Analog-to-digital conversion method and device, equipment and medium

Abstract

The invention relates to the technical field of data processing, in particular to an analog-to-digital conversion method and device, equipment and a medium, and the method comprises the steps: sequentially converting analog signals into visible images according to a time period, and obtaining signal images; determining a target resolution required for identifying the signal image; based on the target resolution, identifying waveform features in the signal image to obtain a signal identification result; the signal identification result is used as a digital signal corresponding to the analog signal, a signal image is obtained by periodically converting the analog signal, and then waveform characteristics in the signal image are identified according to the target resolution and are used as the digital signal corresponding to the analog signal, so that sampling voltage does not need to be converted into a voltage signal; the condition of errors caused by quantization in traditional analog-to-digital conversion is avoided, and the conversion rate is improved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to an analog-to-digital conversion method, device, equipment and medium. Background Art

[0002] Traditional analog-to-digital conversion (ADC) converts a continuous analog signal into a discrete digital signal. Its core steps include sampling, holding, quantization, and encoding. This involves measuring the instantaneous voltage value of the analog signal at fixed time intervals. After sampling, a holding circuit (such as a capacitor) temporarily stores the voltage value to ensure voltage stability during the conversion process. This prevents errors caused by voltage variations during the quantization process. The continuous voltage value is then mapped to discrete quantization levels.

[0003] Since traditional sampling is implemented by circuits and quantization is achieved by measuring voltage, it limits the signal input voltage of analog-to-digital conversion. If the voltage is too high or too low, direct quantization cannot be performed.

[0004] Therefore, how to effectively quantify the analog-to-digital conversion process to avoid the above problems is a technical problem that needs to be solved urgently. Summary of the Invention

[0005] In view of the above problems, the present invention provides an analog-to-digital conversion method, apparatus, device and medium that overcome the above problems or at least partially solve the above problems.

[0006] In a first aspect, the present invention provides an analog-to-digital conversion method, comprising:

[0007] Convert the analog signal into a visible image in sequence according to the time period to obtain a signal image;

[0008] determining a target resolution required for recognizing the signal image;

[0009] Based on the target resolution, identifying waveform features in the signal image to obtain a signal recognition result;

[0010] The signal recognition result is used as the digital signal corresponding to the analog signal.

[0011] Preferably, the target resolution is greater than, less than or equal to the original resolution of the signal image.

[0012] Preferably, after converting the analog signal into a visible image in sequence according to the time period to obtain the signal image, the method further includes:

[0013] Establishing a histogram of the signal image, and locally amplifying the histogram to determine whether Gaussian noise, salt and pepper noise, and / or Poisson noise exists in the signal image;

[0014] When Gaussian noise exists, Gaussian filtering is performed on the signal image for noise reduction; when salt and pepper noise exists, median filtering is performed on the signal image for noise reduction; and / or when Poisson noise exists, mean filtering is performed on the signal image for noise reduction.

[0015] Preferably, based on the target resolution, identifying waveform features in the signal image to obtain a signal recognition result includes:

[0016] Sampling the signal image according to the target resolution to obtain a sampling result;

[0017] Based on the sampling result, image recognition technology is used to extract waveform features in the signal image to obtain a signal recognition result.

[0018] Preferably, using the signal recognition result as a digital signal corresponding to the analog signal includes:

[0019] Converting the signal recognition result into a frequency domain signal;

[0020] Filtering and denoising the frequency domain signal to obtain a denoised signal;

[0021] The noise reduction signal is converted into a time domain signal, that is, a digital signal.

[0022] In a second aspect, the present invention further provides an analog-to-digital conversion device, comprising:

[0023] The sampling module is used to convert the analog signal into a visible image in sequence according to the time period to obtain a signal image;

[0024] A determination module, configured to determine a target resolution required for identifying the signal image;

[0025] an identification module, configured to identify waveform features in the signal image based on the target resolution and obtain a signal identification result;

[0026] A conversion module is configured to use the signal recognition result as a digital signal corresponding to the analog signal. Preferably, the system further includes: a noise detection module configured to establish a histogram of the signal image and locally amplify the histogram to determine whether Gaussian noise, salt and pepper noise, and / or Poisson noise are present in the signal image; and a noise reduction module configured to perform Gaussian filtering on the signal image for noise reduction when Gaussian noise is present, perform median filtering on the signal image for noise reduction when salt and pepper noise is present, and / or perform mean filtering on the signal image for noise reduction when Poisson noise is present.

