Low-frequency time-harmonic multi-component electromagnetic detection method

Abstract

The invention discloses a low-frequency time-harmonic multi-component electromagnetic detection method, and particularly relates to the technical field of geophysical exploration, and the method comprises the steps: S1, transmitting an excitation signal; s2, receiving a signal; s3, signal processing; and S4, conversion imaging. The low-frequency time-harmonic field technology is adopted, the limitation that the detection depth of a traditional ground penetrating radar is small is broken through, the detection depth can reach 0-100 m, the requirement for urban deep underground space detection can be met, the detection depth is large, through collection of multi-component electromagnetic signals and processing of an intelligent inversion algorithm, the geometric parameters of a deep stratum underground target body can be inverted, and the detection accuracy of the ground penetrating radar is improved. The method has the advantages that the resolution is higher than 5% of the depth, fine detection of an underground target body is achieved, the resolution is high, the phase alternating emission technology, the data accumulation averaging technology, the ultra-low noise amplification technology and the like are adopted, base value deviation, external interference signals and noise of a measurement system are effectively restrained, the signal-to-noise ratio and stability of the system are improved, and the anti-jamming capability is high.

Description

Technical Field

[0001] The present invention relates to the field of geophysical detection technology, and in particular to a low-frequency time-harmonic multi-component electromagnetic detection method. Background Art

[0002] With the rapid development of cities, the development and utilization of deep underground space in cities has received increasing attention. However, the current development of urban underground space faces the problem of unclear deep underground information. Traditional detection methods such as ground penetrating radar have technical bottlenecks such as shallow detection depth and poor resolution, which cannot meet the needs of precise detection of deep underground space in cities. In addition, the urban underground environment is complex and contains various interference signals. How to improve the accuracy and anti-interference ability of detection is also an urgent problem to be solved. With the rapid advancement of urbanization and the continuous expansion of urban scale, the development and utilization of deep underground space in cities is becoming increasingly urgent. Deep underground space in cities contains rich resources. The rational development and utilization of underground space is of vital importance to alleviating urban land shortages, optimizing urban infrastructure layout, and improving the comprehensive carrying capacity of cities. For example, the construction of underground transportation networks (such as subways and underground tunnels), underground commercial facilities, underground storage space, and underground integrated pipeline corridors requires a detailed and accurate understanding of the geological structure, geotechnical properties, and hydrogeological conditions of the deep underground space.

[0003] However, the current development of urban underground space faces the serious problem of unclear deep underground information. Traditional detection methods such as ground penetrating radar have many technical bottlenecks in the detection of deep underground space in cities. Ground penetrating radar is a commonly used geophysical detection method. Its working principle is to detect underground targets based on the propagation characteristics of electromagnetic waves in different media. However, in the detection of deep underground space in cities, the detection depth of ground penetrating radar is relatively shallow. It can generally only detect a depth range of several meters to tens of meters underground, which is difficult to meet the detection needs of deep underground space in cities (usually up to hundreds of meters or even deeper). At the same time, the resolution of ground penetrating radar is also poor. It is difficult to achieve clear and accurate imaging and identification of some small-sized targets with unclear dielectric constant differences underground, which cannot meet the needs of fine detection of deep underground space in cities. Summary of the Invention

[0004] The main purpose of the present invention is to provide a low-frequency time-harmonic multi-component electromagnetic detection method, which can effectively solve the problems of shallow detection depth and poor resolution.

[0005] To achieve the above object, the technical solution adopted by the present invention is:

[0006] A low-frequency time-harmonic multi-component electromagnetic detection method comprises the following steps:

[0007] S1. Transmitting excitation signal: The transmitting antenna is used to generate a primary field of a low-frequency time-harmonic field, which forms an eddy current in the formation. The frequency range of the low-frequency time-harmonic field is 20KHz to 10MHz.

