CN103604622B - A kind of Wind turbines on-line monitoring instant alarming and fault diagnosis system - Google Patents
A kind of Wind turbines on-line monitoring instant alarming and fault diagnosis system Download PDFInfo
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- CN103604622B CN103604622B CN201310619384.0A CN201310619384A CN103604622B CN 103604622 B CN103604622 B CN 103604622B CN 201310619384 A CN201310619384 A CN 201310619384A CN 103604622 B CN103604622 B CN 103604622B
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Abstract
The invention discloses a kind of Wind turbines on-line monitoring instant alarming and fault diagnosis system, be made up of slave computer (1) and host computer (2); Slave computer (1) is arranged on Wind turbines; Slave computer (1) is communicated by wired or wireless network with host computer (5).Operationally, send enabled instruction by host computer (5) to slave computer (1), slave computer (1) starts to carry out signal data acquisition, carries out online instant alarming to exception and fault, stores described signal or signal characteristic information meanwhile; Host computer (5) accepts and stores the signal or signal characteristic information that slave computer (1) uploads, and carries out analyzing and processing, and generates various form as required.The present invention can carry out online instant alarming to running of wind generating set state, carries out trend analysis and carry out prediction and warning to potential fault, for reduction Wind turbines catastrophic failure, reduces because the standby loss etc. brought has important value.
Description
Technical field
The present invention designs Wind turbines condition monitoring and fault diagnosis technical field, a kind of Wind turbines on-line monitoring instant alarming of special design and fault diagnosis system.
Background technology
Fault when wind power generating set is run is one of key affecting wind-powered electricity generation operation enterprise benefit.In general, running of wind generating set fault determines that can unit the steady in a long-term key factor run, and its mechanism of production is complicated, relates to many factors.The operation maintenance of current wind energy turbine set understands the running status of unit mainly through the mode of the monitoring of unit master control system and regular visit.Owing to forming the containing much information of annex running status, calculation process process is complicated, and the process of the mass data particularly obtained for high sample frequency needs cycle regular hour; And the fault diagnosis often too late damage retrieved fault and Wind turbines is caused afterwards.Therefore, build Wind turbines on-line monitoring, Realtime Alerts and fault diagnosis system, for monitoring operating condition, take appropriate measures in time, the generation of prevention and minimizing unit fault, and carry out fault pre-alarming by depth data analysis, realizing pre-emptive maintenace, is all very important.
Abroad, research for large-scale wind electricity operating states of the units monitoring system has defined a collection of practical product, such as, SKFWindCon system, the BentlyNevada system of General Electric Co. Limited, the VIBXPERTFFT Data collection and signal analysis instrument of Pruftechnik company, the on-line condition monitoring system of VIBROWEBXP diagnosis type, the VIBRO-IC system etc. of German SCHENCKVIBROGMBH company of Aktiebolaget SKF.Also there are many units to have developed corresponding product for the status monitoring of wind power generating set at present at home, more representationally mainly contain: the Wind turbines on-line monitoring system of Jin Feng scientific & technical corporation, the JK07460 aerogenerator driving unit fault diagnostic device of Beijing Tang Zhi Science and Technology Ltd., Northwestern Polytechnical University's rotating machinery and the CAMD-6100 of wind energy plant observing and controlling research institute and the DASP system etc. of Dongfa Inst. of Vibration & Noise Technology.The analysis of these products and diagnostic function are mostly more weak, and the usual systematic comparison complexity of product that analytic function is strong, involve great expense.Literature survey shows, no matter that home or overseas existing running of wind generating set Condition Monitoring Technology and system mostly adopt slave computer signals collecting, upload long-range host computer and carry out analyzing and note abnormalities, carry out the pattern of reporting to the police, online instant alarming function is generally lacked to real-time device fault, the fault discovery cycle occurred Wind turbines is longer, and bringing therefrom is sometimes catastrophic consequence.
