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 PDF

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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
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signal
module
matrix
crack
electromagnetic field
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PCT/CN2022/102039
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English (en)
French (fr)
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袁新安
李伟
陈国明
殷晓康
李肖
赵建明
赵建超
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中国石油大学(华东)
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Priority claimed from CN202110772687.0A external-priority patent/CN113390954B/zh
Priority claimed from CN202110772811.3A external-priority patent/CN113390955B/zh
Application filed by 中国石油大学(华东) filed Critical 中国石油大学(华东)
Priority to AU2022308214A priority Critical patent/AU2022308214A1/en
Priority to US18/025,188 priority patent/US20240019399A1/en
Publication of WO2023280023A1 publication Critical patent/WO2023280023A1/zh

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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N27/00Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
    • G01N27/72Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating magnetic variables
    • G01N27/82Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating magnetic variables for investigating the presence of flaws
    • G01N27/83Investigating 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
    • G01N27/85Investigating 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
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N27/00Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
    • G01N27/72Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating magnetic variables
    • G01N27/82Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating magnetic variables for investigating the presence of flaws

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  • 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.

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Abstract

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和交流电磁场裂纹可视化监测与评估方法,涉及无损检测缺陷评估技术领域,包括:利用线圈设计制作交流电磁场监测传感阵列,封装形成交流电磁场监测传感模组,设计功率放大电路为交流电磁场监测传感模组提供激励信号,设计差分放大电路对微弱传感信号进行放大,设计多路复用电路实现多路传感信号的分时复用,设计信号滤波放大电路对信号进一步滤波放大,设计检波电路将交流信号转化为直流信号,采用ni采集卡实现激励信号发生、多路复用控制信号输出和信号采集,最终实现结构裂纹扩展可视化监测信号的处理和采集。

