CN112683324B - Intelligent bolt-based real-time monitoring system for Internet of things of electric power iron tower - Google Patents
Intelligent bolt-based real-time monitoring system for Internet of things of electric power iron tower Download PDFInfo
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Abstract
An intelligent bolt-based real-time monitoring system for the Internet of things of an electric power iron tower is characterized in that displacement sensors are respectively arranged on top bolts of the electric power iron tower so as to measure the displacement of the top of the iron tower; a stress sensor is arranged at the bottom bolt of the electric iron tower to measure the stress born by the bottom of the iron tower; a stress sensor is arranged between the iron tower rod pieces through bolts so as to measure stress between the connecting rods; and carrying out stress analysis based on the electric power iron tower model. The invention provides an intelligent bolt-based real-time monitoring system for the Internet of things of an electric power iron tower, which timely grasps the safety of the iron tower by monitoring information of key parts of the electric power iron tower in the systematicness, improves the maintenance efficiency of the electric power iron tower and prolongs the service life of the electric power tower, and has very important practical significance.
Description
Technical Field
The invention belongs to the field of remote monitoring and fault detection, and relates to an intelligent bolt-based real-time monitoring system for an Internet of things of an electric power tower.
Background
In recent years, along with the rapid development of national economy, the power development also advances the stages of large power grids, large units, high voltage and high automation, and higher requirements are put forward for the stable operation and safety management of the power grids. The continuous operation of large capacity, ultrahigh voltage, alternating current-direct current mixing and long-distance transmission engineering is very important in that the complexity of a power system is obviously increased, the safety management of the power system is enhanced, and the stable operation level is improved.
The transmission tower is used as a key part of power transmission and plays a role of supporting ground wires, wires and other accessories in the overhead transmission line, so that the normal operation of a power system can be directly influenced by the structural health state of the transmission tower. The high-voltage transmission tower, in particular to a large-span transmission tower, has the characteristics of high tower body, long span, large flexibility and the like, is strong in response to environmental loads such as earthquakes, wind, wire ice coating and the like, and can generate certain vibration fatigue damage to certain parts of the tower body after long-time operation and use, and dynamic collapse damage under extreme conditions is easy to occur when severe weather such as ice and snow is encountered. Along with the continuous improvement of the installed capacity and voltage level of a national power grid in recent years, the development trend of the power transmission iron tower towards high-rise, large-span and extra-high voltage directions brings higher requirements for the reliability and economy of the iron tower.
At present, the safety research of the electric power iron tower only considers the effects of factors such as earthquake, lightning stroke, icing and the like in the design stage, the detection mode of the structural defects of the built electric power iron tower often depends on manual inspection and visible light inspection with higher cost, and no definite standard and solution are proposed for the structural problems.
Disclosure of Invention
The invention provides an intelligent bolt-based real-time monitoring system for an electric power iron tower Internet of things, which aims to solve the problem that the operation of the existing high-voltage electric power iron tower is difficult to monitor in real time.
