Signal collection and interpretation system for geological radar collection

Abstract

The invention is applied to the technical field of geological exploration, and particularly discloses a geological radar collected signal collection and interpretation system, which comprises a computer, a power supply module, a storage module, a signal collection module and a signal interpretation module, and is characterized in that the computer is connected with the signal collection module and the signal interpretation module. According to the signal collection and interpretation system collected by the geological radar, the collected radar signals are transmitted to the signal interpretation module for interpretation of the radar signals, and before the radar signals are interpreted, a plurality of data preprocessing modules are arranged to carry out interpretation preprocessing on the radar data, including background noise removal and direct current offset removal. The method has the advantages that the radar signal quality is improved to the greatest extent by means of filtering processing and gain adjustment, the interpretation efficiency of the radar image can be improved, the interpreted radar image is classified and stored through the convolutional neural network, and subsequent interpretation of the radar image is assisted.

Description

Technical Field

[0001] The present invention relates to the technical field of geological exploration, and specifically to a signal collection and interpretation system for geological radar collection. Background Art

[0002] Geological exploration refers to the process of investigating and studying the geological structure, rock properties, underground resources, etc. of the earth through technologies and methods. Geological exploration plays an important role in various fields such as resource exploration, engineering construction site selection, environmental assessment, and disaster prevention. Among them, ground penetrating radar can be used to determine the distribution of underground media, which is an important detection means. The ground penetrating radar emits ultra-high frequency electromagnetic wave beams into the underground media. When the electromagnetic waves propagate underground and encounter the interface of different media, due to the differences in physical properties such as dielectric constant, a part of the electromagnetic waves will be reflected back, and the other part will continue to propagate downward. The receiving antenna receives the reflected electromagnetic wave signals, and through the processing and analysis of these signals, the structure and distribution information of the underground media can be obtained.

[0003] At present, the interpretation of radar signals mainly relies on manual operation, so it is highly subjective, inefficient, and difficult to process efficiently in the face of massive and complex data. Moreover, the traditional methods have extremely limited recognition capabilities for tiny abnormal features and deep geological structures, and it is difficult to meet the requirements of geological exploration work. Summary of the Invention

[0004] The purpose of the present invention is to provide a signal collection and interpretation system for geological radar collection, so as to solve the problem that the interpretation of radar signals mainly relies on manual operation and is inefficient as mentioned in the above background art.

[0005] To achieve the above purpose, the present invention provides the following technical solution: A signal collection and interpretation system for geological radar collection, including a computer, a power supply module, a storage module, a signal acquisition module, and a signal interpretation module. The computer is connected to the signal acquisition module and the signal interpretation module. The computer, the signal acquisition module, and the signal interpretation module are jointly mounted on a mobile vehicle. The computer is connected to the power supply module, and the computer is connected to the storage module. Moreover, the storage module is respectively connected to the signal acquisition module and the signal interpretation module, forming a radar signal acquisition and interpretation system with the computer as the system center and multiple modules interconnected.

[0006] Preferably, the power supply module includes a storage battery and an external power interface. The storage battery is installed on the mobile vehicle, and is electrically connected to the computer. The external power interface is provided with power wires respectively connected to the computer and the storage battery.

[0007] With the above technical solution, the power supply module composed of a storage battery and an external power supply interface can stably supply power to the system under different conditions, ensuring the normal operation of the system.

[0008] Preferably, the storage module includes a database and an external storage device. The database and the external storage device are interconnected. The database is built into the computer, and the external storage device is a mobile hard disk. The external storage device is connected to the computer through USB. The database in the storage module is respectively connected to the signal acquisition module and the signal interpretation module to perform real-time storage and backup of radar data.

[0009] With the above technical solution, the use of a database and an external storage device can perform real-time backup of radar data during the operation of the system, avoiding data loss.

[0010] Preferably, the signal acquisition module includes an antenna, a transmitter, a receiver, and an analog-to-digital converter. A plurality of the antennas are arranged in a rectangle. The transmitter is connected to the antenna through a transmission line, the receiver is connected to the antenna through a transmission line, the analog-to-digital converter is connected to the receiver, and the analog-to-digital converter converts the analog electromagnetic signal received by the receiver into a digital signal and uploads it to the database in the computer for storage.

