CN111126231B - Filtering method, device and equipment for aviation electromagnetic data and storage medium - Google Patents
Filtering method, device and equipment for aviation electromagnetic data and storage medium Download PDFInfo
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Abstract
The disclosure provides a filtering method, a filtering device, filtering equipment and a storage medium for aviation electromagnetic data, and relates to the technical field of aviation electromagnetic data preprocessing. The method comprises the following steps: dividing each half period segment of the response signal into first signal data and second signal data, respectively carrying out sliding shearing mean value filtering processing on the response signal based on a preset small window width N and a preset large window width M, and combining the data subjected to the sliding shearing filtering processing according to the first signal data and the second signal data to obtain a filtered signal without the solar electricity. The method can efficiently remove the influence of the natural electric noise on the response signal, and can improve the signal-to-noise ratio of the response signal data.
Description
Technical Field
The disclosure relates to the technical field of time domain aviation electromagnetic data preprocessing, in particular to a filtering method, a filtering device, filtering equipment and a storage medium for aviation electromagnetic data.
Background
The aeronautical electromagnetic measurement, or aeronautical electromagnetic method, is an important method for airborne geophysical prospecting, and is widely applied to many fields. The time domain aeroelectromagnetic system realizes the multi-channel collection of data density, and the collected measured data needs to be prepared for data interpretation through data preprocessing. The original data contains various noises, wherein the sky electric noise has a large influence on the data because of the sharp pulse or oscillation of the response signal caused by the sky electric noise, so the sky electric noise needs to be removed as completely as possible on the premise of keeping the required abnormal signal. The removal of the natural electric noise can improve the signal-to-noise ratio of the response signal data, and is beneficial to increasing the exploration depth and improving the resolution capability of the small anomaly to be searched. Therefore, a filtering method for quickly and efficiently removing the celestial electric noise and preserving the anomaly in the original signal is needed.
In the prior art, the astronomical noise can be removed by an alpha-trim mean/median filtering method, and useful signal data is reserved. The method has the major limitations that firstly, the alpha-trim mean/median filtering method needs to carry out product rounding on the set alpha and the window width length, and the operability of the method is limited; and secondly, the alpha-trim mean/median filtering method can lose original signals or remove the natural electrical noise incompletely because the time domain aviation electromagnetic data comprises power supply and power failure signal data, the amplitude difference of the two signals is large, the original signal noise can be influenced to a certain extent only by setting a simple input parameter, and the situations of excessive averaging, excessive cutting or incomplete removal of the natural electrical noise and the like of response signals after filtering are caused. In summary, the α -trim mean/median filtering is only applicable to the case of small celestial electrical noise and short-time pulses.
Disclosure of Invention
The invention aims to provide a filtering method, a filtering device, filtering equipment and a storage medium for aviation electromagnetic data, wherein a double-window shearing mean filtering method can be adopted for filtering response signals, original useful signals can be reserved, and natural electrical noise can be removed quickly and efficiently.
In order to achieve the purpose, the technical scheme adopted by the disclosure is as follows:
the first aspect of the present disclosure provides a filtering method for airborne electromagnetic data, the method including:
dividing each half period segment of a response signal into first signal data and second signal data, wherein the response signal is a signal generated by a receiving coil of an aeronautical electromagnetic measurement device receiving current periodically transmitted to the underground from a transmitting coil, and the first signal data comprises: the response signal is power supply starting time, power off starting time and peak signal data of each half cycle, and the second signal data comprises: the signal data of the power supply stage and the power off stage of each half cycle of the response signal;
respectively carrying out sliding shearing mean value filtering processing on the response signals based on a preset small window width N and a preset large window width M;
and combining the data subjected to the sliding shearing mean value filtering processing according to the first signal data and the second signal data to obtain a filtered signal subjected to the removal of the solar electricity.
Optionally, the performing, based on a preset small window width N and a preset large window width M, sliding cut mean filtering processing on the response signal respectively includes:
based on the preset small window width N and a first preset shearing length, carrying out shearing mean value filtering processing on the response signal to obtain a small window filtering signal;
and based on the preset large window width M and a second preset shearing length, carrying out shearing mean value filtering processing on the response signal to obtain a large window filtering signal.
Wherein the first preset shearing length and the preset small window width N satisfy: 2 × the first preset clipping length < the preset small window width N;
the second preset shearing length and the preset large window width M satisfy: 2 × the second preset clipping length < the preset large window width M.