[0008] S2. Signal reception: Measure the scattered field signal of the anomaly through the receiving antenna. The scattered field signal includes multi-component signals of electric field and magnetic field.

[0009] S3. Signal processing: Use intelligent inversion algorithms to process the measured multi-array electric and magnetic field information, and interpret the electrical parameters of the formation anomaly into geological entities;

[0010] S4. Conversion imaging: Generate a three-dimensional electrical structure image of the underground target body through an inversion algorithm.

[0011] Preferably, the transmitting antenna is a broadband induction coil with magnetic feedback.

[0012] Preferably, the receiving antenna includes a low-frequency broadband magnetic antenna and a low-frequency broadband electric field antenna, which operates at multiple frequency points in a broadband 20KHz to 10MHz to receive weak secondary field electromagnetic signals.

[0013] Preferably, the intelligent inversion algorithm is based on the least squares algorithm and the Green's function, and the inversion problem is regarded as a minimization problem of the objective function and is solved iteratively using the Newton minimization method.

[0014] Preferably, the objective function is Where μ is the Lagrange multiplier, d is the measured data, F(m) is the model prediction data, m is the model parameter vector, m0 is the prior model parameter, C d is the covariance matrix of the measured data, C m is the covariance matrix of the prior model.

[0015] Preferably, in the S2 signal receiving step, technologies such as a pre-ultra-low noise amplifier, narrowband filtering, a balanced multiplication demodulator, and large dynamic automatic gain adjustment are used to perform low-noise amplification and demodulation on weak signals.

[0016] Preferably, the step S1 of transmitting the excitation signal adopts a phase alternating transmission technology.

[0017] Preferably, in the S4 conversion imaging step, a feature library of underground target bodies is constructed to study the response characteristics of electrical parameters of different target bodies and form an accurate, efficient and adaptive algorithm.

[0018] Compared with the prior art, the present invention has the following beneficial effects:

[0019] 1. The present invention breaks through the limitation of shallow detection depth of traditional ground penetrating radar by adopting low-frequency time-harmonic field technology. The detection depth can reach 0-100m, which can meet the needs of deep underground space detection in cities and has a large detection depth.

[0020] 2. The present invention can invert the geometric parameters of underground targets in deep strata (0-100m) through the collection of multi-component electromagnetic signals and the processing of intelligent inversion algorithms, with a resolution better than 5% of the depth, thus achieving fine detection of underground targets with high resolution.

[0021] 3. The present invention adopts phase-alternating transmission technology, data accumulation and averaging technology, and ultra-low noise amplification technology to effectively suppress the measurement system base value offset, external interference signals and noise, improve the system's signal-to-noise ratio and stability, and have strong anti-interference ability.

[0022] 4. The present invention constructs an underground target feature library and uses an intelligent inversion algorithm to realize intelligent detection and perception of underground target bodies, thereby improving the accuracy and efficiency of detection and having a high degree of intelligence. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a schematic diagram of the overall process of the present invention. DETAILED DESCRIPTION

[0024] In order to make the technical means, creative features, objectives and effects achieved by the present invention easier to understand, the present invention is further described below in conjunction with specific implementation methods.

[0025] like Figure 1 As shown, a low-frequency time-harmonic multi-component electromagnetic detection method includes the following steps:

[0026] S1. Transmitting excitation signal: The transmitting antenna is used to generate a primary field of a low-frequency time-harmonic field, which forms an eddy current in the formation. The frequency range of the low-frequency time-harmonic field is 20KHz~10MHz. The transmitting antenna is a wide-band induction coil with magnetic feedback. The logic controller controls the resonant impedance network switch of the magnetic induction coil by receiving commands from the host computer, so that the magnetic induction coil can operate at multiple frequency points of a wide band of 20KHz~10MHz. The logic controller can conveniently adjust the frequency of the output signal of the direct digital frequency synthesizer by changing the frequency control word. The output signal passes through a digital variable gain driver amplifier and a power amplifier to achieve signal power amplification and is transmitted to the formation through the resonant antenna.

