Radiation monitoring equipment and signal processing method, device and equipment based on combination of wavelet filtering and differential filtering

Abstract

The invention relates to the technical field of radiation detection, in particular to radiation monitoring equipment and a signal processing method, device and equipment based on combination of wavelet filtering and differential filtering, and the signal processing method based on combination of wavelet filtering and differential filtering comprises the following steps: acquiring a signal to be processed; preprocessing the signal to obtain a processed signal; and processing the processed signal by combining a wavelet filtering algorithm with a delay differential filtering algorithm to obtain a pulse signal peak value. According to the signal processing method based on combination of wavelet filtering and differential filtering, the obtained signal is preprocessed, and then the processed signal is processed by combining a wavelet filtering algorithm and a delay differential filtering algorithm to obtain a pulse signal peak value, so that the signal filtering precision is improved; the technical problem that an existing signal processing filtering mode is low in filtering precision is solved.

Description

Technical Field

[0001] The present application relates to the technical field of radiation detection, and in particular, to a radiation monitoring device and a signal processing method, device, and equipment based on wavelet filtering combined with differential filtering. Background Art

[0002] The signals output by nuclear radiation detectors usually contain noise and glitches, which will affect subsequent dose rate calculations and data processing. Existing signal processing can adopt filtering algorithms, moving average filtering methods, wavelet threshold filtering algorithms, and delayed differential filtering methods, etc. Filtering algorithms such as Kalman filters can smooth the signals to a certain extent, but often have problems such as too long response time or insufficient noise suppression. For gamma dosimeters made of semiconductor materials, a moving average filtering method combined with a mutation algorithm is generally used for filtering, which has problems such as low accuracy and slow response speed. Due to its good localization characteristics, the wavelet threshold filtering algorithm has been widely used in the field of signal filtering. The delayed differential filtering method is a simple filtering algorithm with the advantages of small computational complexity and fast response speed. And combined with symbol discrimination calculation, it can extract the pulse signal peak value of the semiconductor dosimeter probe and can be directly applied to the subsequent pulse amplitude discrimination algorithm. Summary of the Invention

[0003] The present application provides a radiation monitoring device and a signal processing method, device, and equipment based on wavelet filtering combined with differential filtering, which are used to solve the technical problem of low filtering accuracy in the existing signal processing filtering methods.

[0004] To achieve the above object, the present application provides the following technical solutions:

[0005] On the one hand, a signal processing method based on wavelet filtering combined with differential filtering is provided, including the following steps:

[0006] Obtain the signal to be processed;

[0007] Preprocess the signal to obtain a processed signal;

[0008] Process the processed signal by using a wavelet filtering algorithm combined with a delayed differential filtering algorithm to obtain the pulse signal peak value.

[0009] Preferably, processing the processed signal by using a wavelet filtering algorithm combined with a delayed differential filtering algorithm to obtain the pulse signal peak value includes:

[0010] Perform wavelet transform and multi-scale decomposition processing on the processed signal to obtain several first wavelet coefficients;

[0011] Perform threshold filtering processing on each of the first wavelet coefficients to obtain the corresponding second wavelet coefficients;

[0012] Perform wavelet reconstruction on all the second wavelet coefficients to obtain a reconstructed waveform; determine the pulse width based on the reconstructed waveform and determine the differential delay parameter based on the pulse width;

[0013] Perform delayed difference filtering on the reconstructed waveform according to the differential delay parameter to obtain several difference values;

[0014] Perform discriminant extraction based on all the difference values to obtain extracted data; plot the extracted data into a pulse signal and extract the peak value of the pulse signal from the pulse signal;

[0015] Wherein, the value of the differential delay parameter is greater than the value of the pulse width.

[0016] Preferably, performing threshold filtering on each of the first wavelet coefficients to obtain the corresponding second wavelet coefficients includes: performing threshold filtering on each of the first wavelet coefficients using a threshold filtering function to obtain the corresponding second wavelet coefficients; the expression of the threshold filtering function is:

[0017]

[0018]

[0019] In the formula, λ is the second wavelet coefficient, x is the first wavelet coefficient, a is the median of all the first wavelet coefficients, and N is the total number of the first wavelet coefficients.

