WO2023280023A1 - 基于交流电磁场的水下结构裂纹扩展可视化监测系统和交流电磁场裂纹可视化监测与评估方法 - Google Patents
基于交流电磁场的水下结构裂纹扩展可视化监测系统和交流电磁场裂纹可视化监测与评估方法 Download PDFInfo
- Publication number
- WO2023280023A1 WO2023280023A1 PCT/CN2022/102039 CN2022102039W WO2023280023A1 WO 2023280023 A1 WO2023280023 A1 WO 2023280023A1 CN 2022102039 W CN2022102039 W CN 2022102039W WO 2023280023 A1 WO2023280023 A1 WO 2023280023A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- signal
- module
- matrix
- crack
- electromagnetic field
- Prior art date
Links
- 238000012544 monitoring process Methods 0.000 title claims abstract description 96
- 230000005672 electromagnetic field Effects 0.000 title claims abstract description 51
- 230000000007 visual effect Effects 0.000 title claims abstract description 30
- 238000011156 evaluation Methods 0.000 title claims abstract description 14
- 230000005284 excitation Effects 0.000 claims abstract description 27
- 238000000034 method Methods 0.000 claims abstract description 25
- 238000001914 filtration Methods 0.000 claims abstract description 12
- 239000011159 matrix material Substances 0.000 claims description 71
- 230000003321 amplification Effects 0.000 claims description 34
- 238000003199 nucleic acid amplification method Methods 0.000 claims description 34
- 238000001514 detection method Methods 0.000 claims description 27
- 238000012360 testing method Methods 0.000 claims description 13
- 230000003750 conditioning effect Effects 0.000 claims description 10
- 230000006641 stabilisation Effects 0.000 claims description 4
- 238000011105 stabilization Methods 0.000 claims description 4
- 230000006698 induction Effects 0.000 claims description 3
- 230000009977 dual effect Effects 0.000 claims description 2
- 239000000758 substrate Substances 0.000 claims description 2
- 230000007547 defect Effects 0.000 abstract description 13
- 238000012545 processing Methods 0.000 abstract description 9
- 238000009659 non-destructive testing Methods 0.000 abstract description 3
- 230000007274 generation of a signal involved in cell-cell signaling Effects 0.000 abstract description 2
- 238000004519 manufacturing process Methods 0.000 abstract description 2
- 238000004806 packaging method and process Methods 0.000 abstract 1
- 238000005516 engineering process Methods 0.000 description 8
- 238000003384 imaging method Methods 0.000 description 6
- 238000000576 coating method Methods 0.000 description 5
- 238000010586 diagram Methods 0.000 description 5
- 238000005260 corrosion Methods 0.000 description 4
- 230000007797 corrosion Effects 0.000 description 4
- 239000011248 coating agent Substances 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 239000000523 sample Substances 0.000 description 3
- 230000000087 stabilizing effect Effects 0.000 description 3
- 238000003491 array Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000004140 cleaning Methods 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 238000007689 inspection Methods 0.000 description 2
- 230000007774 longterm Effects 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 238000011155 quantitative monitoring Methods 0.000 description 2
- 239000013535 sea water Substances 0.000 description 2
- 238000009825 accumulation Methods 0.000 description 1
- 230000006835 compression Effects 0.000 description 1
- 238000007906 compression Methods 0.000 description 1
- 239000004020 conductor Substances 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 230000000977 initiatory effect Effects 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000011068 loading method Methods 0.000 description 1
- 238000011158 quantitative evaluation Methods 0.000 description 1
- 238000011084 recovery Methods 0.000 description 1
- 230000008439 repair process Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 238000000926 separation method Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000012800 visualization Methods 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
- G01N27/72—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating magnetic variables
- G01N27/82—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating magnetic variables for investigating the presence of flaws
- G01N27/83—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating magnetic variables for investigating the presence of flaws by investigating stray magnetic fields
- G01N27/85—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating magnetic variables for investigating the presence of flaws by investigating stray magnetic fields using magnetographic methods
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
- G01N27/72—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating magnetic variables
- G01N27/82—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating magnetic variables for investigating the presence of flaws
Definitions
- the invention relates to the technical field of structural health monitoring, in particular to a visual monitoring system for structural crack propagation based on an AC electromagnetic field and a visual monitoring and evaluation method for cracks in an AC electromagnetic field.
- Marine structures have served in seawater environment for a long time. Due to the corrosion of seawater, various corrosion defects are easily produced on the surface of the structure. Due to factors such as coating coverage and accumulation of attachments, traditional non-destructive testing techniques need to detect and evaluate defects in the process of cleaning up attachments in a large area and completely destroying the coating during the inspection of underwater structures. The operation process is complex and inefficient. , structural surface cleaning and coating repair costs are high. Especially in deep water areas, the interval between routine inspection operations is long, resulting in missed detection of primary crack initiation.
- Alternating Current Field Measurement (ACFM) technology is a new electromagnetic non-destructive testing technology, which is mainly used for crack detection on the surface of conductive materials. It uses the uniform current induced by the detection probe on the surface of the conductive test piece, and the current is generated around the defect. Disturbances cause spatial magnetic field distortion, and defects are detected and evaluated by measuring the distorted magnetic field. When there is no defect, the surface current of the conductive specimen is in a uniform state, and the spatial magnetic field is not disturbed. Due to the advantages of non-contact measurement and quantitative evaluation, it is widely used in the detection of defects in various marine structures.
