In this paper, aiming to improve this classification technique, authors have performed tensile test on concrete specimen in order to determine the signal parameters as well as waveforms and to assess the influence of material to wave propagation. After filtering the raw data, the usual RA-AF classification process is used to determine the proportion of each type of damage (Mode I and Mode II).
KHOA HC & CôNG NGHê Identification of tensile damage in concrete by Acoustic Emission Xác định ứng suất phá hoại kéo bê tơng Sóng phát xạ Nguyễn Tất Tâm, Narintsoa RANAIVOMANANA, Jean-Paul BALAYSSAC Tóm tắt Phương pháp Sóng phát xạ (Acoustic Emission) áp dụng để xác định số dạng phá hoại điển hình kết cấu bê tông Đề cập đến RILEM TC 212-ACD, kĩ thuật xác định dạng phá hoại bê tông gây ứng suất kéo hay ứng suất cắt đặt tên “phương pháp RA”, nhiên phương pháp chưa định lượng tỷ lệ phần trăm ứng suất nói Đó hạn chế phương pháp RA, vốn dựa theo thí nghiệm uốn dầm bê tông đơn giản chịu hai tải trọng tập trung thí nghiệm cắt trực tiếp mẫu bê tơng Trong báo này, nhằm mục đích củng cố kĩ thuật phân loại phá hoại, tác giả tiến hành thí nghiệm kéo mẫu bê tơng để xác định thơng số sóng dạng sóng ảnh hưởng không đồng vật liệu đến đường truyền sóng phát xạ Sau lọc bỏ tín hiệu khơng phù hợp, phương pháp RA áp dụng tỷ lệ dạng ứng suất (Mode I Mode II) xác định Trong biểu đồ RA - AF phân loại ứng suất, điểm biểu đồ xác định từ hai nguồn khác nhau: từ tín hiệu lại sau hồn tất q trình loại bỏ tín hiệu liên quan tiếng ồn, từ việc xác định giá trị trung bình liên tiếp 50 tín hiệu Kết cho thấy phá hoại gây hầu hết ứng suất kéo Tuy nhiên, việc phân tích sâu tín hiệu (thơng số sóng, dạng sóng, tương quan dạng sóng) cho thấy, tín hiệu có chung nguồn gốc phát xạ (event) thông số có giá trị khác nhau, phương pháp cần thảo luận thêm Abstract The existence of typical crack modes in general concrete structure have been determined thanks to Acoustic Emission (AE) technique In RILEM TC 212-ACD, the classification namely RA method can determine the tensile and shear which occurred in concrete damaged objects but the proportion of these stresses are not clarified These are the limitations of this method which is based on the four-point bending tests and the direct shear tests of concrete specimens In this paper, aiming to improve this classification technique, authors have performed tensile test on concrete specimen in order to determine the signal parameters as well as waveforms and to assess the influence of material to wave propagation After filtering the raw data, the usual RA-AF classification process is used to determine the proportion of each type of damage (Mode I and Mode II) The RA-AF on the classification graph is calculated from filtered hit and from average of 50 continuous hits The results show dominant proportion of AE signals are associated with mode I damage However, a further analysis of the signals (AE parameters, wave forms, Cross-correlation) that generated from the same event to check the relevance of this classification shows that it needs to be discussed Keywords: Concrete, Modulus of elasticity, Homogenization, deformation Nguyen Tat Tam Faculty of Civil Engineering Hanoi Architectural University, Vietnam Email: Narintsoa RANAIVOMANANA Jean-Paul BALAYSSAC LMDC, Université de Toulouse, INSA, UPS, France 26 Introduction 1.1 Tensile damage in concrete specimens In general, concrete is considered to be a brittle material Especially in the case of tensile loaded concrete a very brittle behaviour is expected, but in some cases, e.g anchorage and pure bending, tensile loaded concrete exhibits a ductile behaviour [1] By centric ten28 days strength of 52.5 MPa is used Coarse aggregate is gravel, which is composed of unconsolidated rock fragments that have rough surface and general particle size range with maximum value of 16 mm Fine aggregate is crushed fine sand of maximum size not greater than mm The mechanical properties of concrete were determined at 28 days on three ϕ118×225 mm cylinders with a compressive strength (fc’) of 51.0 MPa assessed through direct compression tests; the tensile strength (ft) of 3.3 MPa was assessed by splitting tests The Elastic modulus of 37.5 GPa was determined based on RILEM CPC8 recommendation One concrete specimen was subjected to traction test has dimension of 25×10×10 cm and a 10mm notch around the mid-span The loading system was controlled by two COD1, clip gauges locate across the notches Due to the expected brittle response, the test was conducted by loading was applied with rate of μm/min and 20 μm/min to the CODs for before and after peak load, respectively Figure Loading (kN) and AE amplitude (dB) vs time (s) in tensile specimen Loading platens are glued to both ends of the specimen by epoxy The upper one was glued first and connected to the actuator; whereas the lower one was adjusted its location to the central of the lower platen before it is fixed by the epoxy This step intends to reduce the eccentricity of loading