Summary of the invention
The problem to be solved in the present invention is to provide a kind of Wind turbines on-line monitoring instant alarming and fault diagnosis system, to solve the problem that prior art and system are reported to the police not in time to real time fail, simultaneously, a kind of data analysis and method for diagnosing faults are provided, running of wind generating set Trend Analysis and fault pre-alarming can be realized.
For achieving the above object, the invention provides a kind of Wind turbines on-line monitoring instant alarming and fault diagnosis system, be made up of slave computer 1 and host computer 5, slave computer 1 is for signals collecting, online Realtime Alerts and network service, host computer 5 carries out analysis and generating report forms for controlling described slave computer 1, to the signal data gathered, slave computer 1 is installed on Wind turbines, is undertaken being connected and communicating by wired or wireless network with host computer 5, described slave computer 1 comprises signal acquisition module 2, online fault instant alarming module 3 and network communication interface module 4, wherein, described signal acquisition module 2 comprises data acquisition card 9, signals collecting interface 10 and Signal-regulated kinase 11, for gathering described Wind turbines parts diagnostic message, described online fault instant alarming module 3 comprises Signal Pretreatment 12, signal specific feature extraction 13, feature decision 14 characteristic signal expert knowledge library 15, online fault instant alarming 16 and signal or signal characteristic store 17, signal for gathering described signal acquisition module processes immediately, differentiate, and when noting abnormalities instant alarming, described network communication interface module 4 is for communicating with described host computer 5, receive the steering order of described host computer 5, and send information to designated terminal, described host computer 5 comprises and slave computer communication module 6, data analysis and fault diagnosis module 7 and report generation module 8, wherein, described with slave computer communication module 6 for described slave computer 1 sending controling instruction, and receive the information that described slave computer 1 uploads, described data analysis and fault diagnosis module 7 comprise signature analysis 18, trend analysis 19, traditional analysis 20, Mathematical Method 21 and intelligent analysis method 22, signal data for uploading described slave computer 1 is analyzed, and described report generation module 8 is for generating required form.As shown in Figure 1.
Described slave computer 1 is arranged on Wind turbines, is connected with the various sensors be arranged on Wind turbines by described signal acquisition module 2, and carries out data communication by described network communication interface module 4 with described host computer 5.Described slave computer comprises at least one CPU (central processing unit) (CPU).
Described signal acquisition module 2 comprises capture card 9, signals collecting interface 10 and Signal-regulated kinase 11, does not need the sensor (sensor type 1) carrying out signal condition directly to connect described signals collecting interface 10; The sensor (sensor type 2) carrying out signal condition is needed then to be connected to described signals collecting interface 10 by described Signal-regulated kinase 11.The each several part that described signal acquisition module 2 comprises connects according to relation shown in Fig. 2, wherein, and direction of arrow representative information or energy flow direction.
Described online fault instant alarming module 3 is arranged on described slave computer 1, comprise Signal Pretreatment 12, signal characteristic abstraction 13, characteristic signal expert knowledge library 15, feature decision 14, the online process such as fault instant alarming 16 and signal storage 17, as shown in Figure 3, wherein, the direction of arrow represents process execution sequence or information flow direction; Described signal characteristic refers to and comprises temporal signatures, as index and frequency domain characters such as peak-to-peak value, effective value, variance, crest factor, kurtosis, as the signal characteristic of the indexs such as frequency spectrum, amplitude and phase place; Described Signal Pretreatment 12 is process such as quick filter, noise reduction signal collected to described signal acquisition module 2; Described signal specific feature extraction 13 refers to carry out signal characteristic abstraction to the result of the signal characteristic scope limited according to described characteristic signal expert knowledge library 15 to described Signal Pretreatment 12; Described Signal Pretreatment 12 and described signal specific feature extraction 13 can adopt hardware circuit to realize the real-time improving signal transacting; Characteristic signal expert knowledge library 15 described in described signal characteristic sets up in advance and is stored in one group of abnormality juding rule of described slave computer 1 li and the set of set state signal characteristic, and the set of described set state signal characteristic refers to the set of the signal characteristic describing Wind turbines normal operating condition, parts normal condition, the various defect state of parts, the various abnormality of parts etc.Described online fault instant alarming 16 comprises and sends warning message by described network communication interface module 4 to described host computer 5, and can send warning message to particular terminal with forms such as notes when needed.Described online fault instant alarming module 3 is when performing, first described Signal Pretreatment 12 is carried out to the live signal of online acquisition, then carry out described signal characteristic abstraction 13, next under the support of characteristic signal expert knowledge library 15, the signal characteristic extracted is carried out described feature decision 14; As noted abnormalities, then perform described online fault instant alarming 16, and differentiate according to described signal characteristic the position, parts place that the report the test of 14 breaks down; As no abnormal, then perform described signal or signal characteristic storage 17.
