CN107976172A - Steel tower sedimentation on-line monitoring system and monitoring method under being encouraged based on natural wind - Google Patents
Steel tower sedimentation on-line monitoring system and monitoring method under being encouraged based on natural wind Download PDFInfo
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Abstract
The invention discloses the steel tower under being encouraged based on natural wind to settle on-line monitoring system, its structure includes light 3-axis acceleration sensor, conditioning module, A/D modular converters, microprocessor, 4G communication units and monitoring center.The invention also discloses monitoring method, specific steps include steel tower modeling and model analysis, the processing of acceleration signal, the model analysis of steel tower acceleration signal, steel tower sedimentation four steps of diagnosis.What it was used etc..Contain high-precision Kalman filtering algorithm in microprocessor, for obtaining accurately measured value.Monitoring center carries out model analysis to the data that measurement is returned, and obtains the actual damping ratio matrix of steel tower, and obtain the damping ratio matrix of steel tower theory by emulation.By contrasting and analyzing reality and theoretical value, judge whether electric power pylon settles, realize to settle electric power pylon and monitor on-line.
Description
Technical field
The invention belongs to power transmission state monitoring and diagnostic techniques field, and in particular to one kind is based under natural wind excitation
Steel tower sedimentation on-line monitoring system, the invention further relates to the monitoring method carried out using the monitoring system.
Background technology
In electric system, important step of the electric power pylon as power transmission, its safe operation is to ensure electrical energy transportation
An important factor for.Due to China's physical features complicated condition, acted on plus harsh extraneous natural environment, electric power transmission line steel tower warp
Often it is subjected to displacement, tilts, cracking, phenomena such as sinking, especially in the mollisol matter such as desert area.In recent years, due to some certainly
The right reason such as phenomenon (such as sleet, strong wind) and coal mining, engineering construction, artificial destruction causes tower body to settle inclined feelings
Condition happens occasionally.Tower body sedimentation, which tilts, often causes transmission line of electricity and communication network to interrupt, serious to cause the accident of falling tower.
These normal works all by the safe operation to power transmission network cause great threat, cause damages to people's lives and properties.
Since electric power pylon is mostly distributed in the wild, a large amount of manpowers will be expended according to the method monitoring that traditional personnel make an inspection tour
Material resources, and implement the degree of reliability and be difficult to ensure that.The steel tower stood fast at for nobody, is even more nothing when steel tower sedimentation accident occurs
Method notifies administrative staff to send maintenance personal to recover within the shortest time at the first time, therefore the real-time monitoring for steel tower is aobvious
It is particularly important that obtaining.
The content of the invention
It is an object of the invention to provide the steel tower under a kind of excitation based on natural wind to settle on-line monitoring system, Neng Goushi
Existing steel tower sedimentation on-line monitoring, ensures the normal work of equipment and safeguards in time.
The technical solution adopted in the present invention is that the steel tower under being encouraged based on natural wind settles on-line monitoring system, including
Sequentially connected front end monitoring device, 4G communication units and monitoring center, front end monitoring device add including sequentially connected three axis
Velocity sensor, conditioning module, AD conversion module and microprocessor, microprocessor are connected with 4G communication units.
It is a further object of the present invention to provide a kind of steel tower sedimentation on-line monitoring system using this under being encouraged based on natural wind
The method that system is monitored.
Another technical solution of the present invention is a kind of steel tower sedimentation on-line monitoring system using this under being encouraged based on natural wind
The method that system is monitored, it is characterised in that specifically implement according to following steps：
Step 1, establish model, ask for iron tower structure to be detected it is normal when damping ratio matrix
Step 2, steel tower acceleration is acquired using 3-axis acceleration sensor, and utilizes A/D converter by data
Digital quantity is converted to, gives microprocessor；
Step 3, microprocessor calculates steel tower under different wind speed, wind direction according to actual acquisition signal condition using ITD methods
Damping ratio, and averaged, finally obtain the damping ratio matrix of measurement
Step 4, the damping ratio matrix that will be measured in step 3With the damping ratio obtained under normal condition in step 1
MatrixIt is compared, judges the state of steel tower.
