The concept of the ultrasonic non-destructive assessment essentially applied in the failure analysis as well as quality assessment. The application has vital application in various industries such as bridge structures, microelectronic, manufacturing, aircraft structures as well as packaging. Preferably, it is important that ultrasonic NDE faces the challenge of been detected with the echoes. The recorded echoes tend to be random as well as interfere with the makeable elements and can even be contaminated by the overall noise. Therefore, there are various challenges in recording the backscattered echoes in the process. Conversely, the importance of recording the backscattered echoes cannot be underestimated since they have desired information. Some of the key information associated with the process include orientation, boundaries as well as defect sizes. Furthermore, the analogy of the ultrasonic processes often manifested in material characterization as well as in the overall structural health monitoring. In recent days, developers have come up with different designs and modifications for the algorithm signal processes (Iyer, Sinha, Tittmann and Pedrick 2012 p.135). The design includes both the nonlinear and the non-stationary ultrasonic signals behavior in line with the NDE application. Furthermore, there has been extensive research on different aspects in line with the ultrasonic signal processing. Some of the vital areas mainly discussed in the processes include chirplet signal decomposition, empirical mode decomposition, Hilbert-huang transform, Fractional Fourier transforms as well as active noise cancellation. Other than the benefits of developing algorithms in signal processing of ultrasonic in the industrial applications, there are also different problems which one is likely to encounter in the process. The key challenge is on the implementation bit of the algorithms in the hardware concept. Preferably, there is vast understanding that NDE requires numerous and in-depth fieldworks for one to be able to understand the NDR operators nature. Notably, ultrasonic processes have got wide range of applications and these often have immense advantages in long run.
Ultrasound inspection has paramount application in the detection of the elementary and internal discontinuities in various substances. The application is vital and it is applied for both components and equipment. There is wide application the pulse-echo and this is grounded on the fact that the application is simple. Preferably, pulse-echo test tend to have one transducer in the system. This is used for receiving as well as sending the ultrasonic waves. Also, the pulse-echo is used for checking for the dimensions as well as for verifying for the parametric location. Noise is an essential factor which one must consider in conducting the ultrasonic testing. The factor is an essential ingredient which not only affects the accuracy but also the reliability of measurements recorded. This is considered in both the acoustic and electronic devices. The element plays an essential role in dealing with computational intelligence as well as digital signal processing (Zhang, Yang and Fan 2010 p.529).
This thesis research aims at exploring the non-destructive evaluation using the concept of the ultrasonic signals as well as processing. Furthermore, the study also incorporates the utilization of the transforms and the signal features in the appraisal concept. In essence, this study mainly conducted in line with the yield detection and techniques. There is the application of the linear discriminant analysis or LDA which is referred for the study and the concept regards the overall performance of various classifiers mainly compared and examined in the process (Manjula, Vijayarekha and Venkatraman 2018 p.264).
In this section, there was an overall description of the system, it workability alongside the entities, the below figure gives an illustration of the system with a case study of a Ultrasonic NDE data system of acquisition (Schmerr 2016 p.13).
From the above diagram, we can get two subdivisions which help in explaining the overall data flow. These two divisions are data acquisition subsystem while the other is positioning subsystem. The acquisition subsystem is made up of different sections or units; these include digitizer unit oscilloscope, transducer, virtual instrument which is a program set and run in a computer and lastly the pulse transmitter or the receiver unit (Murta, Vieira, Santos and de Moura 2018 p.40). The other subsystem also includes other entities like step motor and motor controller. At times, another system of a similar nature is run and used commonly in collecting experimental data in the laboratories used to carry out research activities. An example of such programs includes C program or MATILAB. They are usually written to post the process of the data collected for advance processing of signal algorithms. Combining the two steps of signal processing and data acquisition always pose a major challenge thus to curb this; a specified system algorithm is designed carefully for use.
In this paper, a case study of the FPGA-based system is used. The outline of the system is as outlined in the figure below (Kim and Kwon 2015 p.3).