- the existing ACFM technology judges defects based on the characteristic signals Bx, Bz and butterfly diagram, where the Bx and Bz signals are the magnetic field signals parallel to the surface of the test piece (parallel to the scanning direction of the probe) and perpendicular to the surface of the test piece respectively, and the characteristic signal Bx can evaluate the crack depth, and the characteristic signal Bz can evaluate the crack length.
- the probe of the traditional ACFM detection system is a three-dimensional shell structure, which cannot be adapted to fit the key nodes of the structure; at the same time, the sensor arrangement is also a single point or line array, which cannot realize area crack monitoring; the ACFM hardware system is suitable for single array or a small number of array sensors Signal processing cannot meet the signal acquisition and processing of large-scale monitoring sensors.
- the use of conventional Bx and Bz amplitude characteristic signals cannot display crack extension endpoints and edge images, and cannot meet the needs of real-time visual monitoring.
- the present invention provides a visual monitoring system for crack propagation in underwater structures based on AC electromagnetic fields.
- the flexible monitoring sensor array acquires the distorted magnetic field signal of the structure surface in real time, and processes and collects the signal at the same time, so as to detect the defects of marine structures. Detection evaluation and life prediction provide accurate and real-time data source support.
- a visual monitoring system for crack growth in underwater structures based on AC electromagnetic fields including a flexible AC electromagnetic field monitoring sensor module closely attached to the surface to be tested, an AC electromagnetic field monitoring instrument, USB data line and computer, the flexible AC electromagnetic field monitoring sensor module includes a flexible PCB excitation module and a flexible monitoring sensor array, and the AC electromagnetic field monitor includes a signal conditioning module, a signal acquisition module, a power amplification module and a stabilization module pressure module, and the computer is connected to the signal acquisition module in the AC electromagnetic field monitor through a USB data cable.
- the flexible PCB excitation module uses M (M ⁇ 1) layers of double rectangular sensing coils to be printed on the flexible substrate, the dual rectangular sensing coils are respectively loaded with excitation signals in different directions, and the flexible
- the monitoring sensing array includes a flexible planar PCB module and m rows and n columns of sensing coils fixed thereon, the outer diameter of the sensing coil is D (D ⁇ 10mm), and the inner diameter is d (d ⁇ D).
- the number of turns of the sensing coil is N, the axis of the sensing coil is perpendicular to the flexible planar PCB module, and the center distance between two adjacent sensing coils is 3mm-20mm, and the sensing coil can be formed by Magnetic field sensor replacement.
- the voltage stabilizing module is respectively connected to the signal conditioning module, the signal acquisition module and the power amplification module
- the flexible PCB excitation module is connected to the output end of the power amplification module
- the power The input end of the amplification module is connected with the analog signal output end of the signal acquisition module.
- the signal conditioning module includes an AD620 differential amplification module, a multiplexing module, an amplification filtering module and a detection module, the input end of the AD620 differential amplification module is connected to the sensing coil, and the multiplexing
- the signal input end of the module is connected with the signal output end of the AD620 differential amplification module
- the control signal input end of the multiplexing module is connected with the digital signal output end of the signal acquisition module
- the signal output end of the module is connected to the signal input end of the amplification and filtering module
- the signal output end of the amplification and filtering module is connected to the signal input end of the detection module
- the signal output end of the detection module is connected to the signal acquisition
- the analog signal input terminal of the module is connected.
- the present invention provides a method for visual monitoring and evaluation of structural cracks based on AC electromagnetic fields, which presents the visual image of crack monitoring in real time, calculates the length of cracks, and judges whether cracks expand and the type of crack expansion. Defect assessment and life prediction provide accurate and real-time data support.
- the present invention provides a visual monitoring and evaluation method for structural cracks based on AC electromagnetic field detection technology, including:
- Step 1 A uniform induction current is generated on the surface of the test piece through the PCB excitation module, and the induced current causes distortion of the spatial magnetic field.
- a flexible monitoring sensor array composed of m rows and n columns of coils is placed on the surface of the test piece, and the current value in the Z direction at the initial moment of the monitoring area is extracted.
- Magnetic field signal Bz0 matrix Obtain the real-time magnetic field signal Bz matrix in the Z direction of the specimen surface in real time as time goes by performing linear interpolation on the matrix A and drawing an intensity map to obtain a visualized image of crack monitoring at key structural nodes;
- Step 2 Calculate the maximum element position (x1, y1) and the second maximum element position (x2, y2) of matrix A, and extract p ⁇ q element values and their positions centered on (x1, y1) as group a data , extract nine element values centered on (x2, y2) and their positions as group b data;
- Step three according to the formula and Calculate the signal centroids of group a data and group b data respectively, xi is the X coordinate position of the nine elements, yi is the Y coordinate position of the nine elements, and the two endpoint coordinates (xa, ya) and (xb, yb) of the crack are obtained , the crack length is calculated from the distance between the coordinates of the two endpoints;
- Step 4 subtracting the matrix A0 from the matrix A to obtain a signal increment matrix
- Step five according to the formula Calculate the energy value E0 of the matrix A0 and the energy value Ec of the signal increment matrix C, and calculate the ratio of Ec to E0 to obtain the energy distortion rate ⁇ E;
- Step 6 comparing the energy distortion rate ⁇ E with the set energy threshold N, if ⁇ E>N, the crack has expanded, otherwise it is judged that the crack has not expanded, and then proceed to step 7;
- Step 7 Comparing the elements in the signal increment matrix C with the set noise threshold N1, if the elements in the signal increment matrix C ⁇ N1, the crack is length extension, otherwise it is depth extension.
