CN102620807A - System and method for monitoring state of wind generator - Google Patents
System and method for monitoring state of wind generator Download PDFInfo
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- CN102620807A CN102620807A CN2012100919939A CN201210091993A CN102620807A CN 102620807 A CN102620807 A CN 102620807A CN 2012100919939 A CN2012100919939 A CN 2012100919939A CN 201210091993 A CN201210091993 A CN 201210091993A CN 102620807 A CN102620807 A CN 102620807A
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Abstract
The invention relates to a system and a method for monitoring a state of a wind generator. Vibration sensors are respectively arranged on key mechanical vibration parts of the wind generator, and a monitoring system is formed by a signal modulating unit, a signal collecting unit, a digital signal processing (DSP) system and a personal computer (PC). The signal modulating unit is used for modulating a signal outputted by each vibration sensor, and the signal collecting unit is used for completing the analog-to-digital conversion. The DSP system is used for quickly calculating a time-domain characteristic parameter and a frequency-domain characteristic parameter and for transmitting the characteristic parameters to the PC in a communication way. The PC is used for instantaneously displaying a current running state (normal state, state of alarm and state of danger) of the wind generator according to a vibration criterion and the current vibration characteristic parameters of the wind generator and for displaying a tendency chart of each characteristic parameter. Once abnormal states such as a state of alarm appear, the abnormal state is prompted in a striking manner, and different characteristic parameters are stored and recorded to be examined and analyzed.
Description
Technical field
The present invention relates to a kind of aerogenerator condition monitoring system and method, belong to the aerogenerator monitoring technical field.
Technical background
Wind energy is the energy very important and that reserves are huge, and it has safety, cleaning, characteristics such as abundant, stable.At present, wind-power electricity generation has become the principal mode of Wind Power Utilization, and speed of development is very fast.In recent years, the wind-power electricity generation industry began to get into a rapid growth period.By the end of 2009, global aerogenerator installed capacity reached 159213MW, adding new capacity 38312MW, and according to present rising tendency, WWEA predicts at the bottom of the year two thousand twenty, and global installed capacity is at least 1.9 * 106MW.
The development of China wind-powered electricity generation is from 2000, and almost annual growth rate with at double constantly increases, and total installation of generating capacity reaches 25805.3MW in by the end of December, 2009 by, is except that the U.S., the country that has wind-powered electricity generation installed capacity maximum of Germany.
Receive the influence of factors such as wind field physical environment, wind power generating set and power electronic equipment complicacy, the wind power generating set accident increases day by day.The operation expense of wind power generating set great number has had a strong impact on the economic benefit of wind field.According to the related data statistics, for the aerogenerator unit that is 20 years designed life, operation expense estimates to account for 10%～15% of wind field income; For marine wind field, the cost that is used for the wind motor operation maintenance is up to 20%～25% of wind field income.The operation and maintenance cost of great number has increased the operation cost of wind field, has reduced the economic benefit of wind-powered electricity generation.
Wind-driven generator structure is complicated, costs an arm and a leg work under bad environment.Be located in the field, receive effect of natural conditions big.Aerogenerator is installed on five, the 60 meters high tower tube, is in the environment of very severe, and maintenance is difficulty very, therefore, how to accomplish neither superfluous maintenance, can seem particularly important by on-call maintenance again.Can monitor the state of aerogenerator in real time through on-line monitoring system; Can in time grasp its state, in time intervene, preset corresponding maintenance and repair plan; Reduce and shut down number of times and time; Reduce the operation cost of genset significantly, avoid the generation of catastrophic failure, prolong the serviceable life of equipment.Multiple to greatest extent.