Optionally, the combining, according to the first signal data and the second signal data, the data after the sliding cut mean filtering processing to obtain a filtered signal after the removal of the solar power includes:
acquiring a signal corresponding to the first signal data from the small-window filtered signal, and acquiring a signal corresponding to the second signal data from the large-window filtered signal;
and combining the signal corresponding to the first signal data with the signal corresponding to the second signal data to obtain the filtered signal with the solar electricity removed.
Optionally, the preset small window width N and the preset large window width M are odd numbers, and the first preset clipping length and the second preset clipping length are even numbers respectively.
Optionally, before performing sliding window clipping mean filtering processing on the response signal based on the preset small window width N and the preset large window width M, the method further includes:
and respectively adding expanded signal data of the preset large window width M at two ends of the response signal.
Optionally, the increasing the expanded signal data of the preset large window width M at two ends of the response signal respectively includes:
and respectively increasing the expanded signal data with the preset large window width M at two ends of the response signal by adopting a periodic edge expanding mode or a mirror image edge expanding mode.
The second aspect of the present disclosure provides a filtering apparatus for aviation electromagnetic data, including: divide module filtering module and merge module, wherein:
the dividing module is used for dividing each half period of a response signal into first signal data and second signal data, the response signal is a signal generated by a receiving coil of the aerial electromagnetic measuring equipment receiving current periodically transmitted to the underground from a transmitting coil, and the first signal data comprises: the power supply starting time, the power failure starting time and the peak signal data of each half cycle of the response signal, wherein the second signal data comprises: the signal data of the power supply stage and the power off stage of each half cycle of the response signal;
the filtering module is used for respectively carrying out sliding shearing mean value filtering processing on the response signals based on a preset small window width N and a preset large window width M;
and the merging module is used for merging the data subjected to the sliding shearing mean value filtering processing according to the first signal data and the second signal data to obtain a filtered signal subjected to the removal of the solar electricity.
Optionally, the processing module is further configured to perform a shearing mean filtering process on the response signal based on the preset small window width N and a first preset shearing length, so as to obtain a small window filtered signal; and based on the preset large window width M and a second preset shearing length, carrying out shearing mean value filtering processing on the response signal to obtain a large window filtering signal.
Wherein the first preset shearing length and the preset small window width N satisfy: 2 × the first preset clipping length < the preset small window width N;
the second preset shearing length and the preset large window width M satisfy: 2 × the second preset clipping length < the preset large window width M.
Optionally, the apparatus further comprises: an acquisition module and a merging module, wherein:
the acquisition module is used for acquiring a signal corresponding to the first signal data from the small-window filtering signal and acquiring a signal corresponding to the second signal data from the large-window filtering signal;
and the merging module is used for merging the signal corresponding to the first signal data and the signal corresponding to the second signal data to obtain the filtered signal with the solar electricity removed.
Optionally, the apparatus further comprises: and the adding module is used for respectively adding the expanded signal data with the preset large window width M at two ends of the response signal.
Optionally, the adding module is further configured to add the extended signal data with the preset large window width M at two ends of the response signal respectively by using a periodic edge extension mode or a mirror edge extension mode.
A third aspect of the present disclosure provides an apparatus for filtering airborne electromagnetic data, including: a processor, a storage medium and a bus, the storage medium storing machine-readable instructions executable by the processor, the processor and the storage medium communicating via the bus when the airborne electromagnetic data filtering apparatus is in operation, the processor executing the machine-readable instructions to perform the steps of the method according to any one of the first aspect.
A fourth aspect of the present disclosure proposes a storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method according to any one of the first aspects described above.
In the embodiment of the disclosure, the method for removing the natural noise of the original data by using the double-window shearing mean filtering is firstly proposed, the natural noise of the response signal is filtered based on the small-window filtering at the power supply starting time, the power failure starting time and the peak value signal data, the change trend and the stability of the original signal are maintained, the shearing mean filtering processing is performed on the signal data of the power supply stage and the power failure stage of each half period of the response signal based on the large-window filtering, the influence of the natural noise on the data is effectively removed, the signal-to-noise ratio of the response signal is improved, and the exploration depth is increased.
Additional features and advantages of the disclosure will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the disclosure. The objectives and other advantages of the disclosure may be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
To more clearly illustrate the technical solutions of the present disclosure, the drawings needed in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate certain embodiments of the present disclosure and therefore should not be considered as limiting the scope, and those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.