[0027] Preferably, the conversion module is used to:

[0028] Converting the signal recognition result into a frequency domain signal;

[0029] Filtering and denoising the frequency domain signal to obtain a denoised signal;

[0030] The noise reduction signal is used as a digital signal corresponding to the analog signal.

[0031] In a third aspect, the present invention further provides a computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described in the first aspect when executing the program.

[0032] In a fourth aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, which implements the method described in the first aspect when the program is executed by a processor.

[0033] One or more technical solutions in the embodiments of the present invention have at least the following technical effects or advantages:

[0034] The present invention provides an analog-to-digital conversion method, comprising: converting an analog signal into a visible image in sequence according to a time period to obtain a signal image; determining a target resolution required for identifying the signal image; identifying waveform features in the signal image to obtain a signal recognition result; using the signal recognition result as a digital signal corresponding to the analog signal, obtaining a signal image by periodically converting the analog signal, and then identifying the waveform features in the signal image according to the target resolution and using them as a digital signal corresponding to the analog signal. This method does not require sampling voltage to convert into a voltage signal, thereby avoiding the situation where quantization in traditional analog-to-digital conversion causes errors and improving the conversion rate. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. Throughout the drawings, the same reference figures denote the same components. In the drawings:

[0036] Figure 1 A schematic flow chart of the steps of the analog-to-digital conversion method according to an embodiment of the present invention is shown;

[0037] Figure 2 A schematic structural diagram of an analog-to-digital conversion device according to an embodiment of the present invention is shown;

[0038] Figure 3 A schematic structural diagram of a computer device for implementing the analog-to-digital conversion method in an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0039] Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present invention and to fully convey the scope of the present invention to those skilled in the art.

[0040] Example 1:

[0041] The embodiment of the present invention provides an analog-to-digital conversion method, such as Figure 1 As shown, including:

[0042] S101, converting analog signals into visible images in sequence according to time periods to obtain signal images.

[0043] S102, determining a target resolution required for signal image recognition;

[0044] S103, identifying waveform features in the signal image based on the target resolution to obtain a signal recognition result;

[0045] S104: Using the signal recognition result as the digital signal corresponding to the analog signal.

[0046] In a specific embodiment, taking an analog signal of current variation as an example, since current variation causes heat variation, the continuous input of this analog signal forms a time-varying current amplitude image. By sequentially performing time period conversion according to the process of S101, a signal image is obtained. The analog signal can be converted into a signal image using the operating principle of an oscilloscope, or the analog signal can be applied to a heating element (e.g., a resistor) and converted into a thermal image based on the thermal effect of the heating element using a device such as a thermal imager, as the signal image.

[0047] The time period depends on the time length supported by the signal image. Sampling according to the time period makes the signal image continuously changing. The signal image is an image of the signal state at the sampling time point over time. Here, the Mobi image is used to record the continuous change process of the signal state over time.

[0048] For the analog signal y=f(x) of current change, x∈(1, 1000000), if sampling is performed with a time period of 1000, each sampling yields f(x1), f(x2) ... f(xn), where n = 1000. This yields a signal image.

[0049] Next, the signal image can also be subjected to noise reduction processing. Specifically, after converting the analog signal into a visible image in sequence according to the time period to obtain the signal image, the method further includes: establishing a histogram of the signal image and locally amplifying the histogram to determine whether Gaussian noise, salt and pepper noise, and / or Poisson noise exist in the signal image; when Gaussian noise exists, the signal image is subjected to Gaussian filtering for noise reduction, when salt and pepper noise exists, the signal image is subjected to median filtering for noise reduction, and / or when Poisson noise exists, the signal image is subjected to mean filtering for noise reduction. Image processing technology is used to analyze the histogram and locally amplify the image to determine the noise type, including Gaussian noise, salt and pepper noise, and Poisson noise. For Gaussian noise, Gaussian filtering is used, for salt and pepper noise, median filtering is used, and for Poisson noise, mean filtering is used. Noise reduction processing is performed to avoid interference in signal conversion, which may result in a low final accuracy rate.

[0050] Next, S102 is executed to determine the target resolution required for recognizing the signal image.