Domestic large-scale wind driven generator status monitoring situation is: a part of aerogenerator operator uses the condition monitoring system product of external wind-powered electricity generation company; Part aerogenerator has only generated energy and electrical equipment status monitoring system, lacks the status monitoring of machine driven system; The simple and easy monitoring system that some aerogenerator adopts several vibration transducers and simple instrument to form can not satisfy request for utilization.More domestic in recent years companies carry out the research of this type of technical products; The monitoring method of using is a kind of to be to utilize the radio sensing network technology; This method exists that the vibration signal sample rate is slow, signal Processing and shortcomings such as transmission speed is slow, poor reliability, can not satisfy actual requirement; The another kind of Internet network that adopts carries out remote monitoring, uses presence server, remote server etc., the system architecture more complicated, and applicable cases is not clear.
Summary of the invention
The purpose of this invention is to provide a kind of aerogenerator condition monitoring system and method; This system and method can be grasped the aerogenerator state in real time, in time intervenes, and presets corresponding maintenance and repair plan; Reduce and shut down number of times and time; Reduce the operation cost of genset significantly, avoid the generation of catastrophic failure, prolong the serviceable life of equipment.The present invention has also that vibration signal sampling is fast, signal Processing, transmission speed are fast, good reliability, cost are low.
Technical solution:
Aerogenerator condition monitoring system of the present invention; Comprise the two level computer monitoring of structures; Slave computer is digital information processing system DSP, is fixed in the cabin at aerogenerator top, and host computer is the PC computing machine; It is indoor to be positioned at the aerogenerator ground monitoring, and slave computer DSP utilizes communication interface to realize communicating by letter of digital signal with the host computer PC computing machine; Also comprise and be fixed on the sensor on the machine driven system on the aerogenerator; The output terminal of vibration transducer is connected with the input end of signal condition unit; The output terminal of signal condition unit is connected with the input end of signal gathering unit again, and the signal gathering unit output terminal is connected with the input end of digital information processing system DSP.
Said sensor comprises: speed probe, acceleration transducer or speed pickup.
On the cabin of said aerogenerator speed pickup is installed; On the engine input shaft speed probe is installed; Be separately installed with acceleration transducer on main bearing seat, engine bearing and the gearbox.
The monitoring method of aerogenerator condition monitoring system of the present invention is following: the aerogenerator vibration signal of sensor acquisition is through conversion, filtering, the amplification of signal condition unit; Accomplish the conversion of analog quantity by signal gathering unit, send into digital information processing system DSP analyzing and processing again to digital quantity.The Fast estimation that digital information processing system DSP carries out extraction that time domain has dimension characteristic parameter, dimensionless characteristic parameter to each vibration signal and carries out frequency spectrum through the AR model at frequency domain; Thereby obtain the information of aerogenerator vibrational state; Digital information processing system DSP is sent to the PC computing machine with these characteristic parameters through communication interface then; The PC computer real-time shows the state of aerogenerator; Show vibration performance parameter variation tendency figure, the various characteristic parameters under the storage ERST supply to check analysis.
The flow process of said digital information processing system DSP processing signals is following:
1. .DSP is digital quantity to each sensor sample with analog signal conversion, and sampling is undertaken by fixed frequency and data volume, and the sampling edge limit is kept at digital quantity in the DSP internal memory;
2.. the sampled value by speed probe calculates the aerogenerator rotating speed; Calculate the time domain statistical characteristics of vibration signal respectively by the sampled data of each vibration transducer; The time domain statistical nature comprises: mean value, effective value, variance, probability density function, correlation analysis, kurtosis, form factor, nargin index are saved in the DSP internal memory with above result of calculation;
3.. utilize the AR model to calculate the power spectrum of each vibration sensor signal fast, and preserve power spectrum information in the DSP internal memory;
4. .DSP request is communicated by letter with host computer PC, and the time domain statistical nature and the power spectrum information of aerogenerator tachometer value, each vibration sensor signal is sent to the host computer PC computing machine; DSP accomplishes a systemic circulation job;
4. 1. the flow process of DSP processing signals circulate successively to step by above-mentioned steps and carry out.
