CN112629505A - Data processing method and device of distributed measuring and drilling system - Google Patents
Data processing method and device of distributed measuring and drilling system Download PDFInfo
- Publication number
- CN112629505A CN112629505A CN202011376412.7A CN202011376412A CN112629505A CN 112629505 A CN112629505 A CN 112629505A CN 202011376412 A CN202011376412 A CN 202011376412A CN 112629505 A CN112629505 A CN 112629505A
- Authority
- CN
- China
- Prior art keywords
- data
- temperature gradient
- node
- sensor
- survey pin
- 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.)
- Granted
Links
- 238000003672 processing method Methods 0.000 title claims abstract description 13
- 238000005553 drilling Methods 0.000 title claims description 4
- 238000012545 processing Methods 0.000 claims abstract description 11
- 230000000694 effects Effects 0.000 abstract description 3
- 238000000034 method Methods 0.000 abstract description 3
- 239000002689 soil Substances 0.000 description 5
- 238000004364 calculation method Methods 0.000 description 3
- 238000004891 communication Methods 0.000 description 3
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 239000003990 capacitor Substances 0.000 description 1
- 238000013480 data collection Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 238000011900 installation process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000006855 networking Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C15/00—Surveying instruments or accessories not provided for in groups G01C1/00 - G01C13/00
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01K—MEASURING TEMPERATURE; MEASURING QUANTITY OF HEAT; THERMALLY-SENSITIVE ELEMENTS NOT OTHERWISE PROVIDED FOR
- G01K13/00—Thermometers specially adapted for specific purposes
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Testing Or Calibration Of Command Recording Devices (AREA)
- Arrangements For Transmission Of Measured Signals (AREA)
Abstract
The invention discloses a data processing method and a data processing device of a distributed type survey pin system, which are based on the characteristic that a plurality of survey pin nodes are adopted to acquire data in an actual application environment, comprehensively process the data of the plurality of data nodes on the basis of the basic assumption of physical quantity continuity, comprehensively consider the incidence relation among the data of the survey pin nodes by utilizing the fuzzy judgment of temperature field gradient, effectively eliminate invalid survey pin data, have great effect on improving the data effectiveness and improve the accuracy of detected data.
Description
Technical Field
The invention belongs to the technical field of survey pin data processing, and particularly relates to a data processing method and device of a distributed survey pin system.
Background
The measuring drill data has the advantage of real-time performance, but because the working environment is located outdoors and is influenced by external environments such as fallen leaves, sunshine and the like, the problem that the data of individual measuring drill nodes are invalid at individual time can occur. In the existing survey pin technology, the detected data is mainly judged according to the data validity from each survey pin node, and then the data is processed in the next step, but the method for judging the data validity only from each survey pin node does not consider other related data, and the data validity may be misjudged; at present, no report or literature about data processing of data correlation among a plurality of measuring drill nodes is found. In order to further improve the stability of survey pin data, this patent proposes a processing algorithm to data validity between the survey pin node that a plurality of physical position are close to.
Disclosure of Invention
The invention provides a data processing method and a data processing device of a distributed type survey pin system, which can greatly improve the filtering effect of invalid survey pin data through the variance calculation of multipoint temperatures and the effective calculation and fuzzy discrimination of a temperature gradient field.
In order to achieve the purpose, the data processing method of the distributed type survey pin system comprises the steps that the distributed type survey pin system comprises a central node and N-1 sensor nodes, the central node and the sensor nodes are used for collecting survey pin data of positions where the central node and the sensor nodes are located, and the survey pin data comprise survey pin values and temperatures; and judging the validity of the survey pin data by adopting a fuzzy judgment algorithm based on a space temperature gradient field according to the temperatures of the central node and each sensor node.