[0020] Preferably, determining the pulse width based on the reconstructed waveform includes:

[0021] Obtain two adjacent local maxima from the reconstructed waveform, and calculate the interval distance based on the two adjacent local maxima;

[0022] Obtain the sampling frequency of the signal, and calculate the pulse width based on the interval distance and the sampling frequency.

[0023] Preferably, performing discriminant extraction based on all the difference values to obtain the extracted data includes: extracting the difference values greater than the difference threshold from all the difference values to obtain the extracted data.

[0024] Preferably, preprocessing the signal to obtain a processed signal includes: performing a first preprocessing on the signal to obtain the baseline of the signal; processing the signal according to the baseline to obtain the processed signal. Performing a first preprocessing on the signal to obtain the baseline of the signal includes: calculating the mean value of some consecutive low-value data in the signal to obtain the data mean value; using the data mean value as the baseline of the signal.

[0025] Preferably, processing the signal according to the baseline to obtain a processed signal includes: subtracting the data of the baseline from the data of the signal to obtain the processed signal.

[0026] In another aspect, a radiation monitoring device is provided, which includes a device body and a control board built in the device body. A control system is provided on the control board, and a probe for collecting signals is provided on the device body. The control system includes a collection unit and a data processing unit. The collection unit is used for the signals collected by the probe, and the data processing unit is used to process the signal according to the signal processing method based on wavelet filtering combined with differential filtering described above.

[0027] In another aspect, a signal processing device based on wavelet filtering combined with differential filtering is provided, which includes a signal acquisition module, a first signal processing module, and a second signal processing module. The second signal processing module includes a transformation sub-module, a filtering sub-module, a parameter determination sub-module, a processing sub-module, and an extraction sub-module;

[0028] The signal acquisition module is used to acquire the signal to be processed;

[0029] The first signal processing module is used to preprocess the signal to obtain the baseline of the signal; process the signal according to the baseline to obtain a processed signal;

[0030] The second signal processing module is used to process the processed signal by using a wavelet filtering algorithm combined with a delayed differential filtering algorithm to obtain the peak value of the pulse signal;

[0031] The transformation sub-module is used to perform wavelet transform and multi-scale decomposition processing on the processed signal to obtain several first wavelet coefficients;

[0032] The filtering sub-module is used to perform threshold filtering processing on each of the first wavelet coefficients to obtain corresponding second wavelet coefficients;

[0033] The parameter determination sub-module is used to perform wavelet reconstruction on all the second wavelet coefficients to obtain a reconstructed waveform; determine the pulse width according to the reconstructed waveform and determine the differential delay parameter according to the pulse width;

[0034] The processing sub-module is used to perform delayed differential filtering processing on the reconstructed waveform according to the differential delay parameter to obtain several difference values;

[0035] The extraction sub-module is used to perform discriminant extraction according to all the difference values to obtain extraction data; plot all the extraction data into a pulse signal, and extract the peak value of the pulse signal from the pulse signal;

[0036] Among them, the value of the differential delay parameter is greater than the value of the pulse width.

[0037] On the other hand, a terminal device is provided, including a processor and a memory;

[0038] The memory is used to store program codes and transmit the program codes to the processor;

[0039] The processor is used to execute the signal processing method based on wavelet filtering combined with differential filtering described above according to the instructions in the program codes.

[0040] The radiation monitoring device, the signal processing method, device and equipment based on wavelet filtering combined with differential filtering. The signal processing method based on wavelet filtering combined with differential filtering includes obtaining a signal to be processed; preprocessing the signal to obtain the baseline of the signal; processing the signal according to the baseline to obtain a processed signal; and processing the processed signal by using a wavelet filtering algorithm combined with a delayed differential filtering algorithm to obtain the peak value of the pulse signal.