PC computer monitoring program of the present invention is: show aerogenerator status monitoring interface menu; The transmission request signal of responding digital signal processing system DSP receives each frame signal that DSP transmits, and shows time domain, frequency domain character parameter with curve or excellent figure mode; Vibration performance parameter according to each vibration transducer; The criterion of contrast wind-power electricity generation machine vibration, the state of judgement aerogenerator is if vibration values belongs to normally and then shows current vibration values with green; When abnormal vibrations occurring and exceeding standard when little with yellow flicker display alarm state and store alarms value and time of fire alarming; When abnormal vibrations occurring and exceed standard greatly, show that needing to shut down maintenance fixes a breakdown, computing machine shows the vibration performance value and with auditory tone cues, stores exceptional value and time of origin with red flashing mode.
The present invention obtains the aerogenerator status signal through vibration transducer, speed probe, adopts the two-stage monitoring of structures, and digital information processing system DSP and PC computing machine are passed through the quick dependable communications that communication bus is realized digital signal.
The estimation that digital information processing system DSP of the present invention carries out extraction that time domain has dimension, dimensionless eigenwert through signal analysis and processing to each the road vibration signal after gathering and carries out frequency spectrum through the AR model at frequency domain; Obtain the information of aerogenerator vibrational state, utilize communication bus to be sent to the indoor PC computing machine of Ground Control the information of these expression aerogenerator states then.The vibration performance information that shows and store aerogenerator by the PC computer real-time; According to vibration temporal signatures value, development trend and frequency domain character value information analysis-by-synthesis; With wind-power electricity generation machine vibration evaluation criteria contrast, judging the aerogenerator state has non-fault, and state belongs to normally, any in abnormal alarm or the danger; Development degree is like information how, simultaneously recursion storage eigenwert and warning exceptional value.
DSP changes with the digital quantity that certain SF and sampling time control signal collecting unit are accomplished multi-channel analog signal, and the digital quantity that will gather then after changing is kept in the internal memory of DSP.Calculate current tachometer value, calculate the time domain statistical nature of each passage vibration signal fast.The time domain statistical nature comprises: mean value, effective value, variance, probability density function, correlation analysis, kurtosis, form factor, nargin coefficient.Utilize the AR model that the frequency spectrum of vibration signal is carried out the Fast estimation analysis, obtain the spectrum information of each passage vibration signal, with above time domain, frequency domain character information temporary storage in the DSP internal memory.Last DSP utilizes communication bus to communicate by letter with host computer PC, and temporal signatures parameter, the power spectrum information of above tachometer value, each vibration transducer is sent to the PC computing machine.
Host computer PC computing machine: show aerogenerator status monitoring interface menu; The transmission request signal of responding digital signal processing system DSP; Receive each frame signal that DSP transmits, recursion storage aerogenerator vibration performance parameter shows time domain, frequency domain character value with modes such as curve, rod figure; Relatively judge the state that aerogenerator is present with vibration standard: normal, warning, danger, display status information.Can check simultaneously historical alert data, statistics alarming value as required.
Aerogenerator condition monitoring system and method are complex arts that combines subjects such as the information processing technology, computer technology, sensor technology, Probability & Statistics.Utilize that the DSP hardware capability is powerful, reliability is high and the characteristics such as efficient high-speed of software, to the processed of vibration transducer output signal, eliminate the false and retain the true.Utilization time domain Statistics, adopt the AR model extract can responsive reflection aerogenerator state the various features parameter, reach the purpose that real time on-line monitoring is judged the aerogenerator state.
The advantage that produces through aerogenerator condition monitoring system and method is: (1) system adopts the two level computer monitoring system; Give full play to the DSP digital signal processing capability strong, fast, little, the high reliability features of volume, give full play to the powerful graphical display function of PC computing machine, data management and man-machine conversation function; (2) utilize statistical model to vibration signal power spectrum Fast estimation, than the transform method that uses conventional FFT have simply, the spectral resolution advantages of higher; (3) monitoring system is reliable, satisfies the requirement of aerogenerator field condition; Price is low, is convenient to promote the use of.