The technical scheme adopted for solving the technical problems is as follows:
an intelligent bolt-based real-time monitoring system for the Internet of things of an electric power iron tower is characterized in that displacement sensors are respectively arranged on top bolts of the electric power iron tower so as to measure the displacement of the top of the iron tower; a stress sensor is arranged at the bottom bolt of the electric iron tower to measure the stress born by the bottom of the iron tower; a stress sensor is arranged between the iron tower rod pieces through bolts so as to measure stress between the connecting rods;
based on the electric power iron tower model, the stress analysis is carried out, and the process is as follows:
firstly, carrying out displacement and stress calculation on a certain type of electric iron tower under dangerous working conditions, sequencing bolt displacement and stress as shown in formulas (1) - (2), counting out nodes with larger displacement and bolts with larger stress, and preselecting the nodes as key nodes;
δ i ＝ω 1 δ i1 +ω 2 δ i2 (1)
σ i ＝ω 1 σ i1 +ω 2 σ i2 (2)
wherein delta i Representing the weighted displacement value, delta, of the ith bolt i1 And delta i2 Representing the measured displacement value omega of the ith bolt under the working conditions of strong wind and ice coating respectively 1 And omega 2 Respectively representing the weight coefficient and sigma of displacement under the working conditions of strong wind and icing i Representing the weighted stress value, sigma, to which the ith bolt is subjected i1 Sum sigma i2 Respectively representing the measured stress values of the ith bolt under the working conditions of strong wind and ice coating;
secondly, counting preselected key rods of each running state of a certain type of iron tower in order to explore the stress condition of the key rods, taking weighted average values of stress data of each node under different working conditions, taking the stress occupancy rate as a sequencing basis, and selecting the key rods with larger values as the key rods, wherein the stress data is shown in a formula (3)
Wherein alpha is j Represents the weight stress percentage, sigma, of the j-th rod j1 Sum sigma j2 Respectively represent the stress value [ sigma ] of the j-th rod piece under the working conditions of strong wind and ice coating j1 ]Sum [ sigma ] j2 ]Respectively representing the maximum allowable stress of the jth rod piece under the working conditions of strong wind and ice coating;
and finally, arranging corresponding intelligent bolt sensors on the key nodes and the rod pieces according to the calculation results, and realizing real-time monitoring.
Further, the data acquisition system for establishing the basis of fault discrimination acquires a feedback electric signal, converts the feedback electric signal into a digital signal, and receives a displacement value and a stress value of a key node and a connecting rod of the iron tower through operations such as noise reduction, filtering and the like; wherein the displacement value and the stress value of the bolt accepted by the system are the displacement value and the stress value accepted by the node of the iron tower, and the stress of the bolt on a certain connecting rod measured by the sensor needs to be converted into the stress born by the rod, so that for a key rod, a local model with bolt connection is established in ANSYS,
the tension (compression) stress of the rod member has a certain relation with the stress of the bolt, namely
σ Rod ＝f(σ Screw thread )
Therefore, the stress of the rod can be obtained by measuring the stress of the bolt on the rod through the sensor, and then the stress is compared with the allowable stress f of the material in design
A coefficient less than 1;
the rod piece stress can be judged to exceed the warning value, and the iron tower is likely to be in fault and alarm is given;
while the design allowable stress f of the material 1 To f 4 After the iron tower is designed, the method can be obtained according to the following formula:
the intensity of the axial stress component is calculated as shown in a formula (4):
N/(A N ·m)≤f 1 (4)
wherein: n is the design value of axle center pressure or axle center tension;
m-component strength reduction coefficient, and taking a value according to the component strength reduction coefficient of the standard table;
A N -member net cross-sectional area, mm 2 ；
And (3) calculating the stability of the axial compression member, wherein the stability is as shown in a formula (5):
wherein:-the stability coefficient of the pressed component of the iron tower axle center, and the specific numerical value is determined according to the specification;
m N -the compression bar stabilizes the intensity reduction factor;
calculation of the strength in the bending moment plane of the stretch-bending member is shown as formula (6):
wherein: m, bending moment design value, N.mm;
w-section moment resistance, mm 3 ；
Stable calculation of the flexural member as shown in equation (7):
wherein: m is M x 、M y -bending moment design values of the beam section around the x-axis and the y-axis, n·mm;
W x 、W y moment resistance to cross section of x-axis and y-axis, mm 3 。
Preferably, the displacement sensor and the stress sensor are both intelligent bolt sensors, a round drill is drilled at the tail part of the bolt, the diameter of the hole is not more than 2 mm, then the strain gauge is embedded in the round drill, and finally special glue is injected for calibration after the round drill is completely solidified.
Or is: the displacement sensor and the stress sensor are intelligent bolt sensors, and the strain gauge is fixed through the clamping force between the bolt and the gasket so as to feel the change of stress.
Or still further: the displacement sensor and the stress sensor are intelligent bolt sensors, and the gasket is made of a strain gauge for measuring stress change.