Description

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
本公开要求2021年7月8日提交中国国家知识产权局、申请号为202110772811.3、发明名称为“交流电磁场裂纹可视化监测与评估方法”的中国专利申请的优先权,同时,公开要求2021年7月8日提交中国国家知识产权局、申请号为202110772687.0、发明名称为“基于交流电磁场的结构裂纹扩展可视化监测系统”的中国专利申请的优先权,二者的全部内容通过引用结合在本公开中。
技术领域
本发明涉及结构健康监测技术领域,尤其涉及一种基于交流电磁场的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。
背景技术
海洋结构物长期在海水环境中服役,由于海水腐蚀作用,结构表面很容易产生各类腐蚀缺陷。由于涂层覆盖、附着物堆积等因素,传统无损检测技术在水下结构物检测过程中需要在大面积清理附着物、彻底破坏涂层情况下对缺陷进行检测和评估,作业工序复杂,效率低下,结构表面清理和涂层修复成本高昂。尤其在深水区域,例行检测作业间隔周期长,造成初级萌生裂纹漏检。
交流电磁场检测(Alternating Current Field Measurement-ACFM)技术是一种新兴电磁无损检测技术,主要用于导电材料表面裂纹检测,其利用检测探头在导电试件表面感应出的均匀电流,电流在缺陷周围产生扰动引起空间磁场畸变,通过测量畸变磁场进行缺陷的检测和评估。当无缺陷存在时,导电试件表面电流呈均匀状态,空间磁场无扰动。由于具有非接触测量、定量评估等优势,广泛应用于各类海洋结构物缺陷检测。现有ACFM技术依据特征信号Bx、Bz及蝶形图进行缺陷判定,其中Bx和Bz信号分别为平行于试件表面(与探头扫查方向平行)和垂直于试件表面的磁场信号,特征信号Bx可对裂纹深度评估,特征信号Bz对裂纹长度评估。
传统ACFM检测系统探头为立体壳状结构,无法适应结构关键节点贴合;同时传感器排布也为单点或线阵,不能够实现面积区域裂纹监测;ACFM硬件系统适用于单阵列或少数阵 列传感器信号处理,不能满足大规模监测传感器信号采集与处理,此外采用常规Bx和Bz幅值特征信号不能显示裂纹扩展端点和边缘图像,无法满足实时可视化监测需求。
发明内容
针对上述问题,本发明提供了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,柔性监测传感阵列实时获取结构表面畸变磁场信号,同时对该信号进行处理和采集,为海洋结构物缺陷检测评估、寿命预测提供精准、实时数据来源支撑。
本申请的一种典型的实施方式中,提供了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,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。
可选地,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。
可选地,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。
可选地,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。
针对上述问题,本发明提供了一种基于交流电磁场的结构裂纹可视化监测与评估方法,实时呈现裂纹监测可视化图像,同时计算裂纹长度,并对裂纹是否扩展和裂纹扩展类型进行判定,为海洋结构物缺陷评估、寿命预测提供精准、实时数据支撑。
本发明提供了一种基于交流电磁场检测技术的结构裂纹可视化监测与评估方法,包括:
步骤一,通过PCB激励模块在试件表面产生均匀感应电流,感应电流引起空间磁场畸变,利用m行n列线圈组成的柔性监测传感阵列置于试件表面,提取监测区域初时刻Z方向当前磁场信号Bz0矩阵
Figure PCTCN2022102039-appb-000001
随着时间推移实时获取所述试件表面Z方向实时磁场信号Bz矩阵
Figure PCTCN2022102039-appb-000002
对所述矩阵A进行线性插值并绘制强度图,得到结构关键节点裂纹监测的可视化图像;
步骤二,求取矩阵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;
步骤三,按照式
Figure PCTCN2022102039-appb-000003
Figure PCTCN2022102039-appb-000004
