CN107784182A - A kind of electric power pylon sedimentation recognition methods based on model analysis - Google Patents
A kind of electric power pylon sedimentation recognition methods based on model analysis Download PDFInfo
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- CN107784182A CN107784182A CN201711131257.0A CN201711131257A CN107784182A CN 107784182 A CN107784182 A CN 107784182A CN 201711131257 A CN201711131257 A CN 201711131257A CN 107784182 A CN107784182 A CN 107784182A
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- 238000000034 method Methods 0.000 title claims abstract description 23
- 238000004062 sedimentation Methods 0.000 title claims abstract description 20
- 229910000831 Steel Inorganic materials 0.000 claims abstract description 50
- 239000010959 steel Substances 0.000 claims abstract description 50
- 230000001133 acceleration Effects 0.000 claims abstract description 20
- 239000011159 matrix material Substances 0.000 claims abstract description 19
- 230000005284 excitation Effects 0.000 claims abstract description 11
- 230000005540 biological transmission Effects 0.000 claims description 11
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 claims description 10
- 229910052742 iron Inorganic materials 0.000 claims description 5
- 238000005259 measurement Methods 0.000 claims description 4
- 238000012545 processing Methods 0.000 claims description 4
- 238000004088 simulation Methods 0.000 claims description 4
- 238000013016 damping Methods 0.000 claims description 3
- 238000005070 sampling Methods 0.000 claims description 3
- 238000006467 substitution reaction Methods 0.000 claims description 3
- 238000004891 communication Methods 0.000 abstract description 4
- 238000001914 filtration Methods 0.000 abstract 1
- 238000012544 monitoring process Methods 0.000 description 8
- 238000012631 diagnostic technique Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 239000002689 soil Substances 0.000 description 1
- 238000012876 topography Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/23—Design optimisation, verification or simulation using finite element methods [FEM] or finite difference methods [FDM]
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C5/00—Measuring height; Measuring distances transverse to line of sight; Levelling between separated points; Surveyors' levels
Abstract
The invention discloses a kind of electric power pylon based on model analysis to settle recognition methods, and its system includes acceleration transducer, filtering, A/D convertor circuit, control circuit, tuning power hammer, microprocessor and 4G communication modules and Surveillance center.Tuning power is hammered into shape for producing stable pulse excitation, and acceleration transducer is used for the vibration signal for gathering steel tower, integrated in microprocessor a young waiter in a wineshop or an inn multiply complex exponential method (LSCE) method be used for extract the modal parameter that vibrates.Its Surveillance center is analyzed with the intrinsic frequency matrix of the intact steel tower of structure using the intrinsic frequency matrix surveyed in real time, is judged whether steel tower occurs sedimentation accident.
Description
Technical field
The invention belongs to power transmission state monitoring and diagnostic techniques field, and in particular to a kind of based on the defeated of model analysis
Ferroelectric tower settles recognition methods.
Background technology
Electric power pylon is one of important component of power network line, and its most of basis is independent concrete structure.Add
China it is with a varied topography, the places such as electric power pylon can exempt from that mountain region, hills can be erected at unavoidably, the soil is porous.These places are easily
Generation electric power pylon settles accident, and unbalanced tensile force will be produced after steel tower settles, such as can not timely take steel tower
Righting measure, it will cause down the serious accident such as tower, broken string, cause immeasurable economic loss.
China does not have the effective on-line monitoring system of complete set for steel tower sedimentation at present, is mainly manually patrolled with relying on
Based on line method.Artificial line walking not only expends a large amount of manpower and materials, and implements the degree of reliability and be difficult to ensure that.Stood fast at for nobody
Steel tower, when occur steel tower sedimentation accident when, even more administrative staff can not be notified to send maintenance personal most short the very first time
Recover in time, therefore realize that the real-time monitoring for steel tower sedimentation is particularly important.
The content of the invention
It is an object of the invention to provide a kind of electric power pylon based on model analysis to settle recognition methods, realizes to transmission of electricity
The on-line monitoring of steel tower sedimentation.
The technical solution adopted in the present invention is a kind of steel tower sedimentation on-line monitoring method based on model analysis, specifically
Implement according to following steps：
Step 1, the steel tower intact to structure carries out model analysis；
Step 2, the control tuning power hammer of timing taps steel tower, taps produce same pulse excitation δ (s) every time；
Step 3, acceleration is gathered using acceleration transducer；
Step 4, the intrinsic frequency matrix of steel tower under actual condition is calculated using least square complex exponential method, as measurement
Intrinsic frequency matrix
Step 5, the intrinsic frequency matrix that will be calculated in the intrinsic frequency matrix for measuring to obtain in step 4 and step 1
Compare, whenWhen, judge that sedimentation accident occurs for steel tower.