Described network communication interface module 4 comprises wired or wave point and defers to the network communication services program of network communication protocol, be responsible for receiving instruction from described host computer 5 and sending data to described host computer 5, comprise various signal or signal characteristic information and online fault instant alarming information etc., meanwhile, also support to send warning message to designated terminal with the form such as note, multimedia message.
Described host computer 5 is by carrying out data communication with slave computer communication module 6 and described slave computer 1, receive the signal of the running of wind generating set state that described slave computer 1 gathers or signal characteristic information and online instant alarming information, meanwhile, various steering order is sent to described slave computer 1.Described host computer comprises at least one CPU (central processing unit) (CPU).Described host computer 5 can be arranged on, also can not be arranged on described Wind turbines.
Describedly comprise wired or wave point and communication control program with slave computer communication module 6, described communication control program comprises to described slave computer 1 sending controling instruction, receives running of wind generating set status signal or signal characteristic information supervisor process that described slave computer 1 failure warning information and described slave computer 1 gather.
Described data analysis and fault diagnosis module 7 comprise the set of signature analysis 18, trend analysis 19, traditional analysis 20, Mathematical Method 21 and intelligent analysis method 22 supervisor, as shown in Figure 4; Described signature analysis 18 refers to carries out temporal signatures to described running of wind generating set status signal, as index and frequency domain characters such as peak-to-peak value, effective value, variance, crest factor, kurtosis, as the signature analysis of frequency spectrum, amplitude and phase place etc.; Described trend analysis 19 refers to by carrying out determining base contrast and chain rate contrast to two phases or the identical index of continuous print of many phases or ratio by the cycle of specifying to described running of wind generating set status data information, draw their increase and decrease variation direction, number and amplitude, to disclose running of wind generating set trend and to break down to unit parts or defect carries out anticipation; Described traditional analysis method 20 refers to and carries out vibration analysis, oil analysis, noise analysis, infrared measurement of temperature analysis or Nondestructive Detection etc. to described running of wind generating set status data information; Described mathematical methods 21 refer to based on the temporal model diagnosis of probability statistics, fuzzy diagnosis method, fault tree analysis, based on Bayesian decision criterion and based on linear with the pattern-recongnition method of non-linear discriminant function, fault diagnosis method, gray system diagnosis, wavelet analysis, chaos analysis and the fractal geometry analytic approach etc. based on distance criterion; Described intelligent diagnostics method 22 refers to the analytical approachs such as expert system, neural network, genetic algorithm, fuzzy logic and large data technique.
Described report generation module 8, for generating and printing various form needed for wind-powered electricity generation operation enterprise, comprises the forms such as fault instant alarming, operating states of the units trend, operating states of the units early warning, data transmit-receive daily record.
