Open Access A New Fault Diagnosis Method for High Voltage Circuit Breakers Based on Wavelet Packet and Radical Basis Function Neural Network

Transcription

1 Send Orders for Reprnts to 410 The Open Cybernetcs & Systemcs Journal, 2014, 8, Open Access A New Fault Dagnoss Method for Hgh Voltage Crcut Breakers Based on Wavelet Packet and Radcal Bass Functon Neural Network Lu Mnglang 1,2, Wang Keq 1,*, Sun Lajun 2 and Zhang Janfeng 2 1 College of Mechancal and Electrcal Engneerng, Northeast Forestry Unversty, Harbn ,Chna 2 HLJ Provnce Key Lab of Senor-Educaton for Electronc Engneerng (Helongjang Unversty) Harbn Chna Abstract: A new method that researchng fault dagnoss of hgh-voltage (HV) crcut breaker (CB) s proposed. The method combnes Wavelet Packet (WP) wth Radcal Bass Functon (RBF) Neural Network (NN). Frstly, by applyng the theory of WP decomposton and reconstructon, the mechancal vbraton sgnal of CB was decomposed nto dfferent frequency bands, and the coeffcents are reconstructed n the correspondng node. After that, the feature vector was extracted by equal-energy segment entropy from reconstructed sgnals. Fnally, fault dagnoss has been realzed through the classfcaton of feature parameters combned wth RBF neural network. The experment outputs show that the method can be appled n dagnoss. Keywords: Characterstc entropy, equal-energy segment, fault dagnoss, RBF Neural Network, wavelet packet. 1. INTRODUCTION As a key component of power system, HV CB can protect power equpment and nsulate the fault. HV CB status affect the safety operaton of the power system, so HV CB fault dagnoss s of great sgnfcance. Mechancal fault occupes a large proporton n the hgh voltage crcut breaker fault. Therefore, mechancal faults were extensvely studed at present [1-3]. Mechancal vbraton sgnals generated by crcut breaker operaton whch contans a lot of mportant nformaton, the nformaton showed crcut breaker devce status. Hence, mechancal vbraton sgnals can be used to detect the crcut breaker status. The past 30 years, wth the development of scence, the mprovement of computer performance, the progress of sgnal processng technology, fault dagnoss feld has obtaned many achevements. Related technologes ncludng EMD [4, 5], sngularty analyss [6], wavelet [7-9], and wavelet packet [10, 11], etc. Entropy s a measurement scale of rregularty and nformaton entropy s the descrpton of uncertanty to the system. Informaton entropy was the content of the nformaton theory orgnally, but has been wdely used n many felds, such as water qualty evaluaton, hydropower unt operaton qualty degree evaluaton, and scence and technology compettveness evaluaton, rotatng machnery health evaluaton [12, 13], etc. Through the study of WP and the nformaton entropy, ths paper proposes a combnaton of WP and RBF neural *Address correspondence to ths author at College of Mechancal and Electrcal Engneerng, Northeast Forestry Unversty, Harbn, , P.R. Chna; Tel: ; E-mal: zdhwkq@163.com network method for mechancal fault dagnoss. Frst of all, the breaker mechancal vbraton sgnal were decomposed n three layer wth wavelet packet, and then reconstructed the sgnal n the correspondng node of three layers. After that, we put the standard sgnal energy tme segment and computed the ntegral energy entropy. At last, fault dagnoss has been mplemented on the classfcaton of feature parameters combned wth RBF neural network. 2. WAVELET PACKETS Wavelet transform s developed by Fourer transform and s a mult-scale sgnal analyss method. Both n tme and scale wavelet transform has an ablty of denotng local sgnal characterstcs, so t s sutable for analyss of transent non-statonary sgnal and tme-frequency characterstcs. Compared wth wavelet transform, wavelet packet decomposton (WPD) was carred out from low to top of frequency part. WPD mprove the tme-frequency resoluton, whch provdes more elaborate non-statonary sgnal analyss methods [14]. Under the condton of meet the uncertanty prncple, the sgnal can be decomposed nto dfferent frequency bands accordng to arbtrary tme-frequency resoluton through WPD. And composton of tme-frequency can be projected correspondng orthogonal wavelet packet space whch all represents dfferent frequences. Sgnal S, the wavelet packet transform: C j,k (t) = S, j,k (t) ; = 1,2 Where, C j,k (t), wavelet packet coeffcents, frequency range parameter X/ Bentham Open

