Synchronous Sampling Method and Device

Abstract

This disclosure relates to the field of traction converter control technology for rail transit, and provides a synchronous sampling method and apparatus. The method includes: performing a real-time sliding sample on a real-time signal based on a real-time sampling period to obtain real-time sampled data, wherein the initial value of the real-time sampling period is a first preset value; calculating a real-time estimated angular frequency; calculating the next real-time sampling period; determining the next real-time sampling period as the real-time sampling period, and returning to execute the step of performing a real-time sliding sample on the real-time signal based on the real-time sampling period to obtain real-time sampled data, thereby cyclically updating the real-time sampling period. The sampling period of this disclosure changes in real-time with the change of the power grid cycle, improving the phase acquisition accuracy, making the sampling time more precise, greatly reducing delay, and thus obtaining higher control accuracy and achieving a better harmonic control level.

Description

Technical Field

[0001] This disclosure relates to the field of traction converter control technology for rail transit, and in particular to a synchronous sampling method and apparatus. Background Technology

[0002] Real-time control is required in the traction control systems of high-power locomotives or EMUs, which necessitates sampling external electrical analog quantities. Currently, two common sampling methods exist: asynchronous sampling and synchronous sampling. Asynchronous sampling is used in conventional controllers, where the main controller is a DSP (Digital Signal Processor) chip. These chips easily perform fixed-period calculations by executing an internal timer that triggers an interrupt at fixed intervals. Sampling and iterative algorithm calculations are performed at the interrupt point. Because the sampling period is generated by the DSP itself and is not synchronized with the frequency of the input signal (such as mains voltage), this method is called asynchronous sampling. The second method is synchronous sampling, which conditions the input signal, converts it into a square wave signal, and then estimates the sampling period through frequency division. Existing technologies suffer from poor accuracy and dynamic response capabilities, and signal delays affect control performance. Summary of the Invention

[0003] In view of this, the present disclosure provides a synchronous sampling method and apparatus to solve the problems of poor accuracy and dynamic response capability of the prior art, signal delay, and impact on control performance.

[0004] A first aspect of this disclosure provides a synchronous sampling method, comprising:

[0005] Real-time sliding sampling is performed on the real-time signal based on the real-time sampling period to obtain real-time sampling data, wherein the initial value of the real-time sampling period is a first preset value;

[0006] The real-time estimated angular frequency is calculated based on the real-time sampled data and the preset first calculation formula.

[0007] Based on the real-time estimated angular frequency and the preset second calculation formula, the next real-time sampling period is calculated;

[0008] The next real-time sampling period is determined as the real-time sampling period, and the process returns to the step of performing a real-time sliding sample on the real-time signal based on the real-time sampling period to obtain real-time sampled data, so as to cyclically update the real-time sampling period.

[0009] In some embodiments, the sampling points obtained by real-time sliding sampling are stored in a preset storage container, the initial value of which is empty. The step of performing one instance of real-time sliding sampling includes:

[0010] If the storage container is empty, a sampling point carrying a time tag is acquired every real-time sampling period until the number stored in the storage container is not less than the first threshold.

[0011] In some embodiments, the method further includes:

[0012] If the storage container is not empty, discard the first preset number of sampling points with the longest storage time, and store the first preset number of sampling points with the latest sampling time, wherein the first preset number is a positive integer.

[0013] Preferably, the first preset quantity is 1.

[0014] In some embodiments, the real-time estimated angular frequency is calculated based on the real-time sampled data and a preset first calculation formula, including:

[0015] Perform a discrete Fourier transform on the real-time sampled data to calculate the real-time real component and the real-time imaginary component;

[0016] The error signal is calculated based on the latest updated real-time estimated phase angle, the real-time real component and the real-time imaginary component, and a preset first calculation formula, wherein the initial value of the real-time estimated phase angle is a second preset value.

[0017] The angular frequency error is obtained by comparing the error signal with its corresponding real-time signal.