分别求取a组数据与b组数据的信号质心,xi为九个元素X坐标位置,yi为九个元素Y坐标位置,得到裂纹的两个端点坐标(xa,ya)和(xb,yb),由两个端点坐标之间距离计算得到裂纹长度;
步骤四,将所述矩阵A减去所述矩阵A0得到信号增量矩阵
Figure PCTCN2022102039-appb-000005
步骤五,按公式
Figure PCTCN2022102039-appb-000006
求取所述矩阵A0的能量值E0和所述信号增量矩阵C的能量值Ec,求取Ec与E0的比值得到能量畸变率ΔE;
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。
本发明提供的基于交流电磁场检测技术的结构裂纹可视化监测与评估方法,利用交流电 磁场监测传感阵列在试件表面放置监测,实时获取试件表面Z方向磁场信号Bz矩阵A并保存初始Z方向磁场信号Bz矩阵A0,实时的将Z方向磁场信号Bz矩阵A进行线性插值并绘制强度图得到结构裂纹监测的可视化图像,求取Z方向磁场信号Bz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)为中心的九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,分别求取a组数据与b组数据的信号质心得到裂纹的两个端点坐标(xa,ya)和(xb,yb),进而计算得到裂纹长度,将Z方向磁场信号Bz矩阵A与初始Z方向磁场信号Bz矩阵A0做差得到信号增量矩阵C,求取初始Z方向磁场信号Bz矩阵A0的能量值E0和信号增量矩阵C的能量值Ec,求取Ec与E0的比值得到能量畸变率ΔE并与设定好的能量阈值N进行比较,若ΔE>N,则裂纹已扩展,进一步的,若信号增量矩阵C中存在元素小于噪声阈值N1,则裂纹为长度扩展,否则为深度扩展,最终实现结构裂纹的可视化监测与评估。
本发明提供的基于交流电磁场检测技术的结构裂纹扩展可视化监测硬件系统,利用线圈设计制作交流电磁场监测传感阵列,封装形成交流电磁场监测传感模组,设计功率放大模块为交流电磁场监测传感模组提供激励信号,设计AD620差分放大模块对微弱传感信号进行放大,设计多路复用模块实现多路传感信号的分时复用,设计信号放大滤波模块对信号进一步放大滤波,设计检波模块将交流信号转化为直流信号,采用NI采集卡实现激励信号发生、多路复用控制信号输出和信号采集,最终实现结构裂纹扩展可视化监测信号的处理和采集。
附图说明
图1为本发明实施例提供的系统框图;
图2为本发明实施例提供的柔性交流电磁场监测传感模组;
图3为本发明实施例提供的交流电磁场监测仪;
图4为本发明实施例提供的柔性PCB激励模块;
图5为本发明实施例提供的柔性监测传感阵列;
图6为本发明实施例提供的交流电磁场监测硬件系统;
图7为本发明实施例提供的裂纹可视化监测图像;
图8为本发明实施例提供的交流电磁场缺陷在线智能判定与分类识别方法流程图;
图9为本发明实施例提供的交流电磁场监测传感阵列;
图10为本发明实施例提供的结构裂纹监测的可视化图像;
图11为本发明实施例提供的矩阵元素分组示意图;
图12为本发明实施例提供的裂纹深度扩展监测示意图;
图13为本发明实施例提供的裂纹长度扩展监测示意图。
上图中:1、计算机;2、USB数据线;3、交流电磁场监测仪;3.1、信号调理模块;3.1.1、AD620差分放大模块;3.1.2、多路复用模块;3.1.3、放大滤波模块;3.1.4、检波模块;3.2、信号采集模块;3.3、稳压模块;3.4、功率放大模块;4、柔性交流电磁场监测传感模组;4.1、柔性PCB激励模块;4.2、柔性监测传感阵列。
具体实施方式
结合附图1-13,对本发明作进一步的描述:
为使本发明的目的、技术方案和优点更加清楚,下面结合附图及具体实施例对本发明作进一步的详细描述,显然,所描述的实施例只是本发明一部分实施例,而不是全部实施例。基于本发明的实施例,本领域的技术人员在不付出创造性劳动的前提下获取的其他实施例,都属于本发明保护的范围。
需要说明的是,在不冲突的情况下,本发明的实施例和实施例中的特征可以相互组合。
实施例一
本发明实施例提供的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,主要包括:紧密贴附于被测表面的柔性交流电磁场监测传感模组4,交流电磁场监测仪3、USB数据线2和计算机1,所述柔性交流电磁场监测传感模组4包括柔性PCB激励模块4.1和柔性监测传感阵列4.2,所述交流电磁场监测仪3包括信号调理模块3.1、信号采集模块3.2、稳压模块3.3和功率放大模块3.4,所述计算机1通过USB数据线2与交流电磁场监测仪3中的信号采集模块3.2连接,如图1所示;
