two, the two pipelines 401 are connected to the left end and the right end inside the metal shell 301, the pipeline 401 is connected into the connecting device 303, two pipelines 401 can transport water more effectively, so that the service time of the device can be prolonged, and the pipelines 401 can be replaced conveniently.
The first step is as follows: the inlet and outlet water quality data which is provided by a certain sewage treatment plant for five years and is 8760 hours in total is extracted as a training set.
The second step is that: the relation of various parameters of inlet and outlet water quality is analyzed by a PCA method, dimension reduction treatment is carried out on the dimension of the input water quality parameter, and a plurality of parameters with the total number of influence factors exceeding 95% are reserved.
The third step: the training is concentrated into an input unit every n hours in the water quality data of the inlet water (the internal circulation time of the sewage treatment system is n hours), and the input unit slides for one hour each time by adopting a time sliding window, and the input unit is input into the LSTM neural network in batches to train the network.
The fourth step: the trained LSTM network is tested by using the test set, and whether the effluent quality of the sewage treatment is qualified or not can be accurately predicted.
In recent years, an LSTM network which is excellent in performance in a time prediction task is modeled, so that the output water quality of sewage can be accurately predicted; and the data is analyzed by a PCA method, only important sensor parameters are reserved, and the detection efficiency is greatly improved.
When the device is used, the upper end of the pipeline 401 is held, the pipeline 401 is pushed upwards, the pipeline 401 is inserted into the connecting shell 403, the surface of the pipeline 401 is connected with the surface inside the silica gel cushion block 402, the lower end of the pipeline 401 is held at the moment, the pipeline 401 is pushed to move left and right, the pipeline 401 drives the connecting block 404 to be inserted into the metal shell 301, meanwhile, the pipeline 401 can move left and right inside the metal shell 301, the connecting block 404 pushes the rubber cushion block 306 to move left and right, the rubber cushion block 306 starts to compress the second spiral spring 308 to move, the connecting block 404 pushes the second polygonal fixture block 307 to move upwards, the second polygonal fixture block 307 starts to compress the second spiral spring 308, the polygonal fixture block 307 moves on the surface of the fixing rod 305, the polygonal fixture block 307 moves up and down inside the metal shell 301, meanwhile, the connecting device 303, which is arranged inside the metal shell 301, of the upper end of the pipeline 401 moves, so that the top end surface of the pipeline 401 is connected with the bottom end surface of the water outlet device 304, when unable removal, two 308 of coil spring begin to kick-back, two 308 of coil spring promote polygon fixture block 307, and polygon fixture block 307 reciprocates inside metal casing 301, and polygon fixture block 307 joint gets into connecting block 404, with connecting block 404 preliminary fixed, at this moment upwards rotates hexagon socket head cap screw, and hexagon socket head cap screw is with metal casing 301 and connecting block 404 preliminary fixed to fix pipeline 401.
Claims (8)
1. The utility model provides a water quality monitoring equipment with long short-term memory recurrent neural network, includes check out test set (1) and LED display screen (2), its characterized in that: the LED display screen detection device is characterized in that a door lock device (5) is installed at the right end of the front face of the detection device (1), a fixing mechanism (3) is welded on the surface of the bottom end of the detection device (1), a connecting mechanism (4) is connected inside the fixing mechanism (3), and the LED display screen (2) is installed at the upper end of the front face of the detection device (1);
fixing mechanism (3) include metal casing (301) and connecting device (303), the inside coil spring (302) of installing of metal casing (301), the left side skin weld of coil spring (302) has rubber cushion (306), the inside upper end welding of metal casing (301) has coil spring two (308), the inside upper end welding of metal casing (301) has dead lever (305), polygon fixture block (307) are installed to the inside upper end of metal casing (301), metal casing (301) are connected in the top surface of connecting device (303).
2. The water quality monitoring device with the long-short term memory circulation neural network as claimed in claim 1, wherein: coupling mechanism (4) include pipeline (401) and silica gel cushion block (402), the surface mounting of silica gel cushion block (402) has connection shell (403), the left side skin weld who connects shell (403) has connecting block (404), silica gel cushion block (402) are connected in pipeline (401) upper end surface.