Wind turbines on-line monitoring instant alarming provided by the invention and fault diagnosis system can the running statuses of on-line real time monitoring Wind turbines, and can when fault occurs instant alarming, avoid because fault alarm is not in time to the serious consequence brought of wind-powered electricity generation operation enterprise; Simultaneously; anticipation is carried out by described data analysis and fault diagnosis module 7 pairs of running of wind generating set states; diagnose out the running of wind generating set or component failure that exist or be about to produce; timely prompting wind-powered electricity generation operation enterprise maintenance; improve the running of wind generating set life-span, reduce the failure rate of running of wind generating set, reduce the economic loss because Wind turbines disorderly closedown brings.
Accompanying drawing explanation
Fig. 1 is the structural representation of Wind turbines on-line monitoring instant alarming of the present invention and fault diagnosis system.
Fig. 2 is the signal acquisition module structural representation of Wind turbines online monitoring alarm of the present invention and fault diagnosis system.
Fig. 3 is the online fault instant alarming modular structure schematic diagram of Wind turbines online monitoring alarm of the present invention and fault diagnosis system.
Fig. 4 is that the data analysis of Wind turbines online monitoring alarm of the present invention and fault diagnosis system and fault diagnosis module form schematic diagram.
Embodiment
For enabling above-mentioned purpose of the present invention, feature and advantage become apparent more, are described in detail the specific embodiment of the present invention below in conjunction with accompanying drawing.
Be illustrated the present invention below in conjunction with specific embodiment, certainly, the present invention is not limited to this specific embodiment, and the general replacement known by one of ordinary skilled in the art should be encompassed in protection scope of the present invention undoubtedly.
Secondly, the present invention has been described in detail in conjunction with schematic diagram, when describing the embodiment of the present invention in detail, has carried out specific description to Wind turbines on-line monitoring instant alarming and fault diagnosis system, should in this, as limitation of the invention.
Fig. 1 is the general structure schematic diagram of Wind turbines on-line monitoring instant alarming of the present invention and fault diagnosis system.As shown in Figure 1, Wind turbines online monitoring alarm of the present invention and fault diagnosis system are made up of slave computer 1 and host computer 5, and wherein, slave computer 1 comprises signal acquisition module 2, online fault instant alarming module 3 and network communication interface module 4; Host computer 5 comprises and slave computer communication module 6, data analysis and fault diagnosis module 7 and report generation module 8.
Described slave computer 1 is arranged on Wind turbines, is connected with the various sensors be arranged on Wind turbines by described signal acquisition module 2, and is communicated with host computer by described network communication interface module 4.Described slave computer 1 can select single-chip microcomputer, desktop PC or the industrial computer of being with central processing unit; Described slave computer generally runs real time operating system, as real time operating systems etc. such as RealtimeLinux, iEAX, VRTX, and can support one to multiple piece of dissimilar data acquisition card.
Described signal acquisition module 2 supports online real-time data acquisition, comprise capture card 9, signals collecting interface 10 and Signal-regulated kinase 11, the sensor be arranged on Wind turbines is connect by signals collecting, 10 or Signal-regulated kinase 11 be connected to signal acquisition module 2, wherein, described capture card 9 can select one to multiple piece of synchronous or non-synchronous data capture card; Signals collecting interface 10 is terminal strips supporting with capture card 2; The path that Signal-regulated kinase 11 comprises signal conditioning circuit by one or more forms, each path comprises a bars modulate circuit, sensor can be produced ± signal transmitting such as V, ± mA and ± mV become the various signal required for client and isolated transmission to described signals collecting interface 10.