所述柔性PCB激励模块4.1采用2层双矩形传感线圈印制在柔性基底上,如图4所示,柔性基地可方便贴附,用于水下关键节点裂纹监测,解决传统交流电磁场立体结构不易安装和贴附的弊端,双矩形线圈内分别加载方向不同方向的激励信号,两个不同方向激励线圈可 在结构表面产生方向不同的涡流场,涡流场中心区域形成均匀场,当裂纹处于均匀场时引起电流扰动,进一步引起周围磁场畸变,所述柔性监测传感阵列4.2包括柔性平面PCB模块和固定在其上的8行8列的传感线圈,传感线圈拾取均匀电流区域内的畸变磁场,通过阵列传感器可形成面积型监测区域,通过线性插值可获取监测区域畸变磁场图像,实现关键节点裂纹可视化成像监测,传感线圈外径为2mm,内径为0.5mm,传感线圈匝数为500,传感线圈轴线与平面PCB垂直,传感器线圈之间中心距为4mm,如图5所示。传感线圈可由TMR、AMR、霍尔等磁场传感器替代。
所述稳压模块3.3将外部直流电源稳压后与信号调理模块3.1、信号采集模块3.2和功率放大模块3.4连接,所述柔性激励模块4.1与功率放大模块3.4的输出端连接,所述功率放大模块3.4的输入端与信号采集模块3.2的模拟信号输出端连接;信号采集模块可产生正弦激励信号,激励信号经过功率放大后加载至柔性激励模块的双矩形线圈中,加载方式为一侧矩形线圈内产生顺时针电流,另一侧矩形线圈内产生逆时针电流,使得柔性激励模块的矩形线圈加载不同方向的电流。
所述信号调理模块3.1包括AD620差分放大模块3.1.1、多路复用模块3.1.2、放大滤波模块3.1.3和检波模块3.1.4,所述AD620差分放大模块3.1.1的输入端与柔性监测传感阵列4.2连接,多路复用模块采用ADG1607芯片设计,放大滤波模块采用二阶低通和一阶高通有源滤波器组合形成带通滤波器,检波模块针对二极管检波电路进行设计,所述多路复用模块3.1.2的信号输入端与AD620差分放大模块3.1.1的信号输出端连接,所述多路复用模块3.1.2的控制信号输入端与信号采集模块3.2的数字信号输出端连接,所述多路复用模块3.1.2的信号输出端与放大滤波模块3.1.3的信号输入端连接,所述放大滤波模块3.1.3的信号输出端与检波模块3.1.4的信号输入端连接,所述检波模块3.1.4的信号输出端与信号采集模块3.2的模拟信号输入端连接。
传感线圈拾取均匀电流区域内微弱畸变磁场,通过AD620放大后输入至多路复用器,多路复用器可解决多个监测通道及传感线圈阵列信号处理问题,使用一套硬件处理系统可完成多阵列信号的处理,多路复用信号的控制信号由采集卡脉冲数字控制,解决多通道信号多路复用、多路采集的时序控制问题,多路复用信号经过放大滤波模块后进入检波电路,将正弦响应信号变为幅值信号,检测信号通过采集卡进行信号采集,采集完成后信号传递至计算机 内部软件处理。由于计算机与采集卡连接,计算机软件可控制采集卡脉冲触发多路复用,实现多路信号的准确分离,达到多路信号的复原。计算机内部软件根据多阵列传感器信号复原结果,利用幅值信号线性插值呈现监测区域畸变磁场图像,当裂纹萌生或扩展时可成像可视化监测图像,如图7所示。
该实施例的有益效果是:柔性监测传感模组能够适应结构关键节点的紧密贴合;传感阵列采用平面矩阵排布,能够实现一定面积区域内的裂纹监测,对监测信号稍加处理即可显示裂纹扩展端点和边缘图像,摆脱了传统ACFM对面区域检测的繁琐扫查,准确性高、实时性好,可不祛除附着物和涂层情况下对裂纹扩展实现长期、实时、定点的可视化监测,为海洋结构物腐蚀裂纹的监测、评估及寿命预测提供精准数据支撑。
实施例二
上述系统中的计算机执行基于交流电磁场检测技术的缺陷在线智能判定与分类识别方法,如图8所示,该方法包括:
S1,利用如图9所示交流电磁场监测传感阵列对试件表面16mm长的深度扩展裂纹进行监测,实时获取试件表面Z方向磁场信号Bz矩阵A并保存初始Z方向磁场信号Bz矩阵A0,计算机将Z方向磁场信号Bz矩阵A进行线性插值并绘制强度图得到如图10所示结构裂纹监测图像,可有效实现结构表面裂纹的实时成像和可视化监测。矩阵A的元素如下:
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
矩阵A0的元素如下:
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
S2,求取Z方向磁场信号Bz矩阵A的最大元素位置(16,4)与次最大元素位置(16,20),如图11所示,提取以(16,4)为中心的九个元素值及其位置作为a组数据,提取以(16,20)为中心的九个元素值及其位置作为b组数据。
S3,按照式
Figure PCTCN2022102039-appb-000007
Figure PCTCN2022102039-appb-000008
