Signal Processing System for Guided Wave-Based ...

Signal Processing System for Guided WaveBased SHM Technique P. MALINOWSKI, T. WANDOWSKI, W. OSTACHOWICZ, T. LUBA, G. BOROWIK, M. RAWSKI and P. TOMASZEWSKI

ABSTRACT Reported research is focused on practical realization of guided wave-based SHM. Miniaturization of a SHM system could be very interesting in the scope of real life application. Embedded solution allow to minimize the dimensions of the whole system replacing a PC computer for signal processing. In this research damage localization system was developed. Damage localization process is based on elastic wave propagation method. Embedded system was realized on Field Programmable Gate Array FPGA in which system on programmable chip (SoPC) was implemented. Damage localization algorithm was coded in C++ and implemented in this system. Elastic waves were generated and received using dedicated device. Gathered signals representing elastic waves propagating in structures were sent to embedded damage localization system in order to extract damage location. The aim of developed damage localization algorithm is to create colour map that indicates places of elastic waves reflections. Wave reflections are caused by all kind of discontinuities existing in the monitored structures like: boundaries, transducers and most important – damage. In the first approach this algorithm was coded in MATLAB® environment. This software allow to very fast coding of developed algorithms because of large number of functions and libraries included in MATLAB®. The huge disadvantage of this environment is the long time of calculation if we compare it with the code developed in C++. Second thing is a price connected with MATLAB® purchase. In this purpose MATLAB® script code was converted to C++ code with graphic user interface GUI working under the PC with Windows operating system in order to verify the results. In next step C++ software was developed in order to embedded it in post processing unit. Thanks to this the result of damage localisation is displayed on the LCD display of the system. The reported research led to development of an embedded system for signal processing in SHM applications. P. Malinowski, T. Wandowski, W. Ostachowicz, Institute of Fluid-Flow Machinery, Polish Academy of Sciences, Fiszera 14 Street, 80-231, Gdansk, Poland W. Ostachowicz, Warsaw University of Technology, Faculty of Automotive and Construction Machinery, 84 Narbutta St., 02-524 Warsaw, Poland T. Luba, G. Borowik, M. Rawski, P. Tomaszewski, Warsaw University of Technology, Faculty of Electronics and Information Technology, 15/19 Nowowiejska St., 00-665 Warsaw, Poland

INTRODUCTION The research towards creating a Structural Health Monitoring (SHM) systems is becoming more and more popular due to numerous possible advantages of SHM applications. SHM system can significantly increase the safety of various structures due to the fact that diagnostic process of structure can be conducted in real time during its normal operations. Moreover SHM system allows to reduce structure operation costs which are directly linked to expensive application of classic non-destructive testing methods. One of the SHM technique being constantly under development is based on phenomena related to elastic wave propagation [1,2,3].. These waves can be relatively easily excited and registered by piezoelectric transducers. The concept of such system can be visualized as presented in Fig 1.

Figure 1. The concept of structural health monitoring system divided into subsystems. This paper deals with the signal processing and visualization subsystems.

Embedded SHM systems utilizing elastic wave propagation phenomenon for nondestructive structure evaluation were presented in [4,5]. In the first paper [4] some preliminary test of elastic wave based damage characterization for real part of aircraft in the form of wing are conducted. In order to characterize the damage Reconstruction Algorithm for Probabilistic Inspection of Defects called RAPID was used. In the second paper [5] very interesting electronic system for guided wave generation and sensing was developed based on microcontroller with wireless power transmission. In [6] also microcontroller was used as well as a wireless sensor network. Developed sensor nodes performed analog preprocessing of acoustic signals, its digitization, data reduction and network communication. Main component was microcontroller ARM Cortex-M3 manufactured by STMicroelectronics. Each node from the sensor network can be used for Lamb wave excitation by an arbitrary waveform generator.. In another approach proposed in [7] optical fibers both for data communication as well as for the power supply for SHM system dedicated for wind turbine blade were utilized. SHM system was based on acoustic emission as well as acousto-ultrasonic techniques. The optical power supply was realized based on laser source, an optical fiber for the energy transfer, an optical receiver and a communication fiber with receiver and transmitter. In [8] connection of FPGA and 8-bit microcontroller is presented. This approach is called dual-controller architecture. Application of FPGA allow to significantly reduce electrical power consumption. Proposed SHM system also include signal processing