Further, the method comprises the following steps:
step 1, initializing the number N of sensor nodes, and position coordinates of 1 central node and N-1 sensor nodes;
step 2, initializing the data validity of the central node and the data validity of the N-1 sensor nodes to TRUE;
step 3, calculating temperature gradient values between the central node and the N-1 sensor nodes to obtain N-1 temperature gradient values, and judging the sizes of the N-1 temperature gradient values and a temperature gradient threshold WDTD _ TH 1: if any temperature gradient value is larger than a temperature gradient threshold value WDTD _ TH1, updating the data effectiveness of the central node to FALSA; otherwise, the data validity of the central node is not updated;
and 4, circularly finishing the following operations on the sensor nodes with the numbers from 1 to N-1:
setting the number of a certain node as K, wherein K is more than or equal to 1 and less than or equal to N-1, calculating the temperature gradient values between the node and all sensor nodes with the numbers larger than K, judging the size relation between the temperature gradient values and a temperature gradient threshold value WDTD _ TH2, and updating the data effectiveness of the sensor node with the number of K into FALSE if any one temperature gradient value is larger than the temperature gradient threshold value WDTD _ TH 2; otherwise, the data validity of the central node is not updated;
and 5, forming a data set by the number of the survey pin data of the node with the data validity of TURE and the survey pin data in the central node and the N-1 sensor nodes, wherein the data set is the valid data set.
Further, the formula for calculating the temperature gradient value is as follows:
WDTD (i, j) is a temperature gradient value between two nodes numbered as i and j, xi is an abscissa of the sensor node i, and yi is an ordinate of the sensor node i; xj is the abscissa of the sensor node j, and Yj is the ordinate of the sensor node j; ti is the temperature collected by the sensor node i, and Tj is the temperature collected by the sensor node j.
Further, the temperature gradient threshold value WDTD _ TH1 in step 3 and the temperature gradient threshold value WDTD _ TH2 in step 4 are equal.
Further, the temperature gradient thresholds WDTD _ TH1 and WDTD _ TH2 are 0.5 degrees/meter.
The data processing device of the distributed measuring rod system comprises a processor and a memory, wherein the processor is connected with the memory through a bus, the processor is used for judging the effectiveness of measuring rod data according to the temperatures of a central node and each sensor node by adopting a fuzzy judgment algorithm based on a spatial temperature gradient field, and the memory is used for storing the measuring rod data.
Compared with the prior art, the invention has at least the following beneficial technical effects:
based on the characteristic that a plurality of measuring rod nodes are adopted to collect data in an actual application environment, the data of the plurality of data nodes are comprehensively processed based on the basic assumption of physical quantity continuity, the association relation among the data of the measuring rod nodes is comprehensively considered by utilizing the fuzzy judgment of the temperature field gradient, invalid measuring rod data can be effectively eliminated, the data effectiveness is greatly improved, and the accuracy of the detected data is improved. More effective data are provided for the subsequent processing of the survey pin data, and the accuracy of the survey pin result is improved.
The survey pin data processing device provided by the invention can obtain an effective data set only by inputting the central node coordinates, the node coordinates of each sensor and survey pin data obtained by measurement.
Drawings
FIG. 1 is a schematic diagram of a low-power-consumption distributed measuring drill system based on solar power supply;
FIG. 2 is a flowchart of an algorithm for determining whether the survey pin data is valid;
FIG. 3 is a schematic diagram of a data processing device of the distributed survey measuring system.
Detailed Description
In order to make the objects and technical solutions of the present invention clearer and easier to understand. The present invention will be described in further detail with reference to the following drawings and examples, wherein the specific examples are provided for illustrative purposes only and are not intended to limit the present invention.
