Journal of Scientific & Industrial Research

Vol. 62, October 2003, pp 1008-1014

Implementation of Labview based Vibration Monitoring System for Turbine Generator Set in Thermal Power Plants

S S Thakur*, Anil Sonkusare, Pradeep Kumar and A D Kaul

Central Scientifi c Instruments Organization, Chandigarh 160030

Received: 28 Mard I 2003; accepted : 27 June 2003

The paper describes a data acqui sition system using Labview so ftware for acqui ring data from vari ous transducers namely accelerometers, velocity pickups, proximity probes and other sensors mounted at vari ous locati ons of a TG (Turbine Generator) 210 MW set, in thermal power plants. Data from transducers can be acquired on diffe rent channels and various parameters can be set for each channel like channel number, channel name, sensitivity units and scan rate. Delay between acquisitions can also be set. Data can be stored in the programmable tiles , containing complete header in fo rmati on . Data can also be acq uired continuously. Powerful and convenient data acqui sition, storage and retri eval mechani sms ensure that desired data will be available whenever required.

Keywords: Data acquisition system, Transducers, TG set, Thermal power plants, Labview so ft ware

1 Introduction

Maintenance strategies can be divided into three main categories, i.e. , corrective (repair after event) , time scheduled (hours run foll owing recom­mendations and experience), and predictive or condition based (scheduled according to actual conditions as monitored).

All have the ir place in plants, but where the stakes are high like, power plants, running of air crafts, etc., predictive maintenance through monitoring the condition of the machinery becomes essential for numerous reasons as economy demands that higher pl ant availability including safety is achieved in the most effective manner. Rotating machines are highly complex dynamic systems, very sensiti ve to slight changes in operating conditions. The condition of tihe machine is reflected by parameters such as frequency of vibration signal s, direction of predominant amplitude, location of amplitude, influence of axi al shift, loading pressure and temperature. As an example, if the rotor passes particles in the flow medium, its unbalance increases which in turn shows larger vibratory amplitude of the shaft at the running frequencies.

Vibrationl.2 analysis is widely accepted as a tool to monitor the operating conditions of a machine as it

*Author fo r correspondence

is nondestructi ve, re liable, and permj ts continuous monitoring. Often, a fault developed in a machine shows an increase in vibration ampl itude associated with fault. Increasing vibration amplitude is an indication of a deteriorating machine condition and rate of increase is proporti onal to the degree of damage.

Therefore, it is possible to predict the trend of deteri oration of machine by monitori ng the amplitude of its fault related vibration features . Condition monitoring protects the machine from unexpected sudden failure and also provides capability for condition analysis and diagnos is. The obj ective of our program is to ensure higher pl ant ava ilability and avoid costs due to fa ilure .

2 Data Acquisition Hardware

Data acquisiti on hard ware mainly consists of transducers, s ignal conditi oning, data acquisition card (DAQ card) and personal computer. Transducers change physical phenomena into e lectrical signal s. Signal conditioning3

.4 is done as transducer output needs to be conditioned, i.e., amplify low level s ignals, attenuate hi gh level signa ls, iso lati on, and filtering to provide s ignals suitable for the Data Acqui sition Sys tem5

The DAQ card be ing used is AT - MIO - 64E - 3 (NI), which is a 12 bit, 64 channel (SE) card having in put range of ±I OV and sampling rate of sao KS/s.

THAKUR et al.: LABVIEW BASED VIBRATION MONITORING SYSTEM 1009

After conditioning signals are connected to DAQ card, using a connector block. Driver software of the card facilitates direct programming of the DAQ card. These E-series boards feature analog and digital triggering capability, as well as two 12 bit analog outputs, 20 MHz counter timers and 8 digital I/O channels. Data size is limited by the PC data storage media such as hard disk, but not limited by the RAM drive size used as temporary buffer.

3 Data Acquisition Software

The developed software6 comprises following modules:

(I) Data acquisition and processing.

(2) Applying FFf on incoming signal.

(3) File writing and data logging for trending.

(4) Software for communication.

(5) Error handling.