The technical conception of the invention is as follows: and a plurality of intelligent bolt sensors are distributed among the top, the bottom and the connecting rods of each iron tower, replace the traditional bolts, and are arranged at key stress positions of the iron tower and used for measuring the stress and displacement conditions of the positions.
The invention provides an intelligent bolt-based real-time monitoring system for an electric power tower Internet of things based on electric power tower body structure and failure mechanism research, which utilizes various modes such as sensors embedded in bolts to monitor the stress of bolts, the stress of rod pieces and the displacement of the top of a power transmission tower, calculates and analyzes the condition of the power transmission tower and transmits the condition to a diagnosis system, thereby providing decision basis for electric power safety operation departments. The invention monitors the key parts of the electric power iron tower in a systematic manner to timely master the safety of the iron tower, improves the maintenance efficiency of the electric power iron tower and prolongs the service life of the electric power tower, and has very important practical significance.
The beneficial effects of the invention are mainly shown in the following steps:
1. in recent years, a real-time monitoring system has been widely applied in a plurality of industrial fields, plays an important role in safety monitoring for ensuring the safe and stable operation of industrial equipment, but has relatively few aspects in the aspects of real-time monitoring of the operation state and energy efficiency of an electric power iron tower. The intelligent monitoring device is constructed to monitor the safe operation of the electric power iron tower in real time through the intelligent bolts, and monitor the displacement of the top of the iron tower, the stress borne by the bolts at the bottom of the iron tower and the stress between the connecting rods.
2. The stress sensor and the displacement sensor are respectively combined with the bolts in three forms, so that the monitoring system is guaranteed to collect iron tower signals in real time, and finally visual display of the running state of the electric iron tower and intelligent management of equipment operation and maintenance are realized.
3. The method analyzes the main failure modes of the electric power iron towers, calculates and analyzes key nodes with the maximum stress and the maximum displacement of the electric power iron towers of different types, and provides corresponding failure judgment basis of various iron tower models of different types, thereby having good guiding significance for intelligent monitoring of the iron towers.
Drawings
FIG. 1 is a schematic installation view of a smart bolt sensor.
Wherein, 1 bolt displacement sensor; 2, the top of the tower; 3, a tower body; 4, tower foundation; 5 bolt stress sensor; a 6 truss structure; 7, a main material; 8, inclined materials; 9 stress sensor.
Detailed Description
The invention is further described below with reference to the accompanying drawings.
Referring to fig. 1, an intelligent bolt-based real-time monitoring system for the internet of things of an electric power tower is provided with displacement sensors respectively on top bolts of the electric power tower so as to measure the displacement of the top of the electric power tower; a stress sensor is arranged at the bottom bolt of the electric iron tower to measure the stress born by the bottom of the iron tower; a stress sensor is arranged between the iron tower rod pieces through bolts so as to measure stress between the connecting rods;
based on the electric power iron tower model, the stress analysis is carried out, and the process is as follows:
firstly, carrying out displacement and stress calculation on a certain type of electric iron tower under dangerous working conditions (including combined working conditions of strong wind, ice coating and the like), sequencing bolt displacement and stress as shown in formulas (1) - (2), counting out nodes with larger displacement and bolts with larger stress, and preselecting the nodes as key nodes;
δ i ＝ω 1 δ i1 +ω 2 δ i2 (1)
σ i ＝ω 1 σ i1 +ω 2 σ i2 (2)
wherein delta i Representing the weighted displacement value, delta, of the ith bolt i1 And delta i2 Representing the measured displacement value omega of the ith bolt under the working conditions of strong wind and ice coating respectively 1 And omega 2 Respectively representing the weight coefficient and sigma of displacement under the working conditions of strong wind and icing i Representing the weighted stress value, sigma, to which the ith bolt is subjected i1 Sum sigma i2 Respectively representing the measured stress values of the ith bolt under the working conditions of strong wind and ice coating;
secondly, counting preselected key rods of each running state of a certain type of iron tower in order to explore the stress condition of the key rods, taking weighted average values of stress data of each node under different working conditions, taking the stress occupancy rate (stress divided by allowable stress) as a sequencing basis, and selecting the key rods with larger values as the key rods, wherein the stress data is shown in a formula (3)
Wherein alpha is j Represents the weight stress percentage, sigma, of the j-th rod j1 Sum sigma j2 Respectively represent the stress value [ sigma ] of the j-th rod piece under the working conditions of strong wind and ice coating j1 ]Sum [ sigma ] j2 ]Respectively representing the maximum allowable stress of the jth rod piece under the working conditions of strong wind and ice coating;
and finally, arranging corresponding intelligent bolt sensors on the key nodes and the rod pieces according to the calculation results, and realizing real-time monitoring.
