CN102607643A - Overheat fault diagnosis and early warning system and method for electrical equipment of traction substation of electrified railway - Google Patents
Overheat fault diagnosis and early warning system and method for electrical equipment of traction substation of electrified railway Download PDFInfo
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Abstract
The invention discloses an overheat fault diagnosis and early warning system and an overheat fault diagnosis and early warning method for electrical equipment of a traction substation of an electrified railway. The fault diagnosis and early warning system comprises wireless sensors, concentrators, a computer and the like, wherein the wireless sensors comprise wireless temperature sensors, wireless temperature and humidity sensors and wireless current sensors, and measure the temperature of the electrical equipment, the temperature and humidity of an environment and the current of a transmission line respectively; the concentrators receive monitoring point data from each wireless sensor in the whole traction substation, and upload the received data to the computer; and the computer finishes the acquisition and storage of the monitoring data, and finishes intelligent diagnosis and early warning for an overheat fault of the electrical equipment according to the acquired data. By the system, a scientific basis can be provided for the running and overhauling of the traction substation of the electrified railway to ensure the power supply security of the railway.
Description
Technical field
The present invention relates to a kind of fault diagnosis and early warning system and method, particularly a kind of electric railway traction transformer station's device of overheating of electrical fault diagnosis and early warning system and method.
Background technology
There are electrical equipments such as a large amount of high voltage isolators, mutual inductor, isolating switch, transformer and high-tension switch cabinet in the traction substation; Its joint One's name is legion; These electrical equipments are being undertaken the vital task of power converter and conveying; But under the situation of long-time continuous operation, usually can cause the contact point resistance to increase because of reasons such as joint loose contact, aging or surface oxidations; And then temperature rise occurs and cause situation such as heating too much burns out, if the temperature of these heating positions is not monitored timely and effectively, finally possibly cause device damage; Thereby cause to have a power failure even the generation of fire failure the great potential safety hazard that the operation of electric railway is brought.Therefore should take necessary detection method to understand the current running status of each electrical equipment; According to equipment real-time running state data and combine its variation tendency of historical data analysis; Reduce electric power system accident potential thereby reach; Reduce accident rate, shorten troubleshooting, repair time, guarantee the purpose of electric power system safe and reliable operation.
The main both at home and abroad at present electrical equipment temperature monitoring technology that adopts has two big types: the one, and adopt infrared technique (infrared temperature instrument or infrared thermoviewer) to carry out temperature detection with the manual inspection mode; The 2nd, through being furnished with the line sensor network, carry out temperature detection as adopting optical fiber.But these methods all can't satisfy the temperature monitoring demand of traction substation.Mainly be because: traction substation is different from general transformer station; When its supply lines highway section has train to pass through; Related electric equipment just has electric current to pass through, and the apparatus overheat potential faults just can display, and when not having train to pass through; Because the electrical equipment load current is very little, even monitoring this moment relevant device temperature also can't be found potential faults.The infrared technique thermometric is owing to be manual detection; Can't realize that real-time online detects; Temperature to device interior also can't be measured and exist than mistake; Therefore can't realize overheating fault in time, accurately find, the optical fiber temperature-measurement technology is because the wiring complicacy is unfavorable for large-scale application, thereby and is easy to polluted and causes the thermometric accuracy to descend significantly.
Thermometry based on wireless senser begins to have obtained to use widely in recent years.But there is following limitation in it aspect transformer station's electrical equipment monitoring: detected object is merely the temperature of monitored point, through temperature threshold of simple setting, determines whether to have occurred the device of overheating of electrical fault.According to general knowledge; We know that under the different environment temperature and humidity same electrical equipment temperature is often represented different overheating fault results, and different line currents also can cause different running temperature results; Whether therefore overheating fault appear; Not only relevant, also relevant with environment temperature, ambient humidity and line current with the device temperature of measured point, be a comprehensive result who judges.