From the diagram, it is evident that the system incorporates collection of independent entities which work together and collectively for a common purpose. It has a touchscreen board, an FPGA board, an analog-to-digital board. In this research project, XUP Virtex 5 FPGA board development together with board of Genesys FPGA. These boards are used in order to debug and also assist in system implementation. The leading industrial company of FPGA known as Xilinx was responsible for the donation of these boards. Additionally, Xilinx gives a provision of professional software level packages through the program known as Xilinx University program. These soft-wares deal with simulation, design, synthesis alongside implementation. An example of boards of high-speed acquisition like MAX5874 and MAX1213N obtained from Maximum Integrated Inc. are always used and applied to convert analog data to digital data and also from digital to analog form. The conversion is always done at a speed of 100M samplers per second after being implemented. To display results from the conversion, a device LCD touchscreen of an Amulet STK is often used. On the Viretex 5 FPGA, a system which is embedded is designed to run and uses a 32-bit Microblaze processor which operates at a speed of 100 MHZ. The incoming data from ADC is also saved to the DDR memory on the mounted on the board. The input from the GUI which is displayed and runs on the screen is also accepted. The designing of the peripheral device drivers and VHDL uses C language and controlling components of lower-levels. The summary of the overall system function and ability alongside its entities are illustrated in the below diagram (Huggett, Dewan, Wahab, Okeil and Liao 2017 p.187).
Great care must be taken while mounting individual entities. All slots must be properly identified so as to avoid shorting the boards (Hu, Peng, Wang and Zhou 2018 p.92).
The flow of the design uses C and VHDL languages for implementation of hardware alongside software realization of the system. Xilinx 14.5 ISE suit is used as a design package including project navigator, software development kits (SDK) and embedded development kits (EDK). In addition, for trouble shooting design a debugging on-chip tool called Chipscope is used. The diagram below gives a description of the implementation of the software as far as the hardware and system realization is concerned. It shows the hierarchical order of the work flow from one point to the next (Gholizadeh 2016 p.50).
The FPGA board has distinct specifications which lists the conversion boards of digital to analog converter (DAC) and analog to digital data (ADC) board are listed below
Specifications of FPGA Board (Genesys Virtex-5 XC5VLX50T)
Specifications of DAC board (MAX5874 EVKIT)
Specifications of ADC board (MAX1213N EVKIT)
In the course of the research study, there are some key elements which are vital to the connections and general input layout. The daughter boards must be well connected in order to give a proper signal coordination. The main board links all of them together with FPGA and collectively the signals are transmitted. Much time is taken in finding connection faults. Some of the observations generated from this are:
The analog ground and the digital ground are to be separated for the better control of the noise
From FPGA to DAC and ADC daughter boards; the clock runs at 100 MHz thus the interface of high frequency noise deteriorates the signal. To solve this, RF SMA cables were used to direct connection of the clock reducing the noise level (Fang, Lin, Feng, Lu and Emms 2017 p.79).
Being that the output signals from the ADC are in the format of Low-variance differential signal, 24 signals are used to represent 12-bit data. VHDL codes are written to convert differential signal to single-ended signal when using the 12-bit data in the signal processing algorithm running on the embedded system. Being the first time to handle differential signal in practical design using VHDL, there is similar data conversion in the DAC part (Phillips, Duxbury, Huthwaite and Lowe 2018 p.32). The figure below gives an illustration of the output of differential clocks and single-end clock on an oscilloscope (Chen, Ma and Dong 2018 p.194).
A test is conducted to conclude acquisition of data system description. The graphs below give a description of analogies (Dolmatov, Salchak and Pinchuk 2017).
Touch-screen subsystem
The specification of the touch screen is listed below [9].
LCD touch screen (Amulet STK-480272C)
The figure below gives an outline of a communication protocol (Backe, Balle and Eifler 2015 p.93).
The processing of the signals on FPGA the split spectrum processing. The algorithm implementation has been initiated in C program. It was later tested in the laboratory of MATILAB after which implementation in SDK in C. The algorithm test revealed that it worked properly. It took 50second upwards to complete. The interface of the system is relatively slow with the system at attainable sampling rate. The issues arise from operations of the floating point. In a switch to a fixed-point logic, the process would be speeded up with the use of an existing FFT IP (Alobaidi, Alkuam, Al-Rizzo and Sandgren 2015 p.274).
