Two-dimensional sensor network layout method for optimizing acoustic emission positioning precision

Abstract

The invention discloses a two-dimensional sensor network layout method for optimizing acoustic emission positioning precision, and discloses a collaborative optimization mechanism of a sensor envelope range and intra-region connection density on positioning precision by establishing a seismic source analysis positioning model under a non-velocity measurement condition and combining a plurality of groups of sensor layout contrast experiments. Experiments show that high-precision positioning with the average error smaller than or equal to 2.5 mm can be achieved by adopting the sensor combination with the serial numbers of 2, 3, 5, 6 and 9, and a reliable technical scheme is provided for rock mass engineering fracture monitoring.

Description

Technical Field

[0001] The present invention belongs to the technical field of nondestructive testing of rock materials, and specifically relates to a two-dimensional acoustic emission source positioning method based on sensor network layout optimization under non-velocity measurement conditions, which is suitable for high-precision positioning of fracture sources in rock engineering. Background Art

[0002] Rock fracture and instability are important causes of rock engineering disasters (such as rockbursts and slope instability). Accurate monitoring of the evolution mechanism of internal cracks is crucial for disaster prevention and control. Acoustic emission technology can dynamically track the location of the fracture source by capturing the elastic wave signals generated by rock fracture. However, existing acoustic emission positioning methods are mostly based on a single wave velocity model, and the anisotropy of rock materials leads to significant differences in wave velocity propagation paths, resulting in large positioning errors in traditional methods.

[0003] In the existing technology, although the Kundu method, Inglada method and USBM method treat the wave velocity as an unknown variable to improve the accuracy, they still rely on iterative algorithms, have high computational complexity and are easily affected by the initial value. In addition, there is a lack of systematic research on the impact of sensor layout on positioning accuracy. Especially under non-speed measurement conditions, the correlation mechanism between the spatial distribution of sensor networks and positioning accuracy has not yet been clarified. Summary of the invention

[0004] Aiming at the problem of insufficient acoustic emission positioning accuracy under non-speed measurement conditions in the prior art, the present invention proposes a two-dimensional positioning method based on sensor network layout optimization, and determines the optimal sensor configuration scheme by combining theoretical algorithms with experimental verification.

[0005] Technical Solution

[0006] The core of the present invention is to establish an analytical model for earthquake source location under non-velocity measurement conditions, combine multiple sets of sensor layout comparison experiments, reveal the synergistic influence of sensor envelope range and connection density in the area on positioning accuracy, and finally determine a high-precision layout mode. The specific steps are as follows:

[0007] 1. Positioning algorithm construction

[0008] Based on the unknown parameters of the source position (x, y) in the two-dimensional plane, the time node t0 of the source generation and the wave velocity v, the sensor distance equation is established:

[0009]

[0010] Through the transformation of the linear equations and solving Cramer's law, a unique analytical solution is obtained, and the minimum number of sensors is 5.

[0011] 2. Experimental setup and process

[0012] Apparatus: 520mmx400mmx5mm marble plate, 6 ISAS03-150 piezoelectric sensors, 40dB preamplifier, AMSY-6 acoustic emission analyzer.

[0013] process:

[0014] a. Establish a coordinate system with the center of the marble slab as the origin, and use a broken lead (diameter 0.5mm, HB hardness) to simulate the earthquake source. The coordinates of the broken lead point are preset and determined;

[0015] b. Six sensors are arranged according to the preset layout, and the collected signals are amplified and recorded by the AMSY-6 acoustic emission analyzer;

[0016] C. Extract the arrival time of each sensor signal, select 5 sensor combinations (numbered 1, 2, 3, 4, 5, etc.), and calculate the source coordinates and wave velocity;

[0017] d. Eliminate invalid data with wave speed exceeding 3700-4300m / s, calculate the positioning error and standard deviation, and draw a heat map to analyze the effective positioning range.

[0018] 3. Layout Optimization Guidelines

[0019] Sensor envelope range: The larger the coverage area, the higher the positioning accuracy;

[0020] Density of connections within the area: The denser the sensors are distributed near the diagonal lines of the target area, the more significant the improvement in accuracy.

[0021] Beneficial Effects

[0022] The present invention significantly improves the accuracy and reliability of acoustic emission source positioning by optimizing the sensor network layout and constructing an analytical positioning model under non-velocity measurement conditions, which is specifically reflected in the following aspects:

[0023] ① High-precision positioning. Through the coordinated optimization of the sensor envelope range (≥80% coverage) and the connection density in the area (≥3 sensors in the key area), the average positioning error of the optimal layout combination was experimentally verified to be reduced to 6.23mm, with a standard deviation of 3.8mm, which is more than 40% higher than the traditional method;

[0024] ② Simplify the operation process. No need to measure the wave velocity in advance, the source coordinates and wave velocity can be directly solved through the analytical model, eliminating the wave velocity error caused by rock anisotropy, reducing manual intervention and calculation complexity;

[0025] ③ Wide applicability. It is applicable to anisotropic rock materials and can effectively monitor the rupture sources in engineering disasters such as rock bursts and slope instability, providing reliable technical support for disaster early warning;

[0026] ④ Efficiency and economy. The analytical model is based on Cramer's law to achieve fast solution, avoiding the time-consuming problem of iterative algorithm. At the same time, only 5 sensors are needed to complete positioning, reducing the cost of equipment deployment;

[0027] ⑤ Data-driven optimization: Through error screening (eliminating data with wave speeds outside the range of 4000±300m / s) and heat map analysis, the positioning accuracy and effective positioning area are clarified to enhance the pertinence and reliability of engineering applications.

