CN108198090B - Typhoon monitoring and point distribution method for power grid power transmission and distribution facility - Google Patents
Typhoon monitoring and point distribution method for power grid power transmission and distribution facility Download PDFInfo
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- CN108198090B CN108198090B CN201711368148.0A CN201711368148A CN108198090B CN 108198090 B CN108198090 B CN 108198090B CN 201711368148 A CN201711368148 A CN 201711368148A CN 108198090 B CN108198090 B CN 108198090B
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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Abstract
The invention discloses a typhoon monitoring and point distribution method for a power transmission and distribution facility of a power grid, which relates to the field of disaster prevention and reduction of power grid equipment and comprises the following steps: s1, constructing a historical typhoon distribution map; s2, marking the existing power grid power transmission and distribution facilities on the historical typhoon distribution map according to different danger levels; s3, collecting the data of the historical typhoon in the power transmission and distribution facility of the power grid marked in the step S2, calculating the distance between the disaster-causing point and the historical typhoon path, the wind power from the historical typhoon to the disaster-causing point and the wind speed reduction speed, and sequencing the wind power from the historical typhoon to the disaster-causing point and the wind speed reduction speed in sequence; and S4, calculating the distance from the future typhoon to the disaster-causing point according to the time and path of the future typhoon predicted by the main meteorological station, predicting the disaster-causing probability of the disaster-causing point, and distributing the power transmission and distribution facilities of the power grid. The invention has the advantages of wide stationing coverage, less required historical data, simple calculation method, less manpower and material resource consumption and high stationing accuracy.
Description
Technical Field
The invention relates to the field of disaster prevention and reduction of power grid equipment, in particular to a typhoon monitoring and point distribution method for power grid power transmission and distribution facilities.
Background
The typhoon is a tropical cyclone formed on a wide surface of a tropical zone or a subtropical zone at a temperature of more than 26 ℃, the world meteorological organization defines the tropical cyclone with a central continuous wind speed of 12-13 levels as the typhoon, which is one of natural disasters most concentrated in time and most influenced in range, and the typhoon is one of important influence factors for safety and stable operation of a power grid because power grid equipment is wide in distribution range and greatly influenced by the typhoon. At present, the construction and transformation work of the power grid power transmission and distribution facilities mostly directly adopts a wind area diagram or a geographical position meteorological thematic analysis mode of an engineering to determine the numerical value of the designed wind speed, so that the detection data of an automatic meteorological station of a meteorological department needs to be acquired, the detection data of the automatic meteorological station mainly comes from a monitoring station close to an urban area, and for the area far away from the urban area, the environmental difference between the two is large, so that the data detected by the automatic meteorological station can not accurately reflect the real environment far away from the urban area, the detection of the power grid power transmission and distribution facilities on the real typhoon condition is finally caused to be inaccurate, and the monitoring effect of part of the power grid power transmission and distribution facilities is not obvious.
Application publication No.: CN107194494A discloses a power grid power transmission and distribution facility distribution method, which obtains disaster-causing wind speed values based on the correlation analysis of the historical typhoon wind field of the area where the power grid is located and the typhoon faults of the power grid, and uses the frequency of the historical typhoon wind field exceeding the disaster-causing wind speed values as the basis for selecting the sites of monitoring stations, but the method mainly depends on typhoon data and data influenced by the historical typhoon during the historical border-crossing period, the data quantity required to be collected in the distribution process is large, the difficulty in extracting data from numerous data is large, the manpower and material resources are consumed greatly, and the accuracy and the comprehensiveness of the collected historical data can directly influence the disaster-causing wind speed values, thereby influencing the distribution situation of the typhoon monitoring stations. Based on the defects in the prior art, the invention provides a typhoon monitoring and point distribution method for a power transmission and distribution facility of a power grid.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a typhoon monitoring and point distribution method for a power grid power transmission and distribution facility.