[0027] S2. Signal reception: The scattered field signal of the anomaly is measured through the receiving antenna. The scattered field signal includes multi-component signals of the electric field and the magnetic field. The receiving antenna includes a low-frequency broadband magnetic antenna and a low-frequency broadband electric field antenna. The magnetic induction coil and the electric antenna switch the resonant impedance network switch through the control signal, so that the magnetic induction coil and the electric antenna can operate at multiple frequency points of a wide bandwidth of 20KHz to 10MHz, receive weak secondary field (abnormal) electromagnetic signals, amplify them through the ultra-low noise preamplifier, down-convert them to low frequency through the balanced multiplication demodulator, and then pass through the low-frequency filtering and amplification processor. After synchronous conversion by the high-precision 32-bit analog-to-digital signal converter, the weak signal is analog amplified and digitized.

[0028] S3. Signal processing: The intelligent inversion algorithm is used to process the measured multi-array electric and magnetic field information, and the electrical parameters of the formation anomaly are interpreted and imaged. The intelligent inversion algorithm is based on the least squares algorithm and Green's function, and the inversion problem is regarded as a minimization problem of the objective function. It is solved iteratively through the Newton minimization method.

[0029] S4. Conversion imaging: Construct a feature library of underground target bodies, study the response characteristics of electrical parameters of different target bodies, form accurate, efficient and adaptive algorithms, realize intelligent detection and perception of underground target bodies in a two-dimensional or three-dimensional modeling environment, and generate a three-dimensional electrical structure image of the underground target body through an inversion algorithm.

[0030] It should be noted that the Newton minimization method, the least squares algorithm and the Green function are all existing calculation methods. Their algorithm formulas will not be explained in detail. The intelligent inversion algorithm is based on the least squares algorithm and the Green function. It regards the inversion problem as a minimization problem of the objective function and uses the Newton minimization method to iteratively solve it. The objective function is Where μ is the Lagrange multiplier, d is the measured data, F(m) is the model prediction data, m is the model parameter vector, m0 is the prior model parameter, C d is the covariance matrix of the measured data, C m is the covariance matrix of the prior model.

[0031] In the signal receiving step, the pre-stage ultra-low noise amplifier, narrowband filtering, balanced multiplication demodulator, large dynamic automatic gain adjustment and other technologies are used to perform low-noise amplification and demodulation on weak signals. The high-resolution 32-bit analog-to-digital converter and real-time oversampling technology are used to improve the system signal-to-noise ratio and small signal detection capabilities.

[0032] In the step of transmitting the excitation signal, a phase-alternating transmission technology is used to alternately change the phase of the transmitting pulse between 0° and 180°, and subtract the echo signal to suppress the measurement system base value offset and external interference signals.

[0033] The S1 excitation signal transmission step and the S2 signal receiving step involve a low-frequency broadband alternating electromagnetic field transmission system, a low-frequency broadband high-sensitivity receiving circuit system and a position and attitude combined measurement system. The low-frequency broadband alternating electromagnetic field transmission system is mainly composed of a broadband induction coil with magnetic feedback, a coil impedance resonance network, a broadband high-power switching amplifier, a broadband gain-adjustable power driver amplifier, a direct digital frequency synthesizer, a power divider, and logic control. The low-frequency broadband high-sensitivity receiving circuit system is mainly composed of a broadband induction coil, a coil impedance resonance network, an electric antenna and an antenna impedance resonance network, a pre-low noise amplifier, a balanced multiplication demodulator, an intermediate frequency amplification and filtering processor, a driving operational amplifier, and a high-precision 32-bit AD analog-to-digital converter. The position and attitude combined measurement system is composed of a laser level, a rangefinder, and an automatic attitude adjustment platform, which can ensure that the working planes of the transmitting coil and the receiving coil are perpendicular and the centers are at the same height, and measure and record the distance between the transmitter and the receiver in real time.

