CN215581191U - Wireless private network electromagnetic interference monitoring device based on artificial intelligence - Google Patents
Wireless private network electromagnetic interference monitoring device based on artificial intelligence Download PDFInfo
- Publication number
- CN215581191U CN215581191U CN202122501215.XU CN202122501215U CN215581191U CN 215581191 U CN215581191 U CN 215581191U CN 202122501215 U CN202122501215 U CN 202122501215U CN 215581191 U CN215581191 U CN 215581191U
- Authority
- CN
- China
- Prior art keywords
- module
- signal
- wireless
- wireless signal
- electromagnetic interference
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Landscapes
- Monitoring And Testing Of Transmission In General (AREA)
Abstract
The utility model relates to a wireless private network electromagnetic interference monitoring device based on artificial intelligence, which comprises a wireless signal receiving module, wherein the wireless signal receiving module sends a received wireless signal to a preprocessing module, a microprocessor module receives the preprocessed wireless signal sent by the preprocessing module, stores the processed wireless signal in a data storage module and sends an instruction to a wireless signal spectrum characteristic extraction module, the wireless signal spectrum characteristic extraction module sends wireless signal spectrum characteristic information to the artificial intelligence signal characteristic processing module, the artificial intelligence signal characteristic processing module simultaneously sends a characteristic processing signal to a signal positioning resolving module and an electromagnetic interference signal warning module, and the signal positioning resolving module and the electromagnetic interference signal warning module transmit a positioning signal and an early warning signal to a wireless remote communication module. The utility model can improve the timely control characteristics of signal data processing and result pre-judgment of the interference monitoring site.
Description
Technical Field
The utility model belongs to the technical field of information communication, and particularly relates to a wireless private network electromagnetic interference monitoring device based on artificial intelligence.
Background
At present, in the industry fields such as rail transit, medical treatment, scientific and technological research, mainly adopt the wireless communication technology of 1.8GHz frequency channel to realize data acquisition and transmission, as the frequency spectrum resource of public use simultaneously, often there are service conditions such as same frequency channel and adjacent frequency channel of different trades, different business, thereby produce the radio interference condition, will exert an influence to the required receiving signal's of radio communication receipt, lead to the radio communication performance to descend, the quality deteriorates, information error or lose, the going on of communication has even been blocked.
The existing wireless electromagnetic interference monitoring device is mainly realized by collecting field wireless electromagnetic signals, remotely transmitting wireless signal data and analyzing the back end of the data, the comprehensive monitoring efficiency of field multi-frequency band and multi-frequency point is limited, the timely responsiveness to data remote transmission and processing is limited, the application requirement of timely discovery and supervision after wireless electromagnetic interference monitoring to reduce loss cannot be met, and in the aspect of data analysis and processing, the collection and aggregation of the data cannot realize the learning and use of historical data.
SUMMERY OF THE UTILITY MODEL
The utility model aims to provide an artificial intelligence-based wireless private network electromagnetic interference monitoring device, which can realize electromagnetic interference monitoring and real-time alarming on a 1.8GHz wireless private network frequency band, improves the edge side intelligent processing control capability and signal data processing analysis and transmission efficiency of wireless electromagnetic signal monitoring, and solves the problems of difficult detection, untimely alarming, inconvenient outdoor use, low monitoring precision, unavailable application of historical data and the like of the existing electric power 1.8GHz wireless private network interference signal.
In order to achieve the purpose, the utility model adopts the following technical scheme:
an electromagnetic interference monitoring device of a wireless private network based on artificial intelligence comprises a wireless signal receiving module, the wireless signal receiving module sends the received wireless signal to the preprocessing module, the microprocessor module receives the preprocessed wireless signal sent by the preprocessing module and stores the processed wireless signal in the data storage module, and sends instructions to the wireless signal spectrum characteristic extraction module, the wireless signal spectrum characteristic extraction module sends the wireless signal spectrum characteristic information to the artificial intelligent signal characteristic processing module, the artificial intelligence signal characteristic processing module sends the characteristic processing signal to the signal positioning resolving module, the electromagnetic interference signal warning module and the data storage module at the same time, the signal positioning resolving module, the electromagnetic interference signal warning module and the data storage module are transmitted to the wireless remote communication module.