分别求取a组数据与b组数据的信号质心得到裂纹的两个端点坐标(15.956,4.961)和(15.824,19.422),进一步计算得到裂纹长度为14.462mm,在实时成像的基础上实现裂纹长度的定量评估。
S4,将矩阵A减去矩阵A0得到信号增量矩阵C,信号增量矩阵C的元素如下:
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
S5,按公式
Figure PCTCN2022102039-appb-000009
求取矩阵A0的能量值E0=0.333和信号增量矩阵C的能量值Ec=1.559,求取Ec与E0的比值得到能量畸变率ΔE=1.559/0.333=4.683;
S6,将能量畸变率ΔE与设定好的能量阈值N=0.5进行比较,显然ΔE>N,裂纹已扩展,上述步骤可实现裂纹扩展的判定与自主预测,在水下结构关键节点裂纹扩展预警方面有重要实践意义,在判定裂纹扩展的基础上进入步骤七;
S7,判断信号增量矩阵C中若存在元素小于预设噪声阈值N1=-0.2,显然S4步骤矩阵C中不存在元素小于-0.2,裂纹为深度扩展,如图12所示。在另一实施例中可判定裂纹长度扩展,如图13所示。上述在判定裂纹扩展的基础上进一步明确了裂纹扩展类型。上述方法不仅可以预测裂纹扩展,进一步明确裂纹扩展类型,为水下结构关键节点裂纹的精准、定量监测提供有效方法。
实施例三
本发明实施例提供的基于交流电磁场检测技术的缺陷在线智能判定与分类识别方法,如图8所示,包括:
S1,利用如图9所示交流电磁场监测传感阵列对试件表面16mm长的深度扩展裂纹进行监测,实时获取试件表面Z方向磁场信号Bz矩阵A并保存初始Z方向磁场信号Bz矩阵A0,计算机将Z方向磁场信号Bz矩阵A进行线性插值并绘制强度图得到如图10所示结构裂纹监测图像,可有效实现结构表面裂纹的实时成像和可视化监测。矩阵A的元素如下:
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
矩阵A0的元素如下:
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
S2,求取Z方向磁场信号Bz矩阵A的最大元素位置(16,4)与次最大元素位置(16,20),如图11所示,提取以(16,4)为中心的九个元素值及其位置作为a组数据,提取以(16,20)为中心的九个元素值及其位置作为b组数据。
S3,按照式
Figure PCTCN2022102039-appb-000010
Figure PCTCN2022102039-appb-000011
分别求取a组数据与b组数据的信号质心得到裂纹的两个端点坐标(15.956,4.961)和(15.824,19.422),进一步计算得到裂纹长度为14.462mm,在实时成像的基础上实现裂纹长度的定量评估。
S4,将矩阵A减去矩阵A0得到信号增量矩阵C,信号增量矩阵C的元素如下:
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
S5,按公式
Figure PCTCN2022102039-appb-000012
求取矩阵A0的能量值E0=0.333和信号增量矩阵C的能量值Ec=1.559,求取Ec与E0的比值得到能量畸变率ΔE=1.559/0.333=4.683;
S6,将能量畸变率ΔE与设定好的能量阈值N=0.5进行比较,显然ΔE>N,裂纹已扩展,上述步骤可实现裂纹扩展的判定与自主预测,在水下结构关键节点裂纹扩展预警方面有重要实践意义,在判定裂纹扩展的基础上进入步骤七;
S7,判断信号增量矩阵C中若存在元素小于预设噪声阈值N1=-0.2,显然S4步骤矩阵C中不存在元素小于-0.2,裂纹为深度扩展,如图12所示。在另一实施例中可判定裂纹长度扩展,如图13所示。上述在判定裂纹扩展的基础上进一步明确了裂纹扩展类型。上述方法不仅可以预测裂纹扩展,进一步明确裂纹扩展类型,为水下结构关键节点裂纹的精准、定量监测提供有效方法。
该实施例的有益效果是:通过对监测数据处理能够实现一定面积区域内的裂纹实时成像和可视化监测,实现了裂纹断点的确定与裂纹长度的评估,同时还可以实现裂纹是否扩展的判定和扩展类型的判别,准确性高、实时性好,可不祛除附着物和涂层情况下对裂纹扩展实现长期、实时、定点的可视化监测,为海洋结构物腐蚀裂纹的监测、评估及寿命预测提供精准数据支撑。
以上所述,仅为本发明的具体实施方式,但本发明的保护范围并不局限于此,任何熟悉本技术领域的技术人员在本发明揭露的技术范围内,可轻易想到变化或替换,都应涵盖在本发明的保护范围之内。因此,本发明的保护范围应所述以权利要求的保护范围为准。