Further, the data acquisition system for establishing the basis of fault discrimination acquires a feedback electric signal, converts the feedback electric signal into a digital signal, and receives a displacement value and a stress value of a key node and a connecting rod of the iron tower through operations such as noise reduction, filtering and the like; wherein the displacement value and the stress value of the bolt accepted by the system are the displacement value and the stress value accepted by the node of the iron tower, and the stress of the bolt on a certain connecting rod measured by the sensor needs to be converted into the stress born by the rod, so that for a key rod, a local model with bolt connection is established in ANSYS,
the tension (compression) stress of the rod member has a certain relation with the stress of the bolt, namely
σ Rod ＝f(σ Screw thread )
Therefore, the stress of the rod can be obtained by measuring the stress of the bolt on the rod through the sensor, and then the stress is compared with the allowable stress f of the material in design
(/>A coefficient of less than 1)
The rod stress can be judged to exceed the warning value, and the iron tower is likely to be in fault, so that an alarm is given.
While the design allowable stress f (f 1 To f 4 ) After the iron tower is designedCan be obtained according to the following formula.
The intensity of the axle center stress component is calculated as shown in a formula (1):
N/(A N ·m)≤f 1 (1)
wherein: n is the design value of axial compression or axial tension.
m-component strength reduction coefficient, and taking a value according to the component strength reduction coefficient of the standard table;
A N -member net cross-sectional area, mm 2 ；
And (3) calculating the stability of the axial compression member, wherein the stability is as shown in a formula (2):
wherein:-the stability coefficient of the pressed component of the iron tower axle center, and the specific numerical value is determined according to the specification;
m N -the compression bar stabilizes the intensity reduction factor.
Calculation of the strength in the bending moment plane of the stretch-bending member, as shown in formula (3):
wherein: m-bending moment design value, N.mm.
W-section moment resistance, mm 3 。
Stable calculation of the flexural member as shown in equation (4):
wherein: m is M x 、M y -bending moment design values of beam sections around x-axis and y-axis, n·mm.
W x 、W y Moment resistance to cross section of x-axis and y-axis, mm 3 。
In order to ensure the universality of the results, the operation is carried out on other iron towers with different models, key nodes and rod information bases of the iron towers with different models in different running states are established, the stress conditions of the iron towers in each running state are analyzed based on software, corresponding iron tower failure criteria are provided, corresponding data are established into an expert system, and the expert system is connected with an online monitoring system in real time.
The intelligent bolt sensor of the embodiment is manufactured by three modes of traditional bolt transformation, clamping and fixing a strain gauge between a nut and a gasket, and changing the gasket into a strain gauge type gasket. The modified sensors are divided into three types, namely a bolt stress sensor, a bolt displacement sensor and a stress sensor. The bolt displacement sensor is arranged at a tower top node and is used for measuring displacement generated by shaking of the tower top; the bolt stress sensor is arranged at the tower foundation and used for measuring the stress of the tower foundation. The stress sensor is installed on the connecting rod and measures the stress of the connecting rod. The measured data is transmitted to an online monitoring system after noise reduction, filtering and conversion through a collecting system, is compared with an established expert database, carries out real-time fault monitoring on the electric power iron tower, and uploads the data to a monitoring center to ensure safe operation of the electric power iron tower. The system has very important practical significance for improving the self safety of the electric power iron tower, maintaining efficiency and service life.