3.1 Data Acquisition and Processing

Signals from various transducers after conditioning are being acquired at a rate of 5000 samples/s using an AT - MIO - 64E - 3 (NI) DAQ card. Signals are connected as single ended inputs referenced to common ground point. The set up and front panel of data acquisition system is shown in Figure I and 2. This software acquires data continuously for 25 channels out of which 17 channels are for vibration signals namely, absolute bearing vibrations at HPT (Front), HPT (Rear), IPT (Rear), LPT (Rear), HPT (Rear) vertical, HPT (Rear) horizontal, HPT (Rear) vertical (High freq.), IPT (Rear) vertical (High freq.), Axial vibration at LPT (Rear), absolute bearing vibrations at GEN. (Front) vertical, GEN. (Front) horizontal, GEN (Rear) vertical, GEN (Rear) horizontal.

Remaining 8 channels are for process signals which have been tapped in parallel from existing indicators namely Load, Turbine speed, Mean steam temperature, Mean steam pressure, absolute shaft vibration at bearing number I, bearing number 2, bearing number 3 and bearing number 4 with provision for user selectable end time set by user.

Acquired data is in the form of 2-D array . 'Data is split into different I-D array and data of each column contains the data for each channel. For doing so, program calculates dimensions of array. Then indexing is done column-wise. First, it takes out the values of first channel, then second channel , etc. Thus, a 2-D array is converted into different J-D

array. Acquired data in volts (V) can be converted into desired units in the form:

X = Ax + B, where x is acquired data, A and B are coefficients to convert voltage data into engineering units, and X is data in engineering units .

3.2 AppLying FFT on Incoming Signal

As acquired signal7 comprises many frequencies, we apply FFT algorithm in order to obtain the frequency components present in the signal. The signal obtained from DAS program constitutes the time domain representation of the signal. This representation gives the amplitude of the signal at the instant of time during which it had been acquired . However, in this application, we want to know the frequency content of the signal rather than the amplitudes of individual signal. This representation of signal, in terms of its individual frequency components is known as frequency domain representation of the signal.

The algorithm used to transform samples of the data from time domain to frequency is known as the Discrete Fourier Transform (DFT).

DFT establishes the relationship between the samples of signal in time domain and their representation in the frequency domain. Suppose we have obtained N samples of a signal from DAQ program, if DFT is applied to these time domain representation signal, the result is also of the length N samples, but the information it contains is of frequency domain representation .

The relationship between the N samples in the time domain and N samples in frequency domain is explained below. If the signal is sampled at sampling rate of is, then the time interval between the samples (that is sampling interval) is /). t, where /). t = IIJs.

Both the time domain x and the frequency domain X have a total of N samples. Analogous to the time spacing of /).t between the samples of x in the time domain, one can have a frequency spacing of /).f = fslN = IIN/).t.

The sampled signals are denoted by x[i] , 0 ::; i ::; N-J (i.e., we have a total of N samples) ~here the discrete Fourier transform is given by,

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Xk = LXie-J2nikiN for k = 0, 1,2 ... , N-I is i=O

applied to these N samples, the resulting output (X [k], 0 ::; k ::; N-I) is the frequency domain representation of xU],

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Direct implementation of the DFT on N data samples requires approximately N2 complex operations and is a time consuming process. However, when the size of the sequence is a power of 2, N := 2m

for m = I, 2,3 . . .

One can implement the computation of the DFT wi th approx imately Nlog2 (N) operati ons. This makes the calculation of the OFT much faster, and these algorithms are referred as fast Fourier transforms (FFTs). Th e advantages of thi s FFT include speed and memory efficiency, because the VI can compute the FFT in place, i.e, no additional memory buffers are needed to compute the output.

3.3 File Writing and Data Logging for Trending

Acquired data is saved in tex t format in user specified filenames fo r individual channel. Two-line header information is written before the data value is written to the file. It contains date and time, channe l no., fil e name, scan rate, SI No. and sensitivity units. The date and time at which data is acquired is important is used by OLES for processing and analysis work. It can a lso save data in spreadsheet file format where data for a ll channe ls are present in the form of 2-D arrays. In the case of trending, time stamping has been done in front of every rms data acquired for the entire channe ls.

All these trend files are stored in a folder as C:\Backup2002\trend .x ls. In this software, provi sion is avai lab le as year changes or system time changes, program stores the trend data in a folder, according to current year, such as, C:\Backup2003\trend.xls. S imilarly , one can view the trend of frequency components of individual channel (i.e. vibration parameters) and are stored 111 a folder as C:\Backup2002\TrendB 1_ 45.xls and similar names for the channe ls confi:gured in the set up.