The features of the present invention also resides in,
Step 1 is specially：
Step 1.1, the finite element model of steel tower to be detected is established, and carries out steel tower model analysis, steel tower is tried to achieve and does not occur
Damping ratio matrix under settling phase
Step 1.2, it is contemplated that electric power pylon has various voltage class, variously-shaped, and a variety of steel tower moulds are established in modeling
Type, in order to monitor various types of steel towers；
Step 1.3, using the data gathered in step 1.2, mode point is carried out to steel tower using the method for finite element simulation
Analysis, is not there is the intrinsic frequency matrix of bolt looseness steel tower rod pieceThe intrinsic frequency of steel tower rod piece when i.e. state is normal
Matrix
Step 3 specifically,
Step 3.1, by acceleration signal carry out digital filtering, enhanced processing, filters out the interference signal of below 100HZ；
Step 3.2, by the data obtained in step 3.1 do quadratic integral on time t, establishes on dynamic respond
ITD method mathematical models, as shown in formula (3-2-1),
Wherein,
λi=-σi+jωi
Wherein, x (t) be steel tower damping system dynamic respond, piFor each rank modal vibration amplitude of steel tower free response, it is
N × 2n rank matrixes, and it is a linear unrelated, * represents conjugation；E (t) is 2n rank matrixes.The preceding n row of P matrixes and the preceding n of e (t) are a
Element includes modal parameter to be identified；λiRepresent dimensionless Complex Modal Parameter Identification, σiDamped for dimensionless, ωiFor dimensionless frequency
Rate；J represents imaginary part；I=1,2 ... 2n.
Step 3.3, the data matrix for establishing steel tower free response；
Step 3.4, the augmented matrix of steel tower free response is constructed；
Step 3.5, construction steel tower system features equation, i.e. formula (3-5-1)；
And remember,
Wherein, matrix A is the eigenmatrix of steel tower damping system；
Then,
The eigenmatrix A of steel tower damping system can be then calculated,
Step 3.6, estimation modal parameter.
Step 3.3 is specially：
If obtain the free response time history of M measuring pointBy following three form into
Row sampling,
Step 3.3.1, first carries out normal sample, and Δ t is sampled at a certain time interval,
X=[x (t1) x(t2) … x(t2n)]=PE
E=[e (t1) e(t2) … e(t2n)]
Wherein,It is n × 2n rank matrixes for the matrix of the modal displacement of steel tower, matrix E is to derive calculating into row matrix
When a companion matrix introducing, be 2n × 2n rank matrixes；
Step 3.3.2, then sampled into line delay, i.e., after step 3.3.1 samplings, it is delayed after Δ τ, is sampled,
Obtain the matrix of data composition obtained after a delay sampling
Y=[x (t1+Δτ) x(t2+Δτ) … x(t2n+ Δ τ)]=QE
Q=P Δs
Wherein,For M × 2n rank matrixes, matrix Q is the companion matrix introduced when deriving and calculating into row matrix.
Step 3.3.3, after step 3.3.2 samplings, then the 2 Δ τ samplings that are delayed, the data composition matrix sampled
Z=[x (t1+2Δτ) x(t2+2Δτ) … x(t2n+ 2 Δ τ)]=RE
R=Q Δs
Wherein,For M × 2n rank matrixes, matrix R is the companion matrix introduced when deriving and calculating into row matrix.
Step 3.4 specifically,
Step 3.4.1, by during step 3.3.1 normal samples and data structure steel tower that step 3.3.2 delay samplings obtain from
Augmented matrix D is made by what is respondedxy,
Wherein, DxyFor 2n × 2n rank matrixes；
Step 3.4.2, the data sampled by the Δ τ samplings that are delayed in step 3.3.2 with the 2 Δ τ that are delayed in step 3.3.3
Construct augmented matrix Dyz；
Wherein, DyzFor 2n × 2n rank matrixes.
Step 3.6 is specially：
The eigenmatrix A of steel tower damping system in 3.5 is solved, obtains characteristic value
Known by step 3.2, λi=-σi+jωi, bring into Δ i,
：
Then have：
In formula, Re represents real part, and Im represents imaginary part,
Then,
Have,Try to achieve damping ratio matrix
Step 4 is specially：
The damping ratio matrix that will be measured in step 3With the damping ratio matrix obtained under normal condition in step 1
It is compared,
WhenWhen, judge that sedimentation accident occurs for steel tower,
Otherwise, whenWhen, judge that steel tower state is normal.