The features of the present invention also resides in,
Step 1 is specially：
Step 1.1, the intact nothing of iron tower structure is confirmed to carrying out detailed state estimation to scene steel tower to be installed first
Damage；
Step 1.2, model analysis is carried out to steel tower using the method for finite element simulation degree, when not settling
The intrinsic frequency matrix of steel tower
Step 4 is specially：
Step 4.1, acceleration signal is filtered, filters out below 100Hz interference signal；And pass through A/D convertor circuit
1-3 processing, the data-signal after being handled；
Step 4.2, utilize pulse excitation δ (s) the calculating iron in the acceleration signal and step 2 after being handled in step 4.1
Tower System transmission function
Wherein, AlprFor r rank mode residuals, * represents to be conjugated, complex frequency s=j ω, srFor limit；J represents imaginary part, ω
For the frequency of system；N represents the exponent number of steel tower system；
AlprFor complex constant, the system vibration shape and in the response the parameter situation of each rank mode are represented；
Step 4.3, to transmission functionLaplace Transform is done, as shown in formula (4-3-1)；
Wherein,
Wherein, ωrFor steel tower system r rank undamped modal frequencies, ζrFor steel tower system r rank damping ratios,
Step 4.4, discretization transmission function simultaneously construct Prony multinomials, by pulse response time it is Sequence Transformed be one from
Regression model (4-4-1)；
Wherein, m is sampled point, m=1,2 ..., M；Δ is sampling time interval；
Note
A 2N real polynomial P (Z) on Z is constructed, it is Z to make its zero pointr,
I.e.：
Wherein, P (Z) is Sequence Response autoregression model, aKFor autoregressive coefficient；
Step 4.5, autoregressive coefficient a solved by formula (4-5-1)K,
By aKIn substitution formula (4-4-2), multinomial P (Z) root is solvedWith
Then have,
Convolution 4-3-2,
It can obtain,
In formula, αr、βrFor the s being calculatedrReal and imaginary parts.
The invention has the advantages that the present invention can be produced stable pulse excitation, be multiplied using a young waiter in a wineshop or an inn multiple using tuning power hammer
Index method (LSCE) method carries out the operational modal analysis of steel tower, can analyze steel tower according to the acceleration signal that sensor gathers
Intrinsic frequency matrix, then the intrinsic frequency matrix obtained with finite element simulation under same operating are contrasted, and judge whether to occur
Sedimentation.The on-line monitoring to steel tower sedimentation is realized, ensure that steel tower safe operation.
Brief description of the drawings
Fig. 1 is a kind of flow chart of the electric power pylon sedimentation recognition methods based on model analysis in the present invention；
Fig. 2 is the steel tower sedimentation on-line monitoring system entire block diagram based on model analysis in the present invention.
In figure, 1. front end measurement apparatus, 1-1. acceleration transducers, 1-2. filter circuits, 1-3.AD change-over circuits, 1-4.
Control circuit, 1-5. tuning power hammers, 1-6 microprocessors, 2.4G communication units, 3. Surveillance center.
Embodiment
The present invention is described in detail with reference to the accompanying drawings and detailed description.
A kind of electric power pylon sedimentation recognition methods based on model analysis of the present invention, as shown in figure 1, specifically according to the following steps
Implement：
Step 1, the steel tower intact to structure carry out model analysis, concretely comprise the following steps,
Step 1.1, the intact nothing of iron tower structure is confirmed to carrying out detailed state estimation to scene steel tower to be installed first
Damage；
Step 1.2, model analysis is carried out to steel tower using the method for finite element simulation degree, when not settling
The intrinsic frequency matrix of steel tower
Step 2, the control tuning power hammer of timing tap steel tower, tap produce same pulse excitation δ (s) every time；
Step 3, utilize acceleration transducer collection acceleration；
Step 4, the intrinsic frequency matrix for calculating using least square complex exponential method (LSCE) steel tower under actual condition, make
For the intrinsic frequency matrix of measurement
Step 4.1, acceleration signal is filtered, filters out below 100Hz interference signal；And pass through A/D convertor circuit
1-3 processing, the data-signal after being handled；
Step 4.2, utilize pulse excitation δ (s) the calculating iron in the acceleration signal and step 2 after being handled in step 4.1
Tower System transmission function
Wherein, AlprFor r rank mode residuals, * represents to be conjugated, complex frequency s=j ω, srFor limit；J represents imaginary part, ω
For the frequency of system；N represents the exponent number of steel tower system；
AlprFor complex constant, the system vibration shape and in the response the parameter situation of each rank mode are represented.