Further, the device is connected with a power supply module.
Preferably, the power supply module comprises a power module, a storage battery power supply module and/or a photovoltaic power supply module, and the photovoltaic power supply module comprises an external photovoltaic panel module and a photovoltaic interface power supply conversion module.
Furthermore, the preprocessing module comprises a wireless signal amplifying module and a wireless signal frequency mixing filtering module which are connected in sequence, the wireless signal receiving module receives wireless signals and sends the wireless signals to the wireless signal amplifying module, and the wireless signal frequency mixing filtering module sends the preprocessed signals after amplification, frequency mixing and filtering to the microprocessor module.
Further, the electromagnetic interference signal warning module comprises an acoustic warning and/or a luminous warning.
Preferably, the wireless remote communication module includes a wireless communication interface of a 4G public network and a 1.8G wireless private network frequency band of an operator.
The utility model has the beneficial effects that:
according to the technical scheme, the wireless signal receiving module is adopted to collect wireless signals under multiple application scenes, all wireless electromagnetic signals in a field environment are received in real time, preprocessing of the collected signals is completed through the microprocessor module with signal calculation processing and control, the signal amplification, frequency mixing and filtering module, extraction of characteristic information such as amplitude, phase, in-phase component and quadrature component of the preprocessed signals is achieved in a wireless signal spectrum characteristic extraction mode, real-time comprehensive comparison and analysis are conducted on target frequency bands, frequency point data and historical interference monitoring data stored in the data storage module through the artificial intelligent signal characteristic processing module, acousto-optic alarm after interference is monitored in a mode of being close to a field interference source is achieved, the position distance of the interference source from the monitoring device is calculated at the same time, and the output position result is obtained, The interference result is transmitted to a far-end background in a wireless remote transmission mode, in addition, in order to meet the requirements of continuous monitoring and real-time monitoring under an outdoor scene, the photovoltaic panel module, the storage battery power supply module, the power supply module and the photovoltaic interface power supply conversion module which is specifically used according to photovoltaic power supply under the outdoor scene are adopted, the power supply adaptation problem under the outdoor scene is met, and due to the technical characteristics of wireless signal receiving, wireless signal processing, wireless signal artificial intelligence analysis, interference signal warning and the like, the wireless frequency use permission management system can be efficiently applied to the industry field of obtaining radio frequency use permission repetition such as rail transit, energy, medical treatment, scientific research and the like, and the processing timeliness of the interference of the used 1.8GHz frequency band, the real-time performance of warning, the accuracy of historical analysis, the data transmission reliability and the like are improved.
Drawings
FIG. 1 is a system diagram of an artificial intelligence-based wireless private network electromagnetic interference monitoring device according to the present invention;
fig. 2 is a configuration diagram of a power supply module of the present invention.
Description of reference numerals: 1-external photovoltaic panel module, 2-photovoltaic interface power supply conversion module, 3-storage battery power supply module, 4-power supply module, 5-wireless signal receiving module, 6-wireless signal amplification module, 7-wireless signal frequency mixing filtering module, 8-microprocessor module, 9-wireless signal frequency spectrum feature extraction module, 10-artificial intelligent signal feature processing module, 11-signal positioning calculation module, 12-electromagnetic interference signal warning module, 13-data storage module, 14-wireless remote communication module, A-power supply module, B-power supply module, C-2-wireless signal processing module, C-power supply module, C-9-wireless signal frequency spectrum feature extraction module, C-electromagnetic interference signal processing module, C-electromagnetic interference signal alarm module, C-power supply module, C-3-wireless signal processing module, C-wireless signal,
B-a pretreatment module.