[0011] With the above technical solution, the signal acquisition module can collect the radar electromagnetic signal of the geological signal and convert it into a digital signal.

[0012] Preferably, the signal interpretation module includes a data preprocessing part, a feature extraction part, an image generation part, an interpretation analysis part, and a data classification part. The data preprocessing part receives the digital signal from the signal acquisition module and preprocesses the radar signal data. The feature extraction part performs feature extraction and analysis on the preprocessed radar signal data to assist in the recognition of radar images. The image generation part generates a radar image based on the processed radar signal data. The interpretation analysis part analyzes the generated radar image and outputs the geological interpretation result. The data classification part classifies and stores the generated radar image and the corresponding geological interpretation result using a convolutional neural network algorithm to assist in the interpretation of radar images. After the radar signal is input into the data preprocessing part, after various preprocessing steps, data verification of the radar signal is performed. During the data verification process of the radar signal, the quality of the radar signal is detected, and the signal data with unqualified signal quality is eliminated. The qualified signal data after verification is transmitted to the feature extraction part for processing and then the interpretation analysis of the radar signal is performed.

[0013] With the above technical solution, the signal interpretation module can perform the interpretation process of the image signal on the converted radar signal.

[0014] Preferably, the data preprocessing part includes background noise removal, DC offset removal, filtering, and gain adjustment. The background noise removal removes the background noise in the radar signal to highlight the signal of the target object. The background noise removal obtains the background signal by taking the average of the data measured multiple times and subtracts the background signal from the original radar signal. The DC offset removal can remove the DC offset in the radar signal and eliminate the interference caused by the instrument itself or the environment. The DC offset removal uses the differential method, and the differential operation process is as follows:

[0015] d(t) = x(t) - x(t - 1)

[0016] where x(t) is the original signal, d(t) is the signal after differentiation, and t is the time length of the signal;

[0017] The filtering can remove high-frequency noise, low-frequency noise, and electromagnetic interference, and improve the signal-to-noise ratio of the radar signal. In the filtering, a filter is used to process the radar signal. The gain adjustment can perform gain compensation for the attenuation of the radar signal to facilitate subsequent analysis and interpretation. In the gain adjustment, a linear gain adjustment method is used to amplify the radar signal by a certain proportion to improve the quality of the radar signal.

[0018] Adopting the above technical solution, the data preprocessing part can preprocess the radar signal data, enhance the signal quality, and improve the efficiency of subsequent interpretation.

[0019] Preferably, the feature extraction part includes time-domain feature extraction, frequency-domain feature extraction, and statistical feature extraction. In the time-domain feature extraction, specific time-domain features in the radar signal, such as peak value, amplitude, and waveform duration, are extracted. The frequency-domain feature extraction converts the radar signal to the frequency domain, analyzes the frequency components of the signal, and realizes the frequency-domain feature extraction. The statistical feature extraction uses the statistical parameters of the radar signal, such as mean, standard deviation, skewness, kurtosis, etc., as features to analyze the radar signal.

[0020] Adopting the above technical solution, the feature extraction part can extract the features in the radar signal data and improve the interpretation efficiency of the radar image.

[0021] Preferably, in the data classification part, the convolutional neural network algorithm is used to classify the interpreted radar image, a convolutional neural network model of the radar image is constructed, and the convolutional neural network model is trained and evaluated using the radar images stored in the database to assist in the subsequent interpretation of the radar image.

[0022] Adopting the above technical solution, the data classification part can classify the interpreted radar image and assist in the subsequent interpretation of the radar data.

[0023] Compared with the prior art, the beneficial effects of the present invention are as follows: The signal collection and interpretation system collected by the ground penetrating radar:

[0024] 1. In the present invention, the collected radar signals are transmitted to the signal interpretation module for interpretation of the radar signals. Before the radar signals are interpreted, multiple pre-processing modules for data are set up to pre-process the radar data before interpretation, including background noise removal, DC offset removal, filtering processing, and gain adjustment, which can improve the quality of the radar signals to the greatest extent, improve the interpretation efficiency of the radar images, and the interpreted radar images are classified and stored through a convolutional neural network to assist in the subsequent interpretation of the radar images;