[0018] The angular frequency error is added to the rated angular frequency of the real-time signal to obtain the real-time estimated angular frequency;

[0019] The real-time estimated angular frequency is integrated to obtain the real-time estimated phase angle;

[0020] Save and update the real-time estimated phase angle.

[0021] In some embodiments, the first calculation formula includes:

[0022]

[0023] Wherein, the u e Indicates the error signal, u re Represents the real-time component, u im This indicates the amount of data required in real time. This indicates that the phase angle is estimated in real time.

[0024] In some embodiments, before performing the comparison processing based on the error signal and its corresponding real-time signal, the method further includes:

[0025] The error signal is low-pass filtered.

[0026] In some embodiments, calculating the next real-time sampling period based on the real-time estimated angular frequency and a preset second calculation formula includes:

[0027] The next sampling time point is calculated based on the real-time estimated phase angle, the real-time estimated angular frequency, and the preset second calculation formula.

[0028] Calculate the real-time sampling period based on the next sampling time point and the most recent sampling time point;

[0029] The second calculation formula includes:

[0030]

[0031] Among them, T s This indicates the next sampling time point. This indicates the real-time estimated angular frequency, and N represents the preset quantity.

[0032] A second aspect of this disclosure provides a synchronous sampling device, comprising:

[0033] The sampling module is used to perform a real-time sliding sample on the real-time signal based on the real-time sampling period to obtain real-time sampled data, wherein the initial value of the real-time sampling period is a first preset value;

[0034] The first calculation module is used to calculate the real-time estimated angular frequency based on the real-time sampled data and the preset first calculation formula;

[0035] The second calculation module is used to calculate the next real-time sampling period based on the real-time estimated angular frequency and the preset second calculation formula.

[0036] The repeat execution module is used to determine the next real-time sampling period as the real-time sampling period, and return to execute the step of performing a real-time sliding sample on the real-time signal based on the real-time sampling period to obtain real-time sampled data, so as to cyclically update the real-time sampling period.

[0037] In some embodiments, the sampling points obtained by real-time sliding sampling are stored in a preset storage container, the initial value of which is empty. The step of performing one instance of real-time sliding sampling includes:

[0038] If the storage container is empty, a sampling point carrying a time tag is acquired every real-time sampling period until the number stored in the storage container is not less than the first threshold.

[0039] In some embodiments, the step of performing one real-time sliding sampling further includes:

[0040] If the storage container is not empty, discard the first preset number of sampling points with the longest storage time, and store the first preset number of sampling points with the latest sampling time, wherein the first preset number is a positive integer.

[0041] Preferably, the first preset quantity is 1.

[0042] In some embodiments, the real-time estimated angular frequency is calculated based on the real-time sampled data and a preset first calculation formula, including:

[0043] Perform a discrete Fourier transform on the real-time sampled data to calculate the real-time real component and the real-time imaginary component;

[0044] The error signal is calculated based on the latest updated real-time estimated phase angle, the real-time real component and the real-time imaginary component, and a preset first calculation formula, wherein the initial value of the real-time estimated phase angle is a second preset value.

[0045] The angular frequency error is obtained by comparing the error signal with its corresponding real-time signal.

[0046] The angular frequency error is added to the rated angular frequency of the real-time signal to obtain the real-time estimated angular frequency;

[0047] The real-time estimated angular frequency is integrated to obtain the real-time estimated phase angle;

[0048] Save and update the real-time estimated phase angle.

[0049] In some embodiments, the first calculation formula includes:

[0050]

[0051] Wherein, the u e Indicates the error signal, u re Represents the real-time component, u im This indicates the amount of data required in real time. This indicates that the phase angle is estimated in real time.

[0052] In some embodiments, before performing the comparison processing based on the error signal and its corresponding real-time signal, the method further includes:

[0053] The error signal is low-pass filtered.

[0054] In some embodiments, calculating the next real-time sampling period based on the real-time estimated angular frequency and a preset second calculation formula includes:

[0055] The next sampling time point is calculated based on the real-time estimated phase angle, the real-time estimated angular frequency, and the preset second calculation formula.