Detailed Description
The wireless private network electromagnetic interference monitoring device based on artificial intelligence is further described in detail below with reference to the accompanying drawings and specific implementation methods.
Firstly, it should be noted that all modules used in the present invention are existing modules, and only the connection structure is designed, and the improvement in program algorithm is not involved. As shown in fig. 1, the wireless private network electromagnetic interference monitoring device based on artificial intelligence in this embodiment includes a microprocessor module 8 for signal calculation processing and control, a data storage module 13, a wireless signal receiving module 5, a wireless signal amplifying module 6, a wireless signal mixing filtering module 7, a wireless signal spectrum feature extracting module 9, an artificial intelligence signal feature processing module 10, an electromagnetic interference signal warning module 12, a signal positioning calculating module 11, and a wireless remote communication module 14, wherein the wireless signal receiving, amplifying and filtering module is interactively connected with the microprocessor module 8 with signal calculation processing and control capability to realize preprocessing of received wireless electromagnetic signals such as amplification, mixing, filtering, etc., the wireless signal spectrum feature extracting module 9 extracts characteristic information such as amplitude, phase, in-phase component, and quadrature component of the wireless electromagnetic signals, the extracted information is synchronously stored in a data storage module 13, the extracted characteristic information is comprehensively compared and analyzed with target frequency band and frequency point information stored in the data storage module 13 through an artificial intelligence signal characteristic processing module 10, a monitored interference signal result is subjected to real-time acousto-optic alarm through an electromagnetic interference signal alarm module 12, the position calculation of an emission point of an interference signal source is realized for analysis through the positioning of a received wireless electromagnetic signal, and the calculation result and the interference monitoring result are remotely transmitted through a wireless remote communication module 14.
The data storage module 13 may select a Flash memory or a TF card or a memory hard disk connected with the data processing, and is configured to store the wireless private network electromagnetic interference signal monitoring frequency point information set in the early stage, and send the information to the microprocessor module to complete the calculation processing and control of the signal.
The wireless signal receiving module 5 may be of a model ML7820-E5, and is composed of a plurality of antenna chips, a baseband processing unit and related circuits, and specifically includes a 1.8GHz band wireless module, and simultaneously sends the received wireless signal to the wireless signal amplifying module 6 and the wireless signal mixing filtering module 7 through a feeder line.
The model of the wireless signal amplifying module 6 is LX102, and is used for amplifying the received wireless signal and transmitting the amplified wireless signal to the wireless signal mixing filter module 7 through the feeder circuit.
The model number of the wireless signal frequency mixing and filtering module 7 is RX3310A, and the wireless signal frequency mixing and filtering module 7 is configured to perform frequency mixing and filtering processing on the received signal, and send the processed signal to the wireless signal frequency spectrum feature extraction module 9.
The wireless signal spectrum feature extraction module 9 selects the type of RSA320, and is used to extract the features of the signals after the frequency mixing filtering, extract the feature information such as amplitude, phase, in-phase component, and quadrature component, and is used to perform comprehensive feature analysis on the received wireless signals, and transmit the extracted wireless signal spectrum features to the data storage module 13 and the artificial intelligence signal feature processing module 10.
The artificial intelligence signal characteristic processing module 10 is of a type RK1808, and is used for comparing and analyzing the spectrum characteristic of the wireless signal with the spectrum characteristic of the wireless signal of a target frequency band in the data storage module 13, and not comparing the spectrum characteristic at the same frequency point, and transmitting the processed data to the data storage module 13 for storage, so as to be used for efficient monitoring and processing analysis during later signal monitoring, and simultaneously transmitting the data to the electromagnetic interference signal warning module 12 and the signal positioning and resolving module 11.
The signal positioning calculating module 11 finds the radial distance position of the electromagnetic interference signal generating source distance with the monitoring device as the center of a circle according to the time, frequency spectrum, characteristics and other information of the received wireless signal and the transmitting power of the interference signal generating source and the receiving power of the monitoring device, and processes data and transmits the data to the wireless remote communication module 14.