[0041] It can be seen from the above technical solutions that the present application has the following advantages: After preprocessing the obtained signal, the signal processing method based on wavelet filtering combined with differential filtering processes the processed signal by using a wavelet filtering algorithm combined with a delayed differential filtering algorithm to obtain the peak value of the pulse signal, improving the signal filtering accuracy and solving the technical problem of low filtering accuracy existing in the existing signal processing filtering methods.

[0042] The radiation monitoring device realizes the operation of the signal processing method based on wavelet filtering combined with differential filtering through the data processing unit, thereby reducing the requirements of the control board for the hardware circuit and facilitating the subsequent energy spectrum type dose measurement of the radiation monitoring device.

[0043] The signal processing device based on wavelet filtering combined with differential filtering filters the signal obtained by the radiation monitoring device through the signal acquisition module, the first signal processing module and the second signal processing module, improving the efficiency and accuracy of filtering the processed signal. Description of the Drawings

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained according to these drawings without creative efforts.

[0045] Figure 1 It is a step flowchart of the signal processing method based on wavelet filtering combined with differential filtering described in the embodiments of the present application;

[0046] Figure 2 It is a flowchart of the wavelet filtering algorithm combined with the delayed difference filtering algorithm in the signal processing method based on wavelet filtering combined with difference filtering described in the embodiments of the present application.

[0047] Figure 3 It is a schematic diagram of the framework of the radiation monitoring device described in the embodiments of the present application.

[0048] Figure 4 It is a schematic diagram of the framework of the signal processing device based on wavelet filtering combined with difference filtering described in the embodiments of the present application.

[0049] Figure 5 It is a schematic diagram of the terminal device described in the embodiments of the present application. Detailed implementation manners

[0050] To make the objectives, features, and advantages of the present application more obvious and understandable, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the embodiments described below are only a part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.

[0051] In the description of the embodiments of the present application, the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the embodiments of the present application, "a plurality of" means two or more unless otherwise specifically defined.

[0052] In the embodiments of the present application, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed", etc. shall be understood in a broad sense. For example, it may be a fixed connection, a detachable connection, or integrated; it may be a mechanical connection or an electrical connection; it may be directly connected or indirectly connected through an intermediate medium, and it may be the internal communication of two components or the interaction relationship between two components. For those of ordinary skill in the art, the specific meanings of the above terms in the embodiments of the present application can be understood according to specific situations.

[0053] Explanation of the patent terms of the present application:

[0054] Wavelet reconstruction refers to the process of recombining the decomposed wavelet coefficients into the original signal through the inverse process of wavelet transform.

[0055] The embodiments of the present application provide a radiation monitoring device and a signal processing method, device, and equipment based on wavelet filtering combined with differential filtering, which solve the technical problem of low filtering accuracy in the existing filtering methods for signal processing. The radiation monitoring device and the signal processing method, device, and equipment based on wavelet filtering combined with differential filtering will process the signals collected by the probe of the radiation monitoring device through a dual filter of preprocessing and a combination of wavelet filtering algorithm and delayed differential filtering algorithm, enabling the radiation monitoring device to measure within a certain period of time, output the filtered signals on the premise of ensuring the measurement accuracy, extract the peak values of pulse signals, and directly perform pulse amplitude discrimination.

[0056] Embodiment 1:

[0057] Figure 1 It is a flowchart of the steps of the signal processing method based on wavelet filtering combined with differential filtering according to the embodiments of the present application.

[0058] As Figure 1 shown, the embodiments of the present application provide a signal processing method based on wavelet filtering combined with differential filtering, including the following steps:

[0059] S1. Obtain the signal to be processed.

[0060] It should be noted that step S1 is to obtain the signal to be processed. In this embodiment, the signal processing method based on wavelet filtering combined with differential filtering can collect the signal to be processed through a radiation monitoring device to provide data for subsequent steps. Among them, the radiation monitoring device can be a semiconductor radiation dosimeter. In other embodiments, the signal processing method based on wavelet filtering combined with differential filtering can also process the signals collected by other devices (such as wireless data collectors, base station signal collectors, etc.).

[0061] S2. Preprocess the signal to obtain a processed signal.

[0062] It should be noted that step S2 is to preprocess the signal obtained according to step S1 to obtain a processed signal.