Summary of the invention
Technical matters to be solved by this invention provides a kind of electric railway traction transformer station's device of overheating of electrical fault diagnosis and early warning system and method; Realize electrical equipment temperature, environment temperature, ambient humidity and line current are carried out online detection through wireless senser; Foundation is based on the least square method supporting vector machine fault diagnosis and the Early-warning Model of (least squares support vector machines is called for short LSSVM); Thereby realize accurate diagnosis and early warning to the device of overheating of electrical fault; For the reliability service of electrical equipment provides foundation, significantly reduce rate of breakdown.
For realizing above-mentioned purpose, the present invention adopts following technological means:
Electric railway traction transformer station device of overheating of electrical fault diagnosis and early warning system; It is characterized in that: mainly be made up of wireless senser, concentrator and computing machine, wherein wireless senser comprises the radio temperature sensor that is used for the measuring electrical device temperature, the wireless environment Temperature Humidity Sensor that is used for the measurement environment humiture, the radio flow sensor that is used for the measuring circuit electric current; Concentrator is responsible for collecting wireless sensor data and is uploaded to computing machine, and computing machine utilizes least square method supporting vector machine overheating fault Early-warning Model to realize the intelligent diagnostics and the online early warning of device of overheating of electrical fault according to the data of uploading.
Said radio temperature sensor is installed one on each need carry out the electrical equipment of overheating fault monitoring; Said wireless environment Temperature Humidity Sensor is respectively installed one in the zone with collective environment characteristic; Said radio flow sensor is installed one on every circuit with common current characteristic;
Said various wireless senser is a core with the CC2430 chip based on the ZIGBEE technology all; Said radio temperature sensor adopts DS18B20 induction electric device temperature; Said wireless humiture sensor adopts DHT21 induced environment humiture; Said radio flow sensor adopts inductive circular loop to obtain current signal;
A kind of electric railway traction transformer station's device of overheating of electrical fault diagnosis and method for early warning may further comprise the steps:
(1) wireless senser measuring electrical monitoring of equipment point temperature T
Equipment, environment temperature T
Environment, ambient humidity H
EnvironmentWith line current I
Circuit, give concentrator with these data transmission then;
(2) after concentrator receives the data of wireless senser transmission, these data are sent to computing machine with Ethernet, the report cycle with above-mentioned data is back to corresponding sensor as response data packet then;
(3) after computing machine receives the reported data of concentrator transmission, at first store, handle according to following rule according to data type then:, then do not process if data are environment temperature, ambient humidity or line current; If data are the electrical equipment temperature, then confirm point position according to the temperature data of electrical equipment, from computing machine, access ambient temperature data, ambient humidity data then, and the line current data, form measurement data { T
Equipment, T
Environment, H
Environment, I
Circuit;
(4) measurement data { T that step (3) is obtained
Equipment, T
Environment, H
Environment, I
CircuitImport the least square method supporting vector machine overheating fault Early-warning Model of setting up, obtain fault diagnosis and early warning result.
Said least square method supporting vector machine overheating fault Early-warning Model is set up according to following steps:
(1) definite kernel function kind: with RBF
As kernel function, wherein, x is a present input data, x
nBe training sample set, δ is the width parameter of RBF;
(2) adopt the standard search algorithm to confirm the ultra parameter { δ of model
2, γ }, wherein, γ is a regularization parameter;
(3) with the sample in the sample database as training dataset, to the model training, obtain model parameter { α
n, b}, wherein, α
nBe Lagrangian (claiming support factor again), b is a bias;
(4) obtain fault diagnosis model:
Before carrying out fault diagnosis, at first, the data of obtaining are carried out normalization handle;
Computing machine is adjusted the report cycle of electrical equipment temperature data according to the result of fault diagnosis; Said line current report the real-time calling mode that adopts, promptly when computing machine receives the temperature data of wireless electrical equipment after, call the line current data;
Least square method supporting vector machine overheating fault Early-warning Model is upgraded training to model after collecting new fault sample and reaching some.
Compared with prior art; Electric railway traction transformer station's device of overheating of electrical fault diagnosis of the present invention and early warning system and method have the following advantages at least: the present invention has adopted wireless senser to realize the measurement of electrical equipment temperature, efficiently solves high-tension apparatus and is difficult to the problem that online in real time detects; Adopt diagnosis of multiple informix and early warning, can effectively eliminate the electrical equipment temperature variation that the variation because of environment temperature, humidity and line energizing flow amount causes, thereby realize the accurate diagnosis of overheating fault, for power supply safety provides reliable guarantee.