The electromagnetic interference signal warning module 12 specifically includes an acoustic and optical warning circuit unit, and is configured to timely warn and remind an external user of the processed result, and transmit the processed data to the wireless remote communication module 14.
The wireless remote communication module 14 is of the model SRM825W, specifically comprises a plurality of wireless communication chips and related circuits, specifically comprises wireless communication modules of operator public networks 4G and 5G remote communication and wireless private networks 1.8G frequency bands, is of the model F2X16-DK, and is used for receiving positioning information and alarm information and remotely transmitting the positioning information and the alarm information through a wireless antenna unit.
The power supply module specifically comprises an external photovoltaic panel module 1, a storage battery power supply module 3, a power supply module 4 and a photovoltaic interface power supply conversion module 2 specifically used for photovoltaic power supply according to an outdoor scene, and is used for supplying power to the connected module units.
The microprocessor module comprises a DSP chip and an ARM chip which are in communication connection, and specifically comprises a high-performance processor module and a circuit unit, and is used for sending control processing instructions to received wireless signals, sending storage processing instructions to the data storage module 13, sending characteristic processing instructions to the wireless signal spectrum characteristic processing module, and providing calculation control capability for the connected units.
The wireless signal receiving, amplifying and filtering module of the wireless private network electromagnetic interference monitoring device based on artificial intelligence completes the receiving and preprocessing of full-frequency-band wireless electromagnetic signals deployed in an application field, extracts the characteristics of the preprocessed signals, realizes the comprehensive matching analysis of the characteristics of the received wireless electromagnetic signals, a target frequency spectrum and historical interference monitoring data information in an artificial intelligence signal characteristic processing mode, analyzes the positioning data and the interference result of the wireless electromagnetic signals, completes remote transmission of the related positioning result and the alarm information of the electromagnetic interference signals in a wireless remote communication mode, and improves the monitoring efficiency, the processing efficiency and the alarm real-time performance of the on-site wireless interference signals. Compared with the traditional wireless signal interference monitoring of the electric power wireless private network, the wireless signal amplification, frequency mixing, filtering, feature extraction and other modules have comprehensive processing technical means of all received signals, and can effectively solve the problems of signal discrimination, differentiation and identification in a complex wireless signal environment; the artificial intelligence signal characteristic processing module 10 has the combined unified analysis capability of diversified transmission signal data, effectively solves the mixed processing problems of target signals, historical signals, captured signals and the like in a complex electromagnetic environment, realizes the multi-factor comprehensive intelligent analysis of monitoring, and has the machine learning capability of historical signal characteristic information; the micro-processor module 8 integrated processing chip and the signal processing method with signal calculation processing and control can effectively solve the problems of difficult transmission, analysis, study and judgment delay and the like of mass monitoring information at the near field side and improve the real-time level of monitoring control; the adopted photovoltaic and storage battery power supply hybrid mode can adapt to the requirements of long-term monitoring, continuous use and no circuit laying under an outdoor scene, and the problem of flexible power supply under the outdoor scene is solved, so that the purposes of effective acquisition, aggregation, real-time preprocessing, artificial intelligent analysis, result alarm, signal positioning, result data transmission and the like of outdoor hybrid radio monitoring signal data can be realized by utilizing the wireless private network electromagnetic interference monitoring device based on artificial intelligence, the problems of difficult acquisition, difficult aggregation, non-real-time processing, convenient power supply, untimely alarm and the like of complex radio signals under a wide-area environment are solved, and the problems of idleness of historical monitoring data, pressure of background unified processing, low efficiency of field processing, low energy of result analysis and judgment and the like are solved. .
In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the utility model may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the utility model, various features of the utility model are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: that the utility model as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
Those skilled in the art will appreciate that the modules or units or groups of devices in the examples disclosed herein may be arranged in a device as described in this embodiment, or alternatively may be located in one or more devices different from the devices in this example. The modules in the foregoing examples may be combined into one module or may be further divided into multiple sub-modules.