[0063] In the embodiments of the present application, preprocessing the signal to obtain a processed signal includes: performing a first preprocessing on the signal to obtain the baseline of the signal; processing the signal according to the baseline to obtain a processed signal. Performing a first preprocessing on the signal to obtain the baseline of the signal includes: calculating the mean value of some consecutive low-value data in the signal to obtain the data mean value; using the data mean value as the baseline of the signal.

[0064] It should be noted that the signal processing method based on wavelet filtering combined with differential filtering obtains the data mean value as the baseline of the signal by taking the average operation on the low-value data of some consecutive signals obtained in step S1.

[0065] In the embodiment of the present application, processing the signal according to the baseline to obtain a processed signal includes: subtracting the data of the baseline from the data of the signal to obtain the processed signal.

[0066] It should be noted that after obtaining the baseline, in order to extract the peak value of the pulse signal subsequently, it is necessary to subtract the data of the baseline from the data of the signal to obtain the processed signal.

[0067] S3. Process the processed signal by using a wavelet filtering algorithm combined with a delayed difference filtering algorithm to obtain the peak value of the pulse signal.

[0068] It should be noted that in step S3, the peak value of the pulse signal is obtained by using a wavelet filtering algorithm combined with a delayed difference filtering algorithm for the processed signal. In this embodiment, this signal processing method based on wavelet filtering combined with difference filtering can filter out most of the noise of the collected signal and can remove persistent noise by using a wavelet filtering algorithm combined with a delayed difference filtering algorithm, improving the accuracy of extracting the peak value of the pulse signal from the signal.

[0069] In the embodiment of the present application, this signal processing method based on wavelet filtering combined with difference filtering first preprocesses and processes the signal to obtain a processed signal, and then uses a wavelet filtering algorithm combined with a delayed difference filtering algorithm to extract the peak value of the pulse signal, realizing that pulse amplitude discrimination can be directly performed through this signal processing method based on wavelet filtering combined with difference filtering. This signal processing method based on wavelet filtering combined with difference filtering can automatically adjust the difference filter coefficient by using a wavelet filtering algorithm combined with a delayed difference filtering algorithm, improving the filtering accuracy, and obtaining the peak value of the pulse signal by using a wavelet filtering algorithm combined with a delayed difference filtering algorithm, improving the measurement accuracy of the radiation monitoring device.

[0070] A signal processing method based on wavelet filtering combined with difference filtering provided by the present application includes obtaining a signal to be processed; preprocessing the signal to obtain the baseline of the signal; processing the signal according to the baseline to obtain a processed signal; processing the processed signal by using a wavelet filtering algorithm combined with a delayed difference filtering algorithm to obtain the peak value of the pulse signal. This signal processing method based on wavelet filtering combined with difference filtering preprocesses and processes the obtained signal, and then uses a wavelet filtering algorithm combined with a delayed difference filtering algorithm to process the processed signal to obtain the peak value of the pulse signal, improving the signal filtering accuracy; solving the technical problem that the existing filtering method for signal processing has low filtering accuracy.

[0071] It should be noted that on the premise of ensuring the measurement accuracy, the radiation monitoring device can obtain the peak value of the pulse signal through the signal processing method based on wavelet filtering combined with differential filtering, and can directly perform pulse amplitude discrimination. Furthermore, the radiation monitoring device can directly perform energy spectrum counting measurement, improving the filtering accuracy and the measurement accuracy of the radiation monitoring device.

[0072] Figure 2 It is a flowchart of the wavelet filtering algorithm combined with the delayed differential filtering algorithm in the signal processing method based on wavelet filtering combined with differential filtering described in the embodiments of the present application.