FIG. 1 illustrates a flow diagram of a method for filtering airborne electromagnetic data provided by an embodiment of the present disclosure;
FIG. 2 illustrates a time domain aeronautical electromagnetic response signal segment division diagram provided by an embodiment of the present disclosure;
fig. 3 is a waveform diagram illustrating a periodic edge extension method in a clipped mean filtering according to an embodiment of the disclosure;
fig. 4 is a waveform diagram illustrating a mirror edge extension method in a clipped mean filtering according to another embodiment of the disclosure;
FIG. 5 is a flow diagram illustrating a single window clipped mean filtering in the prior art;
FIG. 6 is a graph showing a comparison of waveforms before and after single window filtering window degree versus skyhook noise removal in the prior art;
FIG. 7 is a graph showing a comparison of waveforms before and after single window filtering window degree versus skyhook noise removal in the prior art;
FIG. 8 is a waveform diagram illustrating a response signal of a dual-window clipped mean filter according to response interval division provided by the present disclosure;
FIG. 9 is a schematic diagram illustrating a comparison of waveforms before and after filtering for a power phase with a dual window clipping average provided by the present disclosure;
FIG. 10 is a schematic diagram illustrating a comparison of waveforms before and after filtering in the power-down phase for a dual-window clipping average provided by the present disclosure;
fig. 11 is a schematic structural diagram of an apparatus for filtering airborne electromagnetic data according to an embodiment of the present disclosure;
fig. 12 is a schematic structural diagram of an apparatus for filtering airborne electromagnetic data according to another embodiment of the present disclosure;
fig. 13 is a schematic structural diagram of an apparatus for filtering airborne electromagnetic data according to another embodiment of the present disclosure;
fig. 14 is a schematic block diagram illustrating an exemplary configuration of an apparatus for filtering airborne electromagnetic data according to the present disclosure.
Detailed Description
The technical solutions in the present disclosure will be clearly and completely described below with reference to the drawings in the present disclosure.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
Referring to fig. 1, a flow chart of a filtering method for aviation electromagnetic data according to an embodiment of the present disclosure is shown, in an embodiment of the present disclosure, the filtering method based on aviation electromagnetic measurement may be applied to aviation electromagnetic measurement equipment. The aeronautical electromagnetic measurement equipment can comprise a transmitting coil and a receiving coil, and can inject transmitting current into the transmitting coil periodically to enable the transmitting coil to transmit electromagnetic signals, and in the process, the electromagnetic signals capable of indicating geomagnetic information change, namely response signals, are received through the receiving coil. It should be noted that the aviation electromagnetic measurement based filtering method disclosed in the present disclosure is not limited by the specific sequence shown in fig. 1 and described below, and it should be understood that, in other embodiments, the sequence of some steps in the aviation electromagnetic measurement based filtering method disclosed in the present disclosure may be interchanged according to actual needs, or some steps may be omitted or deleted. The flow shown in fig. 1 will be explained in detail below.
As shown in fig. 1, the method may include:
s101: each half cycle segment of the response signal is divided into first signal data and second signal data.
Wherein the response signal is a signal generated by a receiving coil of the airborne electromagnetic measuring device receiving a current periodically transmitted from a transmitting coil into the ground, and the first signal data comprises: the power supply starting time, the power failure starting time and the peak signal data of each half cycle of the response signal, wherein the second signal data comprises: the power up phase and power down phase signal data for each half cycle of the response signal.
In an implementation example, a signal of each half period section of the response signal may be divided into first signal data and second signal data according to a period of the response signal.
S102: and respectively carrying out sliding shearing mean value filtering processing on the response signals based on the preset small window width N and the preset large window width M.
S103: and merging the data subjected to the sliding shearing mean value filtering processing according to the first signal data and the second signal data to obtain a filtered signal subjected to the removal of the solar electricity.
When the sliding window for performing the average filtering is too small, the sliding window may be noisy, so that it is difficult to completely filter the natural noise, and when the sliding window is too large, the effect of filtering the natural noise is good, but the variation trend of the first signal data is not easy to keep.
Wherein, the width N of the preset small window is smaller than the width M of the preset large window.