- the visual monitoring and evaluation method for structural cracks based on the AC electromagnetic field detection technology uses the AC electromagnetic field monitoring sensor array to be placed on the surface of the test piece for monitoring, and obtains the Z-direction magnetic field signal Bz matrix A of the test piece surface in real time and saves the initial Z-direction magnetic field Signal Bz matrix A0, linearly interpolate the magnetic field signal Bz matrix A in the Z direction in real time and draw the intensity map to obtain the visual image of structural crack monitoring, and calculate the maximum element position (x1, y1) and sub Maximum element position (x2, y2), extract nine element values and their positions centered on (x1, y1) as group a data, extract nine element values and their positions centered on (x2, y2) as b Group data, obtain the signal centroids of group a data and group b data respectively to obtain the two endpoint coordinates (xa, ya) and (xb, yb) of the crack, and then calculate the crack length, and combine the magnetic field signal Bz matrix A in the Z direction
- the structural crack expansion visualization monitoring hardware system based on AC electromagnetic field detection technology uses coils to design and manufacture AC electromagnetic field monitoring sensing arrays, encapsulates and forms AC electromagnetic field monitoring sensing modules, and designs power amplification modules as AC electromagnetic field monitoring sensing modules
- the group provides the excitation signal
- the AD620 differential amplifier module is designed to amplify the weak sensing signal
- the multiplexing module is designed to realize the time-division multiplexing of multiple sensing signals
- the signal amplification and filtering module is designed to further amplify and filter the signal
- the detection module is designed
- the AC signal is converted into a DC signal
- the NI acquisition card is used to realize the excitation signal generation, multiplex control signal output and signal acquisition, and finally realize the processing and acquisition of the visual monitoring signal of structural crack growth.
- Fig. 1 is a system block diagram provided by an embodiment of the present invention
- Fig. 2 is the flexible AC electromagnetic field monitoring sensor module provided by the embodiment of the present invention.
- Fig. 3 is the AC electromagnetic field monitor provided by the embodiment of the present invention.
- Fig. 4 is the flexible PCB excitation module provided by the embodiment of the present invention.
- Fig. 5 is a flexible monitoring sensing array provided by an embodiment of the present invention.
- Fig. 6 is the AC electromagnetic field monitoring hardware system provided by the embodiment of the present invention.
- Fig. 7 is a crack visual monitoring image provided by an embodiment of the present invention.
- Fig. 8 is a flow chart of the online intelligent determination and classification identification method for AC electromagnetic field defects provided by the embodiment of the present invention.
- Fig. 9 is an AC electromagnetic field monitoring sensing array provided by an embodiment of the present invention.
- Fig. 10 is a visualized image of structural crack monitoring provided by an embodiment of the present invention.
- FIG. 11 is a schematic diagram of matrix element grouping provided by an embodiment of the present invention.
- Fig. 12 is a schematic diagram of crack depth monitoring provided by an embodiment of the present invention.
- Fig. 13 is a schematic diagram of crack length monitoring provided by an embodiment of the present invention.
- the embodiment of the present invention provides a visual monitoring system for crack propagation in underwater structures based on AC electromagnetic fields, mainly including: a flexible AC electromagnetic field monitoring sensor module 4 closely attached to the surface to be tested, an AC electromagnetic field monitor 3, and a USB data line 2 and computer 1,
- the flexible AC electromagnetic field monitoring sensing module 4 includes a flexible PCB excitation module 4.1 and a flexible monitoring sensing array 4.2
- the AC electromagnetic field monitor 3 includes a signal conditioning module 3.1, a signal acquisition module 3.2, a stable Compression module 3.3 and power amplification module 3.4, described computer 1 is connected with signal acquisition module 3.2 in AC electromagnetic field monitor 3 by USB data line 2, as shown in Figure 1;
- the flexible PCB excitation module 4.1 is printed on the flexible base with 2 layers of double rectangular sensing coils, as shown in Figure 4, the flexible base can be easily attached, used for crack monitoring of key underwater nodes, and solves the problem of the three-dimensional structure of the traditional AC electromagnetic field Disadvantages of difficult installation and attachment.
- the excitation signals in different directions are respectively loaded in the double rectangular coils.
- the two excitation coils in different directions can generate eddy current fields in different directions on the surface of the structure.
- the central area of the eddy current field forms a uniform field. When the crack is in a uniform
- the current disturbance is caused by the magnetic field, which further causes the surrounding magnetic field to be distorted.
- the flexible monitoring sensor array 4.2 includes a flexible planar PCB module and 8 rows and 8 columns of sensing coils fixed on it.