Description of drawings
Fig. 1 is traction substation device of overheating of electrical On-line Fault diagnosis of the present invention and early warning system structural representation;
Fig. 2 is the radio temperature sensor hardware structure diagram;
Fig. 3 is radio temperature sensor software workflow figure;
Fig. 4 is fault diagnosis and early warning process flow diagram.
Embodiment
An embodiment to electric railway traction transformer station's device of overheating of electrical fault diagnosis of the present invention and early warning system and method is elaborated below in conjunction with accompanying drawing:
The present invention carries out inline diagnosis and early warning to electric railway traction transformer station device of overheating of electrical fault; Its system global structure is as shown in Figure 1, comprises the radio temperature sensor that is used for the measuring electrical device temperature, the wireless environment Temperature Humidity Sensor that is used for the measurement environment humiture, the radio flow sensor that is used for the measuring circuit electric current, is used for the concentrator of collecting sensor data and is used for fault diagnosis and the computing machine of unified monitoring.
In a traction substation, a radio temperature sensor is installed for each electrical equipment (device clamp of locating like transformer, disconnector, isolating switch, current transformer etc., the busbar in the switch cubicle etc.) that need carry out overheating fault monitoring; For zone a wireless environment Temperature Humidity Sensor is installed respectively with collective environment characteristic; Environment temperature that measures and humidity data result supply all the electrical equipment monitoring point fault diagnosises in this zone shared; For example at ambient temperature and humidity sensor of traction substation outdoor mounted; Its measurement result supplies all outdoor electrical equipment overheat fault diagnostics to use; An ambient temperature and humidity sensor is installed in the hyperbaric chamber, and its measurement result supplies all device of overheating of electrical fault diagnosises in the hyperbaric chamber to use; On every circuit with common current characteristic, a radio flow sensor is installed, its data result supplies all the electrical equipment monitoring point fault diagnosises on this circuit shared.
Wireless senser is accomplished electrical equipment monitoring point temperature T
Equipment, environment temperature T
Environment, ambient humidity H
EnvironmentWith line current T
CircuitMeasurement; And measurement result is sent to concentrator through wireless mode; Concentrator can be installed a plurality of according to the traction substation concrete condition, for example one of outdoor mounted, be responsible for the collection of outdoor sensing data; Install one in the hyperbaric chamber, be responsible for the collection of hyperbaric chamber inner sensor data.
After concentrator receives wireless sensor data, data are sent to computing machine through EPA, and the report cycle of the sensor is back to respective sensor as response data packet.
Computing machine at first carries out data storage after receiving reported data, handle according to following rule according to data type then: if data are environment temperature, ambient humidity or line current, then do not process; If data are the electrical equipment temperature, then carry out overheat fault diagnostic and early warning program, be specially:
Computing machine receives the electrical equipment temperature data; And after the completion data storage, at first carry out the data matcher:, confirm point position (being electrical equipment temperature sensor ID) according to the electrical equipment temperature data that receives; Access then and this point position matching environment Temperature Humidity Sensor ID, line current sensor ID; Obtain line current through the calling mode, obtain the ambient temperature and humidity data, form measurement data { T through inquiry latest data from historical data base
Equipment, T
Environment, H
Environment, I
Circuit;
Good LSSVM overheating fault Early-warning Model is set up in the measurement data set input that obtains, obtained fault diagnosis and early warning result, and the result is shown on the monitoring software interface.
Explain below in conjunction with a concrete application example:
As shown in Figure 2; Be used for the thermometric wireless senser of traction substation electrical equipment; Employing realizes based on the CC2430 chip of ZIGBEE technology; This chip internal is integrated low-power scm, power management module, analog-to-digital conversion module, radio-frequency module and memory module etc. can realize the work such as collection, processing and wireless transmission of data with a chip.Temperature acquisition realizes that through DS18B20 this chip temperature is a digital temperature sensor, can obtain temperature data through the number bus mode, and its error is in ± 1.5 ℃.Its communication distance of wireless senser through this technical design can reach 500 meters, satisfies the demand of electrical equipment temperature monitoring fully.
