CN211375602U - Mobile intelligent noise live-action cloud picture modeling system for transformer substation - Google Patents
Mobile intelligent noise live-action cloud picture modeling system for transformer substation Download PDFInfo
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- CN211375602U CN211375602U CN201922288190.2U CN201922288190U CN211375602U CN 211375602 U CN211375602 U CN 211375602U CN 201922288190 U CN201922288190 U CN 201922288190U CN 211375602 U CN211375602 U CN 211375602U
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Abstract
The utility model provides a transformer substation mobile intelligent noise live-action cloud picture modeling system, wherein a positioning device is arranged at the top of a support rod of an intelligent mobile robot and is connected with a control main board; the acoustic measuring device is arranged on a supporting rod of the intelligent mobile robot and is connected with the control main board; the laser radar device is arranged on a support rod of the intelligent mobile robot and is connected with the control main board; the control main board is installed in the intelligent mobile robot and used for receiving the position coordinates collected by the positioning device, the noise sound pressure data collected by the acoustic measurement device and the point cloud data collected by the laser radar device and generating a noise live-action cloud picture. The utility model discloses an intelligent movement formula equipment carries out automatic on-line measuring to the transformer substation universe, through distribution and the size of each building of sensor perception and equipment to establish the unified global three-dimensional stereoscopic scene model of whole transformer substation and further improve transformer substation's radiation noise forecast precision.
Description
Technical Field
The utility model relates to a noise control implementation engineering field, in particular to portable intelligent noise live-action cloud picture modeling system of transformer substation.
Background
The transformer substation is used as a main noise pollution source of a city, and influences on physical and mental health of surrounding residents are not small, so that the noise control of the transformer substation becomes a problem to be solved urgently. Although the national power grid pays attention to the transformer substation noise control, and a great deal of manpower and financial resources are also invested to support the transformer substation noise control project, the actual effect is still not ideal from the current situation analysis after the noise control. One important reason is that the situation of the substation corresponding to the change of the global and the operation condition cannot be really known, and the noise control work of the existing substation cannot timely respond or predict the trend of the sound field changing along with the external conditions, so that the noise control project of the substation meets the national regulations in a certain time period (working condition), and the noise control project of the substation does not meet the requirements of the national regulations in another time period (working condition).
The existing noise sound field simulation technology at least has the following problems: (1) in the acoustic simulation of a substation, the most important data are an accurate three-dimensional stereo model of the substation field and a source intensity model. When the actual transformer substation is subjected to acoustic simulation, for part of transformer substations with longer service life, original construction data are lost, so that the layout size data of the transformer substation is difficult to acquire, and certain difficulties exist in adopting field manual size testing, such as incapability of acquiring high-altitude size and incapability of entering measurement in dangerous environment, and the like, so that an acoustic simulation model with accurate size is difficult to establish; (2) the determination of the intensity of the sound source model adopted in the simulation is also based on the actual measurement on the spot, and the unsteady characteristic that the sound field of the transformer substation changes along with the operation condition and the environmental influence factors causes that the intensity of the sound source model only reflects the test result, the simulation conclusion is only suitable for the current test state, and when the operation condition and the environmental influence factors change, the acoustic simulation result and the test result are often in a larger difference. (3) Models in the acoustic simulation are simplified to a certain extent, certain physical parameters need to be adjusted along with operating conditions and environmental factors, such as sound absorption coefficients and reflection coefficients of various physical interfaces, the results of the acoustic simulation are further corrected through continuous noise measurement, the consistency of the transformer substation simulation and the actual state is reflected, and the adaptability and pertinence of the transformer substation simulation are improved.
SUMMERY OF THE UTILITY MODEL
In order to overcome the defects, the utility model provides a portable intelligent noise live-action cloud picture modeling system of transformer substation improves the high matching nature between noise source model and the operating condition influence factor, improves the operating mode adaptability of transformer substation acoustics prediction and emulation, improves transformer substation noise prediction precision.