The project plan for this project mainly outlined as indicated in the table below
Conclusion
In the research project, the evaluation of the ultrasonic data as well as acquisition in line with real time is appraised and the overall implementation documented. Preferably, there is wide application and utilization of the FPGAs and the adoption often regarded in the system extendibility. The system is set to run at about 100 MSPS for both the data acquisition process as well as the for the parametric LCD display. Moreover, it is expected that all the outlined specifications in the projects should be met by the end of this project. As far as the project and the overall research is concerned, it is important to have further studies on the ultrasonic efficiency and implementation. The platform has got mushrooming applications. Some of the key aspects include implementations of the flexibility applications. The applications in which the ultrasonic signals as well as processing are being applied include ECE areas, control alongside communication.
References
Alobaidi, W.M., Alkuam, E.A., Al-Rizzo, H.M. and Sandgren, E., 2015. Applications of ultrasonic techniques in oil and gas pipeline industries: a review. American Journal of Operations Research, 5(04), p.274.
Backe, D., Balle, F. and Eifler, D., 2015. Fatigue testing of CFRP in the Very High Cycle Fatigue (VHCF) regime at ultrasonic frequencies. Composites Science and Technology, 106, pp.93-99.
Chen, Y., Ma, H.W. and Dong, M., 2018. Automatic classification of welding defects from ultrasonic signals using an SVM-based RBF neural network approach. Insight-Non-Destructive Testing and Condition Monitoring, 60(4), pp.194-199.
Dolmatov, D.O., Salchak, Y.A. and Pinchuk, R., 2017. Frequency-domain imaging algorithm for ultrasonic testing by application of matrix phased arrays. In MATEC Web of Conferences. Vol. 102: Space Engineering.—Les Ulis, 2017.(Vol. 102, p. 1015). EDP Sciences.
Fang, Y., Lin, L., Feng, H., Lu, Z. and Emms, G.W., 2017. Review of the use of air-coupled ultrasonic technologies for nondestructive testing of wood and wood products. Computers and electronics in agriculture, 137, pp.79-87.
Gholizadeh, S., 2016. A review of non-destructive testing methods of composite materials. Procedia Structural Integrity, 1, pp.50-57.
Hu, H., Peng, G., Wang, X. and Zhou, Z., 2018. Weld defect classification using 1-D LBP feature extraction of ultrasonic signals. Nondestructive Testing and Evaluation, 33(1), pp.92-108.
Huggett, D.J., Dewan, M.W., Wahab, M.A., Okeil, A. and Liao, T.W., 2017. Phased array ultrasonic testing for post-weld and online detection of friction stir welding defects. Research in Nondestructive Evaluation, 28(4), pp.187-210.
Iyer, S., Sinha, S.K., Tittmann, B.R. and Pedrick, M.K., 2012. Ultrasonic signal processing methods for detection of defects in concrete pipes. Automation in Construction, 22, pp.135-148.
Jolly, M.R., Prabhakar, A., Sturzu, B., Hollstein, K., Singh, R., Thomas, S., Foote, P. and Shaw, A., 2015. Review of non-destructive testing (NDT) techniques and their applicability to thick walled composites. Procedia CIRP, 38, pp.129-136.
Kim, Y.Y. and Kwon, Y.E., 2015. Review of magnetostrictive patch transducers and applications in ultrasonic nondestructive testing of waveguides. Ultrasonics, 62, pp.3-19.
Manjula, K., Vijayarekha, K. and Venkatraman, B., 2018. Quality Enhancement of Ultrasonic TOFD Signals from Carbon Steel Weld Pad with Notches. Ultrasonics, 84, pp.264-271.
Murta, R.H., Vieira, F.D.A., Santos, V.O. and de Moura, E.P., 2018. Welding Defect Classification from Simulated Ultrasonic Signals. Journal of Nondestructive Evaluation, 37(3), p.40.
Phillips, R., Duxbury, D., Huthwaite, P. and Lowe, M., 2018. Simulating the ultrasonic scattering from complex surface-breaking defects with a three-dimensional hybrid model. NDT & E International, 97, pp.32-41.
Schmerr, L.W., 2016. An ultrasonic system. In Fundamentals of Ultrasonic Nondestructive Evaluation (pp. 1-13). Springer, Cham.
Zhang, Y., Yang, L. and Fan, J., 2010. Study on feature extraction and classification of ultrasonic flaw signals. WSEAS Transactions on Mathmatics, 9(7), pp.529-538.
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