[0073] As Figure 2 shown, in an embodiment of the present application, the wavelet filtering algorithm combined with the delayed differential filtering algorithm is used to process the processed signal, and obtaining the peak value of the pulse signal includes:

[0074] Performing wavelet transform and multi-scale decomposition processing on the processed signal to obtain several first wavelet coefficients;

[0075] Performing threshold filtering processing on each first wavelet coefficient to obtain the corresponding second wavelet coefficient;

[0076] Performing wavelet reconstruction on all the second wavelet coefficients to obtain a reconstructed waveform; determining the pulse width according to the reconstructed waveform and determining the differential delay parameter according to the pulse width;

[0077] Performing delayed differential filtering processing on the reconstructed waveform according to the differential delay parameter to obtain several difference values;

[0078] Performing discriminant extraction according to all the difference values to obtain extracted data; plotting all the extracted data into a pulse signal, and extracting the peak value of the pulse signal from the pulse signal;

[0079] Among them, the value of the differential delay parameter is greater than the value of the pulse width.

[0080] It should be noted that the Daubechies function is selected as the wavelet basis function and the decomposition layer number is set to perform wavelet transform and multi-scale decomposition processing on the processed signal to obtain several first wavelet coefficients. The first wavelet coefficients may include vectors of approximation coefficients and detail coefficients. In this embodiment, the wavelet basis function is selected considering transient capture ability, noise suppression, and energy conservation. The Daubechies wavelet basis function is suitable for the scenarios of denoising low signal-to-noise ratio signals and energy integration. The rule for selecting the decomposition layer number is noise separation and online dose calculation, and the layer number determines the fineness of signal decomposition. Therefore, in the signal processing process, the selection of the wavelet basis function has a great influence on the signal processing effect, and the decomposition layer number of wavelet decomposition determines the fineness of signal decomposition.

[0081] In the embodiment of the present application, a reconstructed waveform is obtained by wavelet reconstruction based on the second wavelet coefficient λ; delay subtraction can be understood as: obtaining signal values for the same signal in the reconstructed waveform according to the differential delay parameter, and subtracting two adjacent signal values to obtain a difference value.

[0082] In an embodiment of the present application, performing threshold filtering on each first wavelet coefficient to obtain the corresponding second wavelet coefficient includes: performing threshold filtering on each first wavelet coefficient using a threshold filtering function to obtain the corresponding second wavelet coefficient; the expression of the threshold filtering function is:

[0083]

[0084]

[0085] In the formula, λ is the second wavelet coefficient, x is the first wavelet coefficient, a is the median of all first wavelet coefficients, and N is the total number of first wavelet coefficients.

[0086] It should be noted that performing threshold filtering on the decomposed first wavelet coefficients using a threshold filtering function to obtain the second wavelet coefficients provides analysis data for subsequent steps. In this embodiment, the second wavelet coefficient contains vectors of approximation coefficients and detail coefficients used in wavelet reconstruction.

[0087] In an embodiment of the present application, determining the pulse width according to the reconstructed waveform includes:

[0088] Obtaining two adjacent local maxima from the reconstructed waveform, and calculating according to the two adjacent local maxima to obtain an interval distance;

[0089] Obtaining the sampling frequency of the signal, and calculating according to the interval distance and the sampling frequency to obtain the pulse width.

[0090] It should be noted that the findpeaks function is used to obtain two adjacent local maxima from the reconstructed waveform. The adjacent local maxima correspond to the start and end of the signal. Calculate the interval distance d between the two adjacent local maxima, and then combine the known sampling frequency f. Divide the interval distance d by the sampling frequency f to obtain the pulse width t, that is, t = d / f.

[0091] In the embodiment of the present application, performing discriminant extraction according to all difference values to obtain extraction data includes: extracting the difference values with difference values greater than the difference threshold from all difference values to obtain extraction data.

[0092] It should be noted that the difference value is compared with the difference threshold. If there is a continuous segment where the difference values are all greater than the difference threshold and a continuous segment where the difference values are all less than the difference threshold. If the distance of the continuous segment where the difference values are greater than the difference threshold is greater than the interval distance d, all the difference data of this segment are used as the extracted data. After performing wavelet transform reconstruction on all the extracted data to obtain a waveform signal, a pulse signal is obtained from the waveform signal, and the peak values of the pulse signals are extracted from all the pulse signals using the findpeaks function. In this embodiment, the difference threshold can be selected as 0. The difference threshold can also be set according to requirements.