[0025] 2. In the present invention, a power supply module is set up to supply power to the system, and a storage battery and an external power supply interface are set in the power supply module. The external power supply interface can be connected to a computer and the storage battery through wires to ensure that the system can operate stably in different environments. Whether it is powered by the storage battery when there is no external power supply during field exploration or the stable charging and power supply switching is realized under the condition of having an external power supply, it can ensure the continuous operation of the system. At the same time, the storage module consists of an interconnected database and an external storage device, which can store and back up radar data in real time to prevent data loss, thereby ensuring data security and reducing detection interruption and errors caused by data loss. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 is a schematic structural diagram of the system of the present invention;

[0027] Figure 2 is a schematic structural diagram of the data processing flow of the present invention;

[0028] Figure 3 is a schematic structural diagram of the data interpretation flow of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0029] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0030] Please refer to Figures 1 - 3 , the present invention provides a technical solution: a signal collection and interpretation system collected by a ground penetrating radar.

[0031] The computer is connected to a signal acquisition module and a signal interpretation module. The computer, the signal acquisition module, and the signal interpretation module are jointly mounted on a mobile vehicle. The computer is connected to a power supply module and a storage module. The storage module is respectively connected to the signal acquisition module and the signal interpretation module, forming a radar signal acquisition and interpretation system with the computer as the system center and multiple modules interconnected. The power supply module includes a storage battery and an external power interface. The storage battery is installed on the mobile vehicle and is electrically connected to the computer. The external power interface is provided with power wires respectively connected to the computer and the storage battery. The storage module includes a database and an external storage device. The database and the external storage device are interconnected. The database is built into the computer, and the external storage device is a mobile hard disk. The external storage device is connected to the computer through USB. The database in the storage module is respectively connected to the signal acquisition module and the signal interpretation module to perform real-time storage and backup of radar data;

[0032] As Figure 1 shown, when using this system to conduct radar surveys on geology, the computer, the signal acquisition module, and the signal interpretation module are moved to the set area by the mobile vehicle. The signal acquisition module is used to collect radar signals, and the radar data is input into the signal interpretation module for interpretation. During this process, devices such as the computer rely on the power supply module for power supply. When there is no external power in the wild, the storage battery is used to supply power to the system. When there is external power, the external power interface is connected to the external power supply, and at the same time, the system is powered on and the storage battery is charged to ensure the normal operation of the system. During the use of the system, the collected data is stored in the storage module, and the database and the external storage device set in the storage module are used to back up the data in real time to avoid data loss.

[0033] The signal acquisition module includes an antenna, a transmitter, a receiver, and an analog-to-digital converter. Multiple antennas are arranged in a rectangle. The transmitter is connected to the antenna through a transmission line, the receiver is connected to the antenna through a transmission line, and the analog-to-digital converter is connected to the receiver. The analog-to-digital converter converts the analog electromagnetic signal received by the receiver into a digital signal and uploads it to the database in the computer for storage. The signal interpretation module includes a data preprocessing part, a feature extraction part, an image generation part, an interpretation analysis part, and a data classification part. The data preprocessing part receives the digital signal from the signal acquisition module and preprocesses the radar signal data. The feature extraction part performs feature extraction and analysis on the preprocessed radar signal data to assist in the recognition of radar images. The image generation part generates a radar image based on the processed radar signal data. The interpretation analysis part analyzes the generated radar image and outputs the geological interpretation result. The data classification part classifies and stores the generated radar image and the corresponding geological interpretation result using a convolutional neural network algorithm to assist in the interpretation of radar images. After the radar signal is input into the data preprocessing part, after multiple preprocessing steps, data verification of the radar signal is performed. During the data verification process of the radar signal, the quality of the radar signal is detected, and the signal data with unqualified quality is eliminated. The qualified signal data after verification is transmitted to the feature extraction part for processing and then the interpretation analysis of the radar signal is carried out.

[0034] As Figure 1 and Figure 2 shown, in the detection area, the signal acquisition module is activated. The transmitter in the signal acquisition module emits an ultra-high frequency electromagnetic wave beam to the ground through the antenna. When the electromagnetic wave encounters the interface of different underground media, part of the electromagnetic wave is reflected back to the ground and received by the receiver, and the electromagnetic signal is converted into a digital signal through the analog-to-digital converter. The digital signal is transmitted to the computer database for storage, providing the original data for subsequent interpretation. The original digital signal generates a radar image of geological information after data preprocessing, feature extraction, and image generation. By interpreting and analyzing the radar image, the geological interpretation result can be output, and the convolutional neural network is used to classify the interpreted radar image to assist in the subsequent interpretation of radar images.