2 A New Fault Dagnoss Method for Hgh Voltage Crcut Breakers The Open Cybernetcs & Systemcs Journal Journal, 2014, Volume Fg. (1). Wavelet packet decomposton. Fg. (2). Segments wth equal energy. j,k j, scale parameters k, translaton parameters j,k (t) wavelet packet functon j (t) = 2 2 (2 j t k); = 1,2 j,k (t), Calculated by wavelet functon through h k flter and g k flter. 2 (t) = 2 h(k) (2t k) 2+1 (t) = 2 g(k) (2t k) WP s the combnaton of a seres of wavelet bass functon, t stll has the orthogonalty and the tme-frequency features of wavelet bass functons [15]. Wavelet packet s superor to wavelet n hgh frequency resoluton. WP can get dfferent frequency resoluton though choosng dfferent bass functons. Wavelet packet decomposton tree of the sgnal n dfferent scales s shown n Fg. (1). 3. ENTROPY Entropy s measure of mcrostate dversty or homogenety n thermodynamcs and whch can reflect thedsorder of the system. In nformaton theory, the random nterference s nevtable n the communcaton, the communcaton system has the characterstcs of statstcs, and nformaton sources can be consdered as a set of random events, the set of (1) randomness and uncertanty s smlar to chaos of mcroscopc n thermodynamc. So the concept of nformaton entropy s proposed by Shannon n 1948 [16], derved from the concept of thermodynamcs, expanded to a varety of source sgnal [17-19]. Defnea system X has several dfferent state x 1, x 2,, x, x N ( = 1,2,n) probablty s p(x ) Its nformaton entropy H(x) s: N H(x) = p(x )log( p(x )) (2) =1 0 p(x ) 1, p(x ) = 1 n =1 Defne: p(x ) = 0, 0log0 = 0 Fault dagnoss of CB s essental for dstngushng normal state from fault state. Fault statuses have dfferent mutatons n relatve to the normal state. Base on ths prncple, we can use segmentaton method to extract the entropy. Ths paper proposes a scheme for CB mechancal fault dagnoss wth equal-energy segment entropy. In the dagnoss method, accordng to the ntegral energy equvalent prncple, the standard envelope sgnal tme axs s segmented and the testng sgnal s segmented n the same way. In Fg. (2), Sg1 s normal envelope sgnal and Sg2 s the fault envelope sgnal. Mutaton events are delayed, Sg2 was

3 412 The Open Cybernetcs & Systemcs Journal Journal, 2014, Volume 8 Mnglang et al. Fg. (3). Standard sgnal of normal state. compared wth Sg1. Sg1 was segmented accordng to the energy equvalent prncple. Each of them has three segments: Seg1, Seg2, and Seg3. Because the Sg 2 s changed compared wth the Sg1, Seg1, Seg2, and Seg3 energes of the Sg2 compared wth the Seg1, Seg2, Seg3 energy of Sg1 are also changed, ndcatng that energy dstrbuton s changed. Therefore, we can transform the changes of Sg1 and Sg2 nto the change of energy dstrbute on unformty of each segment. 4. METHODOLOGY The steps of WP- feature entropy are [20, 21]: Step 1: Gettng rd of the vbraton sgnals nose usng soft threshold. Vbraton sgnals were decomposed at nth layer, radx wavelet selected db10, and sgnals n 2 n nodes at the nth layer were reconstructed; Step 2: Extract envelope energy of the reconsttuted sgnals obtaned n Step 1 respectvely wth Hlbert transform. Step 3: The envelope sgnal of each node was dvded nto M parts n accordance wth the prncple of equal energy along the tme axs and the pecewse pont n tme was extracted. Step 4: A testng sgnal was processed accordng to Step 1 and Step 2. Then the extracted envelope sgnal was dvded nto L parts accordng to the obtaned pecewse ponts of normal sgnal, and the energy of each segment was calculated accordng to Eq. (3). t b Q k () = f (x) 2 dx (3) t a = 1,2,,l, k = 1,2,,n. t a and t b are start pont and end pont of Segment I. Step 5: Correspondng pecewse energy s normalzed as Eq. (4): k () = l =1 Q k () Q k () The characterstcs entropy of the sgnal xt () s [20, 22]: l H k = k ()lg k () (5) =1 (4) Step 6: Wavelet Packet - characterstc entropy vector were defned as: T = [H 0, H 1, H 2...H 2 n 1 ] (6) Partton number l s related to complexty of sgnal, f more vbraton events occur n the vbraton sgnal extracton, the value of l s large, otherwse the value of l s small. The n value dstrbuton range sze reflects the characterstc frequency, whch s the sze of the sgnal frequency resoluton.when the method of Wavelet Packet-entropy s used n fault detecton, t s assumed that the normal state sgnal s unformly dstrbuted and that the testng sgnal dstrbuton under fault condton s not unform. The entropy s a measure of sgnal heterogenety degree. Therefore, we can use WP-entropy to detect the devaton degree of the fault state [23, 24]. 5. RESEARCH DESIGN 5.1. Normal Sgnal Processng Fg. (3) shows the normal standard sgnal of a vacuum crcut breaker. The sgnal was processed accordng to the Wavelet Packet - entropy. Accordng to prevous crcut breaker vbraton sgnal processng method [22], we selected the followng parameters: n=3; m=15; 8 node reconstructon sgnals. The energy fragments of 15 equal tme scales were shown n Table 1. The method s analyzed by smulatng the frequency-varaton sgnal Fg. (3) Frequency Varatons The normal sgnal shown n Fg. (3), and was added wth random nose to obtan 5 analog sgnals. As shown n Fg. (4), nose attenuaton starts from 0.8mv and the hghest frequency s attenuated from 4 khz ampltude wthn 40 ms. Et1 s the orgnal vbraton sgnal. Ef1 sgnal was the nterfered at 50 ms to form Ef2 sgnal; Ef2 sgnal was the nterfered at 100 ms to form Ef3 sgnal; Ef4, Ef5, Ef6, and so forth. The seres of sgnal frequency was changed gradually and the vbraton mpact tme of each event was not changed. Accordng to the feature entropy extracton Steps 4 to 6, we respectvely processed each sgnal n Fg. (4). Wavelet packet feature entropy vector In Table 2. We can see that the entropy of low frequency segment ncreases slghtly and that the entropy of the hgh frequency segment s less changed.