The invention solves the technical problems through the following technical scheme: a typhoon monitoring and point distribution method for a power grid power transmission and distribution facility comprises the following steps:
s1, constructing a historical typhoon distribution map;
s2, marking the existing power grid power transmission and distribution facilities on the historical typhoon distribution map according to different danger levels;
s3, collecting the data of the historical typhoon in the power transmission and distribution facility of the power grid marked in the step S2, calculating the distance between the disaster-causing point and the historical typhoon path, the wind power from the historical typhoon to the disaster-causing point and the wind speed reduction speed, and sequencing the wind power from the historical typhoon to the disaster-causing point and the wind speed reduction speed in sequence;
s4, calculating the distance from the future typhoon to the disaster-causing point according to the time and path of the future typhoon predicted by the weather central office; and predicting the disaster probability of the disaster-causing point, and distributing the power transmission and distribution facilities of the power grid according to the disaster probability.
Further, the method for constructing the historical typhoon distribution map in step S1 includes: collecting a path diagram of historical typhoons, equally dividing each data acquisition point on the path diagram, calculating a risk coefficient through each data acquisition point, calculating a total risk coefficient according to the risk coefficient, and dividing risk grades; and marking the total risk coefficient and the risk level on a path graph of the historical typhoon, and overlapping the marked path graph of the historical typhoon according to the geographical coordinate position to obtain a historical typhoon distribution graph.
Further, the method for calculating the total risk coefficient comprises the following steps: dividing the wind power level and the wind speed level of the data acquisition point into 10 regions respectively, and classifying according to a 0.1-1 mode, wherein the obtained data are risk coefficients; and then adding the wind power grade of the data acquisition point and the risk coefficient value to which the wind power grade belongs to obtain the total risk coefficient value of the data acquisition point.
Further, the 10 regions of the wind power level and the hazard coefficient values are respectively: the wind power is 1 region below 8 levels of wind power, the risk coefficient is 0.1, the wind power is 2 regions 8-9 levels of wind power, the risk coefficient is 0.2, the wind power is 3 regions 9-10 levels of wind power, the risk coefficient is 0.3, the wind power is 4 regions 10-11 levels of wind power, the risk coefficient is 0.4, the wind power is 5 regions 11-12 levels of wind power, the risk coefficient is 0.5, the wind power is 6 regions 12-13 levels of wind power, the risk coefficient is 0.6, the wind power is 7 regions 13-14 levels of wind power, the risk coefficient is 0.7, the wind power is 8 regions 14-15 levels of wind power, the risk coefficient is 0.8, the wind power is 9 regions 15-16 levels of wind power, the risk coefficient is 0.9, the wind power is 10 regions above 16 levels of wind power, and the risk coefficient is 1.
Further, the 10 regions of the wind speed level and the hazard coefficient values are respectively: the wind speed is 1 region below 20.9m/s, the risk coefficient is 0.1, the wind speed is 2 region from 21 m/s to 24.6m/s, the risk coefficient is 0.2, the wind speed is 3 region from 24.7 m/s to 28.5m/s, the risk coefficient is 0.3, the wind speed is 4 region from 28.6 m/s to 32.6m/s, the risk coefficient is 0.4, the wind speed is 5 region from 32.7 m/s to 36.9m/s, the risk coefficient is 0.5, the wind speed is 6 region from 37.0 m/s to 41.4m/s, the risk coefficient is 0.6, the wind speed is 7 region from 41.5 m/s to 46.1m/s, the risk coefficient is 0.7, the wind speed is 8 region from 46.2 m/s to 50.9m/s, the risk coefficient is 0.8, the wind speed is 9 region from 51.0 m/s to 56.0m/s, the risk coefficient is 0.9, the wind speed is 10 region above 56.1m/s, and the risk coefficient is 1.
Further, the danger levels in the step S2 are marked with different colors, and the danger levels are classified into a super high level, a middle level and a low level.
Further, the super high level needs to mark the power grid transmission and distribution facility within 50km from the data acquisition point in step S2, the high level needs to mark the power grid transmission and distribution facility within 40km from the data acquisition point in step S2, the medium level needs to mark the power grid transmission and distribution facility within 30km from the data acquisition point in step S2, and the low level needs to mark the power grid transmission and distribution facility within 20km from the data acquisition point in step S2.
