CN207992717U - A kind of gate of hydropower station on-line condition monitoring system - Google Patents
A kind of gate of hydropower station on-line condition monitoring system Download PDFInfo
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- CN207992717U CN207992717U CN201721694322.6U CN201721694322U CN207992717U CN 207992717 U CN207992717 U CN 207992717U CN 201721694322 U CN201721694322 U CN 201721694322U CN 207992717 U CN207992717 U CN 207992717U
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 19
- 238000013480 data collection Methods 0.000 claims abstract description 11
- 238000013500 data storage Methods 0.000 claims description 3
- 238000013024 troubleshooting Methods 0.000 abstract description 4
- 238000013178 mathematical model Methods 0.000 description 8
- 238000000034 method Methods 0.000 description 8
- 229910000831 Steel Inorganic materials 0.000 description 7
- 239000010959 steel Substances 0.000 description 7
- 238000004458 analytical method Methods 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 4
- 238000012545 processing Methods 0.000 description 4
- 238000007689 inspection Methods 0.000 description 3
- 238000012549 training Methods 0.000 description 3
- 241001269238 Data Species 0.000 description 2
- 230000002159 abnormal effect Effects 0.000 description 2
- HUTDUHSNJYTCAR-UHFFFAOYSA-N ancymidol Chemical compound C1=CC(OC)=CC=C1C(O)(C=1C=NC=NC=1)C1CC1 HUTDUHSNJYTCAR-UHFFFAOYSA-N 0.000 description 2
- 230000007547 defect Effects 0.000 description 2
- 238000003745 diagnosis Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000000605 extraction Methods 0.000 description 2
- 230000004927 fusion Effects 0.000 description 2
- 230000003862 health status Effects 0.000 description 2
- 238000009434 installation Methods 0.000 description 2
- 238000012423 maintenance Methods 0.000 description 2
- 230000000737 periodic effect Effects 0.000 description 2
- 230000008054 signal transmission Effects 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- 240000007509 Phytolacca dioica Species 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 235000013399 edible fruits Nutrition 0.000 description 1
- 230000008030 elimination Effects 0.000 description 1
- 238000003379 elimination reaction Methods 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 230000010365 information processing Effects 0.000 description 1
- 230000007257 malfunction Effects 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000007500 overflow downdraw method Methods 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 238000010183 spectrum analysis Methods 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Abstract
The utility model discloses a kind of gate of hydropower station on-line condition monitoring systems, including controller (1), controller (1) is connected separately with gate switch board (2), floodgate motor frequency converter (3), analog data collection instrument (4) and vibratory string data collecting instrument (5)；The analog data collection instrument (4) is connected separately with gate load sensor (6) and gatage detector (7)；The vibratory string data collecting instrument (5) is connected separately with armored rope tension sensor (8), branch hinge force sensor (9), support arm strain gauge (10) and gate flap strain gauge (11).The utility model has the characteristics that the cost of overhaul can be reduced and improves troubleshooting speed.
Description
Technical field
The utility model is related to a kind of gate of hydropower station control device, especially a kind of gate of hydropower station on-line condition monitoring
System.
Background technology
Due to the unpredictability of the complicated and changeable and big flood of weather, once flood occurs, gate system must assure that place
The flood to soar is coped in high-speed, high efficiency, high performance state.It can come into operation at any time for guarantee system, the inspection of equipment
It repaiies and is inevitable.Most enterprises domestic for a long time are all made of periodic inspection and trouble hunting, and periodic inspection is also referred to as counted
Maintenance is drawn, the state of tube apparatus is not how, expires required.However gate system only can just come into operation in the flood high-incidence season,
The demand usually used is almost nil, and such maintenance mode lacks economy and specific aim, often results in manpower and materials
Significant wastage increases cost；And trouble hunting is just overhauled to equipment after being out of order, discovery that cannot be early
The failure and defect of equipment.Therefore, existing technology is there is cost of overhaul height and the problem of can not eliminate failure in time.