[0035] The data preprocessing part includes background noise removal, DC offset removal, filtering processing, and gain adjustment. Background noise removal removes the background noise in the radar signal to highlight the signal of the target object. Background noise removal obtains the background signal by taking the average of the data measured multiple times and subtracts the background signal from the original radar signal. DC offset removal can remove the DC offset in the radar signal and eliminate the interference caused by the instrument itself or the environment. DC offset removal uses the differential method, and the differential operation process is as follows:

[0036] d(t) = x(t) - x(t - 1)

[0037] Among them, \(x(t)\) is the original signal, \(d(t)\) is the signal after differentiation, and \(t\) is the time length of the signal; filtering can remove high-frequency noise, low-frequency noise, and electromagnetic interference, and improve the signal-to-noise ratio of the radar signal. A filter is used to process the radar signal during filtering. Gain adjustment can perform gain compensation for the attenuation of the radar signal, facilitating subsequent analysis and interpretation. A linear gain adjustment method is adopted in gain adjustment to amplify the radar signal by a certain proportion, improving the quality of the radar signal. The feature extraction part includes time-domain feature extraction, frequency-domain feature extraction, and statistical feature extraction. In time-domain feature extraction, specific time-domain features in the radar signal, such as peak value, amplitude, and waveform duration, are extracted. Frequency-domain feature extraction converts the radar signal to the frequency domain and analyzes the frequency components of the signal to achieve frequency-domain feature extraction. Statistical feature extraction uses statistical parameters of the radar signal, such as mean, standard deviation, skewness, and kurtosis, as characteristics to analyze the radar signal. In the data classification part, a convolutional neural network algorithm is used to classify the interpreted radar image, a convolutional neural network model of the radar image is constructed, and the convolutional neural network model is trained and evaluated using the radar images stored in the database to assist in the subsequent interpretation of the radar image;

[0038] As Figure 3 shown, during the process of processing radar signal data, first, the background noise in the signal is removed. The background signal is obtained by taking the average of the data measured multiple times, and the background signal is subtracted from the original radar signal to highlight the signal of the target object. The data after background noise removal continues to be processed to remove the DC offset. The DC offset is removed by the differential method to eliminate the interference of the instrument itself or the environment on the radar signal. A filter is used to process the radar signal to remove high-frequency noise, low-frequency noise, and electromagnetic interference. The radar signal is amplified by a certain proportion in a linear gain manner to improve the quality of the radar signal. The radar signal after preprocessing continues to be subjected to feature extraction to extract the eigenvalues in the radar signal for the generation of radar images. The radar image is interpreted to obtain the geological exploration results. The interpreted radar image is classified using a convolutional neural network. When subsequent radar image interpretation is carried out, the radar image can be input into the convolutional neural network model. After the radar image is quickly classified, a targeted interpretation process in a certain direction is carried out to improve the interpretation efficiency of the radar signal.

[0039] Working principle: The transmitter emits an electromagnetic wave beam into the ground through an antenna. The receiver receives the electromagnetic wave reflection, converts the electromagnetic signal into a digital signal using an analog-to-digital converter, and uploads it to the database. After the original digital signal undergoes background noise removal, DC offset removal, filtering, and gain adjustment in the data preprocessing section, the signal quality is improved. The data is then transmitted to the feature extraction section to extract the signal feature values and output a radar image. The generated radar image is interpreted to output the geological interpretation result. The interpreted radar image is classified and stored using a convolutional neural network algorithm, and the convolutional neural network model is trained and evaluated using the radar images stored in the database to further assist in the interpretation of the radar image, thereby further improving the accuracy and efficiency of the radar image interpretation.

[0040] Although the embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention.

Claims

1. A signal collection and interpretation system for geological radar, comprising a computer, a power supply module, a storage module, a signal collection module and a signal interpretation module, characterized in that: The computer is connected to a signal acquisition module and a signal interpretation module, and the computer, signal acquisition module and signal interpretation module are jointly mounted on a mobile vehicle. The computer is connected to a power supply module, and the computer is connected to a storage module, and the storage module is respectively connected to the signal acquisition module and the signal interpretation module, forming a radar signal acquisition and interpretation system with the computer as the system center and multiple modules connected to each other.