According to the scheme, after the response signals are filtered based on the preset small window width N and the preset large window width, the filtered data are combined, the fact that the sky electric noise in the aviation electromagnetic data is removed by the double-window shearing mean value filtering method is achieved, the variation trend and the stability of the response signals are kept, the sky electric noise can be effectively removed, and the sky electric noise can be removed more efficiently and more quickly.
Optionally, S102 may include: based on the preset small window width N and the first preset shearing length, carrying out shearing mean value filtering processing on the response signal to obtain a small window filtering signal; and performing shearing mean value filtering processing on the response signal based on the preset large window width M and a second preset shearing length to obtain a large window filtering signal.
Wherein, first preset shearing length and preset small window width N satisfy: 2 x the first preset shearing length < the preset small window width N; the second preset shearing length and the preset large window width M meet the following requirements: 2 x a second preset clipping length < the preset large window width M.
In a possible implementation example, the preset small window width N and the first preset clipping length may be used to perform a clipping average filtering process on the response signal, actually perform a filtering process on first signal data in the response signal, and for second signal data in the response signal, in a filtering process based on the preset small window width N and the first preset clipping length, the second signal data is not actually changed, so as to obtain a small window filtered signal. Then, the small window filtered signal includes: the signal corresponding to the first signal data is the signal filtered by adopting the preset small window width N and the first preset shearing length.
Correspondingly, the preset large window width M and the second preset shearing length may be adopted to perform shearing mean filtering processing on the response signal, actually, second signal data in the response signal is subjected to filtering processing, and for first signal data in the response signal, in the process of performing filtering processing based on the preset large window width M and the second preset shearing length, the actual condition is not changed, so that a large window filtering signal is obtained. Then, the large window filtered signal includes: the signal corresponding to the second signal data is the signal after filtering processing by adopting a preset large window width M and a second preset shearing length.
Optionally, S102 may further include: acquiring a signal corresponding to the first signal data from the small-window filtered signal, and acquiring a signal corresponding to the second signal data from the large-window filtered signal; and combining the signal corresponding to the first signal data and the signal corresponding to the second signal data to obtain a filtered signal with the solar electricity removed.
In a specific implementation, second signal data in the small-window filtered signal may be determined according to the small-window filtered signal and the response signal, and the second signal data in the small-window filtered signal may be removed to obtain a signal corresponding to the first signal data in the small-window filtered signal.
Correspondingly, the first signal data in the large-window filtering signal can be determined according to the large-window filtering signal and the response signal, and the first signal data in the large-window filtering signal is removed, so that a signal corresponding to the second signal data in the large-window filtering signal is obtained.
After the signal corresponding to the first signal data and the signal corresponding to the second signal data are obtained, the signal corresponding to the first signal data and the signal corresponding to the second signal data can be subjected to signal combination, and therefore the filtered signal with the antenna power removed is obtained.
Optionally, as shown above, in an embodiment of the present disclosure, the preset small window width N and the preset large window width M are odd numbers, and the first preset clipping length and the second preset clipping length are even numbers respectively.
Specifically, in the scheme of the present disclosure, the odd number may mean that the preset small window width N and the preset large window width M may include odd number of unit lengths, respectively; even numbers mean that the first and second preset cut lengths may include: an even number of unit lengths.
Optionally, before S102, the extended signal data with the preset large window width M is further added to both ends of the response signal.
And the extended signal data with the preset large window width M is respectively added at the two ends of the response signal by adopting a periodic edge extension mode or a mirror image edge extension mode.
Of course, the expansion method of the signal data is not limited to the above-mentioned periodic edge expansion or mirror edge expansion, and other expansion methods can be adopted as long as the expanded signal data is the width of the preset large window.
Before the signals are subjected to filtering processing, the response signals are expanded, so that the subsequent filtering processing effect is better, the variation trend and the stability of the response signals are more effectively kept, and the sky-electricity noise can be effectively removed, so that the sky-electricity noise is more efficiently and quickly removed.
As explained below in connection with a specific example, a method as shown in any of the above.
Fig. 2 is a time domain aeronautical electromagnetic response signal segment division diagram provided by an embodiment of the present disclosure. The time domain aeroelectromagnetic method is that a primary pulse magnetic field is transmitted to the underground by a transmitting coil by utilizing the principle of electromagnetic induction, an eddy current is excited and generated in an underground medium, a receiving coil receives a primary field directly transmitted back from the air and an electromagnetic signal returned from the underground, and the signal in the receiving coil is a response signal. According to the time domain aeronautical electromagnetic characteristics, the response signals are divided into first signal data and second signal data, the first signal data are power supply starting time, power failure starting time and peak value signal data of each half cycle of the response signals, and the second signal data are power supply stage and power failure stage signal data of each half cycle of the response signals. The power supply starting time is A and E in figure 2, the power failure starting time is C and G in figure 2, the power supply stage is B and F in figure 2, and the power failure time is D and H in figure 2.