[0056] Calculate the real-time sampling period based on the next sampling time point and the most recent sampling time point;

[0057] The second calculation formula includes:

[0058]

[0059] Among them, T s This indicates the next sampling time point. This indicates the real-time estimated angular frequency, and N represents the preset quantity.

[0060] A third aspect of this disclosure provides an electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method described above.

[0061] A fourth aspect of this disclosure provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described method.

[0062] A fifth aspect of this disclosure provides a computer program product comprising a computer program or instructions that, when executed by a processor, implement the steps of the method described above.

[0063] Real-time sampling data is obtained by performing a real-time sliding sample on the real-time signal based on the real-time sampling period; the real-time estimated angular frequency is calculated based on the real-time sampling data and a preset first calculation formula; the next real-time sampling period is calculated based on the real-time estimated angular frequency and a preset second calculation formula; the next real-time sampling period is determined as the real-time sampling period, and the process returns to the step of performing a real-time sliding sample on the real-time signal based on the real-time sampling period to obtain real-time sampling data, so as to cyclically update the real-time sampling period, so that the sampling period of this disclosure changes in real time with the change of the power grid cycle, improves the phase acquisition accuracy, makes the sampling time more accurate, greatly reduces the delay, and thus obtains higher control accuracy and achieves a better harmonic control level. Attached Figure Description

[0064] To more clearly illustrate the technical solutions in the embodiments of this disclosure, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0065] Figure 1 This is a schematic diagram of an application scenario of the synchronous sampling method provided according to the embodiments of this disclosure;

[0066] Figure 2 This is a flowchart of some embodiments of a synchronous sampling method provided according to the present disclosure;

[0067] Figure 3 This is a flowchart of some other embodiments of another synchronous sampling method provided according to the embodiments of this disclosure;

[0068] Figure 4 This is a simplified structural diagram of a synchronous sampling device provided according to an embodiment of the present disclosure;

[0069] Figure 5 This is a schematic diagram of an electronic device provided according to an embodiment of the present disclosure. Detailed Implementation

[0070] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0071] It should also be noted that, for ease of description, only the parts relevant to this disclosure are shown in the accompanying drawings. Unless otherwise specified, the embodiments and features described in this disclosure can be combined with each other.

[0072] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are used only to distinguish different systems, devices, modules or units, and are not used to limit the order of functions performed by these systems, devices, modules or units or their interdependencies.

[0073] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0074] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0075] This disclosure will now be described in detail with reference to the accompanying drawings and embodiments.

[0076] Figure 1This is a schematic diagram of an application scenario of a synchronous sampling method according to some embodiments of the present disclosure.

[0077] exist Figure 1 In the application scenario, firstly, the computing device 101 can perform a real-time sliding sampling on the real-time signal 103 based on the real-time sampling period 102 to obtain real-time sampling data 104, wherein the initial value of the real-time sampling period 102 is a first preset value.

[0078] Secondly, the computing device 101 can calculate the real-time estimated angular frequency 106 based on the real-time sampling data 104 and the preset first calculation formula 105.

[0079] Furthermore, the computing device 101 can calculate the next real-time sampling period 108 based on the real-time estimated angular frequency 106 and the preset second calculation formula 107.

[0080] Finally, the computing device 101 can determine the next real-time sampling period 108 as the real-time sampling period 102, and return to the step of performing a real-time sliding sample on the real-time signal based on the real-time sampling period to obtain real-time sampled data, so as to cyclically update the real-time sampling period 102.

[0081] It should be noted that the aforementioned computing device 101 can be either hardware or software. When the computing device is hardware, it can be implemented as a distributed cluster consisting of multiple servers or terminal devices, or as a single server or a single terminal device. When the computing device is software, it can be installed within the hardware devices listed above. It can be implemented as, for example, multiple software programs or software modules used to provide distributed services, or as a single software program or software module. No specific limitations are made here.