4 A New Fault Dagnoss Method for Hgh Voltage Crcut Breakers The Open Cybernetcs & Systemcs Journal Journal, 2014, Volume Table 1. Tme ponts of each equal-energy segment (Unt: ms). [3,0] [3,1] [3,2] [3,3] [3,4] [3,5] [3,6] [3,7] Fg. (4). Smulated sgnals of frequency-varaton.

5 414 The Open Cybernetcs & Systemcs Journal Journal, 2014, Volume 8 Mnglang et al. Table 2. Testng entropy vectors of frequency-varaton. H 0 H 1 H 2 H 3 H 4 H 5 H 6 H 7 Ef Ef Ef Ef Ef Ef Fg. (5). Varaton curves of entropy-varaton. Table 3. Frequency-varaton eucldean dstance. T 2 T 3 T 4 T 5 T The curve of the entropy dfference between analog sgnal and the normal sgnal of each node are shown n Fg. (5). In the curve, Node 0 and Node 1 showed sgnfcant dfference and other nodes showed no sgnfcant dfference. The dfference among dfference nodes can be nterpreted as follows. Node 0 ndcate the entropy of the frequency components wthn the frequency ranges of [0~3kHz], and Node1 corresponds [3~6 khz], frequency components of that attenuated 4 khz nterference are also dstrbuted n the same two frequency ranges. The smulaton results are fully consstent wth the results. Eucldean dstance also reflected effects on frequency change of characterstcs of entropy n Table Applcatons A vacuum crcut breaker workng wthout load was used for test. Frstly, we selected the nsuffcent lubrcaton crcut breaker to test tme-delay fault. Then, A phase base screw was loosed to test ncorrect fault under the condton of loose screw. Under each condton, crcut breaker was contnuously operated for 3 tmes to obtan 6 groups of vbraton sgnal of Phase A. Then, plus the normal workng state of crcut breaker, we obtaned 7 groups of vbraton sgnals. Accordng to prevous vbraton sgnal acquston method and envronment [21-24], as shown n Fg. (6), the recorded sgnals from top to bottom are respectvely standard sgnal, sgnals under the condton of loose screw (3 sgnals for Fault I,), and sgnals under the condton of tme-delay fault (3 sgnals for Fault II). We processed sgnals shown n Fg. (6) accordng to above sx steps n Secton 4 and tme scale s shown n Table 1. The characterstc entropy vector of each sgnal s shown n Table 4. Through the analyss of the vectors, t s found that after the segmentaton wth equal-energy dstrbuton