and wireless transmission modules. Signal processing allow to extract the coordinates of damage. In [9] real time SHM system for pipelines based on SMART Layers was presented. Proposed system was called Real-time Active Pipeline Integrity Detection. Proposed systems consisted of sensor network, portable electronic hardware and diagnostic software. In [10] prototype of a filament wound composite bottle with embedded SMART Layers was developed and manufactured. In [11] custom designed multiplexing unit for phased array system is presented. Whole system consists of PC computer with LabView and MATLAB® software, arbitrary signal generator, acquisition card and multiplexing unit. In [12] embedded phased array system called PAMELA III (Phased Array Monitoring for Enhanced Life Assessment) was presented. This equipment is capable of generating excitation signals to be applied to an array of integrated piezoelectric Phased Array (PhA) transducers placed on the interrogated structure, registering the response signals, and performing the signal processing in order to obtain SHM maps. In research presented in this paper authors focused on embedded subsystem for damage localization and visualization of results. Proposed subsystem was realized on FPGA with implemented system on programmable chip (SoPC). System on programmable chip includes damage localization software. Such a approach using SoPC system implemented in FPGA is new in the field of SHM systems for damage localization based on elastic wave propagation method. From the literature review it is evident that many embedded solutions are based on microcontrollers like for example ATMEGA128. The main disadvantage of such approach is that microcontrollers can be simply reprogrammed during the modification and development of new version of SHM system however internal architecture of microcontroller is unchangeable. Approach based on FPGA with internally implemented microprocessor allow easily to reconfigure the architecture of this microprocessor or even number of microprocessors. The only limitation is amount of FPGA resources like logic gates and RAM blocks. NUMERICAL ALGORITHM In the reported investigation a numerical algorithm, previously developed by the authors [13], was implemented in the FPGA-based signal processing subsystem. The main aim of damage localization algorithm is to post process the elastic wave signals in order to indicate the places in the specimen where elastic wave reflections occur. In this purpose damage maps that indicate places of elastic waves reflections are created. Wave reflections are caused by all sorts of discontinuities existing in the monitored structures like: boundaries, transducers and most important – damage. Damage localization algorithm was prepared in MATLAB® environment. In the next step C language code was prepared in such a way that it was possible to use this software in embedded solution of SHM signal processing subsystem. In order to create damage map rectangular time window is utilized to cut portions of registered signals. Length of time window is equal to the length of excitation signal. For each portion of signal taken from the signal for particular time instant Fast Fourier Transform (FFT) is calculated and amplitude of carrier frequency related to the excitation signal play a role of damage indicator. Time domain of signals is converted to spatial domain of interrogated structure using velocity of anti-symmetric Lamb wave mode propagation. Damage map is plot

based on the extracted damage indexes correlated with coordinates assigned to inspected region. Results of damage localization is presented in as a colour map. This color map presents places of elastic wave reflections from boundaries and wave reflections between traducers in array. More details about this algorithm can be found in [13]. SIGNAL PROCESSING SYSTEM Elastic waves were excited and sensed using electronic equipment at the laboratory of the Department of Mechanics of Intelligent Structures (Institute of FluidFlow Machinery, Polish Academy of Sciences) . The presented research is focused on signal processing systems and the signals measured by mentioned excitations/sensing system were processed by the developed signal processing system. Developed subsystem was based on FPGA (Field Programmable Gate Array). Because at this moment two developed systems (elastic wave generation and acquisition subsystem and signal processing subsystem) do not cooperate, received signals are sent from PC computer to signal processing unit. In the future two systems will be connected together and whole embedded system will not need a PC computer. The second aim of the research presented here was to investigate possibility of FPGA application for elastic wave signals processing in SHM systems. FPGA, in comparison to very popular microcontrollers, allow to create more elastic systems that can be simply reconfigured. It means that internal architecture of microprocessor is only limited by the resources of CLB in the FPGA. It is possible to use arbitrary number of components in the microprocessor architecture e.g. memory controllers, communication interfaces, DMA channels and so on. In the case of very popular microcontrollers its internal structure is fixed. The FPGA configuration is generally based on a hardware description language which allow to implement any logical function. The FPGA is a integrated circuit that can be customized during the configuration process. FPGA contains some programmable logic components very often called logic blocks or configurable logic blocks CLB and hierarchy of reconfigurable interconnects. Such a architecture allow to connect the blocks together in order to realize complex function. FPGA can be equipped with large number of simple logic blocks or small number of advanced logic blocks. Very interesting is the possibility of implementation of microprocessor structure in the FPGA device. In the structure of FPGA many microprocessors can be implemented that will work in parallel. Ability of reconfiguration at any time make FPGA devices very attractive from the economic point of view. Prototype of embedded signal processing subsystem was developed based on evaluation board DE2-70 produced by Altera and 4.3” 800x480 LCD Panel produced by Terasic Technologies. Evaluation board was equipped with FPGA EP2C70 Cyclone II device, 32 MB SDRAM memory, RS-232 transceiver and many others devices. Signal processing subsystem is based on system on programmable chip SoPC that was embedded into the FPGA structure. SoPC is a microprocessor based system developed in the hardware description language in this case VHDL (Very High Speed Integrated Circuits Hardware Description Language). Programming process of developed microprocessor (SoPC) is realized using high level programming language C. The important advantage of SoPC system is possibility of full reconfiguration.