In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implying any number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. "plurality" means two or more unless otherwise specified. Unless expressly stated or limited otherwise, the terms "mounted," "connected," and "connected" are intended to be inclusive and mean, for example, that they may be fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
Referring to fig. 1, a solar power supply-based low-power-consumption distributed measuring and drilling system comprises a central node and a plurality of sensor nodes, wherein ad hoc networking is realized between the central node and the sensor nodes in a 433M wireless communication mode, and each sensor node simultaneously records water and soil loss conditions and temperature information of different positions, wherein the water and soil loss conditions are represented by ground soil loss thickness, and data are transmitted to the central node based on a low-power-consumption mode. And the central node forms a water and soil loss profile and a temperature gradient field according to the data information of different sensor nodes. The central node is a special sensor node, can realize communication with a remote monitoring system besides a basic sensing measurement function, and returns all data; the sensor node is a basic survey pin sensor node, and survey pin data collection is carried out on the central node only in a wireless communication mode.
The central node adopts a standby working mode, only the 433M wireless monitoring function is started, low-power-consumption work can be realized, and the power lost by the battery can be charged and supplemented through the solar battery.
The sensor node is powered by a solar cell panel and a super capacitor, is started every 1-3 hours, monitors the power supply voltage by a resistance voltage division mode after being started every time, and measures the measuring rod only under the condition that the power supply voltage meets a specified voltage value. For an installed survey pin system, the central node and the sensor nodes can be considered to be located in the same plane, so that the physical position of each node can be identified by two-dimensional rectangular coordinates. In a specific installation process, the distances between the central node and all the sensor nodes are accurately measured, so that the two-dimensional coordinates of the central node and the sensor nodes are known. Assume that a drill rod system consists of 1 central node and N sensor nodes (6< ═ N < ═ 50). The following convention is used to represent the coordinates of the various nodes:
(x0, y 0): coordinates representing a central node;
(x1, y 1): position coordinates of the sensor numbered 1;
(xi, yi): position coordinates of the sensor numbered i;
in order to effectively evaluate the effectiveness of the survey pin data, the invention adopts a fuzzy decision algorithm based on a space temperature gradient field, which specifically comprises the following steps:
for 1 central node and N sensor nodes, there is a total of (N +1) sets of survey data, including: the pin and temperature values are recorded as the following data pairs:
(CQ0, T0) represents the pin value and temperature data for node 0 (i.e., the center node), (CQ1, T1) represents the pin value and temperature data for sensor node number 1, (CQ2, T2) represents the pin value and temperature data for sensor node number 2, and so on, (CQN, TN-1) represents the pin value and temperature data for sensor node number N-1. The measuring drill rod value refers to the thickness of soil descending at the position of the measuring drill rod;
defining the temperature gradient field between any two nodes (the numbers are i and j respectively, and i is not equal to j) as
All values in the calculation formula are subject to international unit system, wherein WDTD (i, j) is a temperature gradient value between two nodes numbered as i and j, xi is an abscissa of the sensor node i, and yi is an ordinate of the sensor node i; xj is the abscissa of the sensor node j, and yj is the ordinate of the sensor node j; ti is the temperature collected by the sensor node i, and Tj is the temperature collected by the sensor node j.
Referring to fig. 2, a data processing method of a distributed survey meter system is used for judging whether survey meter data is valid, and includes the following steps:
step 1, initializing the number N of sensors, position coordinates of 1 central node and N-1 sensor nodes, a temperature gradient threshold WDTD _ TH1 and a temperature gradient threshold WDTD _ TH2, wherein WDTD _ TH1 and WDTD _ TH2 are equal and are all 0.5 degree/meter;
step 2, initializing the data validity of 1 central node and N-1 sensor nodes to TRUE;
step 3, calculating temperature gradient values between the central node and the N-1 sensor nodes to obtain N-1 temperature gradient values, and if any one temperature gradient value is larger than a temperature gradient threshold value WDTD _ TH1, recording the data effectiveness of the central data node as FALSA;
and 4, circularly finishing the following operations on the sensor nodes with the numbers from 1 to N-1:
setting the node number as K, calculating the temperature gradient value between the node and the sensor node with the number larger than K, and if any temperature gradient value is larger than a temperature gradient threshold value WDTD _ TH2, recording the data validity of the sensor node with the number of K as FALSE;
and 5, forming a data set by the number of the survey pin data of the node with the data validity of the TURE and the survey pin data in the central node and all the sensor nodes, wherein the data set is the valid data set.