The beneficial effects of the invention are as follows：
1.STM32 microcontrollers integrate high-precision Kalman filtering algorithm, can obtain accurately acceleration survey
Value.
2. the present invention establishes electric power pylon finite element model, and obtains steel tower by finite element method and do not settle
When damping ratio matrix.There are a various voltage class in view of electric power pylon, it is variously-shaped (wine glass-shaped, cathead, upper font, dry
Font and barrel shape), a variety of iron tower models should be established in modeling, in order to monitor various types of steel towers.
3. the present invention carries out the operational modal analysis of steel tower using ITD methods, the acceleration signal that can be gathered according to sensor
The damping ratio matrix of steel tower is analyzed, then the damping ratio matrix obtained with finite element simulation under same operating is contrasted, and is judged
Whether settle.
4. monitoring center of the present invention can Remote configuration microprocessor parameters, the uploading speed of sample rate, data such as data,
Measuring device zeroing etc..
Brief description of the drawings
Fig. 1 is the structure diagram of the steel tower sedimentation on-line monitoring system under the present invention is encouraged based on natural wind；
Fig. 2 is the flow chart of the steel tower sedimentation on-line monitoring method under the present invention is encouraged based on natural wind.
In figure, 1. front end measuring devices, 1-1. 3-axis acceleration sensors, 1-2. conditioning modules, 1-3.AD modular converters,
1-4. microprocessors, 2.4G communication units, 3. monitoring centers.
Embodiment
The present invention is described in detail with reference to the accompanying drawings and detailed description.
Steel tower under the present invention is encouraged based on natural wind settles on-line monitoring system, as shown in Figure 1, including sequentially connected
Front end monitoring device 1,4G communication units 2 and monitoring center 3.
Wherein, front end monitoring device 1 includes sequentially connected 3-axis acceleration sensor 1-1, conditioning module 1-2, AD turns
Block 1-3 and microprocessor 1-4 is changed the mold, microprocessor 1-4 is connected with 4G communication units 2.
The installment work process of the system is, first transmission pressure steel tower cross-arm and ground wire intersection, tower body bottle mouth position,
The tower body main material highly located apart from ground 30m installs some 3-axis acceleration sensor 1-1, for measuring adding when steel tower vibrates
Speed.The acceleration signal measured need to be filtered by conditioning module 1-2 and enhanced processing, gives AD conversion module afterwards
1-3 carries out AD samplings.A/D modular converters 1-3 is connected by synchronous serial communication mouth iic with microprocessor 1-4, microprocessor 1-4
High-precision Kalman filtering algorithm is internally integrated, for obtaining accurately measured value.Microprocessor 1-4 by asynchronous serial port with
4G communication units 2 connect.The acceleration information of measurement is wirelessly sent to monitoring center 3 by 4G communication units 2.Monitoring
Center 3 docks received data and is parsed and calculated, and judges whether that sedimentation accident occurs.
Steel tower under being encouraged based on natural wind settles on-line monitoring method, above-mentioned monitoring system is make use of, such as Fig. 2 institutes
Show, specifically implement according to the following steps：
Step 1：Establish model, ask for iron tower structure to be detected it is normal when damping ratio matrix
Step 1.1, the finite element model for establishing steel tower to be detected, and steel tower model analysis is carried out, try to achieve steel tower and do not occur
Damping ratio matrix under settling phase
It is (wine glass-shaped, cathead, upper font, dry that step 1.2, have various voltage class in view of electric power pylon, variously-shaped
Font and barrel shape), a variety of iron tower models are established in modeling, in order to monitor various types of steel towers.
Step 2：Steel tower acceleration is acquired using 3-axis acceleration sensor, and utilizes A/D converter by data
Digital quantity is converted to, gives microprocessor.