[0028] The technical solution of the present invention has both theoretical innovation and engineering practicality, and provides an efficient and low-cost technical means for non-destructive testing and safety monitoring of rock mass engineering. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings of the embodiments will be briefly introduced below. Obviously, the drawings in the following description only relate to some embodiments of the present invention, but are not intended to limit the present invention.

[0030] Figure 1 : Schematic diagram of experimental equipment connection;

[0031] Figure 2 : Sensor layout and lead break point coordinate distribution (5 groups of comparison);

[0032] Figure 3 : Scatter plot of positioning results of 5 groups of experiments;

[0033] Figure 4 : Comparison of average positioning error and standard deviation;

[0034] Figure 5 : Positioning heat map, reflecting the effective coverage of different layouts. DETAILED DESCRIPTION

[0035] 1. Select a marble flat plate sample of 520mm×400mm×5mm, and establish a rectangular coordinate system with the center of the sample as the origin. Break the lead on the sample to simulate the earthquake source. The lead core used for breaking the lead has a diameter of 0.5mm and a hardness of HB. When breaking the lead, the lead core extends 2.5mm and maintains a 30° angle with the sample surface.

[0036] 2. Six acoustic emission sensors are dispersed on the surface of the sample to detect the acoustic emission source signal. The source signal is amplified by a 40dB preamplifier, transmitted to the valve acoustic emission signal analyzer (AMSY-6) and recorded by a computer. After obtaining the waveform data of the acoustic emission signal, the arrival time of each sensor can be picked up using the analysis software provided by the system.

[0037] 3. After each lead break, the sensor will receive the acoustic emission signal generated by the lead break. According to the difference in the arrival time of the sensor receiving the signal, 5 sensors with "irregular broken line distribution" are selected to form a group, and the coordinates and wave speed v of different lead break positions are calculated. The calculated coordinates are compared with the lead break coordinates to analyze the positioning accuracy of the sensors under different layout methods.

[0038] 4. Select 5 of the 6 deployed sensors to form a sensor array to locate and invert the earthquake source, and a total of 5 groups can be formed. The first group of array sensors are numbered 1, 2, 3, 4, 5; the second group of array sensors are numbered 1, 2, 3, 4, 6; the third group of array sensors are numbered 1, 2, 3, 5, 6; the fourth group of array sensors are numbered 1, 2, 4, 5, 6; the fifth group of array sensors are numbered 2, 3, 4, 5, 6.

[0039] 5. The wave velocity v of the sample is in the range of about 4000±300m / s. Therefore, in the calculation process, the data of v<3700m / s and v>4300m / s are regarded as invalid positioning. In order to ensure the validity of the experimental results as much as possible, these data are eliminated in the positioning results.

[0040] 6. After excluding invalid coordinates, the positioning results of 5 groups of experiments were obtained ( Figure 3 ), compare the error levels of each group of experiments, and calculate the average error and standard deviation of each group of positioning experiments based on the distance error between the positioning point coordinates calculated for each lead break and the lead break position ( Figure 4 ), and analyze the positioning accuracy based on this.

[0041] 7. The heat map can be used to intuitively see the correlation between data. In the positioning experiment, the closer the positioning result is to the source location, the stronger the correlation is. Based on this, a heat map of the source location of each group of experiments is made ( Figure 5 ) to determine the effective positioning range for each set of experiments.

[0042] 8. In the experiment, the second group of sensor layouts (numbers 1, 2, 3, 4, 6) has an average positioning error of 6.23mm (standard deviation 3.8mm) and is significantly better than other combinations because of its envelope coverage of 85% and the highest target area connection density. The heat map shows that its effective positioning area is expanded by 35%, verifying the reliability of the layout optimization criteria.

Claims

1. A two-dimensional sensor network layout method for optimizing acoustic emission positioning accuracy, characterized in that The following steps are involved: Based on the non-velocity measurement condition, a seismic source location analysis model is established. When each sensor receives the seismic source signal at the time node t i (i=1,2,…n), corresponding to the sensor coordinate S i (x i ,y i )(i=1,2,…n), the source coordinates (x,y), the time point t0 of the source generation, and the wave velocity v are solved by combining the sensor distance equations; Six acoustic emission sensors (numbered 1, 2, 3, 4, 5, and 6) were placed on the surface of the marble slab in five different combinations, and the signals were collected and the positioning error was calculated through the lead breaking experiment. According to the synergistic effect of the sensor envelope range and the connection density in the area on the positioning accuracy, the optimal layout is determined to be a combination of sensor numbers 1, 2, 3, 4, and 6.

2. The method according to claim 1, characterized in that The analytical model solves a system of linear equations using Cramer's rule, which is of the form: AX=B The matrix A and vector B are constructed by the sensor coordinates and the arrival time difference, and the solution vector X contains x, y, v, and t0.

3. The method according to claim 1, characterized in that In the sensor layout, the envelope range covers more than 80% of the marble slab, and each unit area in the target area includes at least 2 sensors.

4. The method according to claim 1, characterized in that By excluding the invalid coordinates and obtaining the positioning results, the error levels of each group of experiments were compared and the positioning accuracy was analyzed.

5. The method according to claim 1, characterized in that The correlation between the positioning results and the source position was analyzed through heat map analysis, the effective positioning area was screened, and the data points with wave speed outside the range of 4000±300m / s were eliminated.

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