Described online fault instant alarming module 3 contains Signal Pretreatment 12, signal characteristic abstraction 13, characteristic signal expert knowledge library 15, feature decision 14, online fault instant alarming 16 and signal or signal characteristic store database and the program processs such as 17, wherein, Signal Pretreatment 12 carries out fast processing to the running of wind generating set status information that described signal acquisition module 2 collects, as carried out signal filtering, nonlinear transformations etc. remove interference process, as low frequency filtering can intercept or weaken the high-frequency signal higher than setting critical value, effective removal signal noise, high-pass filtering then intercepts or weakens the low frequency signal lower than setting critical value, contribute to outstanding fault-signal, described signal characteristic abstraction 13 is the temporal signatures to signal, as index and frequency domain characters such as peak-to-peak value, effective value, variance, crest factor, kurtosis, as frequency spectrum, amplitude and phase place etc. are extracted, for carrying out aspect ratio pair with the described signal characteristic in characteristic signal expert knowledge library 15, described characteristic signal expert knowledge library 15 contains the set of abnormality juding rule or set state signal characteristic data, described abnormality juding rule refers to the description of the corresponding relation of signal characteristic data and its faults, described set state signal characteristic data acquisition refer to signal characteristic data and its reflect the description of the corresponding relation of running status, described online fault instant alarming 16 refers to when described feature decision 14 finds described signal characteristic data when meeting described abnormality juding rule at once to described host computer 5 or send warning message with the form such as note, multimedia message to designated terminal, can directly shut down time serious, described signal or signal characteristic storage refer to and store the result of described signal or signal characteristic abstraction, if desired, for improving processing speed, online fault instant alarming module 3 can adopt hardware circuit to realize, as selected TDS3FFT to realize Fast Fourier Transform (FFT).
Described network communication interface module 4 is made up of wired or wireless interface and the network communication services program deferring to network communication protocol, described wired or wireless interface is as Ethernet card, WIFI wireless network card or 3G, 4G card of surfing Internet or asynchronous transmission standard interface (RS-232, RS-485 etc.) etc.; The described network communication services program deferring to network communication protocol is responsible for realizing receiving instruction from described host computer 5 and sending data to described host computer 5, comprise the function of various signal or signal characteristic data message and online Realtime Alerts information, also the form such as network, note, multimedia message can send warning message to designated terminal when needed.
Described host computer 5 carries out data communication by described with slave computer communication module 6 and described slave computer 1, receive running of wind generating set status data information and online instant alarming information that described slave computer 1 gathers, meanwhile, various steering order is sent to described slave computer 1.The optional industrial computer of described host computer 5, desktop PC or panel computer etc., can run conventional operating system, as operating systems such as Windows, Linux or Android; Described host computer 5 also can select any mobile terminal of band central processing unit.
Describedly to be made up of wired or wireless interface and communication control program with slave computer communication module 6; Described wired or wireless interface is as Ethernet card, WIFI wireless network card or 3G, 4G card of surfing Internet and asynchronous transmission standard interface (as RS-232, RS-485 etc.) etc.; Described communication control program is mainly used to realize to described slave computer 1 sending controling instruction, receives failure warning information that described slave computer 1 sends and the running of wind generating set status information supervisor function that described slave computer 1 gathers.
Described data analysis and fault diagnosis module 7 are made up of described signature analysis 18, trend analysis 19, traditional analysis 20, Mathematical Method 21 and intelligent analysis method 22 supervisor bag, the Wind turbines status information that described data analysis and fault diagnosis module 7 are mainly used in described slave computer 1 gathers carries out off-line analysis, to realize to the anticipation of running of wind generating set state or to occurring that component failure carries out early warning future.When implementing, the described analytical approach that described data analysis and fault diagnosis module 7 comprise can be selected according to actual needs.
Described report generation module 8 is mainly used in generating and prints various form needed for wind-powered electricity generation operation enterprise, comprises the forms such as fault alarm, operating states of the units trend, operating states of the units early warning, data transmit-receive daily record.Actual to implement, can define according to the requirement of different enterprise the described various statement form that described report generation module comprises.