Step 3：Microprocessor calculates steel tower under different wind speed, wind direction according to actual acquisition signal condition using ITD methods
Damping ratio, and averaged, finally obtain the damping ratio matrix of measurementSpecific step is：
Step 3.1, by acceleration signal carry out digital filtering, enhanced processing, filters out the interference signal of below 100HZ；
Step 3.2, by the data obtained in step 3.1 do quadratic integral on time t, establishes on dynamic respond
ITD method mathematical models, as shown in formula (3-2-1),
Wherein,
λi=-σi+jωi
Wherein, x (t) be steel tower damping system dynamic respond, piFor each rank modal vibration amplitude of steel tower free response, it is
N × 2n rank matrixes, and it is a linear unrelated, * represents conjugation；E (t) is 2n rank matrixes.The preceding n row of P matrixes and the preceding n of e (t) are a
Element includes modal parameter to be identified；λiRepresent dimensionless Complex Modal Parameter Identification, σiDamped for dimensionless, ωiFor dimensionless frequency
Rate；J represents imaginary part；I=1,2 ... 2n.
Step 3.3, the data matrix for establishing steel tower free response；Comprise the concrete steps that：
If obtain the free response time history of M measuring pointBy following three form into
Row sampling.
Step 3.3.1, first carries out normal sample, and Δ t is sampled at a certain time interval,
X=[x (t1) x(t2) … x(t2n)]=PE
E=[e (t1) e(t2) … e(t2n)]
Wherein,It is n × 2n rank matrixes for the matrix of the modal displacement of steel tower, matrix E is to derive calculating into row matrix
When a companion matrix introducing, be 2n × 2n rank matrixes.
Step 3.3.2, then sampled into line delay, i.e., after step 3.3.1 samplings, it is delayed after Δ τ, is sampled,
Obtain the matrix of data composition obtained after a delay sampling
Y=[x (t1+Δτ) x(t2+Δτ) … x(t2n+ Δ τ)]=QE
Q=P Δs
Wherein,For M × 2n rank matrixes, matrix Q is the companion matrix introduced when deriving and calculating into row matrix.
Step 3.3.3, after step 3.3.2 samplings, then the 2 Δ τ samplings that are delayed,
Sample obtained data composition matrix
Z=[x (t1+2Δτ) x(t2+2Δτ) … x(t2n+ 2 Δ τ)]=RE
R=Q Δs
Wherein,For M × 2n rank matrixes, matrix R is the companion matrix introduced when deriving and calculating into row matrix.
Step 3.4, the augmented matrix of steel tower free response is constructed；
Step 3.4.1, by during step 3.3.1 normal samples and data structure steel tower that step 3.3.2 delay samplings obtain from
Augmented matrix D is made by what is respondedxy。
Wherein, DxyFor 2n × 2n rank matrixes；
Step 3.4.2, by the 2 Δ τ samplings that are delayed that are delayed in step 3.3.2 in Δ τ samplings and step 3.3.3
Obtained data configuration augmented matrix Dyz；
Wherein, DyzFor 2n × 2n rank matrixes.
Step 3.5, construction steel tower system features equation, i.e. formula (3-5-1)；
And remember,
Wherein, matrix A is the eigenmatrix of steel tower damping system；
Then,
The eigenmatrix A of steel tower damping system can be then calculated,
Step 3.6, estimation modal parameter；
The eigenmatrix A of steel tower damping system in 3.5 is solved, obtains characteristic value
Known by step 3.2, λi=-σi+jωi, bring into Δ i,
：
Then have：
In formula, Re represents real part, and Im represents imaginary part,
Then,
Have,Try to achieve damping ratio matrix
Step 4, the damping ratio matrix that will be measured in step 3With the damping ratio obtained under normal condition in step 1
MatrixIt is compared, judges steel tower state,
WhenWhen, judge that sedimentation accident occurs for steel tower,
Otherwise, whenWhen, judge that steel tower state is normal.
Claims (8)
1. the steel tower under being encouraged based on natural wind settles on-line monitoring system, it is characterised in that is supervised including sequentially connected front end
Surveying device (1), 4G communication units (2) and monitoring center (3), the front end monitoring device (1) includes sequentially connected three axis
Acceleration transducer (1-1), conditioning module (1-2), AD conversion module (1-3) and microprocessor (1-4), the microprocessor
(1-4) is connected with 4G communication units (2).