- the sensing coil picks up the distortion in the uniform current region Magnetic field, an area-type monitoring area can be formed through the array sensor, and the distorted magnetic field image of the monitoring area can be obtained through linear interpolation to realize visual imaging monitoring of cracks at key nodes.
- the outer diameter of the sensing coil is 2mm, the inner diameter is 0.5mm, and the number of turns of the sensing coil is 500, the axis of the sensing coil is perpendicular to the plane PCB, and the center distance between the sensor coils is 4 mm, as shown in Figure 5.
- the sensing coil can be replaced by magnetic field sensors such as TMR, AMR, and Hall.
- the voltage stabilizing module 3.3 is connected with the signal conditioning module 3.1, the signal acquisition module 3.2 and the power amplification module 3.4 after stabilizing the external DC power supply, the flexible excitation module 4.1 is connected with the output end of the power amplification module 3.4, and the power amplification module
- the input terminal of module 3.4 is connected to the analog signal output terminal of signal acquisition module 3.2; the signal acquisition module can generate a sinusoidal excitation signal, and the excitation signal is loaded into the double rectangular coil of the flexible excitation module after power amplification, and the loading method is a rectangular coil on one side A clockwise current is generated in the inside, and a counterclockwise current is generated in the rectangular coil on the other side, so that the rectangular coil of the flexible excitation module is loaded with current in different directions.
- the signal conditioning module 3.1 includes an AD620 differential amplification module 3.1.1, a multiplexing module 3.1.2, an amplification filter module 3.1.3 and a detection module 3.1.4, and the input terminal of the AD620 differential amplification module 3.1.1 is connected to the
- the flexible monitoring sensor array is connected by 4.2, the multiplexing module is designed with ADG1607 chip, the amplification and filtering module is a band-pass filter combined with a second-order low-pass and first-order high-pass active filter, and the detection module is designed for the diode detection circuit.
- the signal input end of described multiplexing module 3.1.2 is connected with the signal output end of AD620 differential amplification module 3.1.1, and the control signal input end of described multiplexing module 3.1.2 is connected with the digital signal acquisition module 3.2.
- the signal output terminal is connected, the signal output terminal of the multiplexing module 3.1.2 is connected to the signal input terminal of the amplification and filtering module 3.1.3, the signal output terminal of the amplification and filtering module 3.1.3 is connected to the detection module 3.1.4 The signal input end of the detection module 3.1.4 is connected to the analog signal input end of the signal acquisition module 3.2.
- the sensing coil picks up the weak distorted magnetic field in the area of uniform current, which is amplified by AD620 and then input to the multiplexer.
- the multiplexer can solve the signal processing problems of multiple monitoring channels and sensing coil arrays.
- the control signal of the multiplexed signal is controlled by the acquisition card pulse digitally, solve the timing control problem of multi-channel signal multiplexing and multi-channel acquisition, the multiplexed signal enters the
- the detection circuit converts the sinusoidal response signal into an amplitude signal, and the detection signal is collected through the acquisition card. After the acquisition is completed, the signal is transmitted to the internal software of the computer for processing.
- the computer software can control the pulse trigger multiplexing of the acquisition card to realize accurate separation of multiple signals and recovery of multiple signals.
- the internal software of the computer uses the linear interpolation of the amplitude signal to present the distorted magnetic field image of the monitoring area.
- the flexible monitoring sensing module can adapt to the close fit of the key nodes of the structure; It can display the crack growth endpoint and edge image, get rid of the cumbersome scanning of the traditional ACFM face area detection, high accuracy and good real-time performance, and realize long-term, real-time, fixed-point visual monitoring of crack growth without removing attachments and coatings , to provide accurate data support for the monitoring, evaluation and life prediction of corrosion cracks in marine structures.
- the computer in the above system executes the defect online intelligent judgment and classification recognition method based on the AC electromagnetic field detection technology, as shown in Figure 8, the method includes:
- the crack length extension can be determined, as shown in FIG. 13 .
- the types of crack growth are further clarified on the basis of the determination of crack growth above. The above method can not only predict crack growth, but also further clarify the type of crack growth, and provide an effective method for accurate and quantitative monitoring of cracks in key joints of underwater structures.
- the defect online intelligent determination and classification identification method based on AC electromagnetic field detection technology provided by the embodiment of the present invention, as shown in Figure 8, includes:
- the crack length extension can be determined, as shown in FIG. 13 .
- the types of crack growth are further clarified. The above method can not only predict crack growth, but also further clarify the type of crack growth, and provide an effective method for accurate and quantitative monitoring of cracks in key joints of underwater structures.
- the beneficial effects of this embodiment are: by processing the monitoring data, real-time imaging and visual monitoring of cracks in a certain area can be realized, the determination of crack breakpoints and the evaluation of crack lengths can be realized, and the judgment and The discrimination of expansion type has high accuracy and good real-time performance. It can realize long-term, real-time and fixed-point visual monitoring of crack growth without removing attachments and coatings, providing accurate monitoring, evaluation and life prediction for marine structure corrosion cracks. data support.