2. The signal collection and interpretation system of a geological radar according to claim 1 is characterized in that: The power supply module includes a battery and an external power interface. The battery is installed on a mobile vehicle. The battery is electrically connected to a computer. The external power interface is provided with power leads respectively connected to the computer and the battery.

3. The signal collection and interpretation system of a geological radar according to claim 1 is characterized in that: The storage module includes a database and an external storage, which are interconnected. The database is built into a computer, and the external storage is a mobile hard disk. The external storage is connected to the computer via a USB. The database in the storage module is respectively connected to a signal acquisition module and a signal interpretation module to perform real-time storage and backup of radar data.

4. The signal collection and interpretation system for geological radar according to claim 1 is characterized by: The signal acquisition module includes an antenna, a transmitter, a receiver, and an analog-to-digital converter. The multiple antennas are arranged in a rectangular shape. The transmitter is connected to the antenna through a transmission line. The receiver is connected to the antenna through a transmission line. The analog-to-digital converter is connected to the receiver. The analog-to-digital converter converts the analog electromagnetic signal received by the receiver into a digital signal and uploads it to a database in a computer for storage.

5. The signal collection and interpretation system of a geological radar according to claim 1 is characterized in that: The signal interpretation module includes a data preprocessing part, a feature extraction part, an image generation part, an interpretation and analysis part and a data classification part. The data preprocessing part receives the digital signal from the signal acquisition module and preprocesses the radar signal data. The feature extraction part performs feature extraction and analysis on the preprocessed radar signal data to assist in the recognition of radar images. The image generation part generates a radar image based on the processed radar signal data. The interpretation and analysis part analyzes the generated radar image and outputs a geological interpretation result. The data classification part classifies and stores the generated radar image and the corresponding geological interpretation result using a convolutional neural network algorithm to assist in the interpretation of the radar image. After the radar signal is input into the data preprocessing part and undergoes multiple preprocessing steps, data verification of the radar signal is performed. During the radar signal data verification process, the radar signal quality is detected, and signal data with substandard signal quality is eliminated. The verified qualified signal data is transmitted to the feature extraction part for processing and then the radar signal is interpreted and analyzed.

6. The signal collection and interpretation system of a geological radar according to claim 5, characterized in that: The data preprocessing part includes background noise removal, DC offset removal, filtering and gain adjustment. The background noise removal removes the background noise in the radar signal, thereby highlighting the signal of the target body. The background noise removal takes the average value of the data measured multiple times to obtain the background signal, and subtracts the background signal from the original radar signal. The DC offset removal can remove the DC offset in the radar signal and remove the interference of the instrument itself or the environment. The DC offset removal adopts the differential method, and the differential operation process is as follows: d(t)=x(t)-x(t-1) Among them, x(t) is the original signal, d(t) is the signal after difference, and t is the time length of the signal; The filtering process can remove high-frequency noise, low-frequency noise, and electromagnetic interference, and improve the signal-to-noise ratio of the radar signal. The filtering process uses a filter to process the radar signal. The gain adjustment can perform gain compensation on the attenuation of the radar signal to facilitate subsequent analysis and interpretation. The gain adjustment uses a linear gain adjustment method to amplify the radar signal by a certain proportion, thereby improving the quality of the radar signal.

7. The signal collection and interpretation system of geological radar according to claim 5, characterized in that: The feature extraction part includes time domain feature extraction, frequency domain feature extraction and statistical feature extraction. In the time domain feature extraction, specific time domain features in the radar signal, such as peak value, amplitude and waveform duration, are extracted. The frequency domain feature extraction converts the radar signal into the frequency domain, analyzes the frequency component of the signal, and realizes frequency domain feature extraction. The statistical feature extraction uses the statistical parameters of the radar signal, such as mean, standard deviation, skewness, kurtosis, etc. as characteristics to analyze the radar signal.

8. The signal collection and interpretation system of geological radar according to claim 5 is characterized by: In the data classification part, a convolutional neural network algorithm is used to classify the interpreted radar images, a convolutional neural network model of the radar images is constructed, and the convolutional neural network model is trained and evaluated using the radar images stored in the database to assist in the subsequent interpretation of radar images.

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