Utility model content
The purpose of the utility model is to provide a kind of gate of hydropower station on-line condition monitoring systems.The utility model has
There is the characteristics of capable of reducing the cost of overhaul and improving troubleshooting speed.
The technical solution of the utility model：A kind of gate of hydropower station on-line condition monitoring system, including controller, controller
It is connected separately with gate switch board, floodgate motor frequency converter, analog data collection instrument and vibratory string data collecting instrument；The mould
Analog quantity data collecting instrument is connected separately with gate load sensor and gatage detector；The vibratory string data collecting instrument point
It is not connected with armored rope tension sensor, branch hinge force sensor, support arm strain gauge and gate flap strain gauge.
In a kind of gate of hydropower station on-line condition monitoring system above-mentioned, the support arm strain gauge and gate flap strain gauge are equal
For strain ga(u)ge, the strain ga(u)ge includes strain gauge main body, and strain gauge main body is connected with measuring resistance, and strain gauge
Main body and measuring resistance constitute strain bridge.
In a kind of gate of hydropower station on-line condition monitoring system above-mentioned, alarm dress is also respectively connected in the controller
It sets and data storage device.
Compared with prior art, the utility model is read and is recorded in real time from gate switch board, gate by controller
Motor inverter, analog data collection instrument and vibratory string data collecting instrument pass through mould for the monitoring signals of gate operating status
Analog quantity data collecting instrument uninterruptedly samples the normal signals such as aperture, the loading of gate, passes through vibratory string data collecting instrument pair
Steel wire rope is supervised in real time by the dynamic static strength of the gates ontologies such as force signal, gate arm, branch hinge and gate flap stress and strain
It surveys, completely can realize for a long time and in an automated way real-time data acquisition truly, realization is to gate
Operating status carries out round-the-clock continual continuous monitoring, convenient for controller to the real-time abnormal conditions of gate carry out early warning with
And can conveniently show the real-time running state of gate, troubleshooting speed can be effectively improved, the repair time is reduced
And cost of labor, to reduce the whole cost of overhaul.It can reduce the cost of overhaul in conclusion the utility model has and carry
The characteristics of high troubleshooting speed.
Description of the drawings
Fig. 1 is the control figure of the utility model.
Label in attached drawing be：1- controllers, 2- gate switch boards, 3- floodgate motor frequency converters, 4- analog datas are adopted
Collect instrument, 5- vibratory string data collecting instruments, 6- gate load sensors, 7- gatage detectors, 8- armored rope tension sensors, 9-
Branch cuts with scissors force sensor, 10- support arm strain gauges, 11- gate flap strain gauges.
Specific implementation mode
The utility model is further described with reference to the accompanying drawings and examples, but is not intended as to the utility model
The foundation of limitation.
Embodiment.A kind of gate of hydropower station on-line condition monitoring system is constituted as shown in Figure 1, include controller 1, controller 1
It is connected separately with gate switch board 2, floodgate motor frequency converter 3, analog data collection instrument 4 and vibratory string data collecting instrument 5；It is described
Analog data collection instrument 4 be connected separately with gate load sensor 6 and gatage detector 7；The vibratory string data
Acquisition Instrument 5 is connected separately with armored rope tension sensor 8, branch hinge force sensor 9, support arm strain gauge 10 and gate flap strain gauge
11。
The support arm strain gauge 10 and gate flap strain gauge 11 is strain ga(u)ge, and the strain ga(u)ge includes answering
Become meter main body, strain gauge main body is connected with measuring resistance, and strain gauge main body and measuring resistance constitute strain bridge.
Warning device and data storage device is also respectively connected in the controller 1.
The course of work of the utility model：The gate loading analog signals detected are transmitted to by gate load sensor
Analog data collection instrument send into controller after the processing of analog data collection instrument and carries out record analysis, establishes loading and steel
The early warning mathematical model run between silk, gatage, analyzes operating condition in real time.