[0082] It should be understood that Figure 1 The number of computing devices shown is merely illustrative. Any number of computing devices can be used depending on implementation needs.

[0083] Continue to refer to Figure 2 The diagram illustrates a flow 200 of some embodiments of the synchronous sampling method according to this disclosure. This method can be... Figure 1 The method of synchronous sampling is performed by the computing device 101. The method includes the following steps:

[0084] Step 201: Perform a real-time sliding sample on the real-time signal based on the real-time sampling period to obtain real-time sampled data, wherein the initial value of the real-time sampling period is a first preset value.

[0085] In some embodiments, the execution subject of the synchronous sampling method (such as...) Figure 1The computing device 101 shown can be connected to the target device via a wired or wireless connection. Then, it performs a real-time sliding sample on the real-time signal based on the real-time sampling period to obtain real-time sampled data. The initial value of the real-time sampling period is a first preset value.

[0086] In this disclosure, the sampling period is calculated and may change with each sampling to improve accuracy. Therefore, the real-time sampling period can refer to the sampling period at the current time, which varies over time. Additionally, during the first run, the real-time sampling period can be set to a value that meets the requirements, i.e., a first preset value. This first preset value can be a sampling period set based on experience, but is not limited to it. Real-time sliding sampling can refer to discarding some previous sampling points and adding at least one new sampling point during sampling.

[0087] In some optional implementations, the sampling points obtained by real-time sliding sampling are stored in a preset storage container, which is initially empty. The steps of performing one real-time sliding sampling include: if the storage container is empty, acquiring a sampling point carrying a time tag every real-time sampling period until the number stored in the storage container is not less than a first threshold. If the storage container is not empty, discarding a first preset number of sampling points with the longest storage time, and storing a first preset number of the most recently sampled sampling points, where the first preset number is a positive integer. Clearly, the more data added in each real-time sliding sampling, the lower the accuracy. Therefore, preferably, the first preset number is 1.

[0088] It should be noted that the aforementioned wireless connection methods may include, but are not limited to, 3G / 4G / 5G connections, WiFi connections, Bluetooth connections, WiMAX connections, Zigbee connections, UWB (ultra wideband) connections, and other currently known or future wireless connection methods.

[0089] Step 202: Calculate the real-time estimated angular frequency based on the real-time sampling data and the preset first calculation formula.

[0090] In some embodiments, the aforementioned execution entity may calculate the real-time estimated angular frequency based on the real-time sampling data and a preset first calculation formula, through the following processing steps:

[0091] The first step is to perform a Discrete Fourier Transform on the real-time sampled data to calculate the real-time real component and the real-time imaginary component. The real-time real component refers to the real number part of the sampled data obtained after calculation. The imaginary real component refers to the imaginary number part of the sampled data obtained after calculation.

[0092] The second step involves calculating the error signal based on the most recently updated real-time estimated phase angle, the real-time real component, the real-time imaginary component, and a preset first calculation formula. The initial value of the real-time estimated phase angle is a second preset value. The real-time estimated phase angle can refer to the phase angle calculated from real-time sampled data. Since the real-time sampled data consists of multiple time-stamped data points, it can form a signal. After processing this signal based on the first calculation formula, an error signal can be obtained, representing the error data between the calculated signal and the actual signal. The first calculation formula can refer to the formula used to calculate the error signal.

[0093] In some alternative implementations, the first calculation formula includes:

[0094]

[0095] Wherein, the u e u represents the error signal for the current iteration. re u represents the real-time component of the current operation. im This indicates the current real-time demand quantity. This indicates the real-time estimated phase angle (or initial phase angle) for the current time.

[0096] The third step involves comparing the error signal with its corresponding real-time signal to obtain the angular frequency error. The angular frequency error refers to the difference between the calculated angular frequency and the actual angular frequency of the real-time signal (or the rated angular frequency).

[0097] The fourth step is to add the angular frequency error to the rated angular frequency of the real-time signal to obtain the estimated real-time angular frequency. The grid angular frequency can refer to the calculated estimated real-time angular frequency of the grid.