Those skilled in the art will appreciate that the modules in the device in an embodiment may be adaptively changed and disposed in one or more devices different from the embodiment. Modules or units or groups in embodiments may be combined into one module or unit or group and may furthermore be divided into sub-modules or sub-units or sub-groups. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Furthermore, those skilled in the art will appreciate that while some embodiments described herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the utility model and form different embodiments. For example, in the claims, any of the claimed embodiments may be used in any combination.
Furthermore, some of the described embodiments are described herein as a method or combination of method elements that can be performed by a processor of a computer system or by other means of performing the described functions. A processor having the necessary instructions for carrying out the method or method elements thus forms a means for carrying out the method or method elements. Further, the elements of the apparatus embodiments described herein are examples of the following apparatus: the apparatus is for performing functions performed by elements for the purpose of carrying out the utility model.
The various techniques described herein may be implemented in connection with hardware or software or, alternatively, with a combination of both. Thus, the methods and apparatus of the present invention, or certain aspects or portions thereof, may take the form of program code (i.e., instructions) embodied in tangible media, such as floppy diskettes, CD-ROMs, hard drives, or any other machine-readable storage medium, wherein, when the program is loaded into and executed by a machine, such as a computer, the machine becomes an apparatus for practicing the utility model.
In the case of program code execution on programmable computers, the computing device will generally include a processor, a storage medium readable by the processor (including volatile and non-volatile memory and/or storage elements), at least one input device, and at least one output device. Wherein the memory is configured to store program code; the processor is configured to perform the method of the utility model according to instructions in said program code stored in the memory.
By way of example, and not limitation, computer readable media may comprise computer storage media and communication media. Computer-readable media includes both computer storage media and communication media. Computer storage media store information such as computer readable instructions, data structures, program modules or other data. Communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media. Combinations of any of the above are also included within the scope of computer readable media.
As used herein, unless otherwise specified the use of the ordinal adjectives "first", "second", "third", etc., to describe a common object, merely indicate that different instances of like objects are being referred to, and are not intended to imply that the objects so described must be in a given sequence, either temporally, spatially, in ranking, or in any other manner.
While the utility model has been described with respect to a limited number of embodiments, those skilled in the art, having benefit of this description, will appreciate that other embodiments can be devised which do not depart from the scope of the utility model as described herein. Furthermore, it should be noted that the language used in the specification has been principally selected for readability and instructional purposes, and may not have been selected to delineate or circumscribe the inventive subject matter. Accordingly, many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the appended claims. The present invention has been disclosed in an illustrative rather than a restrictive sense, and the scope of the present invention is defined by the appended claims.
Claims (6)
1. A wireless private network electromagnetic interference monitoring device based on artificial intelligence is characterized by comprising a wireless signal receiving module (5), wherein the wireless signal receiving module (5) sends received wireless signals to a preprocessing module (B), a microprocessor module (8) receives the preprocessed wireless signals sent by the preprocessing module (B), the processed wireless signals are stored in a data storage module (13) and send instructions to a wireless signal spectrum feature extraction module (9), the wireless signal spectrum feature extraction module (9) sends wireless signal spectrum feature information to an artificial intelligence signal feature processing module (10), the artificial intelligence signal feature processing module (10) sends feature processing signals to a signal positioning calculation module (11), an electromagnetic interference signal warning module (12) and the data storage module (13) simultaneously, the signal positioning calculation module (11), the electromagnetic interference signal warning module (12) and the data storage module (13) are transmitted to a wireless remote communication module (14).
2. The wireless private network electromagnetic interference monitoring device based on artificial intelligence is characterized in that the device is connected with a power supply module (A).
3. The wireless private network electromagnetic interference monitoring device based on artificial intelligence according to claim 2, characterized in that the power supply module (a) comprises a power supply module (4), a storage battery power supply module (3) and/or a photovoltaic power supply module, and the photovoltaic power supply module comprises an external photovoltaic panel module (1) and a photovoltaic interface power supply conversion module (2).