Wireless senser for ambient temperature and humidity and line current measurement; Unique difference is that the front end sensors of being selected for use is different on its hardware configuration; Wherein the measurement environment humiture adopts DHT21; This sensor is the humiture compound sensor of digital signal output, and the measuring circuit electric current adopts homemade inductive circular loop to obtain current signal.
As shown in Figure 3; Wireless electric device temperature sensor, its workflow is: judge at first whether dormancy period arrives, dormancy period is to then entering into the collecting temperature program; And accomplish handling procedures such as data-switching, filtering, then collection result is sent to concentrator and wait-for-response packet; Receive and take a decision as to whether change parameter packet (promptly whether change reporting cycle) after the response data packet of concentrator, if then change relevant parameter as requested.Wireless electric device temperature sensor; Its report cycle can be adjusted according to overheating fault degree self-adaptation; One group of representative value is: report cycle is 30 minutes during non-fault; Report cycle is 10 minutes during minor failure, and report cycle is 5 minutes during the moderate fault, and report cycle is 1 minute during catastrophic failure.
For the ambient temperature and humidity sensor, its report cycle can artificial be provided with, and representative value is to report once in 30 minutes, for current sensor, adopts the calling mode to obtain.
Computing machine obtains electrical equipment monitoring point temperature T
Equipment, environment temperature T
Environment, ambient humidity H
EnvironmentWith line current I
CircuitAfter, adopt fault diagnosis model to carry out overheat fault diagnostic and early warning based on LSSVM, its workflow is as shown in Figure 4.
Judge at first and carry out the fault model training or carry out fault diagnosis that model training carries out under two kinds of situation, the one, when setting up model for the first time, use; The 2nd, elongated along with working time, (for example newly collecting 10 fault samples) upgraded training to model when collecting new fault sample and reaching some.
Fault diagnosis result is divided into four types, is respectively non-fault, minor failure, moderate fault, moderate fault and catastrophic failure, and it is respectively 0,1,2,3 corresponding to the output of LSSVM fault model.In setting up the training sample set process, T
Equipment, T
Environment, H
Environment, I
CircuitAutomatically obtain by on-line monitoring system, and corresponding fault type is rule of thumb specified with analysis result by the operations staff.
After getting into the model training program, at first definite kernel function kind is selected RBF
As the kernel function of LSSVM, wherein, x is a present input data, x
nBe the sample set of training, δ is the width parameter of RBF; Adopt standard searching algorithm in the Matlab mathematical tool case of LSSVM to confirm the ultra parameter { δ of LSSVM model then
2, γ }, wherein, γ is a regularization parameter; Then, as training dataset,, obtain model parameter { α with the sample in the sample database to the training of LSSVM model
n, b}, wherein, α
nBe Lagrangian (claiming support factor again), b is a bias, can obtain fault diagnosis model:
Normal monitor procedure; Model gets into fault diagnosis flow scheme; At first the data of obtaining being carried out normalization handles; Adopt the model
train to obtain fault diagnosis result then and it is shown to monitoring interface; Determine whether to change the report cycle parameter of wireless electric device temperature sensor simultaneously according to the fault order of severity, and deposit the dependent failure data in sample database as sample, when newly-increased sample size reaches 10; Then get into the model modification flow process, existing fault diagnosis model is upgraded.
Traction substation device of overheating of electrical On-line Fault diagnostic method and method for early warning that the present invention provides, the convergence analysis through to each side data such as monitoring point temperature, present position size of current, environment temperature of living in and humidity provides fault diagnosis result; Make diagnostic result under the external condition of various environment and transmission of electricity situation, all can satisfy accurate Diagnosis and Early-warning, satisfied the intelligentized demand of traction substation monitoring well, guaranteed railway power supply safety.
The above is merely one embodiment of the present invention; It or not whole or unique embodiment; The conversion of any equivalence that those of ordinary skills take technical scheme of the present invention through reading instructions of the present invention is claim of the present invention and contains.