[0098] The fifth step is to integrate the real-time estimated angular frequency to obtain the real-time estimated phase angle. The real-time estimated phase angle refers to the calculated, estimated real-time phase angle.

[0099] Step 6: Save and update the real-time estimated phase angle.

[0100] In some optional implementations, before comparing the error signal with its corresponding real-time signal, the method further includes: performing low-pass filtering on the error signal to reduce interference from abnormal signals, thereby increasing the accuracy of the calculations in this disclosure.

[0101] Step 203: Calculate the next real-time sampling period based on the real-time estimated angular frequency and the preset second calculation formula.

[0102] In some embodiments, the aforementioned execution entity may calculate the next real-time sampling period based on the real-time estimated angular frequency and a preset second calculation formula, according to the following steps: First, calculate the next sampling time point based on the real-time estimated phase angle, the real-time estimated angular frequency, and the preset second calculation formula; Second, calculate the real-time sampling period based on the next sampling time point and the most recent sampling time point. The second calculation formula may refer to the formula used to calculate the next time sampling point. Obviously, the difference between the next sampling time point and the most recent sampling time point is the real-time sampling period.

[0103] In some alternative implementations, the second calculation formula includes:

[0104]

[0105] Among them, T s This indicates the next sampling time point. This indicates the real-time estimated angular frequency, and N represents the preset quantity.

[0106] Step 204: Determine the next real-time sampling period as the real-time sampling period, and return to the step of performing a real-time sliding sample on the real-time signal based on the real-time sampling period to obtain real-time sampled data, so as to cyclically update the real-time sampling period.

[0107] In some embodiments, the execution entity may determine the next real-time sampling period as the real-time sampling period and return to the step of performing a real-time sliding sample on the real-time signal based on the real-time sampling period to obtain real-time sampled data, so as to cyclically update the real-time sampling period. Since the parameters of the power grid may change due to various factors in the actual operating environment of the power grid, steps 201-203 need to be continuously executed cyclically to continuously update the real-time sampling period in order to improve control accuracy.

[0108] The beneficial effects of one of the above embodiments of this disclosure include at least the following: obtaining real-time sampled data by performing a real-time sliding sample on the real-time signal based on the real-time sampling period; calculating the real-time estimated angular frequency according to the real-time sampled data and a preset first calculation formula; calculating the next real-time sampling period based on the real-time estimated angular frequency and a preset second calculation formula; determining the next real-time sampling period as the real-time sampling period, and returning to execute the step of performing a real-time sliding sample on the real-time signal based on the real-time sampling period to obtain real-time sampled data, so as to cyclically update the real-time sampling period, so that the sampling period of this disclosure changes in real time with the change of the power grid cycle, improving the phase acquisition accuracy, making the sampling time more accurate, greatly reducing the delay, thereby obtaining higher control accuracy and achieving a better harmonic control level.

[0109] Continue to refer to Figure 3 The flowchart 300, showing some other embodiments of the synchronous sampling method according to the present disclosure, is illustrated. This method can be performed by... Figure 1 The synchronous sampling method is executed by the computing device 101 in the system. The synchronous sampling method includes:

[0110] Step 301: Perform real-time sliding sampling on the real-time signal based on the real-time sampling period to obtain real-time sampled data. The initial value of the real-time sampling period is a first preset value. The sampling points obtained from the real-time sliding sampling are stored in a preset storage container, which is initially empty. The step of performing the real-time sliding sampling once per cycle includes: if the storage container is empty, acquiring a sampling point carrying a time tag every real-time sampling period until the number stored in the storage container is not less than a first threshold. If the storage container is not empty, discarding a first preset number of sampling points with the longest storage time and storing the first preset number of newly sampled sampling points, where the first preset number is a positive integer. Preferably, the first preset number is 1.

[0111] Step 302: Perform a discrete Fourier transform on the real-time sampled data to calculate the real-time real component and the real-time imaginary component.