[0034] In detail, the logic controller controls the resonant impedance network switch of the magnetic induction coil by receiving commands from the host computer, so that the magnetic induction coil can work at multiple frequency points of 20KHz to 10MHz in a wide band. The logic controller can conveniently adjust the frequency of the output signal of the direct digital frequency synthesizer by changing the frequency control word. The output signal passes through the digital variable gain driver amplifier and the power amplifier to achieve signal power amplification, and is transmitted to the formation through the resonant antenna. The magnetic induction coil and the electric antenna switch the resonant impedance network switch through the control signal, so that the magnetic induction coil and the electric antenna can work at multiple frequency points of 20KHz to 10MHz in a wide band, receive weak secondary field (abnormal) electromagnetic signals, amplify them through the ultra-low noise preamplifier, down-convert them to low frequency through the balanced multiplication demodulator, and then pass through the low-frequency filter amplification processor. After synchronous conversion by the high-precision 32-bit analog-to-digital signal converter, the weak signal analog amplification and digitization are realized;

[0035] The laser leveling instrument can ensure that the centers of the transmitting coil measurement platform and the receiving coil measurement platform are in the same horizontal plane with high measurement accuracy. The automatic attitude modulation system can adjust the transmitting surface and the receiving surface to maintain the vertical direction to eliminate the direct coupling signal of the primary field. FPGA, SoC and other technologies are used to integrate the computing, storage and control modules to improve reliability. The integrated system integration design is carried out for each combination unit (alternating magnetic pair generation system, position attitude combination measurement system, low-frequency broadband high-sensitivity receiving system unit, etc.). In response to the high-precision time requirements of the multi-combination unit system, a high-precision time base unification and transmission method based on high-precision clock and high-stability crystal oscillator is established to solve the problem of coordinated control and synchronous acquisition of each combination unit system. Time synchronization redundancy is planned to be adopted. Coding technology is used to ensure reliable synchronization of multi-sensor time. Before preparing for operation, a pulse signal is sent to the alternating magnetic pair generating system, the position and attitude combined measurement system, the low-frequency broadband high-sensitivity receiving system unit, etc. at a certain agreed random interval and the signal sending time is recorded. The pulse reception time is recorded in the alternating magnetic pair generating system, the position and attitude combined measurement system, and the low-frequency broadband high-sensitivity receiving system unit. By matching the pulse sequence interval recorded using satellite time in the position and attitude combined measurement system with the pulse reception time recorded based on the internal clock of the alternating magnetic pair generating system and the low-frequency broadband high-sensitivity receiving system unit, the offset and drift law between the internal clock of each system unit and the satellite clock is calculated, and the time of each system unit is uniformly corrected to the satellite time system to ensure the synchronous operation of each system unit.

[0036] Example 1: Application of a low-frequency time-harmonic multi-component electromagnetic detection method provided by the present invention in deep underground spaces in cities is as follows:

[0037] First, the transmitting antenna and receiving antenna are arranged in the measurement area. The transmitting antenna adopts a wide-band induction coil with magnetic feedback. The transmitting frequency is set to 50KHz and the transmitting power is set to 100W through the logic controller. The receiving antenna includes a low-frequency broadband magnetic antenna and a low-frequency broadband electric field antenna. The receiving frequency is set to 50KHz, the gain of the pre-ultra-low noise amplifier is set to 120dB, the high-precision 32-bit analog-to-digital converter has a sampling rate of 15.6KHz, the maximum input signal is 1V, and the typical dynamic range of the detection signal is 128dB.

[0038] Depend on It can be deduced that the minimum detectable signal value is:

[0039] Then the transmitting system is started, and the transmitting antenna transmits the primary field of the low-frequency time-harmonic field to the formation. The primary field forms eddy currents in the formation and generates a secondary field. The receiving antenna collects the scattered field signal of the anomaly, including multi-component signals of the electric field and magnetic field. The collection time is 10 minutes, and the number of collected data points is 10,000.