Firstly, an intelligent bolt sensor is obtained by modifying a traditional bolt, firstly, a round drill is drilled at the tail part of the bolt, the diameter of the hole is preferably not more than 2 mm, then a strain gauge is embedded in the round drill, finally, special glue is injected, and calibration is carried out after the round drill is completely solidified. The method has high precision, but needs a certain technical grade requirement, and the stress intensity of the bolt itself needs to be checked. Through calculation, the design meets the requirements of national standards.
The second is to fix the strain gauge by the clamping force between the bolt and the spacer to feel the change in stress. The method has the advantages of simpler manufacturing process, low requirements on the technical level and relatively low cost.
And thirdly, manufacturing a special gasket, namely a strain gauge which is made of the material of the gasket and is used for measuring the stress change. This method is used for iron tower stress monitoring with high accuracy but needs to rely on high manufacturing costs.
The data acquisition system acquires the feedback electrical signal that the sensor will receive and convert to a digital signal. And comparing the digital signals with an expert system database for the displacement signals, so as to judge the working condition of key nodes or rod pieces of the iron tower. Furthermore, the system can report the condition of the electric power iron tower to a monitoring center in real time, and a decision basis is provided for an electric power safe operation department.
The embodiments described in this specification are merely illustrative of the manner in which the inventive concepts may be implemented. The scope of the present invention should not be construed as being limited to the specific forms set forth in the embodiments, but the scope of the present invention and the equivalents thereof as would occur to one skilled in the art based on the inventive concept.
Claims (5)
1. The intelligent bolt-based real-time monitoring system for the Internet of things of the electric power iron tower is characterized in that displacement sensors are respectively arranged on the top bolts of the electric power iron tower so as to measure the displacement of the top of the iron tower; a stress sensor is arranged at the bottom bolt of the electric iron tower to measure the stress born by the bottom of the iron tower; a stress sensor is arranged between the iron tower rod pieces through bolts so as to measure stress between the connecting rods;
based on the electric power iron tower model, the stress analysis is carried out, and the process is as follows:
firstly, carrying out displacement and stress calculation on a certain type of electric iron tower under dangerous working conditions, sequencing bolt displacement and stress as shown in formulas (1) - (2), counting out nodes with larger displacement and bolts with larger stress, and preselecting the nodes as key nodes;
δ i ＝ω 1 δ i1 +ω 2 δ i2 (1)
σ i ＝ω 1 σ i1 +ω 2 σ i2 (2)
wherein delta i Representing the weighted displacement value, delta, of the ith bolt i1 And delta i2 Representing the measured displacement value omega of the ith bolt under the working conditions of strong wind and ice coating respectively 1 And omega 2 Respectively representing the weight coefficient and sigma of displacement under the working conditions of strong wind and icing i Representing the weighted stress value, sigma, to which the ith bolt is subjected i1 Sum sigma i2 Respectively representing the measured stress values of the ith bolt under the working conditions of strong wind and ice coating;
secondly, counting preselected key rods of each running state of a certain type of iron tower in order to explore the stress condition of the key rods, taking weighted average values of stress data of each node under different working conditions, taking the stress occupancy rate as a sequencing basis, and selecting the key rods with larger values as the key rods, wherein the stress data is shown in a formula (3)
Wherein alpha is j Represents the weight stress percentage, sigma, of the j-th rod j1 Sum sigma j2 Respectively represent the stress value [ sigma ] of the j-th rod piece under the working conditions of strong wind and ice coating j1 ]Sum [ sigma ] j2 ]Respectively representing the maximum allowable stress of the jth rod piece under the working conditions of strong wind and ice coating;
and finally, arranging corresponding intelligent bolt sensors on the key nodes and the rod pieces according to the calculation results, and realizing real-time monitoring.