Description of drawings
Fig. 1 aerogenerator condition monitoring system principle of work block diagram;
Fig. 2 aerogenerator condition monitoring system sensor mounting arrangements synoptic diagram;
Fig. 3 aerogenerator state monitoring method process flow diagram;
Fig. 4 digital information processing system dsp software process flow diagram.
Embodiment
Specify embodiments of the invention below in conjunction with accompanying drawing:
Digital information processing system DSP is to sensor promptly: the signal that speed pickup 1, acceleration transducer 2 and speed probe 3 collect carries out Treatment Analysis; Extract multiple vibration performance information; According to the aerogenerator vibration standard; Judge the aerogenerator state, thereby realize the real-time state monitoring of aerogenerator.
[sensor]
Sensor is used for obtaining aerogenerator vibration signal and rotating speed.Shown in the accompanying drawing 2 is a kind of embodiment, and sensor comprises six acceleration transducers, two speed pickups, a speed probe.
Shown in Figure 2 is aerogenerator condition monitoring system sensor mounting arrangements synoptic diagram, and aerogenerator mainly comprises parts such as blade, shaft coupling, gearbox, generator, cabin.Arrow is depicted as the installation site of sensor in the present embodiment among the figure.
[signal condition unit]
The signal condition unit carries out conversion, conditioning and anti-aliasing filter to each sensor output signal, and output meets the voltage signal of A/D converter scope.
[signal gathering unit]
The analog signal conversion of signal condition unit output is become digital signal, so that digital information processing system DSP analytical calculation, processing, storage.This element circuit has amplitude limit, insulation blocking measure and analog-digital conversion function.
[digital information processing system DSP]
The state of aerogenerator shows with various vibration performance values, therefore, at first at the position of vibration sensing appropriate sensor, the comprehensive aerogenerator state that obtains is installed; Secondly DSP carries out analytical calculation, extracts the eigenwert of each measuring point vibration signal.Sampling, eigenvalue calculation, frequency spectrum that DSP accomplishes each measuring point sensor signal automatically by fixed frequency calculate.
DSP analyzes the vibration signal characteristics parameter of extracting and mainly comprises: the temporal signatures parameter of vibration signal and frequency domain character parameter; When aerogenerator owing to the mechanical fault reason; If occur that axle misaligns, base flexible, gear of speed increasing box wearing and tearing, will cause in the various characteristic parameters one or several or all eigenwert exceed normal range.Can identify aerogenerator according to criterion and be in the abnormal alarm scope.When the aerogenerator fault degree was serious, vibration amplitude will increase, and it is bigger that the characteristic parameter that DSP extracts will exceed normal range, and the characteristic parameter number that exceeds normal range is also more.Therefore, can obtain in view of the above aerogenerator normal, report to the police, dangerous three kinds of states.
The flow process of said digital information processing system DSP processing signals is following:
1. .DSP is digital quantity to each sensor sample with analog signal conversion, and sampling is undertaken by fixed frequency and data volume, and the sampling edge limit is kept at digital quantity in the DSP internal memory;
2.. the sampled value by speed probe calculates the aerogenerator rotating speed; Calculate the time domain statistical characteristics of vibration signal respectively by the sampled data of each vibration transducer; The time domain statistical nature comprises: mean value, effective value, variance, probability density function, correlation analysis, kurtosis, form factor, nargin index are saved in the DSP internal memory with above result of calculation;
3.. utilize the AR model to calculate the power spectrum of each vibration sensor signal fast, and preserve power spectrum information in the DSP internal memory;
4. .DSP request is communicated by letter with host computer PC, and the time domain statistical nature and the power spectrum information of aerogenerator tachometer value, each vibration sensor signal is sent to the host computer PC computing machine; DSP accomplishes a systemic circulation job;
4. 1. the flow process of DSP processing signals circulate successively to step by above-mentioned steps and carry out.