The technical scheme of the utility model:
a transformer substation mobile intelligent noise live-action cloud picture modeling system comprises an intelligent mobile robot, a power supply device, a robot driving device, a positioning device, an acoustic measuring device, a laser radar device, a driving wheel and a control main board,
the power supply device is arranged in the intelligent mobile robot and used for supplying power to the whole modeling system;
the robot driving device is installed in the intelligent mobile robot, connected with the power supply device, the driving wheel and the control main board and used for driving the intelligent mobile robot to move;
the positioning device is installed at the top of a support rod of the intelligent mobile robot and connected with the control main board, and is used for positioning the intelligent mobile robot in real time;
the acoustic measuring device is arranged on a support rod of the intelligent mobile robot and connected with the control main board to finish the collection of noise sound pressure data of the transformer substation;
the laser radar device is installed on a support rod of the intelligent mobile robot and connected with the control main board, and is used for acquiring point cloud data of equipment and buildings in a substation field;
the control main board is installed in the intelligent mobile robot and used for receiving the position coordinates collected by the positioning device, the noise sound pressure data collected by the acoustic measurement device and the point cloud data collected by the laser radar device and generating a noise live-action cloud picture.
The control mainboard is provided with a processing chip, the control chip comprises a data analysis management module, a noise simulation module and a live-action cloud picture generation module, the data analysis management module is connected with the positioning device, the acoustic measurement device and the laser radar device and used for receiving position coordinate data, noise sound pressure data and point cloud data and storing and managing the data, the noise simulation module is connected with the data analysis management module and used for simulating according to the noise sound pressure data to form a noise cloud picture, and the live-action cloud picture generation module is connected with the noise simulation module and used for generating a sound pressure space-time distribution diagram according to the position coordinate data, the noise sound pressure data and the point cloud data and overlapping the noise cloud picture to generate a noise live-action cloud picture.
The power supply device adopts a rechargeable lithium battery.
The positioning device is a Beidou positioning device or a GPS positioning device.
The acoustic measurement device employs a MEMS microphone.
The laser radar device adopts a Velarray series MEMS laser radar.
The control mainboard is provided with a core I7 processing chip, and ANSYS fluent software is solidified and installed in the processing chip for noise simulation and sound pressure space-time distribution diagram simulation.
Compared with the prior art, the beneficial effects of the utility model are that: the method comprises the steps of automatically detecting the universe of the transformer substation on line through intelligent mobile equipment, sensing the distribution and the size of each building and equipment through sensors, establishing a unified global three-dimensional scene model of the whole transformer substation, and simultaneously collecting and storing real sound pressure of each place in real time. The intelligent mobile equipment can automatically inspect and avoid obstacles according to the set task, continuously complete the monitoring task, realize the automation and the intellectualization of noise monitoring, overcome the problems that the manual operation is limited by the working time and the labor cost, the working fatigue and the like, and improve the reliability of monitoring. The noise space-time distribution graph can be drawn by using a global three-dimensional scene model established by the intelligent mobile equipment and sound pressure data acquired everywhere through the technologies of coordinate conversion, data processing and the like, the change rule of the sound pressure along with the path can be visually seen, the distribution state of a sound field of the transformer substation is truly embodied, the current situation of the noise of the transformer substation can be embodied by the space-time distribution rule of the sound pressure because the change rule is a real state and any artificial parameter setting does not exist, and the design of a noise control scheme of the transformer substation can be scientifically guided. Through continuous testing and noise space-time distribution diagram drawing throughout the year, the change condition of the transformer substation sound field along with the operation condition and the environmental influence factor can be clearly known, and the information is important for the noise management of the transformer substation. Based on a large amount of data accumulated by the noise continuous test, the relation between external influence factors and noise prediction model parameters is researched according to information such as seasons, operation loads and weather states, and the radiation noise prediction precision of the transformer substation is further improved.
Drawings
FIG. 1 is a schematic block diagram of the system of the present invention;
fig. 2 is the utility model discloses intelligent mobile robot schematic structure.