[0093] In the embodiment of the present application, the signal processing method based on wavelet filtering combined with differential filtering has the function of output data stability. The signal processing method based on wavelet filtering combined with differential filtering can, according to the acquired signal, obtain the pulse signal width through processing and analysis by the wavelet filtering algorithm, and after passing through the delayed differential filtering algorithm, the signal-to-noise ratio of the signal is further improved. By analyzing the data result of the delayed differential filtering algorithm in combination with symbol discrimination, the peak values of the pulse signals can be further extracted.

[0094] Embodiment 2:

[0095] Figure 3 It is a schematic framework diagram of the radiation monitoring device described in the embodiment of the present application.

[0096] As Figure 3 shown, the embodiment of the present application provides a radiation monitoring device, including a device body 1 and a control board built in the device body 1. A control system is arranged on the control board, and a probe for collecting signals is arranged on the device body 1. The control system includes a collection unit 2 and a data processing unit 3. The collection unit 2 is used for the signals collected by the probe, and the data processing unit 3 is used to process the signals according to the above-mentioned signal processing method based on wavelet filtering combined with differential filtering.

[0097] It should be noted that the content of the signal processing method based on wavelet filtering combined with differential filtering has been described in Embodiment 1 and will not be repeated in this embodiment. In this embodiment, the measurement result obtained by the radiation monitoring device is regarded as the signal collected by the probe during the waiting time. The signal is processed by a dual filter combining the wavelet filtering algorithm and the delayed differential filtering algorithm, enabling the radiation monitoring device to perform measurements within a certain period of time. On the premise of ensuring the measurement accuracy, it can obtain the peak values of the pulse signals and can directly perform pulse amplitude discrimination. The radiation monitoring device can automatically adjust the differential filter coefficient, improving the filtering accuracy, and can obtain the peak values of the pulse signals on this basis, improving the measurement accuracy of the radiation monitoring device.

[0098] In the embodiment of the present application, the radiation monitoring device runs a signal processing method based on wavelet filtering combined with differential filtering through the data processing unit 3, thereby reducing the requirements of the control board for the hardware circuit and facilitating the radiation monitoring device to implement subsequent energy spectrum type dose measurement.

[0099] Embodiment Three:

[0100] Figure 4 It is a schematic framework diagram of the signal processing device based on wavelet filtering combined with differential filtering described in the embodiment of the present application.

[0101] As Figure 4 shown, the embodiment of the present application provides a signal processing device based on wavelet filtering combined with differential filtering, including a signal acquisition module 10, a first signal processing module 20, and a second signal processing module 30; the second signal processing module 30 includes a transformation sub-module, a filtering sub-module, a parameter determination sub-module, a processing sub-module, and an extraction sub-module;

[0102] The signal acquisition module 10 is used to acquire the signal to be processed;

[0103] The first signal processing module 20 is used to preprocess the signal to obtain the baseline of the signal; process the signal according to the baseline to obtain a processed signal;

[0104] The second signal processing module 30 is used to process the processed signal by using a wavelet filtering algorithm combined with a delayed differential filtering algorithm to obtain the peak value of the pulse signal;

[0105] The transformation sub-module is used to perform wavelet transform and multi-scale decomposition processing on the processed signal to obtain several first wavelet coefficients;

[0106] The filtering sub-module is used to perform threshold filtering processing on each first wavelet coefficient to obtain the corresponding second wavelet coefficient;

[0107] The parameter determination sub-module is used to perform wavelet reconstruction on all the second wavelet coefficients to obtain a reconstructed waveform; determine the pulse width according to the reconstructed waveform and determine the differential delay parameter according to the pulse width;

[0108] The processing sub-module is used to perform delayed differential filtering processing on the reconstructed waveform according to the differential delay parameter to obtain several difference values;

[0109] The extraction sub-module is used to perform discrimination extraction according to all the difference values to obtain extraction data; draw all the extraction data into a pulse signal, and extract the peak value of the pulse signal from the pulse signal;

[0110] Among them, the value of the differential delay parameter is greater than the value of the pulse width.