Moreover so created processor can be simply equipped with additional custom defined instructions. Result presented in this paper was based on SoPC system consists of one 32 bit CPU (central processor unit) with frequency 100 MHz based on Altera NIOS II, JTAG–UART (for upload configuration files from PC to FPGA), UART (for communication PC to FPGA – download input data from PC and upload results to PC), SDRAM memory controller, video memory controller (for LCD panel). In SoPC system damage localization software was implemented. The aim of SoPC system is to download input data from PC computer, signal post processing (damage localization) and presentation of results in the form of damage map on LCD panel. The input data consists of piezoelectric transducers coordinates, signals registered by transducers, signal sampling frequency, guided wave group velocity, number of transducers, number of excitation sine cycles. Output data is in the form of damage maps presented in the color graphic LCD and also as matrix of numeric values that is sent to the PC.

Figure 2. The damage localisation result obtained with the developed system for linear array and one simulated damage(additional mass), 250 kHz excitation

RESULTS The developed signal processing subsystem was tested on the elastic wave propagation signals taken from panel with dimensions 1m x 1m x 0.001 m made out of aluminum alloy. Three excitation signals were tested, namely 220, 250 and 300 kHz. The excitation signal was in the form of tone burst signal with 5 cycles. Elastic waves were excited and sensed using Noliac CMAP06 transducers arranged in network consisting of nine transducer. In the research presented in this paper only A0 mode was utilized for damage localization purpose. Each transducer work as exciter and sensor of elastic waves, however not simultaneously. Excitation was applied

sequentially to each transducer. Two configurations of transducer network were tested linear array and cross array. In the both cases transducer array were located at the middle of the panel surface. Four damage scenarios were investigated: 1. 2. 3. 4.

One defect simulated as additional mass (1.5 g, position: 90⁰) One defects simulated as cut (0.5 mm-deep, 10 mm-long, position: 135⁰) One defect simulated as additional mass (1.5 g, position: 0⁰) Three defects simulated as cut (0.5 mm-deep, 10 mm-long, position: 135⁰), hole (diameter: 2.5 mm, position: 90⁰), through thickness cut (10 mm-long, position: 175⁰) Results corresponding to the investigated scenarios are depicted in Fig. 2-5, respectively. Due to the properties of applied numerical algorithm the results for linear array are symmetric in relation to axis on which the piezoelectric transducers lay. Results are presented as damage map shown on LCD screen of embedded damage localization subsystem. It should be underlined that parts of signals related to the wave reflections between transducers and to wave reflections from panel boundary were rejected from signal processing.

Figure 3. The damage localisation result obtained with the developed system for linear array and one simulated damage (cut), 220 kHz excitation

In the case of second damage scenario (Fig. 3) On can notice two indication on the damage map despite the fact there was only on cut. The indication closer to the array (red area) is related to the faster S0 wave that was amplified in this region by the signal processing algorithm.