Landscapes
- Chemical & Material Sciences (AREA)
- Chemical Kinetics & Catalysis (AREA)
- Electrochemistry (AREA)
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Investigating Or Analyzing Materials By The Use Of Magnetic Means (AREA)
Abstract
Description
0.028 | 0.028 | 0.058 | 0.016 | 0.156 | 0.068 | 0.015 | 0.004 |
0.026 | 0.022 | 0.07 | 0.267 | 1.085 | 0.243 | 0.058 | 0.04 |
0.009 | 0.006 | 0.043 | 0.224 | 0.506 | 0.166 | 0.063 | 0.021 |
0.021 | 0.027 | 0.022 | 0.039 | 0.015 | 0.007 | 0.018 | 0.007 |
0.013 | 0.017 | 0.001 | 0.136 | 0.389 | 0.113 | 0.04 | 0.012 |
0.022 | 0.017 | 0.027 | 0.237 | 1.095 | 0.196 | 0.027 | 0.002 |
0.021 | 0.02 | 0.003 | 0.073 | 0.182 | 0.029 | 0.034 | 0.003 |
0.045 | 0.037 | 0.045 | 0.029 | 0.014 | 0.024 | 0.015 | 0.028 |
0.016 | 0 | 0.011 | 0.011 | 0.069 | 0.03 | 0.004 | 0.005 |
0.009 | 0.012 | 0.006 | 0.097 | 0.389 | 0.089 | 0.01 | 0.002 |
0.008 | 0.007 | 0.009 | 0.036 | 0.054 | 0.024 | 0.011 | 0.005 |
0.01 | 0.004 | 0.009 | 0.005 | 0.018 | 0.018 | 0.013 | 0.006 |
0.012 | 0.007 | 0.001 | 0.026 | 0.073 | 0.011 | 0.032 | 0.015 |
0.017 | 0.017 | 0 | 0.065 | 0.36 | 0.059 | 0.007 | 0.002 |
0 | 0.003 | 0 | 0.028 | 0.062 | 0.017 | 0.021 | 0.014 |
0.005 | 0 | 0.001 | 0.007 | 0.014 | 0.01 | 0.003 | 0.012 |
0.012 | 0.028 | 0.047 | 0.005 | 0.087 | 0.038 | 0.011 | -0.001 |
0.017 | 0.01 | 0.064 | 0.17 | 0.696 | 0.154 | 0.048 | 0.038 |
0.001 | -0.001 | 0.034 | 0.188 | 0.452 | 0.142 | 0.052 | 0.016 |
0.011 | 0.023 | 0.013 | 0.034 | -0.003 | -0.011 | 0.005 | 0.001 |
0.001 | 0.01 | 0 | 0.11 | 0.316 | 0.102 | 0.008 | -0.003 |
0.005 | 0 | 0.027 | 0.172 | 0.735 | 0.137 | 0.02 | 0 |
0.021 | 0.017 | 0.003 | 0.045 | 0.12 | 0.012 | 0.013 | -0.011 |
0.04 | 0.037 | 0.044 | 0.022 | 0 | 0.014 | 0.012 | 0.016 |
0.028 | 0.028 | 0.058 | 0.016 | 0.156 | 0.068 | 0.015 | 0.004 |
0.026 | 0.022 | 0.07 | 0.267 | 1.085 | 0.243 | 0.058 | 0.04 |
0.009 | 0.006 | 0.043 | 0.224 | 0.506 | 0.166 | 0.063 | 0.021 |
0.021 | 0.027 | 0.022 | 0.039 | 0.015 | 0.007 | 0.018 | 0.007 |
0.013 | 0.017 | 0.001 | 0.136 | 0.389 | 0.113 | 0.04 | 0.012 |
0.022 | 0.017 | 0.027 | 0.237 | 1.095 | 0.196 | 0.027 | 0.002 |
0.021 | 0.02 | 0.003 | 0.073 | 0.182 | 0.029 | 0.034 | 0.003 |
0.045 | 0.037 | 0.045 | 0.029 | 0.014 | 0.024 | 0.015 | 0.028 |
0.016 | 0 | 0.011 | 0.011 | 0.069 | 0.03 | 0.004 | 0.005 |
0.009 | 0.012 | 0.006 | 0.097 | 0.389 | 0.089 | 0.01 | 0.002 |
0.008 | 0.007 | 0.009 | 0.036 | 0.054 | 0.024 | 0.011 | 0.005 |
0.01 | 0.004 | 0.009 | 0.005 | 0.018 | 0.018 | 0.013 | 0.006 |
0.012 | 0.007 | 0.001 | 0.026 | 0.073 | 0.011 | 0.032 | 0.015 |
0.017 | 0.017 | 0 | 0.065 | 0.36 | 0.059 | 0.007 | 0.002 |
0 | 0.003 | 0 | 0.028 | 0.062 | 0.017 | 0.021 | 0.014 |
0.005 | 0 | 0.001 | 0.007 | 0.014 | 0.01 | 0.003 | 0.012 |
0.012 | 0.028 | 0.047 | 0.005 | 0.087 | 0.038 | 0.011 | -0.001 |
0.017 | 0.01 | 0.064 | 0.17 | 0.696 | 0.154 | 0.048 | 0.038 |
0.001 | -0.001 | 0.034 | 0.188 | 0.452 | 0.142 | 0.052 | 0.016 |