Data expansion before the filtering process is exemplified with continued reference to fig. 3 and 4. Fig. 3 illustrates a waveform diagram of a periodic edge extension method in a clipped mean filtering according to an embodiment of the present disclosure. In fig. 3, the periodic edge extension method is to extend data with length of [ M/2] at two ends of the response signal respectively to obtain a new response signal, if the length of the original response signal is ndata, the length of the new response signal is ndata + M, and M is a preset large window width used for the clipping average filtering.
Fig. 4 shows a waveform diagram of a mirror edge extension method in a clipped mean filtering according to another embodiment of the present disclosure. The mirror image method adopts a mirror/reflection-like manner to expand the edge of the data, as shown in fig. 4, the mirror image expansion is to sequentially invert [ M/2] data before and after two ends of the response signal at two corresponding ends of the response data. After the edge expansion, the new response signal is called as the response signal of the later shearing mean value filtering. Of course, in practical applications, the response signal may also be expanded in other manners, and the manner of expanding the response signal in the embodiment of the disclosure is not particularly limited.
After the original response signal, i.e., the response signal received by the receiving coil, is subjected to edge extension, the clipped mean value filtering process is performed on the extended response signal (hereinafter referred to as a response signal). The method firstly proposes double-window shearing mean filtering, and before introducing the double-window shearing mean filtering, simply introduces the process of single-window shearing mean filtering processing.
Fig. 5 shows a flow diagram of single window clipped mean filtering in the prior art. The flow of the specific single-window clipping mean filtering is shown in fig. 5. Firstly, selecting data with a corresponding filtering window width of N from response signals, and performing ascending and descending sequencing on the data in the window; shearing data at two ends of the sequencing sequence, wherein the unilateral shearing length is Lw, then taking the average value of the residual data as the result of the final shearing average value filtering, and finally performing the shearing average value filtering on all data to be processed by a sliding window, wherein the relation between a specific input response signal and a filtered response signal can be represented by the following formula (1):
where y is the result data after single window clipping mean filtering, N is the window width (odd number) of filtering, lw is the length of the single-sided clipping window,in which 2 xLw needs to be satisfied<N，x i Representing the number of data in the window.
It can be seen that the filtering parameters include window width and unilateral shearing length, the filtering effect has close relation with the reasonable selection of the two parameters, and if the selection is not proper, the output signal loses the original signal characteristics.
The filtering method based on time domain aviation electromagnetic data preprocessing provided by the disclosure can be applied to any continuous time sequence containing space-time electric noise, and is not limited to the time domain aviation electromagnetic field. The filtering method of the present disclosure is not limited to time domain avionics electromagnetic system hardware, and may be applied to other computing devices.
The following discusses the effect of the filter parameters on the filtering effect. Firstly, selecting a single-side shearing length as 8 and filtering window widths as 21, 41 and 101 respectively for the influence of the single-window filtering window width length on the removal of the natural noise, and comparing the effect of shearing mean value filtering through different window widths. Fig. 6 shows a comparison of waveforms before and after single window filtering window degree versus sky electric noise removal in the prior art. Fig. 6 is a graph showing the effect of single window filtering window degree on the pre-sky-electric noise removal in the prior art according to the present disclosure. In contrast, when the window width is small (such as 21 or 41), the response signal after denoising better maintains the variation trend of the large part of the original data difference (such as at the power supply time b and the power off time c), but the sky-electricity noise is not completely filtered (at the power off period a). When the window width is large (such as 101), the noise (at the power-off period a) can be filtered well, but the data change trends corresponding to the power-on time, the power-off time and the peak signal time can be changed, such as the situation that the data is too average to lose a useful signal (at the power-off time c) or the power-on data is early (at the power-on time b), the power-off data is late (at the power-off time c) and the peak value is reduced.
Because the data change of the response signal at the power supply starting time, the power failure starting time and the peak value time is obvious, the data change trend can be well kept by performing the shearing mean value filtering on the response signal through a small sliding window. The response signals have consistent change trend in the power supply period, the data in the power supply stage and the power failure stage slowly change, and the data in the period can be better removed by adopting a larger sliding window to carry out shearing mean filtering processing on the data in the period, so that the signal-to-noise ratio of the data is improved.