The gatage analog signals detected are transmitted to analog data collection instrument by gatage detector, simulation
It is sent after amount data collecting instrument processing and is noted down and analyzed into controller, monitor gatage, analysis operation control effect in real time
Fruit.
By armored rope tension sensor installation on a steel cord, monitor steel wire operating condition, analysis prediction steel wire situation and
Whether there is fracture, and predicts whether steel wire needs repairing.
Installation branch cuts with scissors force sensor, the real-time stress situation of monitoring left and right two branch hinge in left and right branch hinge, and passes through
Vibratory string data collecting instrument by the signal transmission detected to controller, establish pre- between gate ontology and branch hinge stress by controller
Alert mathematical model, analyzes operating condition in real time
Respectively multiple support arm strain gauges and gate flap strain gauge are installed on support arm and gate flap, and pass through vibratory string data collecting instrument
By the signal transmission detected to controller, controller establishes early warning mathematical model between gate ontology and support arm stress, in real time
Analyze the strained situation of support arm and gate flap.
The support arm strain gauge and gate flap strain gauge mainly use strain ga(u)ge, and strain detecting is divided into two kinds of works of sound
Condition, the strain gauge and measuring resistance of point layout constitute strain bridge, and output voltage is linear with dependent variable variation,
Multichannel vibrating wire acquirer is sent into carry out surveying and carrying out its data in real time dynamically recording, filtering, de-noising, average, recurrence etc.
Processing, the strain measured value according to each measuring point all directions calculate relevant stress value, generate the strain time domain procedures of each measuring point
Figure.
Controller reads out the signal that gate is promoted, declined and stopped from gate switch board and introduces controller, carries out pre-
Judge.
It includes the signals such as voltage, electric current, rotating speed that controller is read also from floodgate motor frequency converter, is supervised in real time to it
Control, and early warning mathematical model is built, analyze operation mechanism, forecasting system operating condition.
Controller is according to the keying of collected true floodgate motor, voltage and current signal, the opening amount signal of gate, steel
Cord, by information such as force signals, is extracted each component of gate in fully closed shelves water and opened by force signal, gate arm, branch hinge and gate flap
Stress state when movement is closed, and using the gathered data of each monitoring variable of Virtual Instrument Technique Analysis and has carried out spectrum analysis,
Each measuring point signal characteristic value is extracted, the processing of gate on-line condition monitoring system information, statistics, alarm platform is established, builds failure
The early warning mathematical model of diagnosis positioning and health status, realizes real-time abnormal conditions early warning and the display of operating status of gate.
Both it can complete outside to the monitoring of gate faults of monitoring system, the dynamic static strength of gate and strain can also have been monitored,
A large amount of gate stress datas are surveyed.
Controller is to capture hidden failure by monitoring the variation of its health degree for the health status prediction of gate, early
It was found that failure, positioning failure and elimination failure.I.e. by the acquisition of signal, information processing, feature extraction, data fusion method
To carry out fault diagnosis and prediction.Decision-level fusion is first carried out feature extraction and made locally to sentence by the sensor of each measuring point
Certainly, then in decision-making level global decisions are obtained using Data fusion technique.
Early warning mathematical model is used according to device history fault sample data judges that equipment may institute using K arest neighbors methods
The failure classes of category.Arest neighbors (K Nearest Neighbors, KNN) is a kind of commonly sorting technique based on distance metric,
Specific distance has different definition, is judged by Minkowski Distance calculation formula and is classified.Minkowski
Distance is：
M (A, B) is Minkowski Distance, A (x in formulai) it is Singapore dollar
The vector distance of group, B (xi) be first ancestral vector distance, q is positive number (preferred value 2).