Further, the data in step S3 includes a disaster level, a disaster frequency, and a wind speed at a disaster point.
Further, the specific standard of performing distribution of the power transmission and distribution facility of the power grid according to the disaster probability in step S4 is as follows: if the disaster probability is more than 80%, counting the number of power transmission and distribution facilities within 10km of a square circle by taking the disaster point as a center, and distributing points according to the standard that at least 3 power transmission and distribution facilities exist; if the disaster probability is between 50% and 80%, counting the number of power grid power transmission and distribution facilities within 10km of a square circle by taking the disaster point as a center, and distributing points according to the standard that at least 2 power grid power transmission and distribution facilities exist; if the disaster probability is between 20% and 50%, counting the number of power grid power transmission and distribution facilities within 10km of a square circle by taking the disaster point as a center, and distributing points according to the standard that at least 1 power grid power transmission and distribution facility exists; if the disaster probability is below 20%, statistics are not carried out.
Compared with the prior art, the typhoon monitoring and stationing method for the power transmission and distribution facilities of the power grid has the advantages of wide stationing coverage range, less required historical data, simple calculation method, less consumption of manpower and material resources and high stationing accuracy; the historical typhoon distribution diagram is constructed by utilizing the path, wind power, wind speed and geographic coordinates of the historical typhoon, the risk coefficient of each data acquisition point on the historical typhoon distribution map is calculated, the calculation method is simple, the risk coefficient is divided into four risk levels which are visually displayed in the historical typhoon distribution map, so that a designer can observe and research the historical typhoon condition conveniently, and then collect the historical typhoon data of the power transmission and distribution facilities of the power grid according to the danger level, obviously reduce the quantity of the historical typhoon data, reduce the consumption of manpower and material resources, and then calculate the disaster probability of the disaster point by combining the data of the disaster point in the power transmission and distribution facilities of the power grid within the range and the data of the future typhoon, and according to the disaster probability, the distribution of the power transmission and distribution facilities of the power grid is carried out, the effective coverage rate of the power transmission and distribution facilities of the power grid is improved, the resource waste is reduced, and the distribution accuracy of the power transmission and distribution facilities of the power grid is ensured.
Detailed Description
The technical solutions in the present invention are clearly and completely described below, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides a typhoon monitoring and stationing method for a power grid power transmission and distribution facility, which comprises the following steps:
s1, constructing a historical typhoon distribution map: collecting a path diagram of historical typhoon, equally dividing each data acquisition point on the path diagram, calculating a risk coefficient through each data acquisition point, dividing the wind power grade and the wind speed grade of each data acquisition point into 10 regions respectively, and classifying according to a mode of 0.1-1, wherein the obtained data are risk coefficients; adding the wind power grade and the risk coefficient value to which the wind power grade belongs of the data acquisition point to obtain a total risk coefficient value of the data acquisition point; the danger coefficient is divided into a high level, a middle level and a low level, and is marked by different colors; marking the total risk coefficient and the risk grades of different colors on a path graph of the historical typhoon, and finally overlapping a plurality of marked path graphs of the historical typhoon according to the geographical coordinate position to obtain a historical typhoon distribution graph;