3.4 Software for Communication

Data Acquisition software is totally online and processing is done by Online Expert System (OLES). OAS acquires first set of data for 25 channels, di splays time plot and frequency plot fo r each channel and finally writes data fil es in a format required by OLES .

Both the computers are connected to each other through local area network (LAN), sharing the hard di sk, so that data transfer can be done. All data files are transferred from DAS to OLES and having a maximum data transfe r rate of 10/1 00 Mbps, while

retaining the CSMAICO Ethernet protoco l. The total size of one complete set of data files is 1.41 MB .

OLES does data processing and it takes approximately 3 min for processing. During these three minutes, DAS acquires data and di splay time and frequency plot and write data file fo r trending. After 3 min , agai n next set of data is acquired and whole process is repeated.

Since both the software are access ing same files and OLES takes the most recent data, there must be some communication between the two softwares so that at a time onl y one software accesses the files. As both softwares open and read status f i Ie, an error handler routine is app lied in both softwares. In case any of them tries to open the status fi le while other is accessing the fi le , program does not ha lt and handles the error.

Status File

To process thi s raw data as soon as it is acquired by the data acqui sition system a handshaking protocol is establ ished for thi s purpose. A fil e named 'status. txt' file is mainta ined in the F:\Olesdata directory.

Thi s file contain s a f lag (an integer) that indicates the current status of the communicati on between the computers that acqu ires the data (henceforth ca ll ed OAS PC) and the computer that processes this data (henceforth called OLES PC) .

For achieving thi s, it has an integer va lue, which can be:

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When DAS (OAS PC) completes acquiring of most of the data it writes zero (0) in the statu s file , which means that data is acquired and it is avai labl e in RAM and no data files have been written. After acquiring first set of data for 25 channe'ls, 25 data files are written in specified path in hard disk. After completion of writing 25 data files D AS writes one ( I) in the status file, which means data files are available for OLES to do processi ng. When OLES completes process ing of data it writes two (2) in the status fil e . DAS is reading the status file and on recei ving two (2) in the status fi Ie OAS starts acquiring new set of data.

In this software, there is provIsIon for Continuous Data Acquisition , displ ay time and fre-

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1014 J SCI IND RES VOL 62 OCTO BER 2003

quency plot, a larming limits as shown in setup, online checking if any s ignal crosses these alarming limits, and fil e writing without process ing. If any signal crosses these limit, ind icator glows, as shown in front panel, It means after doing one acquisition and writing one set of data files, program repeats the acqui sition and do fil e writing by appending data to the fil es with time stamping for trending.

3. 5 Error Handler

Error handler is a program, which handles ihe error without halting the program. File open function, gives value zero at one of its output terminal, if there is no error. At this output error code va lue is taken and if thi s value is zero, software continues to be in loop and tries to reopen the fil e without showing any message.

4 Offline Analysis of Trend Data

Thi s is bas ically used to see the trend of signal s of the last 24 h, 7 d, I month or as much acquired data, ava ilable in the backup. The display of trend data for vibration and process signals are shown in Figure 3. In the case of vi brati on parameters, limits has been set for indi vidual channe l as al lowable limit (Green indicator), tolerable limit (Blue indicator) and unacceptable limit (Orange indicator) in accordance with standard limits available and consultation with Indian Institute of Technology, Delhi . If any signal crosses the danger li mit its indicati on of fault in the TG set, and E xpert System should be consulted for prediction of poss ible fault.

S Results and Conclusions

Instrumentation a long with data acqui sition system as a stand-alone unit has been implemented at Unit No. I of Guru Gov ind Singh Super Thermal Power Pl ant, Ropar. Data is acquired , di splayed, FFf analys is is carried out , and is be ing analysed fo r poss ible faults, trending is be ing done . The

development of data acqlllSltl on system UStng Labview soft ware has resul ted in a more compact, re li able, and effic ient progra m fo r th is applicati on. The system is now be ing ex tens ive ly used to acquire data and for further process ing. The performance of the system is found to be sati sfactory.

Acknowledgements

The authors are grateful to Department of Sc ience and Techn ology (DST), New Delhi for fi nancial help. We are al so thankful to Guru Gobind Singh Super Thehnal Power Pl ant, Ropar for providing fac iliti es and fo r giving suggestions from time to time. The work done by Department of Mechanical Engineering, lIT, De lh i in preparing Online Ex pert System is gratefull y acknowledged .

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