[0111] It should be noted that the content of the modules in the device of Embodiment 3 has been described in the steps of the method of Embodiment 1, and the content of the modules of the signal processing device based on wavelet filtering combined with differential filtering will not be repeated in this embodiment. In this embodiment, the signal processing device based on wavelet filtering combined with differential filtering filters the signals obtained by the radiation monitoring device through a signal acquisition module, a first signal processing module, and a second signal processing module, improving the efficiency and accuracy of filtering the signals.

[0112] Embodiment 4:

[0113] Figure 5 It is a schematic diagram of the terminal device described in the embodiments of the present application.

[0114] As Figure 5 shown, the embodiments of the present application provide a terminal device, including a processor and a memory;

[0115] The memory is used to store program codes and transmit the program codes to the processor;

[0116] The processor is used to execute the above-mentioned signal processing method based on wavelet filtering combined with differential filtering according to the instructions in the program codes.

[0117] It should be noted that the processor is used to execute the steps in the above-mentioned embodiment of a signal processing method based on wavelet filtering combined with differential filtering according to the instructions in the program codes. Or, when the processor executes the computer program, it realizes the functions of each module / unit in the above-mentioned system / device embodiments.

[0118] Exemplarily, the computer program can be divided into one or more modules / units. One or more modules / units are stored in the memory and executed by the processor to complete the present application. One or more modules / units can be a series of computer program instruction segments capable of performing specific functions, and the instruction segments are used to describe the execution process of the computer program in the terminal device.

[0119] The terminal device can be a computing device such as a desktop computer, a notebook, a palm computer, and a cloud server. The terminal device may include, but is not limited to, a processor and a memory. Those skilled in the art can understand that it does not constitute a limitation on the terminal device, and it may include more or fewer components than shown in the figure, or combine certain components, or different components. For example, the terminal device may further include input / output devices, network access devices, buses, etc.

[0120] The so-called processor may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0121] The memory may be an internal storage unit of the terminal device, such as the hard disk or memory of the terminal device. The memory may also be an external storage device of the terminal device, such as a plug-in hard disk, SmartMedia Card (SMC), Secure Digital (SD) card, Flash Card, etc. equipped on the terminal device. Further, the memory may also include both the internal storage unit and the external storage device of the terminal device. The memory is used to store computer programs and other programs and data required by the terminal device. The memory may also be used to temporarily store data that has been output or is to be output.

[0122] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the above-described systems, devices, and units can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0123] In several embodiments provided in the present application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other may be through some interfaces, and the indirect couplings or communication connections of the devices or units may be in electrical, mechanical, or other forms.

[0124] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0125] In addition, each functional unit in various embodiments of the present invention may be integrated into a processing unit, may exist physically as individual units, or two or more units may be integrated into one unit. The above-mentioned integrated units may be implemented in the form of hardware or in the form of software functional units.

[0126] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, may be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs, etc., which can store program codes.

[0127] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of the present application.

Claims

1. A signal processing method based on wavelet filtering combined with differential filtering, characterized in that Including the following steps: Obtain the signal to be processed; Perform preprocessing on the signal to obtain a processed signal; Process the processed signal using a wavelet filtering algorithm combined with a delayed difference filtering algorithm to obtain the peak value of the pulse signal.

2. The signal processing method based on wavelet filtering combined with differential filtering according to claim 1, wherein, Processing the processed signal using a wavelet filtering algorithm combined with a delayed difference filtering algorithm to obtain the peak value of the pulse signal includes: Perform wavelet transform and multi-scale decomposition processing on the processed signal to obtain several first wavelet coefficients; Perform threshold filtering processing on each of the first wavelet coefficients to obtain corresponding second wavelet coefficients; Perform wavelet reconstruction on all the second wavelet coefficients to obtain a reconstructed waveform; determine the pulse width according to the reconstructed waveform and determine the differential delay parameter according to the pulse width; Perform delayed difference filtering processing on the reconstructed waveform according to the differential delay parameter to obtain several difference values; Perform discriminant extraction according to all the difference values to obtain extraction data; plot all the extraction data into a pulse signal, and extract the peak value of the pulse signal from the pulse signal; Wherein, the value of the differential delay parameter is greater than the value of the pulse width.