s2, marking the existing power grid power transmission and distribution facilities on the historical typhoon distribution diagram according to different levels of danger levels by taking the data acquisition points on the historical typhoon distribution diagram as centers, wherein the range of the power grid power transmission and distribution facilities needing to be marked with extremely high danger levels is within 50km from the data acquisition points, the range of the power grid power transmission and distribution facilities needing to be marked with extremely high danger levels is within 40km from the data acquisition points, the range of the power grid power transmission and distribution facilities needing to be marked with medium danger levels is within 30km from the data acquisition points, and the range of the power grid power transmission and distribution facilities needing to be marked with low danger levels is within 20km from the data acquisition points;
s3, collecting data of historical typhoons in the power transmission and distribution facilities of the power grid marked in the step S2, wherein the data comprise disaster-causing levels, disaster-causing frequencies and wind speeds of disaster-causing points, calculating the distance between the disaster-causing points and the nearest point in the path of the historical typhoons, the wind power and wind speed reduction speeds from the historical typhoons to the disaster-causing points, and sequencing the wind power and wind speed reduction speeds from the historical typhoons to the disaster-causing points in sequence;
s4, calculating the distance from the future typhoon to the disaster-causing point according to the time and path of the future typhoon predicted by the weather central office; selecting the wind power and the wind speed reduction speed of the disaster-causing point calculated in the step S3 to predict the disaster-causing probability of the disaster-causing point; distributing the power transmission and distribution facilities of the power grid according to the disaster probability, counting the number of the power transmission and distribution facilities within 10km of a square circle by taking the disaster point as a center if the disaster probability is more than 80%, and distributing according to the standard that at least 3 power transmission and distribution facilities exist; if the disaster probability is between 50% and 80%, counting the number of power grid power transmission and distribution facilities within 10km of a square circle by taking the disaster point as a center, and distributing points according to the standard that at least 2 power grid power transmission and distribution facilities exist; if the disaster probability is between 20% and 50%, counting the number of power grid power transmission and distribution facilities within 10km of a square circle by taking the disaster point as a center, and distributing points according to the standard that at least 1 power grid power transmission and distribution facility exists; if the disaster probability is below 20%, statistics are not carried out.
The 10 areas of the wind power class and the hazard coefficient values are respectively: the wind power is 1 region below 8 levels of wind power, the risk coefficient is 0.1, the wind power is 2 regions 8-9 levels of wind power, the risk coefficient is 0.2, the wind power is 3 regions 9-10 levels of wind power, the risk coefficient is 0.3, the wind power is 4 regions 10-11 levels of wind power, the risk coefficient is 0.4, the wind power is 5 regions 11-12 levels of wind power, the risk coefficient is 0.5, the wind power is 6 regions 12-13 levels of wind power, the risk coefficient is 0.6, the wind power is 7 regions 13-14 levels of wind power, the risk coefficient is 0.7, the wind power is 8 regions 14-15 levels of wind power, the risk coefficient is 0.8, the wind power is 9 regions 15-16 levels of wind power, the risk coefficient is 0.9, the wind power is 10 regions above 16 levels of wind power, and the risk coefficient is 1.
The 10 areas of wind speed and the hazard coefficient values are: the wind speed is 1 region below 20.9m/s, the risk coefficient is 0.1, the wind speed is 2 region from 21 m/s to 24.6m/s, the risk coefficient is 0.2, the wind speed is 3 region from 24.7 m/s to 28.5m/s, the risk coefficient is 0.3, the wind speed is 4 region from 28.6 m/s to 32.6m/s, the risk coefficient is 0.4, the wind speed is 5 region from 32.7 m/s to 36.9m/s, the risk coefficient is 0.5, the wind speed is 6 region from 37.0 m/s to 41.4m/s, the risk coefficient is 0.6, the wind speed is 7 region from 41.5 m/s to 46.1m/s, the risk coefficient is 0.7, the wind speed is 8 region from 46.2 m/s to 50.9m/s, the risk coefficient is 0.8, the wind speed is 9 region from 51.0 m/s to 56.0m/s, the risk coefficient is 0.9, the wind speed is 10 region above 56.1m/s, and the risk coefficient is 1.
The above disclosure is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of changes or modifications within the technical scope of the present invention, and shall be covered by the scope of the present invention.