3. The water quality monitoring device with the long-short term memory recurrent neural network as claimed in claim 2, wherein: the pipeline (401) is connected to the inside of the connecting device (303), the connecting device (303) is connected to the upper end of the water outlet device (304), the water outlet device (304) is connected to the top end surface of the pipeline (401), the pipeline (401) is connected to the left end of the metal shell (301), and the metal shell (301) is welded to the bottom end surface of the detection device (1).
4. The water quality monitoring device with the long-short term memory circulation neural network as claimed in claim 3, wherein: the left end of the connecting block (404) is connected with an inner hexagonal bolt, the inner hexagonal bolt is connected to the left end of the metal shell (301), the connecting block (404) is connected to the lower end surface of the polygonal fixture block (307), the connecting block (404) is inserted into the metal shell (301), and the connecting block (404) is connected to the right side surface of the rubber cushion block (306).
5. The water quality monitoring device with the long-short term memory recurrent neural network as claimed in claim 1, wherein: the two polygonal fixture blocks (307) are connected to the bottom end surface of the second spiral spring (308), the two polygonal fixture blocks (307) are connected to the surface of the fixing rod (305), and the two polygonal fixture blocks (307) are connected to the left end and the right end of the inner portion of the metal shell (301).
6. The water quality monitoring device with the long-short term memory recurrent neural network as claimed in claim 5, wherein: the number of the fixing rods (305) is four, two fixing rods (305) are one group, two groups of fixing rods (305) are connected to the left end and the right end of the metal shell (301), two fixing rods (305) are connected to the left end and the right end of the polygonal fixture block (307), and two fixing rods (305) are connected to the left side and the right side of the second spiral spring (308).
7. The water quality monitoring device with the long-short term memory circulation neural network as claimed in claim 2, wherein: the number of the silica gel cushion blocks (402) is two, the two silica gel cushion blocks (402) are connected to the front face and the back face of the pipeline (401), the pipeline (401) is connected to the inside of the connecting shell (403), and the connecting shell (403) is connected to the inside of the metal shell (301).
8. The water quality monitoring device with the long-short term memory circulation neural network as claimed in claim 2, wherein: the number of the pipelines (401) is two, the two pipelines (401) are connected to the left end and the right end inside the metal shell (301), and the pipelines (401) are connected inside the connecting device (303).
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| CN202220752635.7U CN217033904U (en) | 2022-04-02 | 2022-04-02 | Water quality monitoring equipment with long-term and short-term memory recurrent neural network |
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| CN202220752635.7U CN217033904U (en) | 2022-04-02 | 2022-04-02 | Water quality monitoring equipment with long-term and short-term memory recurrent neural network |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117192063A (en) * | 2023-11-06 | 2023-12-08 | 山东大学 | Water quality prediction method and system based on coupled Kalman filtering data assimilation |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117192063A (en) * | 2023-11-06 | 2023-12-08 | 山东大学 | Water quality prediction method and system based on coupled Kalman filtering data assimilation |
| CN117192063B (en) * | 2023-11-06 | 2024-03-15 | 山东大学 | Water quality prediction method and system based on coupled Kalman filtering data assimilation |
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Effective date of registration: 20221213 Address after: 518000 Unit 3510-260, Luohu Business Center, No. 2028, Shennan East Road, Chengdong Community, Dongmen Street, Luohu District, Shenzhen, Guangdong Patentee after: Gulfstream smart environment (Shenzhen) Co.,Ltd. Patentee after: Gulfstream Ecological Environment Management (Guangdong) Co.,Ltd. Address before: 518000 C, floor 3, plant 2, YUDAFU Industrial Park, No. 10, Xingye West Road, Heyi community, Shajing street, Bao'an District, Shenzhen, Guangdong Province Patentee before: Gulfstream smart environment (Shenzhen) Co.,Ltd. |
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