From the processing result of fig. 6, it can be seen that the small-window filtering can well maintain the data change conditions of the power supply start time, the peak time, and the power failure start time, and the large-window filtering can better remove the natural noise in the data.
It is particularly important to select the appropriate window width, but the reasonable single-edge shear length is not negligible. Fig. 7 shows a comparison of waveforms before and after single window filtering window degree versus sky electric noise removal in the prior art. Setting the length of a shearing window to be 101, respectively setting the unilateral shearing lengths Lw to be 8, 30 and 45, and comparing the influence of three different shearing lengths on the filtering effect. In contrast, when the cut lengths are 8 and 30, respectively, the data of the power supply start time and the power outage start time and the data of the peak time are averaged, resulting in problems of advancing the power supply start time, delaying the power outage start time, decreasing the peak time, and the like (at b and c in fig. 7). When the cut length is 45, the data at the filtered response peak is flattened (at b and c in fig. 7), and the filtered data fluctuates obviously (at a in fig. 7) when the sky-electricity pulse appears after the power failure.
Combining fig. 6 and fig. 7, it can be seen that the single-window clipping mean filtering is severely limited by the values of the window length and the clipping length. Therefore, the present disclosure provides a method of double-window clipping mean filtering for the first time on the basis of the formula 1. First, based on a preset small window width N =21 and a first preset clipping length Lw 1 =8 perform a cut mean filtering process on the response signal to obtain a small window filtered signal, and then, based on the preset large window width M =101 and the second preset cut length Lw 2 =40, performing a shearing mean filtering process on the response signal to obtain a large-window filtered signal, and finally, according to a response signal interval division rule, combining the first signal data and the second signal data of the large window and the small window to obtain a filtered response signal, that is, a filtered signal after the solar power is generated. FIG. 8 illustrates a schematic representation of the disclosureAnd obtaining a waveform schematic diagram of the response signal of the double-window shearing mean filtering according to the response interval division.
It should be noted that the specific sizes of the preset small window width N, the preset large window width M, the first preset clipping length, and the second preset clipping length may be obtained by setting in advance. The present disclosure is not limited to the parameters in the embodiments, and any parameter satisfying the condition may be set.
Specifically, the effect of the double-window shearing mean filtering is displayed. Fig. 9 shows a schematic diagram of comparing waveforms before and after filtering in the power-on stage by the dual-window clipping average value provided by the present disclosure, and fig. 10 is a schematic diagram of comparing waveforms before and after filtering in the power-off stage by the dual-window clipping average value provided by the present disclosure. Fig. 9 and fig. 10 show the denoising effect of the filtering method of the present disclosure when the power supply stage and the power off stage contain natural electrical noise, respectively. Based on the preset small window width N =11 and the first preset shearing length Lw 1 =3 filtering the response signal to obtain a small window filtered signal, based on the preset large window width N =101 and the second preset shearing length Lw 2 And =30, filtering the response signal to obtain a large-window filtered signal. After the double-window shearing mean value filtering, the first signal data, namely the power supply time, the power failure time and the peak value time signal keep the change trend of the original response signal, and the second signal data, namely the natural electrical noise contained in the power supply stage and power failure stage signals is better removed.
In summary, it can be known from analysis that the small-window parameter filtering has the characteristic of keeping the original response signal undamaged, and meanwhile, the condition of incomplete removal of the natural noise is caused, and the large-window parameter filtering can well remove the natural noise, but at the same time, data at different noise data change trends are excessively averaged, and the condition of serious loss of the original response signal occurs. Therefore, the method for removing the natural noise by using the double-window shearing mean value filtering method is provided for the first time, the variation trend and the stability of the response signal are reserved, the natural noise can be effectively removed, and the natural noise is removed more efficiently and more quickly.