[0112] Step 303: Calculate the error signal based on the most recently updated real-time estimated phase angle, the real-time real component and the real-time imaginary component, and the preset first calculation formula, wherein the initial value of the real-time estimated phase angle is a second preset value.

[0113] Step 304: Compare the error signal with its corresponding real-time signal to obtain the angular frequency error.

[0114] Step 305: Add the angular frequency error to the rated angular frequency of the real-time signal to obtain the real-time estimated angular frequency.

[0115] Step 306: Integrate the real-time estimated angular frequency to obtain the real-time estimated phase angle.

[0116] Step 307: Save and update the real-time estimated phase angle.

[0117] Step 308: Calculate the next sampling time point based on the real-time estimated phase angle, the real-time estimated angular frequency, and the preset second calculation formula.

[0118] Step 309: Calculate the real-time sampling period based on the next sampling time point and the most recent sampling time point.

[0119] Step 310: Determine the next real-time sampling period as the real-time sampling period, and return to the step of performing a real-time sliding sample on the real-time signal based on the real-time sampling period to obtain real-time sampled data, so as to cyclically update the real-time sampling period.

[0120] In some embodiments, the specific implementation of steps 301-310 and the resulting technical effects can be found in [reference needed]. Figure 2 The steps in those corresponding embodiments will not be repeated here.

[0121] All of the above-mentioned optional technical solutions can be combined in any way to form the optional embodiments of this application, and will not be described in detail here.

[0122] The following are embodiments of the apparatus disclosed herein, which can be used to execute embodiments of the method disclosed herein. For details not disclosed in the apparatus embodiments of this disclosure, please refer to the embodiments of the method disclosed herein.

[0123] Further reference Figure 4 As an implementation of the methods described in the above figures, this disclosure provides some embodiments of a synchronous sampling device, which are similar to... Figure 2 The above-described method embodiments correspond to these.

[0124] like Figure 4 As shown, the synchronous sampling device 400 in some embodiments includes:

[0125] The sampling module 401 is used to perform a real-time sliding sampling on the real-time signal based on the real-time sampling period to obtain real-time sampling data, wherein the initial value of the real-time sampling period is a first preset value.

[0126] The first calculation module 402 is used to calculate the real-time estimated angular frequency based on the real-time sampled data and the preset first calculation formula.

[0127] The second calculation module 403 is used to calculate the next real-time sampling period based on the real-time estimated angular frequency and the preset second calculation formula.

[0128] The repeat execution module 404 is used to determine the next real-time sampling period as the real-time sampling period, and return to the step of performing a real-time sliding sampling on the real-time signal based on the real-time sampling period to obtain real-time sampling data, so as to cyclically update the real-time sampling period.

[0129] In some optional implementations of certain embodiments, the sampling points obtained by real-time sliding sampling are stored in a preset storage container, the initial value of which is empty. The step of performing one instance of real-time sliding sampling includes:

[0130] If the storage container is empty, a sampling point carrying a time tag is acquired every real-time sampling period until the number stored in the storage container is not less than the first threshold.

[0131] In some optional implementations of certain embodiments, the step of performing the real-time sliding sampling once further includes:

[0132] If the storage container is not empty, discard the first preset number of sampling points with the longest storage time, and store the first preset number of sampling points with the latest sampling time, wherein the first preset number is a positive integer.

[0133] Preferably, the first preset quantity is 1.

[0134] In some optional implementations of certain embodiments, calculating the real-time estimated angular frequency based on the real-time sampled data and a preset first calculation formula includes:

[0135] Perform a discrete Fourier transform on the real-time sampled data to calculate the real-time real component and the real-time imaginary component;

[0136] The error signal is calculated based on the latest updated real-time estimated phase angle, the real-time real component and the real-time imaginary component, and a preset first calculation formula, wherein the initial value of the real-time estimated phase angle is a second preset value.

[0137] The angular frequency error is obtained by comparing the error signal with its corresponding real-time signal.