0.011 | 0.023 | 0.013 | 0.034 | -0.003 | -0.011 | 0.005 | 0.001 |
0.001 | 0.01 | 0 | 0.11 | 0.316 | 0.102 | 0.008 | -0.003 |
0.005 | 0 | 0.027 | 0.172 | 0.735 | 0.137 | 0.02 | 0 |
0.021 | 0.017 | 0.003 | 0.045 | 0.12 | 0.012 | 0.013 | -0.011 |
0.04 | 0.037 | 0.044 | 0.022 | 0 | 0.014 | 0.012 | 0.016 |
Claims (16)
- 一种基于交流电磁场的水下结构裂纹扩展可视化监测系统,其特征在于,所述系统包括:紧密贴附于被测表面的柔性交流电磁场监测传感模组、交流电磁场监测仪、USB数据线和计算机,所述柔性交流电磁场监测传感模组包括柔性PCB激励模块和柔性监测传感阵列,所述交流电磁场监测仪包括信号调理模块、信号采集模块、功率放大模块和稳压模块,所述计算机通过USB数据线与所述交流电磁场监测仪中的所述信号采集模块连接。
- 根据权利要求1所述的监测系统,其特征在于,所述柔性PCB激励模块采用M(M≥1)层双矩形传感线圈印制在柔性基底上,所述双矩形传感线圈内分别加载方向不同方向的激励信号,所述柔性监测传感阵列包括柔性平面PCB模块和固定在其上的m行n列的传感线圈,所述传感线圈外径为D(D<10mm),内径为d(d<D),所述传感线圈的匝数为N,所述传感线圈的轴线与所述柔性平面PCB模块垂直,相邻的两个所述传感线圈之间中心距离为3mm-20mm,所述传感线圈可由磁场传感器替代。
- 根据权利要求1所述的监测系统,其特征在于:所述稳压模块分别与所述信号调理模块、所述信号采集模块和所述功率放大模块连接,所述柔性PCB激励模块与所述功率放大模块的输出端连接,所述功率放大模块的输入端与所述信号采集模块的模拟信号输出端连接。
- 根据权利要求1所述的监测系统,其特征在于,所述信号调理模块包括AD620差分放大模块、多路复用模块、放大滤波模块和检波模块,所述AD620差分放大模块的输入端与所述传感线圈连接,所述多路复用模块的信号输入端与所述AD620差分放大模块的信号输出端连接,所述多路复用模块的控制信号输入端与所述信号采集模块的数字信号输出端连接,所述多路复用模块的信号输出端与所述放大滤波模块的信号输入端连接,所述放大滤波模块的信号输出端与所述检波模块的信号输入端连接,所述检波模块的信号输出端与所述信号采集模块的模拟信号输入端连接。
- 根据权利要求5所述的监测系统,其特征在于,所述方法还包括:步骤二:求取所述矩阵A的最大元素位置(x1,y1)与次最大元素位置(x2,y2),提取以(x1,y1) 为中心的p×q个元素值及其位置作为a组数据,提取以(x2,y2)为中心的九个元素值及其位置作为b组数据。
- 根据权利要求9所述的监测系统,其特征在于,所述方法还包括:步骤六:将所述能量畸变率ΔE与设定好的能量阈值N进行比较,若ΔE>N,则裂纹已扩展,否则判断裂纹未扩展,进入步骤七;步骤七:将所述信号增量矩阵C中元素与设定好的噪声阈值N1进行比较,若所述信号增量矩阵C中元素<N1,则裂纹为长度扩展,否则为深度扩展。
- 根据权利要求11所述的方法,其特征在于,包括步骤二:求取所述矩阵A的最大元素位置(x1,y1)与次最大元素位置(x2,y2),提取以(x1,y1)为中心的p×q个元素值及其位置作为a组数据,提取以(x2,y2)为中心的九个元素值及其位置作为b组数据。
- 根据权利要求15所述的方法,其特征在于,包括:步骤六:将所述能量畸变率ΔE与设定好的能量阈值N进行比较,若ΔE>N,则裂纹已扩展,否则判断裂纹未扩展,进入步骤七;步骤七:将所述信号增量矩阵C中元素与设定好的噪声阈值N1进行比较,若所述信号增量矩阵C中元素<N1,则裂纹为长度扩展,否则为深度扩展。
Priority Applications (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
AU2022308214A AU2022308214A1 (en) | 2021-07-08 | 2022-06-28 | Underwater structure crack propagation visual monitoring system based on alternating-current electromagnetic field, and alternating-current electromagnetic field crack visual monitoring and evaluation method |
US18/025,188 US20240019399A1 (en) | 2021-07-08 | 2022-06-28 | Monitoring System Of Crack Propagation Of Underwater Structure Visual Based on Alternating Current Field, and Alternating Current Field Crack Visual Monitoring and Evaluation method |
Applications Claiming Priority (4)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202110772687.0A CN113390954B (zh) | 2021-07-08 | 2021-07-08 | 基于交流电磁场的水下结构裂纹扩展可视化监测系统 |
CN202110772811.3 | 2021-07-08 | ||
CN202110772687.0 | 2021-07-08 | ||
CN202110772811.3A CN113390955B (zh) | 2021-07-08 | 2021-07-08 | 交流电磁场裂纹可视化监测与评估方法 |
Publications (1)
Publication Number | Publication Date |
---|---|
WO2023280023A1 true WO2023280023A1 (zh) | 2023-01-12 |
Family
ID=84800368
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/CN2022/102039 WO2023280023A1 (zh) | 2021-07-08 | 2022-06-28 | 基于交流电磁场的水下结构裂纹扩展可视化监测系统和交流电磁场裂纹可视化监测与评估方法 |
Country Status (3)
Country | Link |