[0040] The collected data is transmitted to the data processing system. The echo signal is first processed using phase alternating transmission technology to suppress interference signals. The signal is then subjected to low-noise amplification, demodulation, filtering, and analog-to-digital conversion to obtain a digital signal.

[0041] The digital signal is processed using an intelligent inversion algorithm. Based on the least squares algorithm and Green's function, the objective function is constructed and it is iteratively solved using the Newton minimization method to invert the electrical parameters of the anomaly in the formation. At the same time, the underground target body feature library is called to intelligently identify and interpret the inversion results to generate a three-dimensional image of the underground target body.

[0042] Through processing and analysis of actual measurement data, the detection depth reached 100m, the resolution was better than 5%, and the recognition accuracy was better than 70%, indicating that the low-frequency time-harmonic multi-component electromagnetic detection method of the present invention can effectively realize the fine detection and intelligent perception of target bodies in deep underground spaces in cities.

[0043] The basic principles, main features, and advantages of the present invention are shown and described above. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions are merely illustrative of the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of protection claimed in the present invention is defined by the appended claims and their equivalents.

Claims

1. A low-frequency time-harmonic multi-component electromagnetic detection method, characterized in that: The following steps are involved: S1. Transmitting excitation signal: The transmitting antenna is used to generate a primary field of a low-frequency time-harmonic field, which forms an eddy current in the stratum. The frequency range of the low-frequency time-harmonic field is 20KH. z ~10MH z ; S2. Signal reception: Measure the scattered field signal of the anomaly through the receiving antenna. The scattered field signal includes multi-component signals of electric field and magnetic field. S3. Signal processing: Use intelligent inversion algorithms to process the measured multi-array electric and magnetic field information, and interpret the electrical parameters of the formation anomaly into geological entities; S4. Conversion imaging: Generate a three-dimensional electrical structure image of the underground target body through an inversion algorithm.

2. A low-frequency time-harmonic multi-component electromagnetic detection method according to claim 1, characterized in that: The transmitting antenna is a broadband induction coil with magnetic feedback.

3. A low-frequency time-harmonic multi-component electromagnetic detection method according to claim 1, characterized in that: The receiving antenna includes a low-frequency broadband magnetic antenna and a low-frequency broadband electric field antenna. z ~10MH z It works at multiple frequencies and receives weak secondary field electromagnetic signals.

4. A low-frequency time-harmonic multi-component electromagnetic detection method according to claim 1, characterized in that: The intelligent inversion algorithm is based on the least squares algorithm and Green's function, and regards the inversion problem as a minimization problem of the objective function and uses the Newton minimization method to iteratively solve it.

5. A low-frequency time-harmonic multi-component electromagnetic detection method according to claim 4, characterized in that: The objective function is Where μ is the Lagrange multiplier, d is the measured data, F(m) is the model prediction data, m is the model parameter vector, m0 is the prior model parameter, C d is the covariance matrix of the measured data, C m is the covariance matrix of the prior model.

6. A low-frequency time-harmonic multi-component electromagnetic detection method according to claim 1, characterized in that: In the S2 signal receiving step, a pre-stage ultra-low noise amplifier, narrowband filtering, a balanced multiplication demodulator, a large dynamic automatic gain adjustment and other technologies are used to perform low-noise amplification and demodulation on the weak signal.

7. A low-frequency time-harmonic multi-component electromagnetic detection method according to claim 1, characterized in that: The step S1 of transmitting the excitation signal adopts a phase-alternating transmission technology.

8. A low-frequency time-harmonic multi-component electromagnetic detection method according to claim 1, characterized in that: In the S4 conversion imaging step, an underground target body feature library is constructed to study the response characteristics of electrical parameters of different target bodies and form an accurate, efficient and adaptive algorithm.

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