[0051] The target resolution can be greater than, less than, or equal to the original resolution of the signal image.

[0052] In existing analog-to-digital conversion methods, analog signals can only be converted to a fixed resolution. The data processing unit can only passively receive the resolution of the analog-to-digital conversion result. In comparison, the present application is more flexible in terms of resolution requirements.

[0053] In the present invention, the data processing unit can obtain the required resolution through parameter configuration and other means. The target requirement is determined according to different scenarios. The resolution can be increased, decreased, or unchanged. The specific determination is based on different needs.

[0054] Scenario for increasing resolution: The application has high resolution requirements. The hardware device has strong processing capabilities and can support higher resolutions. The resolution needs to be increased to improve the effect.

[0055] Scenarios where resolution is reduced: The processing power of the hardware device is limited, or the application does not require high precision.

[0056] Scenario with constant resolution: This is an ideal situation based on the first two, and is not necessary.

[0057] Then, step S103 is executed to identify waveform features in the signal image based on the target resolution to obtain a signal recognition result.

[0058] Specifically, the signal image is sampled according to the target resolution to obtain a sampling result;

[0059] Based on the sampling results, image recognition technology is used to extract the waveform features in the signal image to obtain the signal recognition results.

[0060] The target resolution can be the spatial sampling density, where the sampling interval in the spatial domain must meet the Nyquist criterion. First, the sampling rate is calculated based on the target resolution. For example, if the original resolution of the signal image is 1000×1000 and the target resolution is 500×500, then the sampling rate is 0.5. Sampling can be performed using methods such as the nearest neighbor method, bilinear interpolation, or bicubic interpolation. This yields the sampling result.

[0061] Then, based on the sampling results, the waveform features in the signal image are extracted using image recognition technology for each sampling result to obtain a signal recognition result.

[0062] Specifically, the extraction of waveform features may include the extraction of geometric features and the extraction of texture features, wherein the geometric features include the extraction of corners, edges, and contours, and the texture features include: gray level co-occurrence matrix quantization of roughness and directionality.

[0063] Finally, S104 is executed to use the signal recognition result as the digital signal corresponding to the analog signal.

[0064] In the received analog signal graph within a period, except for the signal itself, all other parts are identical in brightness. The signal will always be the brightest pixel or unit. Based on the relative position of the brightest pixel or unit, the time domain signal graph can be obtained.

[0065] In this step, since the signal recognition result belongs to the time domain signal, there is an interference signal, which may cause the final time domain signal to be interfered. Therefore, in order to improve the accuracy, the signal recognition result can be converted into a frequency domain signal first.

[0066] This process is just like the Fourier transform of the signal graph time domain data in the previous step.

[0067] The frequency domain signal has a strong anti-interference ability. By removing the interference and then converting the frequency domain signal into a time domain signal, the time domain signal is obtained.

[0068] Specifically, the signal recognition result is converted into a frequency domain signal; the frequency domain signal is filtered and denoised to obtain a noise-reduced signal; and the noise-reduced signal is converted into a time domain signal as a digital signal corresponding to the analog signal.

[0069] In a specific implementation, the noise reduction signal may be converted into a time domain signal by using an inverse Fourier transform.

[0070]

[0071] Among them, F(jw) is the noise reduction signal after filtering and noise reduction, which is a frequency domain signal, and f(t) is the time domain signal, that is, a digital signal.

[0072] One or more technical solutions in the embodiments of the present invention have at least the following technical effects or advantages:

[0073] The present invention provides an analog-to-digital conversion method, comprising: converting an analog signal into a visible image in sequence according to a time period to obtain a signal image; determining a target resolution required for identifying the signal image; identifying waveform features in the signal image based on the target resolution to obtain a signal recognition result; using the signal recognition result as a digital signal corresponding to the analog signal, obtaining a signal image by periodically converting the analog signal, and then identifying the waveform features in the signal image according to the target resolution as a digital signal corresponding to the analog signal, without converting the sampling voltage into a voltage signal, thereby avoiding the situation where quantization in traditional analog-to-digital conversion will cause errors and improving the conversion rate.

[0074] As an extension of this embodiment, after obtaining the digital signal corresponding to the analog signal, each value of the digital signal can be amplified as needed. Then, when the digital signal is converted back to an analog signal again, the analog signal is amplified. This process does not require the addition of circuit hardware such as a voltage amplifier like the existing analog-to-digital converter.