Claims (7)
1. A typhoon monitoring and point distribution method for a power grid power transmission and distribution facility is characterized by comprising the following steps: the method comprises the following steps:
s1, constructing a historical typhoon distribution map;
the method for constructing the historical typhoon distribution map in the step S1 includes: collecting a path diagram of historical typhoons, equally dividing each data acquisition point on the path diagram, calculating a risk coefficient through each data acquisition point, calculating a total risk coefficient according to the risk coefficient, and dividing risk grades; marking the total risk coefficient and the risk level on a path graph of the historical typhoon, and overlapping the marked path graph of the historical typhoon according to the geographical coordinate position to obtain a historical typhoon distribution graph;
s2, marking the existing power grid power transmission and distribution facilities on the historical typhoon distribution map according to different danger levels;
s3, collecting the data of the historical typhoon in the power transmission and distribution facility of the power grid marked in the step S2, calculating the distance between the disaster-causing point and the historical typhoon path, the wind power from the historical typhoon to the disaster-causing point and the wind speed reduction speed, and sequencing the wind power from the historical typhoon to the disaster-causing point and the wind speed reduction speed in sequence;
s4, calculating the distance from the future typhoon to the disaster-causing point according to the time and path of the future typhoon predicted by the weather central office; predicting the disaster probability of the disaster-causing point, and distributing the power transmission and distribution facilities of the power grid according to the disaster probability;
the specific standard for performing distribution of the power transmission and distribution facility of the power grid according to the disaster-stricken probability in the step S4 is as follows: if the disaster probability is more than 80%, counting the number of power transmission and distribution facilities within 10km of a square circle by taking the disaster point as a center, and distributing points according to the standard that at least 3 power transmission and distribution facilities exist; if the disaster probability is between 50% and 80%, counting the number of power grid power transmission and distribution facilities within 10km of a square circle by taking the disaster point as a center, and distributing points according to the standard that at least 2 power grid power transmission and distribution facilities exist; if the disaster probability is between 20% and 50%, counting the number of power grid power transmission and distribution facilities within 10km of a square circle by taking the disaster point as a center, and distributing points according to the standard that at least 1 power grid power transmission and distribution facility exists; if the disaster probability is below 20%, statistics are not carried out.
2. The grid power transmission and distribution facility typhoon monitoring and stationing method according to claim 1, characterized in that: the method for calculating the total risk coefficient comprises the following steps: dividing the wind power level and the wind speed level of the data acquisition point into 10 regions respectively, and classifying according to a 0.1-1 mode, wherein the obtained data are risk coefficients; and then adding the wind power grade of the data acquisition point and the risk coefficient value to which the wind power grade belongs to obtain the total risk coefficient value of the data acquisition point.
3. The grid power transmission and distribution facility typhoon monitoring and stationing method according to claim 2, characterized in that: the 10 regions of the wind power level and the hazard coefficient values are respectively as follows: the wind power is 1 region below 8 levels of wind power, the risk coefficient is 0.1, the wind power is 2 regions 8-9 levels of wind power, the risk coefficient is 0.2, the wind power is 3 regions 9-10 levels of wind power, the risk coefficient is 0.3, the wind power is 4 regions 10-11 levels of wind power, the risk coefficient is 0.4, the wind power is 5 regions 11-12 levels of wind power, the risk coefficient is 0.5, the wind power is 6 regions 12-13 levels of wind power, the risk coefficient is 0.6, the wind power is 7 regions 13-14 levels of wind power, the risk coefficient is 0.7, the wind power is 8 regions 14-15 levels of wind power, the risk coefficient is 0.8, the wind power is 9 regions 15-16 levels of wind power, the risk coefficient is 0.9, the wind power is 10 regions above 16 levels of wind power, and the risk coefficient is 1.
4. The grid power transmission and distribution facility typhoon monitoring and stationing method according to claim 2, characterized in that: the 10 areas of the wind speed grade and the hazard coefficient values are respectively as follows: the wind speed is 1 region below 20.9m/s, the risk coefficient is 0.1, the wind speed is 2 region from 21 m/s to 24.6m/s, the risk coefficient is 0.2, the wind speed is 3 region from 24.7 m/s to 28.5m/s, the risk coefficient is 0.3, the wind speed is 4 region from 28.6 m/s to 32.6m/s, the risk coefficient is 0.4, the wind speed is 5 region from 32.7 m/s to 36.9m/s, the risk coefficient is 0.5, the wind speed is 6 region from 37.0 m/s to 41.4m/s, the risk coefficient is 0.6, the wind speed is 7 region from 41.5 m/s to 46.1m/s, the risk coefficient is 0.7, the wind speed is 8 region from 46.2 m/s to 50.9m/s, the risk coefficient is 0.8, the wind speed is 9 region from 51.0 m/s to 56.0m/s, the risk coefficient is 0.9, the wind speed is 10 region above 56.1m/s, and the risk coefficient is 1.