Shown in Figure 4 is digital information processing system dsp software process flow diagram.
[PC computing machine]
Show aerogenerator status monitoring interface menu; The transmission request signal of responding digital signal processing system DSP; Receive each frame signal that DSP transmits, recursion storage aerogenerator vibration performance parameter shows time domain, frequency domain character value with modes such as curve, rod figure; Relatively judge the state that aerogenerator is present with vibration standard: normal, warning, danger provide warning message.Can check simultaneously historical alert data, statistics alarming value as required.
According to each measuring point vibration performance value contrast vibration criterion, judge which kind of state aerogenerator is in and also shows on computers.When vibration values normally then shows current vibration values with green; When abnormal vibrations occurring and exceeding standard when little with yellow flicker display alarm state and store alarms value and time of fire alarming; When abnormal vibrations occurring and exceed standard greatly, show that needing to shut down maintenance fixes a breakdown, computing machine shows the vibration performance value and with auditory tone cues, stores exceptional value and time of origin with red flashing mode, supplies the usefulness of analysis.
In sum; The present invention relates to aerogenerator condition monitoring system and method; Obtain the aerogenerator status signal respectively through a plurality of sensors are installed, utilize the fast signal analyzing and processing function of digital information processing system DSP, adopt signal time domain statistical analysis technique and AR model Fast estimation power spectrum; Extract the characteristic parameter of various sensitivities and good stability, and then be that judgement aerogenerator shape body is established solid foundation.Through communication interface information such as the temporal signatures parameter of rotating speed, each vibration transducer, power spectrum are sent to the PC computing machine that is positioned at the ground monitoring chamber again; The PC computer real-time shows the current state information and the various vibration performance parameter of aerogenerator, and store alarms value and time of fire alarming.
The present invention give full play to the DSP digital signal processing capability strong, fast, high reliability features; Give full play to the powerful graphical display function of PC computing machine, data management and man-machine conversation function.The present invention gets up dsp system and PC computing machine combine well, displays one's respective advantages, and forms a kind of reliable, effective aerogenerator condition monitoring system and method.
Claims (6)
1. aerogenerator condition monitoring system; Be last the next two level computer monitoring of structures; Slave computer is digital information processing system DSP, is fixed in the cabin at aerogenerator top, and host computer is the PC computing machine; It is indoor to be positioned at the aerogenerator ground monitoring, and slave computer DSP utilizes communication interface to realize communicating by letter of digital signal with the host computer PC computing machine; It is characterized in that; Also comprise the sensor that is fixed on the aerogenerator machine driven system; The output terminal of sensor is connected with the input end of signal condition unit; The output terminal of signal condition unit is connected with the input end of signal gathering unit again, and the signal gathering unit output terminal is connected with the input end of digital information processing system DSP.
2. aerogenerator condition monitoring system according to claim 1 is characterized in that sensor comprises: speed probe, acceleration transducer, speed pickup.
3. aerogenerator condition monitoring system according to claim 2 is characterized in that, on the cabin of aerogenerator speed pickup is installed; On the engine input shaft speed probe is installed; Be separately installed with acceleration transducer on main bearing seat, engine shaft bearing and the gearbox.
4. the monitoring method of aerogenerator condition monitoring system; It is characterized in that; The aerogenerator vibration signal of sensor acquisition is through conversion, filtering, the amplification of signal condition unit; Accomplish the conversion of analog quantity by signal gathering unit, send into digital information processing system DSP analyzing and processing again to digital quantity.The Fast estimation that digital information processing system DSP carries out extraction that time domain has dimension characteristic parameter, dimensionless characteristic parameter to each vibration signal and carries out frequency spectrum through the AR model at frequency domain; Thereby obtain the information of aerogenerator vibrational state; Digital information processing system DSP is sent to the PC computing machine with these characteristic parameters through communication interface then; The PC computer real-time shows the state of aerogenerator; Show vibration performance parameter variation tendency figure, the various characteristic parameters under the storage ERST supply to check analysis.