2. a kind of settle what on-line monitoring system was monitored using described in claim 1 based on the steel tower under natural wind excitation
Method, it is characterised in that specifically implement according to following steps：
Step 1, establish model, ask for iron tower structure to be detected it is normal when damping ratio matrix
Step 2, steel tower acceleration is acquired using 3-axis acceleration sensor, and utilizes A/D converter by data conversion
For digital quantity, microprocessor is given；
Step 3, microprocessor calculates the resistance of steel tower under different wind speed, wind direction using ITD methods according to actual acquisition signal condition
Buddhist nun's ratio, and averaged, finally obtain the damping ratio matrix of measurement
Step 4, the damping ratio matrix that will be measured in step 3With the damping ratio matrix obtained under normal condition in step 1
It is compared, judges the state of steel tower.
3. the side that the steel tower sedimentation on-line monitoring system under the excitation according to claim 2 based on natural wind is monitored
Method, it is characterised in that the step 1 is specially：
Step 1.1, the finite element model of steel tower to be detected is established, and carries out steel tower model analysis, steel tower is tried to achieve and does not settle
Damping ratio matrix under state
Step 1.2, it is contemplated that electric power pylon has various voltage class, variously-shaped, and a variety of iron tower models are established in modeling, with
Easy to monitor various types of steel towers；
Step 1.3, using the data gathered in step 1.2, model analysis is carried out to steel tower using the method for finite element simulation, is obtained
To the intrinsic frequency matrix for not having bolt looseness steel tower rod pieceThe intrinsic frequency matrix of steel tower rod piece when i.e. state is normal
What 4. the steel tower sedimentation on-line monitoring system according to claim 2 using under being encouraged based on natural wind was monitored
Method, it is characterised in that the step 3 specifically,
Step 3.1, by acceleration signal carry out digital filtering, enhanced processing, filters out the interference signal of below 100HZ；
Step 3.2, by the data obtained in step 3.1 do quadratic integral on time t, establishes the ITD methods on dynamic respond
Mathematical model, as shown in formula (3-2-1),
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λi=-σi+jωi
Wherein, x (t) be steel tower damping system dynamic respond, piIt is n × 2n for each rank modal vibration amplitude of steel tower free response
Rank matrix, and it is a linear unrelated, * represents conjugation；E (t) is 2n rank matrixes；The preceding n row of P matrixes and the preceding n element of e (t)
Include modal parameter to be identified；λiRepresent dimensionless Complex Modal Parameter Identification, σiDamped for dimensionless, ωiFor dimensionless frequency；J tables
Show imaginary part；I=1,2 ... 2n；
Step 3.3, the data matrix for establishing steel tower free response；
Step 3.4, the augmented matrix of steel tower free response is constructed；
Step 3.5, construction steel tower system features equation, i.e. formula (3-5-1)；
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Wherein, matrix A is the eigenmatrix of steel tower damping system；
Then,
The eigenmatrix A of steel tower damping system can be then calculated,
Step 3.6, estimation modal parameter.
What 5. the steel tower sedimentation on-line monitoring system according to claim 4 using under being encouraged based on natural wind was monitored
Method, it is characterised in that the step 3.3 is specially：
If obtain the free response time history of M measuring pointAdopted by following three form
Sample,
Step 3.3.1, first carries out normal sample, and Δ t is sampled at a certain time interval,
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X=[x (t1) x(t2) … x(t2n)]=PE
E=[e (t1) e(t2) … e(t2n)]
Wherein,It is n × 2n rank matrixes for the matrix of the modal displacement of steel tower, matrix E is to draw when deriving and calculating into row matrix
The companion matrix entered, is 2n × 2n rank matrixes；
Step 3.3.2, then sampled into line delay, i.e., after step 3.3.1 samplings, it is delayed after Δ τ, is sampled,
Obtain the matrix of data composition obtained after a delay sampling
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Y=[x (t1+Δτ) x(t2+Δτ) … x(t2n+ Δ τ)]=QE
Q=P Δs
Wherein,For M × 2n rank matrixes, matrix Q is the companion matrix introduced when deriving and calculating into row matrix；
Step 3.3.3, after step 3.3.2 samplings, then the 2 Δ τ samplings that are delayed, the data composition matrix sampled
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Z=[x (t1+2Δτ) x(t2+2Δτ) … x(t2n+ 2 Δ τ)]=RE
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Wherein,For M × 2n rank matrixes, matrix R is the companion matrix introduced when deriving and calculating into row matrix.