Claims (16)

  1. 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。
  2. 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。
  3. 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。
  4. 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。
  5. 根据权利要求1所述的监测系统,其特征在于,所述计算机执行:
    步骤一:通过PCB激励模块PCB激励模块在试件表面产生均匀感应电流,感应电流引起空间磁场畸变,利用m行n列线圈组成的柔性监测传感阵列置于试件表面,获取监测区域初时刻Z方向当前磁场信号Bz0矩阵
    Figure PCTCN2022102039-appb-100001
    随着时间推移实时获取所述试件表面Z方向实时磁场信号Bz矩阵
    Figure PCTCN2022102039-appb-100002
    对所述矩阵A进行线性插值并绘制强度图,得到结构关键节点裂纹监测的可视化图像。
  6. 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。
  7. 根据权利要求6所述的监测系统,其特征在于,所述方法还包括:
    步骤三:按照式
    Figure PCTCN2022102039-appb-100003
    Figure PCTCN2022102039-appb-100004
    分别求取a组数据与b组数据的信号质心,xi为九个元素X坐标位置,yi为九个元素Y坐标位置,得到裂纹的两个端点坐标(xa,ya)和(xb,yb),由两个端点坐标之间距离计算得到裂纹长度。
  8. 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四:
    将所述矩阵A减去所述矩阵A0得到信号增量矩阵
    Figure PCTCN2022102039-appb-100005
  9. 根据权利要求8所述的监测系统,其特征在于,所述方法还包括步骤五:
    按公式
    Figure PCTCN2022102039-appb-100006
    求取所述矩阵A0的能量值E0和所述信号增量矩阵C的能量值Ec,求取Ec与E0的比值得到能量畸变率ΔE。
  10. 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。
  11. 一种交流电磁场裂纹可视化监测与评估方法,其特征在于,包括步骤一:
    通过PCB激励模块PCB激励模块在试件表面产生均匀感应电流,感应电流引起空间磁场畸变,利用m行n列线圈组成的柔性监测传感阵列置于试件表面,获取监测区域初时刻Z方向当前磁场信号Bz0矩阵
    Figure PCTCN2022102039-appb-100007
    随着时间推移实时获取所述试件表面Z方向实时磁场信号Bz矩阵
    Figure PCTCN2022102039-appb-100008
    对所述矩阵A进行线性插值并绘制强度图,得到结构关键节点裂纹监测的可视化图像。
  12. 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。
  13. 根据权利要求12所述的方法,其特征在于,包括步骤三:
    按照式
    Figure PCTCN2022102039-appb-100009
    Figure PCTCN2022102039-appb-100010
    分别求取a组数据与b组数据的信号质心,xi为九个元素X坐标位置,yi为九个元素Y坐标位置,得到裂纹的两个端点坐标(xa,ya)和(xb,yb),由两个端点坐标之间距离计算得到裂纹长度。
  14. 根据权利要求11所述的方法,其特征在于,包括步骤四:
    将所述矩阵A减去所述矩阵A0得到信号增量矩阵
    Figure PCTCN2022102039-appb-100011
  15. 根据权利要求14所述的方法,其特征在于,包括步骤五:
    按公式
    Figure PCTCN2022102039-appb-100012
    求取所述矩阵A0的能量值E0和所述信号增量矩阵C的能量值Ec,求取Ec与E0的比值得到能量畸变率ΔE。
  16. 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。
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Cited By (1)

* Cited by examiner, † Cited by third party
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)

* Cited by examiner, † Cited by third party
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)

* Cited by examiner, † Cited by third party
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

Patent Citations (14)

* Cited by examiner, † Cited by third party
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)

* Cited by examiner, † Cited by third party
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)

* Cited by examiner, † Cited by third party
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

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