Referring to fig. 3, a data processing apparatus of a distributed drill rod measuring system includes a processor 100 and a memory 200, wherein the processor 100 is connected to the memory 200 through a bus 300, and is configured to call program codes and data in the memory 200 in real time through the bus 300, and execute the above steps 1, 2, 3, 4 and 5; the memory 200 is used to store program codes and drill rod data for executing the data processing method of the distributed drill rod system described above.
The above-mentioned contents are only for illustrating the technical idea of the present invention, and the protection scope of the present invention is not limited thereby, and any modification made on the basis of the technical idea of the present invention falls within the protection scope of the claims of the present invention.
Claims (6)
1. The data processing method of the distributed type survey pin system is characterized in that the distributed type survey pin system comprises a central node and N-1 sensor nodes, wherein the central node and the sensor nodes are used for collecting survey pin data of positions of the central node and the sensor nodes, and the survey pin data comprises a survey pin value and temperature; and judging the validity of the survey pin data by adopting a fuzzy judgment algorithm based on a space temperature gradient field according to the temperatures of the central node and each sensor node.
2. The data processing method of the distributed measuring and boring system according to claim 1, comprising the steps of:
step 1, initializing the number N of sensor nodes, and position coordinates of 1 central node and N-1 sensor nodes;
step 2, initializing the data validity of the central node and the data validity of the N-1 sensor nodes to TRUE;
step 3, calculating temperature gradient values between the central node and the N-1 sensor nodes to obtain N-1 temperature gradient values, and judging the sizes of the N-1 temperature gradient values and a temperature gradient threshold WDTD _ TH 1: if any temperature gradient value is larger than a temperature gradient threshold value WDTD _ TH1, updating the data effectiveness of the central node to FALSA; otherwise, the data validity of the central node is not updated;
and 4, circularly finishing the following operations on the sensor nodes with the numbers from 1 to N-1:
setting the number of a certain node as K, wherein K is more than or equal to 1 and less than or equal to N-1, calculating the temperature gradient values between the node and all sensor nodes with the numbers larger than K, judging the size relation between the temperature gradient values and a temperature gradient threshold value WDTD _ TH2, and updating the data effectiveness of the sensor node with the number of K into FALSE if any one temperature gradient value is larger than the temperature gradient threshold value WDTD _ TH 2; otherwise, the data validity of the central node is not updated;
and 5, forming a data set by the number of the survey pin data of the node with the data validity of TURE and the survey pin data in the central node and the N-1 sensor nodes, wherein the data set is the valid data set.
3. The data processing method of the distributed measuring system according to claim 2, wherein the temperature gradient value is calculated by the formula:
WDTD (i, j) is a temperature gradient value between two nodes numbered as i and j, xi is an abscissa of the sensor node i, and yi is an ordinate of the sensor node i; xj is the abscissa of the sensor node j, and yj is the ordinate of the sensor node j; ti is the temperature collected by the sensor node i, and Tj is the temperature collected by the sensor node j.
4. The data processing method of the distributed drilling system of claim 2, wherein the temperature gradient threshold value WDTD _ TH1 in step 3 and the temperature gradient threshold value WDTD _ TH2 in step 4 are equal.
5. The data processing method of a distributed drill rod system of claim 2, wherein the temperature gradient thresholds WDTD _ TH1 and WDTD _ TH2 are 0.5 degrees/meter.