---|---|
US (1) | US20240019399A1 (zh) |
AU (1) | AU2022308214A1 (zh) |
WO (1) | WO2023280023A1 (zh) |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN116413332A (zh) * | 2023-06-12 | 2023-07-11 | 中国石油大学(华东) | 水下结构裂纹柔性阵列监测探头 |
Families Citing this family (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN118549757B (zh) * | 2024-07-30 | 2024-10-11 | 青岛理研电线电缆有限公司 | 一种电缆裂纹检测方法 |
Citations (14)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2006292496A (ja) * | 2005-04-08 | 2006-10-26 | Ishikawajima Inspection & Instrumentation Co | 交流電磁場測定法による探傷検査装置及び方法 |
JP2008267943A (ja) * | 2007-04-19 | 2008-11-06 | Taisei Corp | ひび割れ検出方法 |
CN101701934A (zh) * | 2009-11-16 | 2010-05-05 | 中国石油大学(华东) | Acfm缺陷智能可视化检测系统 |
CN102495129A (zh) * | 2011-11-23 | 2012-06-13 | 北京理工大学 | 一种金属损伤的可调节磁激励阵列检测方法与装置 |
CN102520059A (zh) * | 2011-12-30 | 2012-06-27 | 南昌航空大学 | 基于扰动磁场检测仪的电路装置 |
CN107132270A (zh) * | 2017-06-27 | 2017-09-05 | 华东交通大学 | 一种探伤仪 |
CN108375629A (zh) * | 2018-01-30 | 2018-08-07 | 昆明理工大学 | 一种基于柔性pcb技术的脉冲涡流无损检测系统 |
CN110230976A (zh) * | 2019-05-14 | 2019-09-13 | 桂林理工大学 | 一种无损检测钢轨滚动接触疲劳裂纹扩展垂直深度的方法 |
CN110243923A (zh) * | 2019-06-19 | 2019-09-17 | 中国石油大学(华东) | 基于交流电磁场的腐蚀缺陷可视化成像及评估方法 |
CN111122697A (zh) * | 2019-12-26 | 2020-05-08 | 兰州空间技术物理研究所 | 一种基于脉冲涡流的导电材料缺陷高精度成像检测方法 |
CN112215810A (zh) * | 2020-09-27 | 2021-01-12 | 武汉大学 | 一种疲劳测试裂纹监测方法及装置 |
CN112858467A (zh) * | 2021-04-09 | 2021-05-28 | 中国石油大学(华东) | 一种旋转电磁场管道任意方向裂纹检测探头及检测系统 |
CN113390955A (zh) * | 2021-07-08 | 2021-09-14 | 中国石油大学(华东) | 交流电磁场裂纹可视化监测与评估方法 |
CN113390954A (zh) * | 2021-07-08 | 2021-09-14 | 中国石油大学(华东) | 基于交流电磁场的水下结构裂纹扩展可视化监测系统 |
-
2022
- 2022-06-28 US US18/025,188 patent/US20240019399A1/en active Pending
- 2022-06-28 AU AU2022308214A patent/AU2022308214A1/en active Pending
- 2022-06-28 WO PCT/CN2022/102039 patent/WO2023280023A1/zh active Application Filing
Patent Citations (14)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2006292496A (ja) * | 2005-04-08 | 2006-10-26 | Ishikawajima Inspection & Instrumentation Co | 交流電磁場測定法による探傷検査装置及び方法 |
JP2008267943A (ja) * | 2007-04-19 | 2008-11-06 | Taisei Corp | ひび割れ検出方法 |
CN101701934A (zh) * | 2009-11-16 | 2010-05-05 | 中国石油大学(华东) | Acfm缺陷智能可视化检测系统 |
CN102495129A (zh) * | 2011-11-23 | 2012-06-13 | 北京理工大学 | 一种金属损伤的可调节磁激励阵列检测方法与装置 |
CN102520059A (zh) * | 2011-12-30 | 2012-06-27 | 南昌航空大学 | 基于扰动磁场检测仪的电路装置 |
CN107132270A (zh) * | 2017-06-27 | 2017-09-05 | 华东交通大学 | 一种探伤仪 |
CN108375629A (zh) * | 2018-01-30 | 2018-08-07 | 昆明理工大学 | 一种基于柔性pcb技术的脉冲涡流无损检测系统 |
CN110230976A (zh) * | 2019-05-14 | 2019-09-13 | 桂林理工大学 | 一种无损检测钢轨滚动接触疲劳裂纹扩展垂直深度的方法 |
CN110243923A (zh) * | 2019-06-19 | 2019-09-17 | 中国石油大学(华东) | 基于交流电磁场的腐蚀缺陷可视化成像及评估方法 |
CN111122697A (zh) * | 2019-12-26 | 2020-05-08 | 兰州空间技术物理研究所 | 一种基于脉冲涡流的导电材料缺陷高精度成像检测方法 |
CN112215810A (zh) * | 2020-09-27 | 2021-01-12 | 武汉大学 | 一种疲劳测试裂纹监测方法及装置 |
CN112858467A (zh) * | 2021-04-09 | 2021-05-28 | 中国石油大学(华东) | 一种旋转电磁场管道任意方向裂纹检测探头及检测系统 |