Detailed Description
The technical solutions in the embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments in the present invention, all other embodiments obtained by a person skilled in the art without creative work belong to the protection scope of the present invention.
Referring to fig. 1 and fig. 2, the present invention provides a technical solution:
a transformer substation mobile intelligent noise live-action cloud picture modeling system comprises an intelligent mobile robot 1, a power supply device 2, a robot driving device 3, a positioning device 4, an acoustic measuring device 5, a laser radar device 6, a driving wheel 10 and a control mainboard 11,
the power supply device 2 is arranged in the intelligent mobile robot 1 and used for supplying power to the whole modeling system;
the robot driving device 3 is installed in the intelligent mobile robot 1, connected with the power supply device 2, the driving wheel 10 and the control main board 11, and used for driving the intelligent mobile robot 1 to move;
the positioning device 4 is installed on the top of a support rod of the intelligent mobile robot 1 and connected with the control main board 11, is used for positioning the intelligent mobile robot 1 in real time, is used for controlling the intelligent mobile robot to walk in a substation field according to a set route, can stay at a planned measuring point to complete the acquisition of the point cloud data of the substation, and can record the coordinate value of the measuring point;
the acoustic measurement device 5 is installed on a support rod of the intelligent mobile robot 1 and connected with the control main board 11 to complete collection of noise sound pressure data of the transformer substation;
the laser radar device 6 is installed on a support rod of the intelligent mobile robot 1 and connected with the control main board 11, and is used for acquiring point cloud data of equipment and buildings in a substation field; the laser radar acquires the distribution and size information of buildings and equipment around the current position of the robot, extracts effective characteristic points from the information, matches the characteristic points to calculate a change matrix of the pose of the robot when the robot moves to the next position, and splices the two maps monitored by the positions into one map according to the calculated change matrix.
The control main board 11 is installed inside the intelligent mobile robot 1 and used for receiving the position coordinates collected by the positioning device 4, the noise sound pressure data collected by the acoustic measurement device 5 and the point cloud data collected by the laser radar device 6 and generating a noise live-action cloud picture.
The control mainboard 11 is provided with a processing chip, the control chip comprises a data analysis management module 7, a noise simulation module 8 and a real cloud picture generation module 9, the data analysis management module 7 is connected with the positioning device 4, the acoustic measurement device 5 and the laser radar device 6 and is used for receiving position coordinate data, noise sound pressure data and point cloud data and storing and managing the data, the noise simulation module 8 is connected with the data analysis management module 7, and the noise simulation module 8 is used for completing prediction and calculation of the transformer substation global sound field distribution; comparing the measured data of the transformer substation, and setting acoustic parameters: and correcting the material reflection coefficient, the material sound absorption coefficient, the diffraction boundary, the acoustic field point setting and the like, so that the noise simulation and the field actual measurement keep acceptable errors. And according to the noise sound pressure data, carrying out simulation to form a noise cloud picture, wherein the live-action cloud picture generation module 9 is connected with the noise simulation module 8 and used for generating a sound pressure space-time distribution map according to the position coordinate data, the noise sound pressure data and the point cloud data and overlapping the sound pressure space-time distribution map with the noise cloud picture to generate a noise live-action cloud picture, and displaying the distribution of noise in the substation field from the whole situation to make the noise 'visible'.
The power supply device 2 employs a rechargeable lithium battery.
The positioning device 4 is a Beidou positioning device or a GPS positioning device.
The acoustic measurement device 5 employs a MEMS microphone.
The lidar device 6 employs a velraray series MEMS lidar.