It includes device history fault record data that KNN technologies, which assume entire training set (i.e. fault category database) not only,
Collection also includes each tuple (historical failure data record) desired class label.When to a new tuple (letter for i.e. each measuring point
Number characteristic value) when being classified, it is first determined then it further considers training set at a distance from each tuple in training set
Middle K with new tuple at a distance of nearest tuple.New tuple will be assigned in a class, this class contains K nearest tuples
In most tuple.When measuring point is in normally between malfunction, i.e., equipment is in the sub-health state of operation, at this moment very
It is doubt to say that type of failure occurs in the future for equipment.The result classified using fuzzy technology is no longer a mould
Formula explicitly belongs to certain one kind or is not belonging to certain one kind, but belongs to each classification with certain degree of membership.Such result is past
Toward more really, there are more information.If classifying and identifying system is multistage, such result is beneficial to determining for next stage
Plan.It, can be according to relatively all kinds of person in servitude of pattern if this is the decision of afterbody, and requires a specific classification to judge
Category degree or some other index, such as approach degree, fuzzy division apparentization can for example be made in the following method by carrying out hardness classification：
If | | xj-vi| |=min | | xj-vi| |, then sentence xjWith viBelong to same class；Wherein xjIt is to wait for knowledge pattern, vi(i=
1 ... ..., c) it is the class heart, | | xj-vi| | obtain distance for Europe is several.
Equipment failure rate is assessed using the appraisal procedure of early warning mathematical model, when which has
Effect property and accuracy are efficiently solved due to by the historical statistics data defect that umbra is not rung.
This method is by establishing the fault tree early warning mathematical model of gate equipment, it is contemplated that influence of the different time to event
Degree is different, and the importance of each event is determined using Fuzzy AHP, realizes the calculating to measuring point reliability.
Claims (2)
1. a kind of gate of hydropower station on-line condition monitoring system, it is characterised in that：Including controller (1), controller (1) connects respectively
It is connected to gate switch board (2), floodgate motor frequency converter (3), analog data collection instrument (4) and vibratory string data collecting instrument (5)；Institute
The analog data collection instrument (4) stated is connected separately with gate load sensor (6) and gatage detector (7)；Described
Vibratory string data collecting instrument (5) is connected separately with armored rope tension sensor (8), branch hinge force sensor (9), support arm strain gauge
(10) and gate flap strain gauge (11)；The support arm strain gauge (10) and gate flap strain gauge (11) is strain ga(u)ge, described
Strain ga(u)ge include strain gauge main body, strain gauge main body is connected with measuring resistance, and strain gauge main body and measuring resistance structure
At strain bridge.
2. gate of hydropower station on-line condition monitoring system according to claim 1, it is characterised in that：The controller
(1) warning device and data storage device is also respectively connected.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201721694322.6U CN207992717U (en) | 2017-12-07 | 2017-12-07 | A kind of gate of hydropower station on-line condition monitoring system |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201721694322.6U CN207992717U (en) | 2017-12-07 | 2017-12-07 | A kind of gate of hydropower station on-line condition monitoring system |
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| CN207992717U true CN207992717U (en) | 2018-10-19 |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107844067A (en) * | 2017-12-07 | 2018-03-27 | 国家电网公司 | A kind of gate of hydropower station on-line condition monitoring control method and monitoring system |
| TWI684926B (en) * | 2019-02-22 | 2020-02-11 | 神通資訊科技股份有限公司 | Access gate system with self-trainning function |
| CN115906336A (en) * | 2023-01-06 | 2023-04-04 | 常熟天地煤机装备有限公司 | Coal mining machine digital twin model modeling method and system based on hardware-in-the-loop simulation |
-
2017
- 2017-12-07 CN CN201721694322.6U patent/CN207992717U/en active Active
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107844067A (en) * | 2017-12-07 | 2018-03-27 | 国家电网公司 | A kind of gate of hydropower station on-line condition monitoring control method and monitoring system |
| TWI684926B (en) * | 2019-02-22 | 2020-02-11 | 神通資訊科技股份有限公司 | Access gate system with self-trainning function |
| CN115906336A (en) * | 2023-01-06 | 2023-04-04 | 常熟天地煤机装备有限公司 | Coal mining machine digital twin model modeling method and system based on hardware-in-the-loop simulation |
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