6. The data processing device of the distributed type survey pin system comprises a processor (100) and a memory (200), wherein the processor (100) is connected with the memory (200) through a bus (300), the processor (100) is used for judging the validity of survey pin data according to the temperature of a central node and each sensor node by adopting a fuzzy decision algorithm based on a spatial temperature gradient field, and the memory (200) is used for storing the survey pin data.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011376412.7A CN112629505B (en) | 2020-11-30 | 2020-11-30 | Data processing method and device of distributed measuring and drilling system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011376412.7A CN112629505B (en) | 2020-11-30 | 2020-11-30 | Data processing method and device of distributed measuring and drilling system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112629505A true CN112629505A (en) | 2021-04-09 |
| CN112629505B CN112629505B (en) | 2022-08-02 |
Family
ID=75306986
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011376412.7A Active CN112629505B (en) | 2020-11-30 | 2020-11-30 | Data processing method and device of distributed measuring and drilling system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112629505B (en) |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1827923A (en) * | 2006-03-16 | 2006-09-06 | 杨建坤 | Automatic drilling machine |
| KR101227684B1 (en) * | 2012-11-30 | 2013-02-01 | 동방지적 주식회사 | Plane-table for cadastral surveying |
| JP2015045558A (en) * | 2013-08-28 | 2015-03-12 | 株式会社パスコ | Data analyzer, data analysis method, and program |
| CN205619934U (en) * | 2016-05-13 | 2016-10-05 | 江苏建筑职业技术学院 | Fixed survey pin device |
| CN107179061A (en) * | 2017-06-26 | 2017-09-19 | 国家电网公司 | A kind of ultrasonic survey pin device of self calibration and measuring method |
| CN107340019A (en) * | 2017-07-14 | 2017-11-10 | 国家电网公司 | A kind of water and soil conservation on-Line Monitor Device and monitoring method |
| CN108827401A (en) * | 2018-09-10 | 2018-11-16 | 东北林业大学 | A kind of novel water and soil conservation value device and method |
| CN109470407A (en) * | 2018-11-15 | 2019-03-15 | 北京华航无线电测量研究所 | The calibration method of distributed multinode fluid temperature, pressure sensor measurement data |
| CN110030986A (en) * | 2019-05-10 | 2019-07-19 | 辽宁工程技术大学 | A kind of theodolite survey pin device and its application method |
| CN111089662A (en) * | 2019-12-31 | 2020-05-01 | 核工业北京地质研究院 | Method for measuring shallow geothermal energy |
| AU2020101224A4 (en) * | 2020-07-02 | 2020-08-13 | Guangdong Ocean University | Method for Constructing Temperature Profile Based on the Sounding Data of Flat Drift Balloon |
| CN211505523U (en) * | 2020-02-17 | 2020-09-15 | 山东绿景生态工程设计有限公司 | Device for automatically measuring soil erosion thickness and measuring soil loss by measuring and monitoring method |
-
2020
- 2020-11-30 CN CN202011376412.7A patent/CN112629505B/en active Active
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1827923A (en) * | 2006-03-16 | 2006-09-06 | 杨建坤 | Automatic drilling machine |
| KR101227684B1 (en) * | 2012-11-30 | 2013-02-01 | 동방지적 주식회사 | Plane-table for cadastral surveying |
| JP2015045558A (en) * | 2013-08-28 | 2015-03-12 | 株式会社パスコ | Data analyzer, data analysis method, and program |
| CN205619934U (en) * | 2016-05-13 | 2016-10-05 | 江苏建筑职业技术学院 | Fixed survey pin device |
| CN107179061A (en) * | 2017-06-26 | 2017-09-19 | 国家电网公司 | A kind of ultrasonic survey pin device of self calibration and measuring method |
| CN107340019A (en) * | 2017-07-14 | 2017-11-10 | 国家电网公司 | A kind of water and soil conservation on-Line Monitor Device and monitoring method |
| CN108827401A (en) * | 2018-09-10 | 2018-11-16 | 东北林业大学 | A kind of novel water and soil conservation value device and method |
| CN109470407A (en) * | 2018-11-15 | 2019-03-15 | 北京华航无线电测量研究所 | The calibration method of distributed multinode fluid temperature, pressure sensor measurement data |
| CN110030986A (en) * | 2019-05-10 | 2019-07-19 | 辽宁工程技术大学 | A kind of theodolite survey pin device and its application method |