2. The intelligent bolt-based real-time monitoring system for the Internet of things of the electric power iron tower is characterized in that a data acquisition system for establishing a fault discrimination basis acquires feedback electric signals, the feedback electric signals are converted into digital signals, and a receiver receives displacement values and stress values at key nodes and connecting rods of the iron tower through noise reduction and filtering operations; the displacement value and the stress value of the bolt accepted by the system are the displacement value and the stress value accepted by the node of the iron tower, and the stress of the bolt on a certain connecting rod measured by the sensor needs to be converted into the stress born by the rod, so that for a key rod, a local model with the bolt connection is established in ANSYS, and a certain relation exists between the tensile stress or the compressive stress of the rod and the stress born by the bolt, namely
σ Rod ＝f(σ Screw thread )
Therefore, the stress of the rod can be obtained by measuring the stress of the bolt on the rod through the sensor, and then the stress is compared with the allowable stress f of the material in design
A coefficient less than 1;
the rod piece stress can be judged to exceed the warning value, and the iron tower is likely to be in fault and alarm is given;
while the design allowable stress f of the material 1 To f 4 After the iron tower is designed, the method can be obtained according to the following formula:
the intensity of the axial stress component is calculated as shown in a formula (4):
N/(A N ·m)≤f 1 (4)
wherein: n is the design value of axle center pressure or axle center tension;
m-component strength reduction coefficient, and taking a value according to the component strength reduction coefficient of the standard table;
A N -member net cross-sectional area, mm 2 ；
And (3) calculating the stability of the axial compression member, wherein the stability is as shown in a formula (5):
wherein:iron tower axle center compression componentThe stability coefficient and the specific numerical value are determined according to the specification;
m N -the compression bar stabilizes the intensity reduction factor;
calculation of the strength in the bending moment plane of the stretch-bending member is shown as formula (6):
wherein: m, bending moment design value, N.mm;
w-section moment resistance, mm 3 ；
Stable calculation of the flexural member as shown in equation (7):
wherein: m is M x 、M y -bending moment design values of the beam section around the x-axis and the y-axis, n·mm;
W x 、W y moment resistance to cross section of x-axis and y-axis, mm 3 。
3. The intelligent bolt-based power tower internet of things real-time monitoring system according to claim 1 or 2, wherein the displacement sensor and the stress sensor are intelligent bolt sensors, a round drill is drilled at the tail of the bolt, the diameter of the hole is not more than 2 mm, then a strain gauge is buried in the round drill, finally glue is injected, and calibration is carried out after the round drill is completely solidified.
4. The intelligent bolt-based real-time monitoring system for the internet of things of the electric power iron tower according to claim 1 or 2, wherein the displacement sensor and the stress sensor are intelligent bolt sensors, and the strain gauge is fixed through the clamping force between the bolt and the gasket so as to sense the change of the stress.
5. The intelligent bolt-based real-time monitoring system for the Internet of things of the electric power iron tower according to claim 1 or 2, wherein the displacement sensor and the stress sensor are both intelligent bolt sensors, and the gasket is made of a strain gauge for measuring stress change.