5. the monitoring method of aerogenerator condition monitoring system according to claim 4 is characterized in that, the flow process of said digital information processing system DSP processing signals is following:
1. .DSP is digital quantity to each sensor sample with analog signal conversion, and sampling is undertaken by fixed frequency and data volume, and the sampling edge limit is kept at digital quantity in the DSP internal memory;
2.. the sampled value by speed probe calculates the aerogenerator rotating speed; Calculate the time domain statistical characteristics of vibration signal respectively by the sampled data of each vibration transducer; The time domain statistical nature comprises: mean value, effective value, variance, probability density function, correlation analysis, kurtosis, form factor, nargin index are saved in the DSP internal memory with above result of calculation;
3.. utilize the AR model to calculate the power spectrum of each vibration sensor signal fast, and preserve power spectrum information in the DSP internal memory;
4. .DSP request is communicated by letter with host computer PC, and the time domain statistical nature and the power spectrum information of aerogenerator tachometer value, each vibration sensor signal is sent to the host computer PC computing machine; DSP accomplishes a systemic circulation job;
4. 1. the flow process of DSP processing signals circulate successively to step by above-mentioned steps and carry out.
6. according to the monitoring method of claim 4 or 5 described aerogenerator condition monitoring systems; It is characterized in that PC computer monitoring program is: show aerogenerator status monitoring interface menu, the transmission request signal of responding digital signal processing system DSP; Receive each frame signal that DSP transmits; Show time domain, frequency domain character parameter with curve or excellent figure mode, according to the vibration performance parameter of each vibration transducer, the criterion of contrast wind-power electricity generation machine vibration; Judge the state of aerogenerator, if vibration values belongs to normally and then shows current vibration values with green; When abnormal vibrations occurring and exceeding standard when little with yellow flicker display alarm state and store alarms value and time of fire alarming; When abnormal vibrations occurring and exceed standard greatly, show that needing to shut down maintenance fixes a breakdown, computing machine shows the vibration performance value and with auditory tone cues, stores exceptional value and time of origin with red flashing mode.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1113739A (en) * | 1994-06-23 | 1995-12-27 | 王湘生 | Function testing system for vegetative nervous system and its method |
| US20060129389A1 (en) * | 2000-05-17 | 2006-06-15 | Den Brinker Albertus C | Spectrum modeling |
| CN101118437A (en) * | 2007-09-03 | 2008-02-06 | 石毅 | New style numerically controlled machine remote condition monitoring and failure diagnosis system realizing method |
| CN201417174Y (en) * | 2009-06-19 | 2010-03-03 | 武汉钢铁(集团)公司 | Monitoring system of electro-mechanic equipment |
| CN102156043A (en) * | 2010-12-31 | 2011-08-17 | 北京四方继保自动化股份有限公司 | Online state monitoring and fault diagnosis system of wind generator set |
-
2012
- 2012-03-22 CN CN2012100919939A patent/CN102620807A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1113739A (en) * | 1994-06-23 | 1995-12-27 | 王湘生 | Function testing system for vegetative nervous system and its method |
| US20060129389A1 (en) * | 2000-05-17 | 2006-06-15 | Den Brinker Albertus C | Spectrum modeling |
| CN101118437A (en) * | 2007-09-03 | 2008-02-06 | 石毅 | New style numerically controlled machine remote condition monitoring and failure diagnosis system realizing method |
| CN201417174Y (en) * | 2009-06-19 | 2010-03-03 | 武汉钢铁(集团)公司 | Monitoring system of electro-mechanic equipment |
| CN102156043A (en) * | 2010-12-31 | 2011-08-17 | 北京四方继保自动化股份有限公司 | Online state monitoring and fault diagnosis system of wind generator set |
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