Wind turbines online monitoring alarm of the present invention and fault diagnosis system are operationally, enabled instruction is sent to described slave computer 1 by described host computer 5, described slave computer 1 starts to carry out signal data acquisition, start described online fault instant alarming module 3 simultaneously, process online signal collected, and online instant alarming is carried out to abnormal signal and fault, described signal or signal characteristic information are stored meanwhile; Described host computer 5 sends data transfer instruction to described slave computer 1, and accept that described slave computer 1 uploads be stored in described signal on described slave computer 1 or signal characteristic information, and be stored on described host computer 5; On described host computer 5, analyzing and processing can be carried out to received described signal or signal characteristic information by described data analysis and fault diagnosis module 7, obtain described running of wind generating set state trend, find fault and carry out failure prediction and early warning, and generate described various form by described report generation module 8 as required.
The described online fault instant alarming module 3 of Wind turbines on-line monitoring instant alarming of the present invention and fault diagnosis system solves prior art and system cannot carry out the online problem to instant fault alarm to running of wind generating set state, simultaneously, the described data analysis that Wind turbines on-line monitoring instant alarming of the present invention and fault diagnosis system provide and fault diagnosis module 7 can realize running of wind generating set Trend Analysis and carry out failure prediction and early warning to the potential source of trouble, for the heavy economic losses that reduction Wind turbines catastrophic failure brings, promote operation enterprise maintenance efficiency, reduce because Wind turbines fault or standby the brought loss etc. of prophylactic repair have important meaning and value.
Obviously, those skilled in the art can carry out various change and modification to the present invention, under the premise without departing from the spirit and scope of the present invention, if the amendment make the present invention and modification belong within the scope of the claims in the present invention and equivalent technologies thereof, then the present invention is also intended to comprise these change and modification.
Claims (7)
1. a Wind turbines on-line monitoring instant alarming and fault diagnosis system, it is characterized in that, comprise: slave computer (1) and host computer (5), slave computer (1) is for signals collecting, online Realtime Alerts and network service, host computer (5) carries out analysis and generating report forms for controlling described slave computer (1), to the signal data that slave computer (1) gathers, slave computer (1) is installed on Wind turbines, is communicated by wired or wireless network with host computer (5);
Described slave computer (1) comprises signal acquisition module (2), online fault instant alarming module (3) and network communication interface module (4), wherein,
Described signal acquisition module (2), for gathering described Wind turbines parts diagnostic message, comprises data acquisition card (9), signals collecting interface (10) and Signal-regulated kinase (11),
Described online fault instant alarming module (3) immediately processes for the signal gathered described signal acquisition module, differentiates, and when noting abnormalities instant alarming, comprise Signal Pretreatment (12), signal specific feature extraction (13), feature decision (14), characteristic signal expert knowledge library (15), online fault instant alarming (16) and signal or signal characteristic storage (17)
Described network communication interface module (4), for communicating with described host computer (5), receives the steering order of described host computer (5), and sends information to designated terminal;
Described host computer (5) comprises and slave computer communication module (6), data analysis and fault diagnosis module (7) and report generation module (8), wherein,
Described with slave computer communication module (6) for described slave computer (1) sending controling instruction, and receive the information that slave computer (1) uploads,
Described data analysis and fault diagnosis module (7) are analyzed for the signal data uploaded described slave computer (1), comprise signature analysis (18), trend analysis (19),
Described report generation module (8) is for generating required form.
2. Wind turbines on-line monitoring instant alarming as claimed in claim 1 and fault diagnosis system, is characterized in that, described slave computer (1) adopts single-chip microcomputer or industrial computer.
3. Wind turbines on-line monitoring instant alarming as claimed in claim 1 and fault diagnosis system, is characterized in that, described online fault instant alarming module (3) adopts hardware circuit to realize accelerating.
4. Wind turbines on-line monitoring instant alarming as claimed in claim 1 and fault diagnosis system, it is characterized in that, described characteristic signal expert knowledge library (15) is made up of abnormality juding rule and the set of set state signal characteristic, described abnormality juding rule refers to the corresponding relation of signal characteristic data and its fault reflected, the set of described set state signal characteristic refers to the corresponding relation of signal characteristic data and its operating states of the units reflected.