Referring to fig. 11, a schematic structural diagram of an airborne electromagnetic data filtering apparatus provided in an embodiment of the present disclosure is shown, it should be noted that the basic principle and the generated technical effect of the airborne electromagnetic data filtering provided in the embodiment are the same as those of the corresponding method embodiment, and for brief description, reference may be made to corresponding contents in the method embodiment for parts not mentioned in the embodiment. As shown in fig. 10, the apparatus includes: a dividing module 201, a filtering module 202 and a combining module 203, wherein:
a dividing module 201, configured to divide each half cycle segment of the response signal into first signal data and second signal data, where the response signal is a signal generated by a receiving coil of the airborne electromagnetic measurement apparatus receiving a current periodically transmitted to the underground from a transmitting coil, and the first signal data includes: the power supply start time, the power off start time and the peak signal data of each half cycle of the response signal, the second signal data comprises: the power up phase and power down phase signal data for each half cycle of the response signal.
And the filtering module 202 is configured to perform sliding shearing mean filtering processing on the response signal based on a preset small window width N and a preset large window width M, respectively.
And a merging module 203, configured to merge the data subjected to the sliding shearing mean filtering processing according to the first signal data and the second signal data, so as to obtain a filtered signal from which the solar power is removed.
Optionally, the filtering module 202 is further configured to perform a shearing mean filtering process on the response signal based on a preset small window width N and a first preset shearing length, so as to obtain a small window filtering signal; and performing shearing mean value filtering processing on the response signal based on the preset large window width M and a second preset shearing length to obtain a large window filtering signal.
Wherein, first preset shearing length and preset small window width N satisfy: 2 x the first preset shearing length < the preset small window width N;
the second preset shearing length and the preset large window width M meet the following requirements: 2 x a second preset clipping length < the preset large window width M.
Referring to fig. 12, a schematic structural diagram of a filtering apparatus for airborne electromagnetic data according to another embodiment of the present disclosure is shown, the apparatus further includes: an acquisition module 204, wherein:
an obtaining module 204 is configured to obtain a signal corresponding to the first signal data from the small-window filtered signal, and obtain a signal corresponding to the second signal data from the large-window filtered signal.
And a combining module 203, configured to combine the signal corresponding to the first signal data with the signal corresponding to the second signal data, so as to obtain a filtered signal with the antenna power removed.
Referring to fig. 13, a schematic structural diagram of a filtering apparatus for airborne electromagnetic data according to another embodiment of the present disclosure is shown, the apparatus further includes: an adding module 205, configured to add the extended signal data with the preset large window width M at two ends of the response signal respectively.
Optionally, the adding module 205 is further configured to add expanded signal data with a preset large window width M at two ends of the response signal by using a periodic edge expanding manner or a mirror edge expanding manner.
Fig. 14 is a schematic structural module diagram of a filtering apparatus for airborne electromagnetic data according to the present disclosure. The airborne electromagnetic measurement apparatus may include a processor 501, a computer-readable storage medium 502 and a bus 503, the computer-readable storage medium 502 stores machine-readable instructions executable by the processor 501, when the airborne electromagnetic measurement apparatus is operated, the processor 501 and the computer-readable storage medium 502 communicate through the bus 503, and the processor 501 executes the machine-readable instructions, so that the above-mentioned method embodiments can be realized. The specific implementation and technical effects are similar, and are not described herein again.
Optionally, the present disclosure also provides a computer-readable storage medium, on which a computer program is stored, and the computer program is executed by a processor when executed, so as to implement the above method embodiments.
In the several embodiments provided in the present disclosure, it should be understood that the above-described apparatus embodiments are merely illustrative, and the disclosed apparatus and method may be implemented in other ways. For example, the division of the unit is only a logical function division, and in actual implementation, there may be another division manner, for example, multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or may not be executed, for example, each unit may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
It is noted that, in the present disclosure, relational terms such as "first" and "second", and the like, are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrases "comprising a," "...," or "comprising" does not exclude the presence of additional like elements in a process, method, article, or apparatus that comprises the element.
The above description is only a preferred embodiment of the present disclosure and is not intended to limit the present disclosure, and various modifications and changes may be made to the present disclosure by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present disclosure should be included in the protection scope of the present disclosure.
Claims (10)
1. A method of filtering airborne electromagnetic data, the method comprising:
dividing each half period segment of a response signal into first signal data and second signal data, wherein the response signal is a signal generated by a receiving coil of an aeronautical electromagnetic measurement device receiving current periodically transmitted to the underground from a transmitting coil, and the first signal data comprises: the response signal is power supply starting time, power off starting time and peak signal data of each half cycle, and the second signal data comprises: the signal data of the power supply stage and the power off stage of each half cycle of the response signal;
respectively carrying out sliding shearing mean value filtering processing on the response signals based on a preset small window width N and a preset large window width M;
and merging the data subjected to the sliding shearing mean filtering processing according to the first signal data and the second signal data to obtain a filtered signal subjected to the removal of the natural electricity.