Claims (8)
1. electric railway traction transformer station device of overheating of electrical fault diagnosis and early warning system; It is characterized in that: mainly be made up of wireless senser, concentrator and computing machine, wherein wireless senser comprises the radio temperature sensor that is used for the measuring electrical device temperature, the wireless environment Temperature Humidity Sensor that is used for the measurement environment humiture, the radio flow sensor that is used for the measuring circuit electric current; Concentrator is responsible for collecting wireless sensor data and is uploaded to computing machine, and computing machine utilizes least square method supporting vector machine overheating fault Early-warning Model to realize the intelligent diagnostics and the online early warning of device of overheating of electrical fault according to the data of uploading.
2. electric railway traction transformer station's device of overheating of electrical fault diagnosis according to claim 1 and early warning system is characterized in that: said radio temperature sensor is installed one on each need carry out the electrical equipment of overheating fault monitoring; Said wireless environment Temperature Humidity Sensor is respectively installed one in the zone with collective environment characteristic; Said radio flow sensor is installed one on every circuit with common current characteristic.
3. electric railway traction transformer station's device of overheating of electrical fault diagnosis according to claim 2 and early warning system is characterized in that: said various wireless sensers are core with the CC2430 chip based on the ZIGBEE technology all; Said radio temperature sensor adopts DS18B20 induction electric device temperature; Said wireless humiture sensor adopts DHT21 induced environment humiture; Said radio flow sensor adopts inductive circular loop to obtain current signal.
4. the overheat fault diagnostic and the method for early warning of the described electric railway traction of claim 1 transformer station's device of overheating of electrical fault diagnosis and early warning system is characterized in that: may further comprise the steps:
(1) wireless senser measuring electrical monitoring of equipment point temperature T
Equipment, environment temperature T
Environment, ambient humidity H
EnvironmentWith line current I
Circuit, give concentrator with these data transmission then;
(2) after concentrator receives the data of wireless senser transmission, these data are sent to computing machine with Ethernet, the report cycle with above-mentioned data is back to corresponding sensor as response data packet then;
(3) after computing machine receives the reported data of concentrator transmission, at first store, handle according to following rule according to data type then:, then do not process if data are environment temperature, ambient humidity or line current; If data are the electrical equipment temperature, then confirm point position according to the temperature data of electrical equipment, from computing machine, access ambient temperature data, ambient humidity data with this location matches then, and the line current data, form measurement data { T
Equipment, T
Environment, H
Environment, I
Circuit;
(4) measurement data { T that step (3) is obtained
Equipment, T
Environment, H
Environment, I
CircuitImport the least square method supporting vector machine overheating fault Early-warning Model of setting up, obtain fault diagnosis and early warning result.
5. overheat fault diagnostic as claimed in claim 4 and method for early warning is characterized in that: said least square method supporting vector machine overheating fault Early-warning Model is set up according to following steps:
(1) definite kernel function kind: with RBF
As kernel function, wherein, x is a present input data, x
nBe training sample set, δ is the width parameter of RBF;
(2) adopt the standard search algorithm to confirm the ultra parameter { δ of model
2, γ }, wherein, γ is a regularization parameter;
(3) with the sample in the sample database as training dataset, to the model training, obtain model parameter { α
n, b}, wherein, α
nBe Lagrangian, b is a bias;
(4) obtain fault diagnosis model:
6. overheat fault diagnostic as claimed in claim 4 and method for early warning is characterized in that: before carrying out fault diagnosis, at first, the data of obtaining are carried out normalization handle.
7. overheat fault diagnostic as claimed in claim 4 and method for early warning is characterized in that: computing machine is adjusted the report cycle of electrical equipment temperature data according to the result of fault diagnosis; Said line current report the real-time calling mode that adopts, promptly when computing machine receives the temperature data of wireless electrical equipment after, call the line current data.
8. like claim 4 or 5 described overheat fault diagnostic and method for early warning, it is characterized in that: least square method supporting vector machine overheating fault Early-warning Model is upgraded training to model after collecting new fault sample and reaching some.
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