during the test 2.2 Acoustic emission setup The AE activity recorded was performed using eightchannel PCI–8 acquisition device of the Physical Acoustic Corporation (PAC) For recording the characteristic parameters an AEwin for SAMOS version 2008 software was used AE detection was performed by sensors, R15-α series of PAC whose specification: Operating frequency range 50 Table AE sensors arrangement on specimen Sensor no X (cm) Y (cm) Z (cm) 15.7 10 9.3 10 15.7 9.3 8.3 10.5 16.7 S¬ 28 - 2017 27 KHOA HC & CôNG NGHê Figure Tensile specimen (a) and AE events at notch portion (b) – 400kHz, Resonant frequency 150kHz, Peak sensitivity 80dB These sensors are mounted on the surface of the specimens with silicon grease as coupling agent, and they were placed close to the expected location of the future cracks path to minimize errors in the AE event localization (Figure 2) These sensors have a coordinate that indicated in Table as 3D analyses perform Figure Damage classification at Peak load The PAC preamplifiers model 2/4/6 (gain selectable 20/40/60 dB + 5% dB) were fixed a gain of 40 dBs intend to eliminate the background noise The acquisition system was calibrated before each test using a standard source pencil lead break procedure Hsu-Nielsen and to verify that nothing has changed on sensors sensitivity before and after the test, the Auto Sensor Test was performed In these tests, the AE events are located by applying the wave velocity of 4,000 m/sec Figure Damage classification at failure Crack classification applying RA value Figure Damage classification at Peak load 3.1 AE raw data filtering Figure Damage classification at failure After the time duration of 260s, the testing system stopped as a result of the Table AE parameters in event Record Channel di (cm) Rise time (μs) Amp (dB) AF (kHz) Counts Duration (μs) RA (ms/V) 3.34 32 50 117 34 290 ABEN (aJ) 1.012 393.68 4.32 28 48 90 19 212 1.115 188.03 7.04 45 49 184 0.000 79.45 7.76 21 44 59 12 202 1.325 106.06 11.03 48 54 92 45 487 0.958 718.98 9.54 48 59 23 387 0.159 198.01 Table Normalized Cross-correlation (NCC) of signals in selected events Event Number of records Group name Record 0-1 Record 0-2 Record 0-3 Record 0-4 Record 0-5 Concentrate -0.08 -0.01 -0.13 -0.08 -0.13 Scatter -0.09 -0.01 0.30 0.08 -0.20 28 TP CH KHOA HC KIƯN TRC - XY DẳNG (a) (b) (c) Figure 3D event localization (a), crack classification for six signals of event (b) and event (c) in those papers, users are possible to cite that AE energy can be a feature to determine the fracture energy of concrete They also confirm in the three-point-bending test with notched concrete beam, the high energy events are located above the tip of the notch In addition to above filtering task, signals that have the Duration higher than the Frame-time that definite by AEwin before starting of signal recording will also be discarded To determine the appropriate Duration value, the Hit Definition Time (HDT, μs) is calculated through the input parameters According to [10], HDT is defined as follows Eq HDT= 1024 × Figure 10 Signal waveforms of Record to of event specimen was completely damaged and the number of AE hits that recorded thanks to six sensors is 30,607 The peak value of loading is 21.23 kN corresponding to the CMOD of 4.8 μm (Figure 3) After this peak point, the curve gradually dropped up to a brittle failure of the specimen By observing the images (a) and (b) in Figure 4, the location of the crack on specimen is good agreement with the events which are localized by AEwin The first observed AE signals are on the upper part of the beam and they concentrated beneath the loading-jack possible due to contact damages The next hits are visible at the lower location and random in fracture process zone The number of AE signals obtained in experiment tests is almost large with inconsistent shapes and either their parameters Filtering work on AE hits may be associated to raw data with surround noise elimination The hits with low magnitude (Duration less than 10 μs and Count less than 2) could be related to background noise [8] And it is noteworthy in some studies [9] that the AE energy have a good correlation to the fracture energy And as the comments L −P S Eq Where: L (μs) - Length in k (1 k = 1024 μs) of signal; S – Sample rate in MSPS (Millions of Samples Per Second), MSPS = 106 Hz; P (μs) is Pre-trigger time In this test, L = k, S = MSPS and P = 96 μs then HDT = 1952 μs In this test, AE data filtering work has removed the signals with Count less than 2, zero of PAC energy and Duration higher than 1952 μs Comparing to the raw data with 30,607 hits, the filtered data remaining 15,121 hits (49.4%), thus, 50.6% of inconsonant signals have been eliminated after filtering work 3.2 Crack classification applying filtered RA value The result of damage classification performing to 275 hits which are recording from the beginning of the test to peak loading is indicated in Figure It can be seen, the number of hits that resulting damage Mode I is