Figure 4. The damage localisation result obtained with the developed system for cross array and one simulated damage (additional mass), 250 kHz excitation

Figure 5. The damage localisation result obtained with the developed system for cross array and three simulated damage (cut, hole and through thickness cut), 300 kHz excitation

CONCLUSIONS In this paper results of development of embedded signal processing subsystem for SHM based on FPGA were presented. By using the FPGA the software and structure of whole subsystem can be easily updated. Experimental verification shown that

developed damage localization algorithm as well as whole embedded system works correctly. In future research the focus will be on the development of multiple CPU units in the subsystem and application of parallel computing. Further investigations related to the connection of already developed subsystem for elastic wave generation and sensing with embedded signal processing subsystem are needed. In the final version standalone SHM system that do not need a PC computer is planned to be realized. ACKNOWLEDGEMENTS The authors acknowledge the support provided by project “Structural Health Monitoring System Based on Lamb Wave Propagation Analysis” WNDPOIG.01.03.01-22-078/09. Project is co-financed by the European Regional Development Fund under the Innovative Economy Operational Programme. Tomasz Wandowski and Pawel Malinowski acknowledge also the support provided by projects IUVENTUS Plus No. IP2011 058971 and No. IP2011 033071 founded by Ministry of Science and Higher Education. REFERENCES 1. Giurgiutiu, V. 2008. Structural Health Monitoring with piezoelectric wafer active sensors. Elsevier. 2. Sohn, H, D. Dutta, J.Y. Yang, H.J. Park, M. De Simio, S. Olson and E. Swenson. 2011. “Delamination detection in composites through guided wave field image processing”, Composites Science and Technology, 71: 1250–1256. 3. Chakraborty, N., V.T. Rathod, D.R. Mahapatra and G. Gopalakrishnan. 2012. “Guided wave based detection of damage in honeycomb core sandwich structures”, NDT&E International, 49: 27–33. 4. Zhao, X., H. Gao, G. Zhang, B. Ayhan, F. Yan, C. Kwan and J.L. Rose. 2007. “Active health monitoring of an aircraft wing with embedded piezoelectric sensor/actuator network: I. Defect detection, localization and growth monitoring”, Smart Mater. Struct., 16: 1208–1217. 5. Zhao, X., T. Qian, G. Mei, C. Kwan, R. Zane, C. Walsh, T. Paing and Z. Popovic. 2007. “Active health monitoring of an aircraft wing with an embedded piezoelectric sensor/actuator network: II. Wireless approaches”, Smart Mater. Struct., 16: 1218–1225. 6. Lieske, U., A. Dietrich, L. Schubert and B. Frankenstein.2012. “Wireless System for Structural Health Monitoring Based on Lamb Waves”, Proc. of the 6th European Workshop on Structural Health Monitoring, 1: 573–579. 7. Frankenstein, B., D. Fischer, B. Weihnacht and R. Rieske. 2012. “Lightning Safe Rotor Blade Monitoring Using an Optical Power Supply for Ultrasonic Techniques”, Proc. of the 6th European Workshop on Structural Health Monitoring, 1: 552-560. 8. Liu, L., F.G. Yuan. 2008. “Active damage localization for plate-like structures using wireless sensors and a distributed algorithm”, Smart Mater. Struct., 17: 055022 (12pp). 9. Qing, X.P., S. Beard, S.B. Shen, S. Banerjee, I. Bradley, M.M. Salama and F.-K. Chang. 2009. “Development of a real-time active pipeline integrity detection system”, Smart Mater. Struct., 18: 115010 (10pp). 10. Qing, X. P., S.J. Beard, A. Kumar, H.-L. Chan and R. Ikegami. 2006. “Advances in the development of built-in diagnostic system for filament wound composite structures”, Composites Science and Technology, 66: 1694–1702. 11. Silva, C., B. Rocha and A. Suleman. 2011. “PZT Network and Phased Array Lamb Wave Based SHM Systems”, Journal of Physics: Conference Series, 305: 012087. 12. Cokonaj, V., A. Cano, S. Corbo, A. Alcaide, G. Aranguren, L. Casado, E. Barrera and M. Ruiz. 2012. “Integrated Phased Array Transducer for On-Board Structural Health Monitoring”, Proc. of the 6th European Workshop on SHM, 1: 533-541. 13. Wandowski, T., P. Malinowski and W.M. Ostachowicz. 2011. „Damage detection with concentrated configurations of piezoelectric transducers”, Smart Mater. Struct., 20: 025002.