| CN111089662A (en) * | 2019-12-31 | 2020-05-01 | 核工业北京地质研究院 | Method for measuring shallow geothermal energy |
| CN211505523U (en) * | 2020-02-17 | 2020-09-15 | 山东绿景生态工程设计有限公司 | Device for automatically measuring soil erosion thickness and measuring soil loss by measuring and monitoring method |
| AU2020101224A4 (en) * | 2020-07-02 | 2020-08-13 | Guangdong Ocean University | Method for Constructing Temperature Profile Based on the Sounding Data of Flat Drift Balloon |
Non-Patent Citations (1)
| Title |
|---|
| 杨建民等: "新型水土流失监测装置及其应用", <<中国水土保持科学>> * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112629505B (en) | 2022-08-02 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105764162B (en) | A kind of wireless sensor network accident detection method based on more Attribute Associations | |
| CN110795510B (en) | Spacecraft system health state evaluation method based on high-dimensional data association mining | |
| CN111401460B (en) | Abnormal electric quantity data identification method based on limit value learning | |
| CN107705515A (en) | A kind of geological disaster monitoring system based on big data | |
| CN110087207B (en) | Method for reconstructing missing data of wireless sensor network | |
| CN109324241B (en) | Corrosion diagnosis early warning method and system for transformer substation grounding grid | |
| CN108520267B (en) | Hydrological telemetering data anomaly detection method based on space-time characteristics | |
| CN110071692A (en) | Photovoltaic module failure judgment method, device and controller | |
| CN102306206A (en) | Self-adapting consistent data fusion method | |
| CN117093947B (en) | Power generation diesel engine operation abnormity monitoring method and system | |
| CN114116689A (en) | Big data cleaning method based on building structure safety monitoring | |
| CN112629505B (en) | Data processing method and device of distributed measuring and drilling system | |
| CN118032046A (en) | Wireless environment monitoring method for closed area | |
| CN113034305B (en) | Non-invasive load monitoring event classification method and storage medium | |
| CN113268730A (en) | Smart grid false data injection attack detection method based on reinforcement learning | |
| CN117102082A (en) | Sorting method and system for liquid metal batteries | |
| CN111060949A (en) | Method for estimating detection data background of seawater radionuclide by marine environment parameters | |
| CN110824293A (en) | Power grid fault diagnosis method based on multi-feature fusion parameters of wolf pack algorithm | |
| CN107085934B (en) | Performance detection method and system for electricity consumption information acquisition equipment | |
| CN108335042A (en) | Method for calculating cleaning index of dynamic photovoltaic panel | |
| CN118052540B (en) | Intelligent management method and system for equipment maintenance scheme | |
| CN116448359A (en) | Method and device for identifying faults of key parts of coal mine equipment based on vibration signals | |
| CN118501720B (en) | Lithium battery abnormality detection system based on big data analysis | |
| Deshpande et al. | Road Surface Data Acquisition and Monitoring System | |
| CN111542084B (en) | Device for measuring normal underground signals of Internet of things equipment on well |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20240429 Address after: No. 669, Hangtian Middle Road, Xi'an national civil aerospace industry base, Shaanxi 710100 Patentee after: Electric Power Research Institute of State Grid Shaanxi Electric Power Co.,Ltd. Country or region after: China Patentee after: National Network (Xi'an) Environmental Protection Technology Center Co.,Ltd. Patentee after: State Grid Shaanxi Electric Power Co.,Ltd. Patentee after: STATE GRID CORPORATION OF CHINA Address before: No.669, Hangtian Middle Road, Chang'an District, Xi'an City, Shaanxi Province Patentee before: STATE GRID SHAANXI ELECTRIC POWER Research Institute Country or region before: China Patentee before: National Network (Xi'an) Environmental Protection Technology Center Co.,Ltd. Patentee before: STATE GRID SHAANXI ELECTRIC POWER Co. Patentee before: STATE GRID CORPORATION OF CHINA |
|
| TR01 | Transfer of patent right |