[0075] Example 2:

[0076] Based on the same inventive concept, an embodiment of the present invention further provides an analog-to-digital conversion device, such as Figure 2 As shown, including:

[0077] The sampling module 201 is used to convert the analog signal into a visible image in sequence according to the time period to obtain a signal image;

[0078] A determination module 202 is used to determine a target resolution required for recognizing the signal image;

[0079] An identification module 203 is configured to identify waveform features in the signal image based on the target resolution to obtain a signal identification result;

[0080] The conversion module 204 is configured to use the signal recognition result as a digital signal corresponding to the analog signal.

[0081] In an optional embodiment, the method further includes:

[0082] a noise determination module, configured to establish a histogram of the signal image and locally amplify the histogram to determine whether Gaussian noise, salt and pepper noise, and / or Poisson noise exists in the signal image;

[0083] The denoising module is configured to perform Gaussian filtering on the signal image to reduce noise when Gaussian noise is present, perform median filtering on the signal image to reduce noise when salt and pepper noise is present, and / or perform mean filtering on the signal image to reduce noise when Poisson noise is present.

[0084] In an optional implementation, the target resolution is greater than or less than the original resolution of the signal image.

[0085] In an optional implementation, the identification module 203 is configured to:

[0086] Sampling the signal image according to the target resolution to obtain a sampling result;

[0087] Based on the sampling result, image recognition technology is used to extract waveform features in the signal image to obtain a signal recognition result.

[0088] In an optional implementation, the conversion module 204 is configured to:

[0089] Converting the signal recognition result into a frequency domain signal;

[0090] Filtering and denoising the frequency domain signal to obtain a denoised signal;

[0091] The noise reduction signal is used as a digital signal corresponding to the analog signal.

[0092] Example 3:

[0093] Based on the same inventive concept, an embodiment of the present invention provides a computer device, such as Figure 3 As shown, it includes a memory 304, a processor 302 and a computer program stored in the memory 304 and executable on the processor 302. When the processor 302 executes the program, the steps of the above-mentioned analog-to-digital conversion method are implemented.

[0094] Among them, Figure 3In the embodiment of the present invention, a bus architecture (represented by bus 300) is shown. Bus 300 may include any number of interconnected buses and bridges, and bus 300 links together various circuits including one or more processors represented by processor 302 and memory represented by memory 304. Bus 300 may also link together various other circuits such as peripherals, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. Bus interface 306 provides an interface between bus 300 and receiver 301 and transmitter 303. Receiver 301 and transmitter 303 may be the same component, namely a transceiver, which provides a unit for communicating with various other devices over a transmission medium. Processor 302 is responsible for managing bus 300 and general processing, while memory 304 may be used to store data used by processor 302 when performing operations.

[0095] Example 4:

[0096] Based on the same inventive concept, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the above-mentioned analog-to-digital conversion method when executed by a processor.

[0097] The algorithm and display provided herein are not inherently related to any particular computer, virtual system or other device. Various general-purpose systems can also be used together with the teachings based on this. According to the above description, it is obvious that the structure required for constructing this type of system. In addition, the present invention is not directed to any specific programming language. It should be understood that various programming languages can be utilized to realize the content of the present invention described herein, and the above description of specific languages is for the purpose of disclosing the best mode of the present invention.

[0098] In the description provided herein, numerous specific details are described. However, it is understood that embodiments of the present invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques are not shown in detail so as not to obscure the understanding of this description.

[0099] Similarly, it should be understood that in order to streamline the present invention and aid in understanding one or more of the various inventive aspects, in the above description of exemplary embodiments of the present invention, various features of the present invention are sometimes grouped together into a single embodiment, figure, or description thereof. However, this disclosed method should not be interpreted as reflecting an intention that the claimed invention requires more features than those explicitly recited in each embodiment. Rather, as reflected in each embodiment, inventive aspects lie in fewer than all the features of the individual embodiments previously disclosed. Accordingly, the claims that follow the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of the present invention.