occupied 97.1%, thus, the dominant damage mode is tensile And at the failure (15,121 hits), Mode I is increased and accounted for 98.4% as shown in Figure AE analysis confirmed that the damage in specimen is caused by tensile stress The Shear mode exists but it contributes low proportion with 1.6% 3.3 Crack classification applying RA value of average 50 continuous AE hits As indicated in Subsection 1.2, in NDIS 2421 [3] classification process, the RA and AF value are calculated Sơ 28 - 2017 29 KHOA HC & CôNG NGHê from the moving average of more than 50 hits [4] In this subsection, RA and AF value of individual hit are determined and then the average value of group 50 continuous hits is created At peak load, the plots show 100% tensile crack in the specimen as show in Figure The dots in the graph represent the average value of RA and AF of 50 continuous hits In the following process after peak, the result on the plot clarifies that 100% damage mode during this process is tensile (Figure 8) Figure 11 Correlation Record - Record with NCC = -0.01, event AE events source discrimination The NDIS 2421 damage classification has been applied RA value as well as Average frequency of signals but without considering other independent parameters of those signals such as Amplitude, Figure 12 Correlation Record - Record with NCC = 0.3, event Count, Duration, Energy and etc Thus, by generated from one event and having the similar damage correlation aims to find the similarity between waveforms, mode, but the received signals at individual sensor have the thereby, it could help to evaluate if the received signals by differential shapes and parameters Figure 9.a) depicts an sensor to are compatible or incompatible with each other event with the ranges to the sensors are di (i = - 6) It can The correlation result reaches a peak at the time when the be seen, the different in travel distance from source to the two signals have the best match When the two signals are sensors possible influence to the waveforms To verify this, identical in terms of shape, this peak is reached at time t two events are extracted from the 3D event localization then = without delay However, if one of these two signals has classify by RA value and Cross-correlation The Cartesian delay time and is possibly influenced by the travel distance coordinate of event is (2.21; 12.44; 7.18) and event (1.91; then correlation is a good method to measure that delay The 10.09; 2.92) cm Cross-correlation (CC) of discrete signal is defined as Eq In Figure 9.b) and c), it is clearly seen that all signals of N −1 CC ( x, y ) = ∑ X [ n]Y[ n] the event and event are classified in Mode I Although n =0 having the similar mode I but the distribution of records on Eq the RA - AF chart is different to the events and there are Where: N is number samples in the signal In the AE two trends of signal grouping The first is ‘concentrate’, for signal acquirement system, N is determined by a rate of example the signals in event are closely located on the plot point per μs In this test, AE signals are recorded with N that represents the same RA and AF value In contrast, the = 2048 samples (equivalent to 2048 μs) and it will stop at second Group is ‘scatter’ as event 2, the position of signals point which is zero Amplitude And X and Y are function of [n] [n] are varying in larger zone comparing to event with AF from physical quantity varies over time or spacy 50-120 kHz, RA from 0-2 ms/V In general, the CC is a measure of how similar signals In terms of waveform, the Figure 10 presents the are and the high CC indicates that the signals are quite the waveforms of Record to of event It can be seen, the same However, if two events that have high energy (or high presence of high AF in the signal waveforms improve that amplitude) at some samples at different time, the CC value they are tensile mode As indicated in [11], when the distance could be comparatively high but actually the signals are not from sensors to event increase, the AF and energy decrease quite similar Thus, the CC value may cause the misleading while RA increases By observing the events that defined in to the users Then the normalized of Cross-correlation (NCC) the tensile test, authors recognized that these events are is necessary apply to the two signals to conclude that they incompatible with above attenuation rule in [11] For example, are identical or not, as defined in Eq from Record to 4, the distances from the sensors to the N −1 ∑ n =0 X [n]Y[n] event rise from 3.34 cm (Record 0) to 11.03 cm (Record 4) NCC ( x, y ) = while the Amplitudes reduce from 50 to 44 dB (in Record to N −1 X [ n] ∑ nN −01Y[2n] ∑ n 0= 3) but increase to 54 dB in Record Similarity, the fluctuation = Eq of RA and ABEN (Absolute Energy) from Record to clarify To evaluate the correlation between signals in the two that there is no exhaust regulation on these factors (Table 2) groups named ‘concentrate’ and ‘scatter’ that mentioned Signal waveform Cross-correlation above, signals