6 A New Fault Dagnoss Method for Hgh Voltage Crcut Breakers The Open Cybernetcs & Systemcs Journal Journal, 2014, Volume Fg. (6). Orgnal sgnal of A. Table 4. Vectors of characterstc entropy. The Type of Fault H 0 H 1 H 2 H 3 H 4 H 5 H 6 H 7 Normal Sgnal Fault I Fault I Fault I Fault II Fault II Fault II model of normal condton sgnals, the energy dstrbuton unformty of the fault sgnal s destroyed. Therefore, the entropy s changed. The change s related to the fault severty. The each element of entropy vector obtaned wth fault sgnals s generally smaller than that obtaned wth normal sgnals and the element dstrbuton s scattered. It s ndcated that each frequency band energy dstrbuton s obvously dsturbed under the fault state and can be used as the judgment crteron of crcut breaker fault. Moreover, the entropy of sgnals obtaned under screw loosenng fault s generally less than that obtaned under the tme delay fault. As shown n Fg. (7), n the RBF neural network structure. Snce each wavelet packet characterstc entropy s

7 416 The Open Cybernetcs & Systemcs Journal Journal, 2014, Volume 8 Mnglang et al. Fg. (7). Structure of REF neural network. Table 5. Testng results of REF neural network. Normal Sgnal Fault I sg 1 Fault I sg 2 Fault I sg 3 Fault II sg 1 Fault II sg 2 Fault II sg 3 Outputs y y 2 y an 8 dmensonal vector, so RBF neural network nput layer has 8 nodes. There were three knds states correspondng to output, two faults, and a normal sgnal, hence, output layer has 3 neurons. The hdden layer s created by the Newbe functon n Matlab [25]. Hdden layer nodes, through tral and error method, repeated comparson dagnostc output as a result, the fnal number of hdden layer nodes s 15. The network traned wth vectors shown n Table 4 gves the output results shown n Table 5. The expermental data shows that the RBF network desgn acheved better classfcaton results. Ths knd of method to extract the characterstc parameters can be used to accurately dstngush between the all knds of common faults. CONCLUSION Instances of ths paper results show that the characterstcs entropy and RBF neural network can better accomplsh fault dagnoss. Moreover, we analyzed two fault condtons of the crcut breaker tself (loose screw and tme delay) wth the method. At the same tme, the smulaton results also ndcated that the method could be used for soft fault dagnoss of other equpment based on sgnal processng. However, neural network tranng requres a lot of samples and the crcut breaker acton very lttle, so we need to contnue to mprove the accuracy of neural network n few samples. ABOUT THE AUTHORS Frst Author Lu Mnglang, Assocate professor of Helongjang Unversty. The author s major s Intellgent Detecton and Fault Dagnoss. Second Author Wang Keq, professor of Northeast Forestry Unversty. The author s major s Mechatronc Engneerng. Thrd Author Sun Lajun, Assocate professor of Helongjang Unversty. The author s major s Agrculture Detecton. Fourth Author Zhang Janfeng, The master of Helongjang Unversty. The author s major s Fault Dagnoss. CONFLICT OF INTEREST The author confrms that ths artcle content has no conflct of nterest. ACKNOWLEDGEMENTS Ths work s supported by natural scence foundaton of Helongjang provnce of Chna (E201233). REFERENCES [1] X. Ln, Y. L, Y. Ma, G. Wu, Dynamc characterstcs analyss on novel motor actuator of hgh voltage crcut breaker, Electrc Machnes and Control, vol. 13, no. 2, pp , [2] A. Polycarpou, A. Soom, V. Swarnakar, R. A. Valtn, R. Acharya, V. Demjanenko, M. Soumekh, D. Benenson, J. W. Porter, Event tmng and shape analyss of vbraton bursts from power crcut breakers, IEEE Transactons on Power Delvery, vol. 11, no. 2, pp , 1996 [3] J. Huang, X. G. Hu, Y. N. Gong, F. Yang, Machnery fault dagnoss expert system for hgh voltage crcut breaker, Electrc Machnes and Control, vol. 15, no. 10, pp , [4] Q. Ma, M. Z. Rong, S. L. Ja, Study of swtchng synchronzaton of hgh voltage breakers based on the wavelet packets extracton