CN113390955A (zh) * | 2021-07-08 | 2021-09-14 | 中国石油大学(华东) | 交流电磁场裂纹可视化监测与评估方法 |
CN113390954A (zh) * | 2021-07-08 | 2021-09-14 | 中国石油大学(华东) | 基于交流电磁场的水下结构裂纹扩展可视化监测系统 |
Non-Patent Citations (1)
Title |
---|
XINAN YUAN, WEI LI, XIAOKANG YIN, GUOMING CHEN, JIANMING ZHAO, WEIYU JIANG, ZHAN ZHANG, RUIQI XUE: "Visual Reconstruction of Irregular Crack in Austenitic Stainless Steel Based on ACFM Technique", JIXIE GONEHENG XUEBAI - CHINESE JOURNAL OF MECHANICAL ENGINEERING, JIXIE GONGYE CHUBANCHE, BEIJING, CN, vol. 56, no. 10, 1 January 2020 (2020-01-01), CN , pages 27, XP093022565, ISSN: 0577-6686, DOI: 10.3901/JME.2020.10.027 * |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN116413332A (zh) * | 2023-06-12 | 2023-07-11 | 中国石油大学(华东) | 水下结构裂纹柔性阵列监测探头 |
CN116413332B (zh) * | 2023-06-12 | 2023-09-08 | 中国石油大学(华东) | 水下结构裂纹柔性阵列监测探头 |
Also Published As
Publication number | Publication date |
---|---|
AU2022308214A1 (en) | 2024-02-29 |
US20240019399A1 (en) | 2024-01-18 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
WO2023280023A1 (zh) | 基于交流电磁场的水下结构裂纹扩展可视化监测系统和交流电磁场裂纹可视化监测与评估方法 | |
CN110231394B (zh) | 基于交流电磁场的非铁磁性材料不规则裂纹成像方法 | |
JP4814511B2 (ja) | パルス渦電流センサプローブ及び検査方法 | |
CN110243922B (zh) | 铁磁性材料不规则裂纹acfm可视化成像方法 | |
CN113390955B (zh) | 交流电磁场裂纹可视化监测与评估方法 | |
CN110243923B (zh) | 基于交流电磁场的腐蚀缺陷可视化成像及评估方法 | |
KR101085563B1 (ko) | 자기센서를 이용한 냉연강판의 개재물 탐상 장치 | |
US9494558B2 (en) | Flaw-detection apparatus and flaw-detection method | |
CN110231397A (zh) | 一种多通道脉冲涡流在线监测系统与监测方法 | |
CN110687208A (zh) | 一种基于双曲线定位的无基准Lamb波损伤监测方法 | |
CN107843642B (zh) | 一种海洋结构物缺陷交流电磁场三维成像检测探头 | |
Ye et al. | Flexible array probe with in-plane differential multichannels for inspection of microdefects on curved surface | |
CN113390954B (zh) | 基于交流电磁场的水下结构裂纹扩展可视化监测系统 | |
CN112782650B (zh) | 一种基于正方体阵列的声发射源定位方法及系统 | |
JP4650167B2 (ja) | 欠陥検出方法および欠陥検出装置 | |
CN110763755A (zh) | 一种可快速评估金属材料裂纹类缺陷方向的评定方法 | |
US20180266993A1 (en) | Non-destructive evaluation of additive manufacturing components | |
KR101966168B1 (ko) | 비파괴 검사를 위한 와전류 검사 장치 | |
WO2024000981A1 (zh) | 一种内穿式弱磁检测探头及其工作方法 | |
CN111398409A (zh) | 基于交流电磁场的水下导电金属材料裂纹剖面重构方法 | |
CN207636538U (zh) | 一种金属管道腐蚀缺陷检测用低频电磁阵列传感器 | |
WO2018217626A1 (en) | Non-destructive evaluation of additive manufacturing components | |
CN112067171A (zh) | 一种油气管道交流电磁场应力成像的内检测装置及方法 | |
CN108896609B (zh) | 一种金属材料不连续性交直流激励检测装置及方法 | |
JP2007163263A (ja) | 渦電流探傷センサ |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 22836777 Country of ref document: EP Kind code of ref document: A1 |
|
WWE | Wipo information: entry into national phase |
Ref document number: 18025188 Country of ref document: US |
|
WWE | Wipo information: entry into national phase |
Ref document number: AU2022308214 Country of ref document: AU |
|
NENP | Non-entry into the national phase |
Ref country code: DE |
|
ENP | Entry into the national phase |
Ref document number: 2022308214 Country of ref document: AU Date of ref document: 20220628 Kind code of ref document: A |