The control mainboard 11 is provided with a core I7 processing chip, and ANSYS Fluent software is fixedly arranged in the processing chip for carrying out noise simulation and sound pressure space-time distribution diagram simulation.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (5)
1. A transformer substation mobile intelligent noise live-action cloud picture modeling system is characterized by comprising an intelligent mobile robot (1), a power supply device (2), a robot driving device (3), a positioning device (4), an acoustic measuring device (5), a laser radar device (6), a driving wheel (10) and a control main board (11),
the power supply device (2) is arranged in the intelligent mobile robot (1) and used for supplying power to the whole modeling system;
the robot driving device (3) is installed in the intelligent mobile robot (1), connected with the power supply device (2), the driving wheel (10) and the control main board (11) and used for driving the intelligent mobile robot (1) to move;
the positioning device (4) is installed at the top of a support rod of the intelligent mobile robot (1) and connected with the control main board (11) and used for positioning the intelligent mobile robot (1) in real time;
the acoustic measurement device (5) is arranged on a support rod of the intelligent mobile robot (1) and connected with the control main board (11) to complete collection of noise sound pressure data of the transformer substation;
the laser radar device (6) is installed on a support rod of the intelligent mobile robot (1) and connected with the control main board (11) to achieve acquisition of point cloud data of equipment and buildings in the substation field;
the control main board (11) is installed in the intelligent mobile robot (1) and used for receiving position coordinates collected by the positioning device (4), noise sound pressure data collected by the acoustic measurement device (5) and point cloud data collected by the laser radar device (6) and generating a noise live-action cloud picture.
2. The substation mobile intelligent noise live-action cloud picture modeling system according to claim 1, characterized in that the power supply device (2) employs a rechargeable lithium battery.
3. The substation mobile intelligent noise live-action cloud picture modeling system according to claim 1, characterized in that the positioning device (4) is a Beidou positioning device or a GPS positioning device.
4. A substation mobile intelligent noise live-action cloud picture modeling system according to claim 1, characterized in that said acoustic measurement device (5) employs a MEMS microphone.
5. A substation mobile intelligent noise live-action cloud picture modeling system according to claim 1, characterized in that said lidar device (6) employs a MEMS lidar of the veilarray series.
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| CN201922288190.2U CN211375602U (en) | 2019-12-18 | 2019-12-18 | Mobile intelligent noise live-action cloud picture modeling system for transformer substation |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113139349A (en) * | 2021-05-12 | 2021-07-20 | 江西师范大学 | Method, device and equipment for removing atmospheric noise in InSAR time sequence |
| CN113239521A (en) * | 2021-04-20 | 2021-08-10 | 武汉理工大学 | Dynamic visual display method for transformer substation noise |
| CN113252165A (en) * | 2021-03-31 | 2021-08-13 | 国网河北省电力有限公司电力科学研究院 | Transformer substation noise monitoring method |
| CN114838810A (en) * | 2022-03-25 | 2022-08-02 | 武汉理工大学 | Inspection robot |
| CN115272560A (en) * | 2021-12-06 | 2022-11-01 | 中国电力科学研究院有限公司 | Three-dimensional sound field cloud picture based substation equipment hidden danger positioning method and system |
-
2019
- 2019-12-18 CN CN201922288190.2U patent/CN211375602U/en active Active
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113252165A (en) * | 2021-03-31 | 2021-08-13 | 国网河北省电力有限公司电力科学研究院 | Transformer substation noise monitoring method |
| CN113252165B (en) * | 2021-03-31 | 2022-06-14 | 国网河北省电力有限公司电力科学研究院 | Transformer substation noise monitoring method |
| CN113239521A (en) * | 2021-04-20 | 2021-08-10 | 武汉理工大学 | Dynamic visual display method for transformer substation noise |
| CN113139349A (en) * | 2021-05-12 | 2021-07-20 | 江西师范大学 | Method, device and equipment for removing atmospheric noise in InSAR time sequence |
| CN115272560A (en) * | 2021-12-06 | 2022-11-01 | 中国电力科学研究院有限公司 | Three-dimensional sound field cloud picture based substation equipment hidden danger positioning method and system |
| CN115272560B (en) * | 2021-12-06 | 2023-09-19 | 中国电力科学研究院有限公司 | Substation equipment hidden danger positioning method and system based on three-dimensional sound field cloud picture |
| CN114838810A (en) * | 2022-03-25 | 2022-08-02 | 武汉理工大学 | Inspection robot |
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