[0138] The angular frequency error is added to the rated angular frequency of the real-time signal to obtain the real-time estimated angular frequency;

[0139] The real-time estimated angular frequency is integrated to obtain the real-time estimated phase angle;

[0140] Save and update the real-time estimated phase angle.

[0141] In some optional implementations of certain embodiments, the first calculation formula includes:

[0142]

[0143] Wherein, the u e Indicates the error signal, u re Represents the real-time component, u im This indicates the amount of data required in real time. This indicates that the phase angle is estimated in real time.

[0144] In some optional implementations of certain embodiments, before the comparison processing based on the error signal and its corresponding real-time signal, the method further includes:

[0145] The error signal is low-pass filtered.

[0146] In some optional implementations of certain embodiments, calculating the next real-time sampling period based on the real-time estimated angular frequency and a preset second calculation formula includes:

[0147] The next sampling time point is calculated based on the real-time estimated phase angle, the real-time estimated angular frequency, and the preset second calculation formula.

[0148] Calculate the real-time sampling period based on the next sampling time point and the most recent sampling time point;

[0149] The second calculation formula includes:

[0150]

[0151] Among them, T s This indicates the next sampling time point. This indicates the real-time estimated angular frequency, and N represents the preset quantity.

[0152] It is understandable that the modules described in the device 400 are similar to those in the reference. Figure 2 The steps in the described method correspond accordingly. Therefore, the operations, features, and beneficial effects described above for the method also apply to device 400 and the modules contained therein, and will not be repeated here.

[0153] like Figure 5 As shown, the electronic device 500 may include a processing unit (e.g., a central processing unit, a graphics processor, etc.) 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage device 508 into a random access memory (RAM) 503. The RAM 503 also stores various programs and data required for the operation of the electronic device 500. The processing unit 501, ROM 502, and RAM 503 are interconnected via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0154] Typically, the following devices can be connected to I / O interface 505: input devices 506 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 507 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 508 including, for example, magnetic tapes, hard disks, etc.; and communication devices 509. Communication device 509 allows electronic device 500 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 5An electronic device 500 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively. Figure 5 Each box shown can represent a device or multiple devices as needed.

[0155] In particular, according to some embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, some embodiments of this disclosure include a computer program product comprising a computer program or instructions carried on a computer-readable medium, the computer program or instructions containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 509, or installed from a storage device 508, or installed from a ROM 502. When the computer program is executed by the processing device 501, it performs the functions defined in the methods of some embodiments of this disclosure.

[0156] It should be noted that, in some embodiments of this disclosure, the computer-readable medium described above may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In some embodiments of this disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In some embodiments of this disclosure, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0157] In some implementations, clients and servers can communicate using any currently known or future-developed network protocol such as HTTP (Hypertext Transfer Protocol) and can interconnect with digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), the Internet (e.g., the Internet of Things), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future-developed networks.

[0158] The aforementioned computer-readable medium may be included in the aforementioned device; or it may exist independently and not assembled into the electronic device. The aforementioned computer-readable medium carries one or more programs that, when executed by the electronic device, cause the electronic device to: perform a real-time sliding sample on the real-time signal based on a real-time sampling period to obtain real-time sampled data, wherein the initial value of the real-time sampling period is a first preset value; calculate a real-time estimated angular frequency based on the real-time sampled data and a preset first calculation formula; calculate the next real-time sampling period based on the real-time estimated angular frequency and a preset second calculation formula; determine the next real-time sampling period as the real-time sampling period, and return to execute the step of performing a real-time sliding sample on the real-time signal based on the real-time sampling period to obtain real-time sampled data, thereby cyclically updating the real-time sampling period.

[0159] Computer program code for performing operations of some embodiments of this disclosure can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0160] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0161] The modules described in some embodiments of this disclosure can be implemented in software or hardware. The described modules can also be located in a processor, for example, and can be described as:

[0162] The system comprises a sampling module, a first calculation module, a second calculation module, and a repetitive execution module. For example, the sampling module can also be described as "a module that performs a real-time sliding sample on a real-time signal based on a real-time sampling period to obtain real-time sampled data."