3. The signal processing method based on wavelet filtering combined with differential filtering according to claim 2, characterized in that, Performing threshold filtering processing on each of the first wavelet coefficients to obtain corresponding second wavelet coefficients includes: performing threshold filtering processing on each of the first wavelet coefficients using a threshold filtering function to obtain corresponding second wavelet coefficients; the expression of the threshold filtering function is: In the formula, λ is the second wavelet coefficient, x is the first wavelet coefficient, a is the median of all the first wavelet coefficients, and N is the total number of the first wavelet coefficients.

4. The signal processing method based on wavelet filtering combined with differential filtering according to claim 2, wherein Determining the pulse width according to the reconstructed waveform includes: Obtain two adjacent local maxima from the reconstructed waveform, and calculate according to the two adjacent local maxima to obtain an interval distance; Obtain the sampling frequency of the signal, and calculate according to the interval distance and the sampling frequency to obtain the pulse width.

5. The signal processing method based on wavelet filtering combined with differential filtering according to claim 2, wherein Performing discriminant extraction according to all the difference values to obtain extraction data includes: extracting the difference values whose difference values are greater than the difference threshold from all the difference values to obtain extraction data.

6. The signal processing method based on wavelet filtering combined with differential filtering according to any one of claims 1-5, characterized in that, Performing preprocessing on the signal to obtain a processed signal includes: performing first preprocessing on the signal to obtain the baseline of the signal; processing the signal according to the baseline to obtain a processed signal.

7. The signal processing method based on wavelet filtering combined with differential filtering according to claim 6, wherein, Processing the signal according to the baseline to obtain a processed signal includes: subtracting the data of the baseline from the data of the signal to obtain a processed signal.

8. A radiation monitoring device, characterized in that, Including a device body and a control board built in the device body, a control system is arranged on the control board, a probe for collecting signals is arranged on the device body, the control system includes a collection unit and a data processing unit, the collection unit is used for the signal collected by the probe, and the data processing unit is used for processing the signal according to the signal processing method based on wavelet filtering combined with difference filtering according to any one of claims 1-7.

9. A signal processing device based on wavelet filtering combined with differential filtering, characterized in that, Including: A signal acquisition module, a first signal processing module and a second signal processing module, the second signal processing module includes a transformation sub-module, a filtering sub-module, a parameter determination sub-module, a processing sub-module and an extraction sub-module; The signal acquisition module is configured to acquire the signal to be processed; The first signal processing module is configured to preprocess the signal to obtain the baseline of the signal; process the signal according to the baseline to obtain a processed signal; The second signal processing module is configured to process the processed signal by using a wavelet filtering algorithm combined with a delayed difference filtering algorithm to obtain the peak value of the pulse signal; The transformation sub-module is configured to perform wavelet transform and multi-scale decomposition processing on the processed signal to obtain several first wavelet coefficients; The filtering sub-module is configured to perform threshold filtering processing on each of the first wavelet coefficients to obtain corresponding second wavelet coefficients; The parameter determination sub-module is configured to perform wavelet reconstruction on all the second wavelet coefficients to obtain a reconstructed waveform; Determine the pulse width according to the reconstructed waveform and determine the differential delay parameter according to the pulse width; The processing sub-module is configured to perform delayed difference filtering processing on the reconstructed waveform according to the differential delay parameter to obtain several difference values; The extraction sub-module is configured to perform discriminant extraction according to all the difference values to obtain extraction data; plot all the extraction data into a pulse signal, and extract the peak value of the pulse signal from the pulse signal; Wherein, the value of the differential delay parameter is greater than the value of the pulse width.

10. A terminal device, characterized in that, It includes a processor and a memory; The memory is configured to store program code and transmit the program code to the processor; The processor is configured to execute the signal processing method based on wavelet filtering combined with differential filtering according to the instructions in the program code as described in any one of claims 1-7.

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