[0100] Those skilled in the art will appreciate that the modules in the devices in the embodiments may be adaptively changed and arranged in one or more devices different from the embodiments. The modules or units or components in the embodiments may be combined into one module or unit or component, and in addition may be divided into multiple submodules or subunits or subcomponents. All features disclosed in this specification (including the accompanying claims, abstracts and drawings) and all processes or units of any method or device disclosed herein may be combined in any combination, except that at least some of such features and / or processes or units are mutually exclusive. Unless expressly stated otherwise, each feature disclosed in this specification (including the accompanying claims, abstracts and drawings) may be replaced by an alternative feature providing the same, equivalent or similar purpose.

[0101] Furthermore, those skilled in the art will appreciate that although some embodiments herein include certain features included in other embodiments but not other features, combinations of features from different embodiments are intended to be within the scope of the present invention and to form different embodiments. For example, in a specific embodiment, any one of the claimed embodiments may be used in any combination.

[0102] The various component embodiments of the present invention can be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. It will be appreciated by those skilled in the art that a microprocessor or digital signal processor (DSP) can be used in practice to implement some or all of the functions of some or all of the components in the analog-to-digital conversion device or computer equipment according to an embodiment of the present invention. The present invention can also be implemented as a device or device program (e.g., a computer program and a computer program product) for executing a part or all of the methods described herein. Such a program implementing the present invention can be stored on a computer-readable medium, or can have the form of one or more signals. Such a signal can be downloaded from an Internet website, or provided on a carrier signal, or provided in any other form.

[0103] It should be noted that the above embodiments illustrate rather than limit the invention, and that those skilled in the art may devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between brackets should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The present invention may be implemented by means of hardware comprising several different elements and by means of appropriately programmed computers. In a unit claim enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third etc. does not indicate any order. These words may be interpreted as names.

Claims

1. An analog-to-digital conversion method, characterized in that: include: Convert the analog signal into a visible image in sequence according to the time period to obtain a signal image; determining a target resolution required for recognizing the signal image; Based on the target resolution, identifying waveform features in the signal image to obtain a signal recognition result; The signal recognition result is used as the digital signal corresponding to the analog signal.

2. The method according to claim 1, wherein The target resolution is greater than, less than or equal to the original resolution of the signal image.

3. The method according to claim 1, wherein After converting the analog signal into a visible image in sequence according to the time period to obtain the signal image, the following steps are also included: Establishing a histogram of the signal image, and locally amplifying the histogram to determine whether Gaussian noise, salt and pepper noise, and / or Poisson noise exists in the signal image; When Gaussian noise exists, Gaussian filtering is performed on the signal image for noise reduction; when salt and pepper noise exists, median filtering is performed on the signal image for noise reduction; and / or when Poisson noise exists, mean filtering is performed on the signal image for noise reduction.

4. The method according to claim 1, wherein Based on the target resolution, identifying waveform features in the signal image to obtain a signal recognition result includes: Sampling the signal image according to the target resolution to obtain a sampling result; Based on the sampling result, image recognition technology is used to extract waveform features in the signal image to obtain a signal recognition result.

5. The method according to claim 1, wherein Using the signal recognition result as a digital signal corresponding to the analog signal includes: Converting the signal recognition result into a frequency domain signal; Filtering and denoising the frequency domain signal to obtain a denoised signal; The noise reduction signal is used as a digital signal corresponding to the analog signal.

6. An analog-to-digital conversion device, characterized in that: include: The sampling module is used to convert the analog signal into a visible image according to the time period and obtain the signal image in sequence; A determination module, configured to determine a target resolution required for identifying the signal image; an identification module, configured to identify waveform features in the signal image based on the target resolution and obtain a signal identification result; A conversion module is used to use the signal recognition result as a digital signal corresponding to the analog signal.

7. The device according to claim 6, characterized in that Also includes: a noise determination module, configured to establish a histogram of the signal image and locally amplify the histogram to determine whether Gaussian noise, salt and pepper noise, and / or Poisson noise exists in the signal image; The denoising module is configured to perform Gaussian filtering on the signal image to reduce noise when Gaussian noise is present, perform median filtering on the signal image to reduce noise when salt and pepper noise is present, and / or perform mean filtering on the signal image to reduce noise when Poisson noise is present.

8. The device according to claim 6, wherein Conversion modules for: Converting the signal recognition result into a frequency domain signal; Filtering and denoising the frequency domain signal to obtain a denoised signal; The noise reduction signal is converted into a time domain signal, that is, a digital signal.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the method according to any one of claims 1 to 5 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

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