[0163] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0164] The above description is merely a selection of preferred embodiments of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in the embodiments of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described inventive concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features with similar functions disclosed in the embodiments of this disclosure.

Claims

1. A synchronous sampling method, characterized in that, include: Real-time sampling data is obtained by performing a real-time sliding sample on the real-time signal based on the real-time sampling period, wherein the initial value of the real-time sampling period is a first preset value. The real-time sampled data is subjected to Discrete Fourier Transform to calculate the real-time real and imaginary components. Based on the most recently updated real-time estimated phase angle, the real-time real and imaginary components, and a preset first calculation formula, an error signal is calculated, wherein the initial value of the real-time estimated phase angle is a second preset value. The error signal is compared with its corresponding real-time signal to obtain the angular frequency error. The angular frequency error is added to the rated angular frequency of the real-time signal to obtain the real-time estimated angular frequency. The real-time estimated angular frequency is integrated to obtain the real-time estimated phase angle. The real-time estimated phase angle is saved and updated. The next sampling time point is calculated based on the real-time estimated phase angle, the real-time estimated angular frequency, and the preset second calculation formula; the real-time sampling period is calculated based on the next sampling time point and the most recent sampling time point. The next real-time sampling period is determined as the real-time sampling period, and the process returns to the step of performing a real-time sliding sample on the real-time signal based on the real-time sampling period to obtain real-time sampled data, so as to cyclically update the real-time sampling period.

2. The method according to claim 1, characterized in that, The sampling points obtained by real-time sliding sampling are stored in a preset storage container, which is initially empty. The steps of performing one real-time sliding sampling include: If the storage container is empty, a sampling point carrying a time tag is acquired every real-time sampling period until the number stored in the storage container is not less than the first threshold.

3. The method according to claim 2, characterized in that, The method further includes: If the storage container is not empty, discard the first preset number of sampling points with the longest storage time, and store the first preset number of sampling points with the latest sampling time, wherein the first preset number is a positive integer; The first preset quantity is 1.

4. The method according to claim 1, characterized in that, The first calculation formula includes: Among them, the Indicates the error signal. Represents the real-time component. This represents the real-time imaginary component. This indicates that the phase angle is estimated in real time.

5. The method according to claim 1, characterized in that, Before performing the comparison processing based on the error signal and its corresponding real-time signal, the method further includes: The error signal is low-pass filtered.

6. The method according to claim 1, characterized in that, The second calculation formula includes: in, This indicates the next sampling time point. This indicates real-time estimation of angular frequency. N This indicates the preset quantity.

7. A synchronous sampling device, characterized in that, include: The sampling module is used to perform a real-time sliding sample on the real-time signal based on the real-time sampling period to obtain real-time sampled data, wherein the initial value of the real-time sampling period is a first preset value; The first calculation module is used to perform a discrete Fourier transform on the real-time sampled data to calculate the real-time real component and the real-time imaginary component; calculate an error signal based on the most recently updated real-time estimated phase angle, the real-time real component and the real-time imaginary component, and a preset first calculation formula, wherein the initial value of the real-time estimated phase angle is a second preset value; compare the error signal with its corresponding real-time signal to obtain the angular frequency error; add the angular frequency error to the rated angular frequency of the real-time signal to obtain the real-time estimated angular frequency; perform an integral operation on the real-time estimated angular frequency to obtain the real-time estimated phase angle; and save and update the real-time estimated phase angle. The second calculation module is used to calculate the next sampling time point based on the real-time estimated phase angle, the real-time estimated angular frequency, and the preset second calculation formula; and to calculate the real-time sampling period based on the next sampling time point and the most recent sampling time point. The repeat execution module is used to determine the next real-time sampling period as the real-time sampling period, and return to the step of performing a real-time sliding sample on the real-time signal based on the real-time sampling period to obtain real-time sampled data, so as to cyclically update the real-time sampling period.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 6.

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