8 A New Fault Dagnoss Method for Hgh Voltage Crcut Breakers The Open Cybernetcs & Systemcs Journal Journal, 2014, Volume algorthm and short tme analyss method, In: Proceedngs of CSEE, vol. 25, no. 13, pp , [5] C. Lu, X.G. Hu. A new method of fault dagnoss for hgh-voltage crcut-breakers based on Hlbert-Huang transform, In: 2 nd IEEE Conference on Industral Electroncs and Applcaton Chna, IEEE, pp , [6] X. G. Hu, J. M. Da, Y. C. J, W. B. Yu, The fault dagnoss of hgh voltage breakers based on wavelet sngularty detecton, Proceedngs of the CSEE, vol. 21, no.5, pp , [7] J. L, New sgnal process scheme based on wavelet for onlne montorng of hgh voltage crcut breaker, Journal of Bejng Insttute of Machnery, vol. 22, no. 1, pp , [8] Y. Dong, D.M. Xao, Applcaton of dual spectrum analyss to mechancal vbraton sgnal process of hgh voltage crcut breakers based on WP-AR model, Hgh Voltage Apparatus, vol. 45, no. 4, pp , [9] G. Chang, Y. Wang, W. Wang, Mechancal fault dagnoss of hgh voltage crcut breakers utlzng zero-phase flter tme-frequency entropy of vbraton sgnal, In: Proceedngs of the CSEE, vol. 33, no. 3, pp , [10] Y. L. L, R. P. Shao, J. M. Cao, A new and effectve method of gear fault dagnoss usng wavelet packet transform combned wth support vector machne, Journal of Northwestern Polytechncal Unversty, vol. 28, no. 4, pp , [11] X. G. Hu, J. Wang, Y. J, The applcaton of the wavelet analyss of analytc sgnals n mechancal fault dagnoss of crcut breakers, In: IEEE Power Engneerng Socety General Meetng, 4. Canada: IEEE/PES 2003, pp , [12] M. Runde, T. Aurud, L. E. Lundgaard, G. E. Ottesen, K. Faugstad, Acoustc dagnoss of hgh voltage crcut-breakers, IEEE Transactons on Power Delvery, vol. 7, no. 3, [13] Z. Y. He, Y. M Ca, Q. Q. Qan, A study of wavelet entropy theory and ts applcaton n electrc power system fault detecton, In: Proceedng of the CSEE, vol. 25, no. 5, pp , [14] Z. X. Cheng, Wavelet Analyss Algorthms and Applcaton, X an Jaotong Unversty Press, [15] L. J. Sun, M. L. Lu, J. J. Zhen, G. Ye, A new fault dagnoss method for HV crcut breakers based on wavelet packet-neural network, In: 6 th IEEE Conference Industral Electroncs Applcatons, 2011, pp [16] Shannon, A mathematcal theory of communcaton, Bell System Techncal Journal, 1948, vol. 27, no. 1-2, pp [17] R. Rakoczy, M. Kordas, G. Story, M. Konopack, The characterzaton of the resdence tme dstrbuton n a magnetc mxer by means of the nformaton entropy, Chem. Eng. Sc., vol, 105, no. 2, pp , [18] H. Z. Su, J. Hu, Z. P. Wen, Structure analyss for concrete-faced rockfll dams based on nformaton entropy theory and fnte element method, Int. J. Num. Anal. Meth. Geomech., vol. 36, no. 8, pp , [19] Y. L. L, R. P. Shao, J. M. Cao, A new and effectve method of gear fault dagnoss usng wavelet packet transform combned wth support vector machne, J. Northwestern Polytech. Unv., vol. 28, no. 4, pp , [20] L. J. Sun, X. G. Hu, Y. C. J, A new method of fault dagnoss for hgh voltage crcut breakers based on vbraton sgnals, In: Proceedngs CSEE, vol. 26, no. 6, pp , [21] L.J. Sun, Tme-varaton and frequency-varaton analyss of wavelet packet-characterstc entropy for vbraton sgnals, Hgh Voltage Engneerng, vol. 8, no. 8, pp , [22] J. C. Ma, J. J. Ye, Aero-engne faults dagnoss based on wavelet packet analyss, Computer Smulaton, vol. 27, no. 2, pp , 2010 [23] M. L. Lu, L. J. Sun, J. J. Zhen, Fault dagnoss of hgh voltage crcut breaker based on multple entropy strps method, In: 6 th IEEE Conference on Industral Electroncs Applcatons 2011, pp [24] L. J. Sun, X. G. Hu, Y. C. J, Fault dagnoss for HV crcut breakers wth characterstc entropy of wavelet packet, Automat. Elect. Power Syst., vol. 26, no. 8, pp , [25] X. B. Zhang, W. Tan, Y. Y. Hou, Quantty test of SteelW re - rope LF damage base on RBF neural network and MATLAB realzaton, Coal Mne Mach., vol. 30, no. 3, pp , Receved: October 16, 2014 Revsed: December 23, 2014 Accepted: December 31, 2014 Mnglang et al.; Lcensee Bentham Open. Ths s an open access artcle lcensed under the terms of the Creatve Commons Attrbuton Non-Commercal Lcense ( whch permts unrestrcted, non-commercal use, dstrbuton and reproducton n any medum, provded the work s properly cted.