5. The grid power transmission and distribution facility typhoon monitoring and stationing method according to claim 1, characterized in that: the danger levels in the step S2 are marked with different colors, and the danger levels are classified into a very high level, a medium level, and a low level.
6. The grid power transmission and distribution facility typhoon monitoring and stationing method according to claim 5, characterized in that: the range of the grid power transmission and distribution facilities to be marked by the super high level in step S2 is within 50km from the data acquisition point, the range of the grid power transmission and distribution facilities to be marked by the high level in step S2 is within 40km from the data acquisition point, the range of the grid power transmission and distribution facilities to be marked by the medium level in step S2 is within 30km from the data acquisition point, and the range of the grid power transmission and distribution facilities to be marked by the low level in step S2 is within 20km from the data acquisition point.
7. The grid power transmission and distribution facility typhoon monitoring and stationing method according to claim 1, characterized in that: the data in the step S3 includes a disaster level, a disaster frequency, and a wind speed at a disaster point.
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| CN109901244B (en) * | 2019-03-29 | 2021-07-27 | 云南电网有限责任公司电力科学研究院 | High-altitude area power transmission line strong wind monitoring and point distribution method and device |
| CN117610898A (en) * | 2024-01-24 | 2024-02-27 | 北京玖天气象科技有限公司 | Point distribution method and device for power grid meteorological monitoring network device |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104050518A (en) * | 2014-07-04 | 2014-09-17 | 国家电网公司 | Power grid convection disaster-causing strong wind early warning method based on Doppler weather radar |
| CN104951585A (en) * | 2014-09-04 | 2015-09-30 | 国网山东省电力公司应急管理中心 | Grid equipment based typhoon warning method and device |
| CN106780738A (en) * | 2017-01-23 | 2017-05-31 | 国网山东省电力公司电力科学研究院 | Path site optimization method based on project of transmitting and converting electricity environmental sensitive area |
| CN106842367A (en) * | 2017-01-04 | 2017-06-13 | 广西电网有限责任公司电力科学研究院 | A kind of power network typhoon method for prewarning risk |
| CN107194494A (en) * | 2017-04-20 | 2017-09-22 | 国网浙江省电力公司电力科学研究院 | A kind of power network Typhoon Monitoring station points distributing method |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106845698A (en) * | 2017-01-04 | 2017-06-13 | 广西电网有限责任公司电力科学研究院 | A kind of Forecasting Methodology of typhoon influence power network outage |
-
2017
- 2017-12-18 CN CN201711368148.0A patent/CN108198090B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104050518A (en) * | 2014-07-04 | 2014-09-17 | 国家电网公司 | Power grid convection disaster-causing strong wind early warning method based on Doppler weather radar |
| CN104951585A (en) * | 2014-09-04 | 2015-09-30 | 国网山东省电力公司应急管理中心 | Grid equipment based typhoon warning method and device |
| CN106842367A (en) * | 2017-01-04 | 2017-06-13 | 广西电网有限责任公司电力科学研究院 | A kind of power network typhoon method for prewarning risk |
| CN106780738A (en) * | 2017-01-23 | 2017-05-31 | 国网山东省电力公司电力科学研究院 | Path site optimization method based on project of transmitting and converting electricity environmental sensitive area |
| CN107194494A (en) * | 2017-04-20 | 2017-09-22 | 国网浙江省电力公司电力科学研究院 | A kind of power network Typhoon Monitoring station points distributing method |
Non-Patent Citations (1)
| Title |
|---|
| 基于Super-ZigBee的高大建筑物台风监测系统;李宗醒等;《仪表技术与传感器》;20111015;第44-45页 * |
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