4. The wireless private network electromagnetic interference monitoring device based on artificial intelligence of claim 1, wherein the preprocessing module (B) comprises a wireless signal amplifying module (6) and a wireless signal mixing and filtering module (7) which are connected in sequence, the wireless signal receiving module (5) receives the wireless signal and transmits the wireless signal to the wireless signal amplifying module (6), and the wireless signal mixing and filtering module (7) transmits the amplified, mixed and filtered preprocessed signal to the microprocessor module (8).
5. The wireless private network electromagnetic interference monitoring device based on artificial intelligence of claim 1, characterized in that: the electromagnetic interference signal warning module (12) comprises an acoustic warning and/or a luminous warning.
6. The wireless private network electromagnetic interference monitoring device based on artificial intelligence of claim 1, characterized in that:
the wireless remote communication module (14) comprises wireless communication interfaces of operator public networks 4G and wireless private networks 1.8G.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202122501215.XU CN215581191U (en) | 2021-10-18 | 2021-10-18 | Wireless private network electromagnetic interference monitoring device based on artificial intelligence |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202122501215.XU CN215581191U (en) | 2021-10-18 | 2021-10-18 | Wireless private network electromagnetic interference monitoring device based on artificial intelligence |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN215581191U true CN215581191U (en) | 2022-01-18 |
Family
ID=79853603
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202122501215.XU Active CN215581191U (en) | 2021-10-18 | 2021-10-18 | Wireless private network electromagnetic interference monitoring device based on artificial intelligence |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN215581191U (en) |
-
2021
- 2021-10-18 CN CN202122501215.XU patent/CN215581191U/en active Active
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107968850A (en) | The taiwan area identifying system and method for power line carrier | |
| CN204376922U (en) | Parallel duplex FM modulated broadcast signal acquisition and processing device | |
| CN203444631U (en) | Ad-hoc network micropower wireless communication module | |
| CN105591670A (en) | Photovoltaic assembly state information monitoring device based on power line communication and monitoring method thereof | |
| CN204967832U (en) | Jointly disturb system based on frequency spectrum perception and modulation recognition | |
| CN103823111A (en) | Remote network unified phase color identification system | |
| CN215581191U (en) | Wireless private network electromagnetic interference monitoring device based on artificial intelligence | |
| CN103106629A (en) | Station area passenger flow density acquisition system | |
| CN201181484Y (en) | Attendance-recording machine based on GSM | |
| CN207200999U (en) | TD LTE standard type mobile communication terminal intelligent positioners and system | |
| CN204013884U (en) | Radar video supervisory control system | |
| CN110536255B (en) | Access point transmitting power optimization method based on indoor propagation loss model | |
| CN201365344Y (en) | Apparatus and system with real-time import of remote SIM card data based on singlechip | |
| CN207282000U (en) | A kind of antenna data automated collection systems | |
| CN103279098A (en) | Electrical equipment monitoring device based on image identification | |
| CN203788276U (en) | Ad-hoc network micro-power wireless communication module | |
| CN204216906U (en) | Portable railway disturbed test device | |
| CN108229621A (en) | A kind of money case delivery system based on ultrahigh frequency RFID and LoRa technologies | |
| CN208796070U (en) | Radio ammeter managing and control system based on LIFI technology | |
| CN208351478U (en) | Detection device capable of identifying various types of electronic tags | |
| CN112929615A (en) | Image transmission device and method based on satellite communication | |
| CN205249210U (en) | Airborne station circuit model | |
| CN101778402B (en) | Device, system and method based on remote subscriber identity module (SIM) card data introduced by singlechip in real time | |
| CN210015512U (en) | Line loss statistical analysis device and system | |
| CN206282428U (en) | Based on far infrared diffusing reflection cloud platform power collection systems |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| GR01 | Patent grant | ||
| GR01 | Patent grant |