What 6. the steel tower sedimentation on-line monitoring system according to claim 4 using under being encouraged based on natural wind was monitored
Method, it is characterised in that the step 3.4 specifically,
Step 3.4.1, by freely being rung with data structure steel tower that step 3.3.2 delay samplings obtain during step 3.3.1 normal samples
That answers makes augmented matrix Dxy,
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Wherein, DxyFor 2n × 2n rank matrixes；
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Augmented matrix Dyz；
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What 7. the steel tower sedimentation on-line monitoring system according to claim 4 using under being encouraged based on natural wind was monitored
Method, it is characterised in that the step 3.6 is specially：
The eigenmatrix A of steel tower damping system in 3.5 is solved, obtains characteristic value
Known by step 3.2, λi=-σi+jωi, bring into Δ i,
：
Then have：
In formula, Re represents real part, and Im represents imaginary part,
Then,
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Have,Try to achieve damping ratio matrix
What 8. the steel tower sedimentation on-line monitoring system according to claim 2 using under being encouraged based on natural wind was monitored
Method, it is characterised in that the step 4 is specially：
The damping ratio matrix that will be measured in step 3With the damping ratio matrix obtained under normal condition in step 1Carry out
Compare,
WhenWhen, judge that sedimentation accident occurs for steel tower,
Otherwise, whenWhen, judge that steel tower state is normal.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108918118A (en) * | 2018-07-06 | 2018-11-30 | 西安工程大学 | A kind of electric power pylon bolt looseness monitoring system and method based on artificial excitation |
| CN109870318A (en) * | 2019-03-25 | 2019-06-11 | 国网宁夏电力有限公司电力科学研究院 | GIS foundation bolt loosening diagnosis method based on frequency response curve peak Distribution |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101446517A (en) * | 2008-12-17 | 2009-06-03 | 中国电力科学研究院 | Method for testing vibration of high-tower structure of transmission line |
| CN101782475A (en) * | 2010-02-08 | 2010-07-21 | 天津工业大学 | Blade fault diagnosing method based on vibration of wind generating set |
| CN203561387U (en) * | 2013-11-30 | 2014-04-23 | 广东天信电力工程检测有限公司 | Power-transmission iron-tower safety monitoring system |
| CN203798386U (en) * | 2014-04-28 | 2014-08-27 | 鼎兴联通（北京）网络科技有限公司 | Iron tower data acquisition device based on combination of multiple sensors |
| CN106525368A (en) * | 2015-09-11 | 2017-03-22 | 中国电力科学研究院 | Cat head-type transmission tower damping ratio recognition method |
| CN106548009A (en) * | 2016-10-11 | 2017-03-29 | 中国电力科学研究院 | The appraisal procedure and device of goaf power transmission tower dynamic impact effects |
-
2017
- 2017-11-15 CN CN201711129631.3A patent/CN107976172B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101446517A (en) * | 2008-12-17 | 2009-06-03 | 中国电力科学研究院 | Method for testing vibration of high-tower structure of transmission line |
| CN101782475A (en) * | 2010-02-08 | 2010-07-21 | 天津工业大学 | Blade fault diagnosing method based on vibration of wind generating set |
| CN203561387U (en) * | 2013-11-30 | 2014-04-23 | 广东天信电力工程检测有限公司 | Power-transmission iron-tower safety monitoring system |
| CN203798386U (en) * | 2014-04-28 | 2014-08-27 | 鼎兴联通（北京）网络科技有限公司 | Iron tower data acquisition device based on combination of multiple sensors |
| CN106525368A (en) * | 2015-09-11 | 2017-03-22 | 中国电力科学研究院 | Cat head-type transmission tower damping ratio recognition method |
| CN106548009A (en) * | 2016-10-11 | 2017-03-29 | 中国电力科学研究院 | The appraisal procedure and device of goaf power transmission tower dynamic impact effects |
Non-Patent Citations (1)
| Title |
|---|
| 曹树谦 等: "《振动结构模态分析 理论实验与应用 第2版》", 30 September 2012, 天津大学出版社 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108918118A (en) * | 2018-07-06 | 2018-11-30 | 西安工程大学 | A kind of electric power pylon bolt looseness monitoring system and method based on artificial excitation |
| CN109870318A (en) * | 2019-03-25 | 2019-06-11 | 国网宁夏电力有限公司电力科学研究院 | GIS foundation bolt loosening diagnosis method based on frequency response curve peak Distribution |
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