in some events will be selected to calculate Another technique for AE sources discrimination the correlation and normalized value The events in Group consists in applying Cross-correlation method Wave Cross- one is event and Group two is event The results of the 30 T„P CHŠ KHOA H“C KI¦N TR”C - XŸY D¼NG Figure 13 Crack shape at the notch (a) and plan view (b) calculation are shown in Table It can be seen that event gives higher NCC value than event For example, by assess the Record and 3, the NCC value in event is 0.30 while in event has NCC = -0.13 Figure 11 presents the waveform of Record and Record of event with the normalized cross-correlation between the two records is NCC = -0.01 Similarity, Figure 12 demonstrates the waveform of Record and Record in event with NCC = 0.3 Comments and conclusions The filtering plays an important role in eliminating the signals that could be related to surrounding noise (low of count, duration and energy) It is about 50% of the raw signals have been removed from the classification processes On the crack classification chart, signals concentrated in high AF areas exhibit damage mode I, which is consistent with RILEM TC 212-ACD By observing the crack shape and also section in Figure 13, it is identified that the almost mode I cracks have pulled out the gravels and divided them in to two parts The occurrence of shear stress (1.6%) when Tài liệu tham khảo Gert Konig and Herbert Duda, “Basic concept for using concrete tensile strength,” ETH Zür Rämistrasse 101 8092 Zür Schweiz Wwwlibraryethzch, 1991 Hans W Reinhardt, Hans A W Cornelissen, and Dirk A Hordijk, “Tensile tests and failure analysis of Concrete,” Univ Neb.-Linc 060613, 2013 Kentaro Ohno and Masayasu Ohtsu, “Crack classification in concrete based on acoustic emission,” Constr Build Mater., vol 24, no 12, pp 2339–2346, Dec 2010 RILEM Technical Committee, “Recommendation of RILEM TC 212-ACD: acoustic emission and related NDE techniques for crack detection and damage evaluation in concrete: Test method for classification of active cracks in concrete structures by acoustic emission,” Mater Struct., vol 43, no 9, pp 1187–1189, Nov 2010 Kanji Ono, “Application of acoustic emission for structure diagnosis,” Diagn ISSN 1641-6414, pp 3–18, 2011 D.G Aggelis, “Classification of cracking mode in concrete by determining RA-AF from individual hits can be caused by damage at the interface between the aggregate and mortar (de-bonding), slip damage between the two materials is possible to generate shear mode However, by determining the RA-AF from the mean value of 50 continuous hits, mode II is noticeably dissipated The possible reason is that the number of mode I is negligible compared to mode II, thus by applying the average, mode II was filtered out There are significant differences when comparing the waveforms of the signals that generate from the similar event Although the signals share the same damage zone (mode I or mode II) but the correlation between waveforms and parameters varies considerably This could be due to the influence of the transmission distance and the heterogeneous of material to the waveform In [11], when the distance between the sensor and the event increases, the RA value increase while the AF, Amplitude and Energy decrease However, this attenuation rule was not observed in the signals that received from tensile experiment; instead, these values fluctuate without identify the trend./ acoustic emission parameters,” Mech Res Commun., vol 38, no 3, pp 153–157, Apr 2011 Arash Behnia, Hwa Kian Chai, and Tomoki Shiotani, “Advanced structural health monitoring of concrete structures with the aid of acoustic emission,” Constr Build Mater., vol 65, pp 282–302, Aug 2014 L Calabrese, G Campanella, and E Proverbio, “Noise removal by cluster analysis after long time AE corrosion monitoring of steel reinforcement in concrete,” Constr Build Mater., vol 34, pp 362–371, Sep 2012 R Vidya Sagar and B K Raghu Prasad, “An experimental study on acoustic emission energy as a quantitative measure of size independent specific fracture energy of concrete beams,” Constr Build Mater., vol 25, no 5, pp 2349–2357, May 2011 10 MISTRAS Group, Inc, SAMOS AE system User’s Manual, Rev 2011 11 D Polyzos, A Papacharalampopoulos, T Shiotani, and D G Aggelis, “Dependence of AE parameters on the propagation distance,” J Acoust Emiss, vol 29, pp 57–67, 2011 S¬ 28 - 2017 31 ... filtering work 3.2 Crack classification applying filtered RA value The result of damage classification performing to 275 hits which are recording from the beginning of the test to peak loading is indicated... “Application of acoustic emission for structure diagnosis,” Diagn ISSN 1641-6414, pp 3–18, 2011 D.G Aggelis, “Classification of cracking mode in concrete by determining RA-AF from individual hits... NDE techniques for crack detection and damage evaluation in concrete: Test method for classification of active cracks in concrete structures by acoustic emission, ” Mater Struct., vol 43, no 9,