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Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH08303046A (en) * | 1995-05-11 | 1996-11-19 | Mitsubishi Heavy Ind Ltd | Bracing device for tower form structure |
| JP2006177761A (en) * | 2004-12-22 | 2006-07-06 | Hokkaido Electric Power Co Inc:The | Detection method of displacement stress produced in member of steel tower |
| CN103488903A (en) * | 2013-09-27 | 2014-01-01 | 国家电网公司 | Method for measuring influences of bolt sliding on steel structure load-bearing |
| KR101353387B1 (en) * | 2013-07-30 | 2014-01-21 | 주식회사 지앤티네트웍스 | Communication tower-structure status monitoring system using displacement sensor |
| CN104006981A (en) * | 2014-05-26 | 2014-08-27 | 西安工程大学 | On-line monitoring system and monitoring method for fracture mechanism of power transmission line iron tower |
| CN104063564A (en) * | 2014-07-17 | 2014-09-24 | 云南电网公司技术分公司 | Method for selecting mounting points of transmission iron tower stress sensors based on finite element analysis |
| CN104092308A (en) * | 2014-07-17 | 2014-10-08 | 云南电网公司技术分公司 | Transmission tower online safety monitoring system and method for stress measuring |
| CN106528902A (en) * | 2015-09-14 | 2017-03-22 | 中国电力科学研究院 | Method for evaluating anti-loosening property of double-nut bolt of power transmission iron tower |
| CN107543641A (en) * | 2017-07-17 | 2018-01-05 | 上海电力学院 | A kind of electric power pylon mechanical characteristic and safety Analysis monitoring system |
| CN109711024A (en) * | 2018-12-18 | 2019-05-03 | 国网内蒙古东部电力有限公司经济技术研究院 | One kind being bolted a Force Optimal Analysis method |
| CN208848050U (en) * | 2018-10-31 | 2019-05-10 | 桂林师范高等专科学校 | Steel tower safety detection system |
| CN111693091A (en) * | 2020-06-11 | 2020-09-22 | 国网河北省电力有限公司建设公司 | Iron tower working condition Internet of things monitoring system |
| CN111697490A (en) * | 2020-04-30 | 2020-09-22 | 国网浙江省电力有限公司 | Electric power iron tower wiring device based on Internet of things equipment and use method |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10209291B2 (en) * | 2016-02-04 | 2019-02-19 | The University Of Akron | System and method for condition monitoring of electricity transmission structures |
-
2020
- 2020-11-25 CN CN202011336902.4A patent/CN112683324B/en active Active
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH08303046A (en) * | 1995-05-11 | 1996-11-19 | Mitsubishi Heavy Ind Ltd | Bracing device for tower form structure |
| JP2006177761A (en) * | 2004-12-22 | 2006-07-06 | Hokkaido Electric Power Co Inc:The | Detection method of displacement stress produced in member of steel tower |
| KR101353387B1 (en) * | 2013-07-30 | 2014-01-21 | 주식회사 지앤티네트웍스 | Communication tower-structure status monitoring system using displacement sensor |
| CN103488903A (en) * | 2013-09-27 | 2014-01-01 | 国家电网公司 | Method for measuring influences of bolt sliding on steel structure load-bearing |
| CN104006981A (en) * | 2014-05-26 | 2014-08-27 | 西安工程大学 | On-line monitoring system and monitoring method for fracture mechanism of power transmission line iron tower |
| CN104092308A (en) * | 2014-07-17 | 2014-10-08 | 云南电网公司技术分公司 | Transmission tower online safety monitoring system and method for stress measuring |
| CN104063564A (en) * | 2014-07-17 | 2014-09-24 | 云南电网公司技术分公司 | Method for selecting mounting points of transmission iron tower stress sensors based on finite element analysis |
| CN106528902A (en) * | 2015-09-14 | 2017-03-22 | 中国电力科学研究院 | Method for evaluating anti-loosening property of double-nut bolt of power transmission iron tower |
| CN107543641A (en) * | 2017-07-17 | 2018-01-05 | 上海电力学院 | A kind of electric power pylon mechanical characteristic and safety Analysis monitoring system |
| CN208848050U (en) * | 2018-10-31 | 2019-05-10 | 桂林师范高等专科学校 | Steel tower safety detection system |
| CN109711024A (en) * | 2018-12-18 | 2019-05-03 | 国网内蒙古东部电力有限公司经济技术研究院 | One kind being bolted a Force Optimal Analysis method |
| CN111697490A (en) * | 2020-04-30 | 2020-09-22 | 国网浙江省电力有限公司 | Electric power iron tower wiring device based on Internet of things equipment and use method |
| CN111693091A (en) * | 2020-06-11 | 2020-09-22 | 国网河北省电力有限公司建设公司 | Iron tower working condition Internet of things monitoring system |
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