Step 4.3, to transmission functionLaplace Transform is done, as shown in formula (4-3-1)；
Wherein,
Wherein, ωrFor steel tower system r rank undamped modal frequencies, ζrFor steel tower system r rank damping ratios,
Step 4.4, discretization transmission function simultaneously construct Prony multinomials, by pulse response time it is Sequence Transformed be one from
Regression model (4-4-1)；
Wherein, m is sampled point, m=1,2 ..., M；Δ is sampling time interval；
Note
A 2N real polynomial P (Z) on Z is constructed, it is Z to make its zero pointr,
I.e.：
Wherein, P (Z) is Sequence Response autoregression model, aKFor autoregressive coefficient；
Step 4.5, autoregressive coefficient a solved by formula (4-5-1)K,
By aKIn substitution formula (4-4-2), multinomial P (Z) root is solvedWith
Then have,
Convolution 4-3-2,
It can obtain,
In formula, αr、βrFor the s being calculatedrReal and imaginary parts.
Step 5, the intrinsic frequency matrix that will be calculated in the intrinsic frequency matrix for measuring to obtain in step 4 and step 1
Compare, whenWhen, judge that sedimentation accident occurs for steel tower.
Steel tower of the present invention based on model analysis settles on-line monitoring system as shown in Fig. 2 the front end including being sequentially connected
Device 1,4G communication modules 2 and Surveillance center 3.
Fore device 1 includes acceleration transducer 1-1, filter circuit 1-2 and the A/D convertor circuit 1-3 being sequentially connected,
Microprocessor 1-6 also hammers 1-5 into shape with tuning power by control circuit 1-4 and connected.
The installation of the system and the course of work are that fore device 1 is installed first at electric power pylon column foot.Tune power hammer 1-
5 are used to produce pulse excitation, can be struck when needing to produce excitation by microprocessor 1-6 transmitting order to lower levels through control circuit 1-4 controls
Hit.Because column foot has bolt restraint of liberty degree, natural excitation (wind) does not almost influence on the vibration at column foot, measured data
Nearly all it is due to produced by tuning power hammer 1-5 is tapped.Acceleration transducer 1-1 is used for the acceleration letter for gathering steel tower vibration
Number, give microprocessor 1-6 processing after filtered circuit 1-2, A/D change-over circuit 1-3 of acceleration signal of collection.Microprocessor
1-6 is internally integrated least square complex exponential method (LSCE) algorithm, for extracting the modal parameter of steel tower.And pass through 4G communication units
Modal data is sent to Surveillance center 3 by 2.Surveillance center 3 is analyzed the data received, judges whether that sedimentation thing occurs
Therefore.
Claims (3)
1. a kind of electric power pylon sedimentation recognition methods based on model analysis, it is characterised in that specifically implement according to following steps：
Step 1, the steel tower intact to structure carries out model analysis；
Step 2, the control tuning power hammer of timing taps steel tower, taps produce same pulse excitation δ (s) every time；
Step 3, acceleration is gathered using acceleration transducer；
Step 4, the intrinsic frequency matrix of steel tower under actual condition is calculated using least square complex exponential method, as consolidating for measurement
There is frequency matrix
Step 5, by the intrinsic frequency matrix for measuring to obtain in step 4 compared with the intrinsic frequency matrix being calculated in step 1,
WhenWhen, judge that sedimentation accident occurs for steel tower.
2. the electric power pylon sedimentation recognition methods according to claim 1 based on model analysis, it is characterised in that described
Step 1 is specially：
Step 1.1, confirm that iron tower structure stands intact to carrying out detailed state estimation to scene steel tower to be installed first；
Step 1.2, model analysis, steel tower when not settling are carried out to steel tower using the method for finite element simulation degree
Intrinsic frequency matrix
3. the electric power pylon sedimentation recognition methods according to claim 1 based on model analysis, it is characterised in that described
Step 4 specifically,
Step 4.1, acceleration signal is filtered, filters out below 100Hz interference signal；And by A/D convertor circuit 1-3
Processing, the data-signal after being handled；
Step 4.2, utilize pulse excitation δ (s) the calculating steel towers system in the acceleration signal and step 2 after being handled in step 4.1
System transmission function
Wherein, AlprFor r rank mode residuals, * represents to be conjugated, complex frequency s=j ω, srFor limit；J represents imaginary part, and ω is to be
The frequency of system；N represents the exponent number of steel tower system；
AlprFor complex constant, the system vibration shape and in the response the parameter situation of each rank mode are represented；
Step 4.3, to transmission functionLaplace Transform is done, as shown in formula (4-3-1)；
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711131257.0A CN107784182B (en) | 2017-11-15 | 2017-11-15 | Power transmission tower settlement identification method based on modal analysis |
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| CN201711131257.0A CN107784182B (en) | 2017-11-15 | 2017-11-15 | Power transmission tower settlement identification method based on modal analysis |
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| CN107784182B CN107784182B (en) | 2021-07-30 |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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| CN111504551A (en) * | 2020-03-10 | 2020-08-07 | 天津大学 | Strain-type torquer bandwidth extension method based on least square complex exponential method |
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