5. Wind turbines on-line monitoring instant alarming as claimed in claim 1 and fault diagnosis system, it is characterized in that, described network communication interface module (4) is made up of wired or wireless interface and the network communication services program deferring to network communication protocol, and sends warning message to designated terminal by network, note, multimedia message form.
6. Wind turbines on-line monitoring instant alarming as claimed in claim 1 and fault diagnosis system, is characterized in that, described host computer (5) adopts single-chip microcomputer, industrial computer or mobile terminal.
7. Wind turbines on-line monitoring instant alarming as claimed in claim 1 and fault diagnosis system, it is characterized in that, described host computer (5) is communicated with described slave computer (1) with slave computer communication module (6) by described.
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| CN105099804B (en) * | 2014-05-15 | 2019-01-18 | 中国石油天然气股份有限公司 | Detection method, server and the terminal of unit failure |
| CN105402092B (en) * | 2015-12-10 | 2018-10-02 | 北京天诚同创电气有限公司 | Detection method and device of wind generating set |
| CN108508358A (en) * | 2017-03-01 | 2018-09-07 | 北京鼎好鑫源科技有限公司 | A kind of online Wind turbines dual signal trouble-shooter and diagnostic method |
| US11549491B2 (en) * | 2017-06-14 | 2023-01-10 | Kk Wind Solutions A/S | Independent monitoring system for a wind turbine |
| CN107092247B (en) * | 2017-06-16 | 2019-11-22 | 温州大学 | A kind of packaging production line method for diagnosing faults based on status data |
| CN107544462B (en) * | 2017-09-07 | 2019-07-16 | 新疆金风科技股份有限公司 | For diagnosing the method and system of the failure of wind power generating set |
| CN109947786A (en) * | 2017-10-17 | 2019-06-28 | 中车株洲电力机车研究所有限公司 | Failure checks method, apparatus and computer readable storage medium automatically in wind power plant |
| CN110096036A (en) * | 2018-01-29 | 2019-08-06 | 阿里巴巴集团控股有限公司 | A kind of determination method, device and equipment of equipment state |
| CN108985467A (en) * | 2018-06-22 | 2018-12-11 | 贵州电网有限责任公司 | Secondary device lean management-control method based on artificial intelligence |
| CN108646697A (en) * | 2018-07-17 | 2018-10-12 | 河南聚合科技有限公司 | A kind of equipment fault remote diagnosis cloud platform |
| CN109444709B (en) * | 2018-09-07 | 2021-02-12 | 南京理工大学 | Wind turbine generator testing system design method based on virtual instrument technology |
| CN112071031A (en) * | 2020-07-22 | 2020-12-11 | 中冶南方都市环保工程技术股份有限公司 | Alarm diagnosis method and system based on real-time data monitoring |
| CN113985814B (en) * | 2021-10-25 | 2024-05-10 | 东华大学 | Processing process self-adaptive control method based on digital twin |
| CN114323521B (en) * | 2021-12-30 | 2024-03-08 | 筑美抗震支架技术(烟台)有限公司 | Intelligent monitoring cloud platform system of anti-seismic and shock-insulation support |
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| US20110020122A1 (en) * | 2009-07-24 | 2011-01-27 | Honeywell International Inc. | Integrated condition based maintenance system for wind turbines |
| CN102053596B (en) * | 2010-09-26 | 2012-09-12 | 陕西宇宏国际建机有限公司 | Intelligent analyzing monitoring device and method of wind power plant and wind power engine room |
| CN102156043B (en) * | 2010-12-31 | 2013-01-16 | 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 |
| CN102829977B (en) * | 2012-08-23 | 2015-01-14 | 天津瑞能电气有限公司 | Method for monitoring low-frequency vibration of wind power generation set |
| CN103234585A (en) * | 2013-04-16 | 2013-08-07 | 内蒙古航天亿久科技发展有限责任公司 | Online monitoring and fault diagnosis system of large wind turbine units |
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