2. The method of claim 1, wherein the performing sliding-cut mean filtering processing on the response signal based on a preset small-window width N and a preset large-window width M, respectively, comprises:
based on the preset small window width N and a first preset shearing length, carrying out shearing mean value filtering processing on the response signal to obtain a small window filtering signal;
based on the preset large window width M and a second preset shearing length, carrying out shearing mean value filtering processing on the response signal to obtain a large window filtering signal;
wherein the first preset shearing length and the preset small window width N satisfy: 2 × the first preset clipping length < the preset small window width N;
the second preset shearing length and the preset large window width M satisfy: 2 × the second preset clipping length < the preset large window width M.
3. The method of claim 2, wherein said combining said sliding-cut mean filtered data according to said first signal data and said second signal data to obtain a filtered signal with removed sky-electricity comprises:
acquiring a signal corresponding to the first signal data from the small-window filtered signal, and acquiring a signal corresponding to the second signal data from the large-window filtered signal;
and combining the signal corresponding to the first signal data with the signal corresponding to the second signal data to obtain the filtered signal with the solar electricity removed.
4. A method according to claim 2 or 3, wherein the predetermined small window width N and the predetermined large window width M are odd numbers, and the first predetermined clipping length and the second predetermined clipping length are even numbers, respectively.
5. The method according to claim 2 or 3, wherein before the sliding window clipped mean filtering processing is performed on the response signal based on the preset small window width N and the preset large window width M, the method further comprises:
and respectively increasing the extension signal data of the preset large window width M at two ends of the response signal.
6. The method of claim 5, wherein the adding the extended signal data of the preset large window width M at both ends of the response signal comprises:
and respectively increasing the expanded signal data with the preset large window width M at two ends of the response signal by adopting a periodic edge expanding mode or a mirror image edge expanding mode.
7. An apparatus for filtering airborne electromagnetic data, comprising: divide module, filtering module and merge module, wherein:
the dividing module is used for dividing each half period of a response signal into first signal data and second signal data, the response signal is a signal generated by a receiving coil of the aerial electromagnetic measuring equipment receiving current periodically transmitted to the underground from a transmitting coil, and the first signal data comprises: the power supply starting time, the power failure starting time and the peak signal data of each half cycle of the response signal, wherein the second signal data comprises: the signal data of the power supply stage and the power off stage of each half cycle of the response signal;
the filtering module is used for respectively carrying out sliding shearing mean value filtering processing on the response signals based on a preset small window width N and a preset large window width M;
and the merging module is used for merging the data subjected to the sliding shearing mean filtering processing according to the first signal data and the second signal data to obtain a filtered signal subjected to the removal of the natural electricity.
8. The filtering device according to claim 7, wherein the filtering module is specifically configured to perform a clipping mean filtering process on the response signal based on the preset small window width N and a first preset clipping length, so as to obtain a small window filtered signal; based on the preset large window width M and a second preset shearing length, carrying out shearing mean value filtering processing on the response signal to obtain a large window filtering signal;
wherein the first preset shearing length and the preset small window width N satisfy: 2 × the first preset clipping length < the preset small window width N;
the second preset shearing length and the preset large window width M satisfy: 2 × the second preset clipping length < the preset large window width M.
9. An airborne electromagnetic data filtering device, comprising: the apparatus comprises: a processor, a storage medium and a bus, the storage medium storing machine-readable instructions executable by the processor, the processor and the storage medium communicating via the bus when the airborne electromagnetic data filtering apparatus is operated, the processor executing the machine-readable instructions to perform the method of any of claims 1-6.
10. A storage medium, comprising: the storage medium has stored thereon a computer program which, when executed by a processor, performs the method of any of the preceding claims 1-6.
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| WO2015112266A2 (en) * | 2013-12-06 | 2015-07-30 | The Regents Of The University Of Michigan | Epsilon-tube filter for blunt noise removal |
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| CN104316936A (en) * | 2014-11-01 | 2015-01-28 | 中国民航大学 | Comprehensive DME pulse interference restraining method |
| CN104793253A (en) * | 2015-04-22 | 2015-07-22 | 吉林大学 | Airborne electromagnetic data denoising method based on mathematical morphology |
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