Synchronous sampling method and device

Abstract

The invention relates to the technical field of rail transit traction converter control, and provides a synchronous sampling method and device. The method comprises the steps that one-time real-time sliding sampling is carried out on a real-time signal based on a real-time sampling period, real-time sampling data are obtained, and the initial value of the real-time sampling period is a first preset value; calculating a real-time estimated angular frequency; calculating a next real-time sampling period; and determining the next real-time sampling period as the real-time sampling period, and returning to the step of performing one-time 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 circularly update the real-time sampling period. The phase acquisition precision is improved, the sampling time is more accurate, and the delay is greatly reduced, so that higher control precision is obtained, and a better harmonic control level is realized.

Description

Technical Field

[0001] The present disclosure relates to the technical field of rail transit traction converter control, and in particular to a synchronous sampling method and device. Background Art

[0002] Real-time control is required in the traction control system of high-power locomotives or EMUs, and real-time control requires sampling of external electrical analog quantities. There are two commonly used sampling methods at present. One is asynchronous sampling. The main control of the current conventional controller is a DSP (digital signal processor) chip. This chip is easy to perform fixed-cycle operations. The method is to execute a timer internally, which will trigger an interrupt at a fixed time. Sampling is performed at the interrupt time and the algorithm is iterated. This sampling method is called asynchronous sampling because the sampling period is generated by the DSP itself and is not consistent with the frequency of the input signal (such as the grid voltage); the second method is synchronous sampling. After conditioning the input signal, it is converted into a square wave signal, and then the sampling period is estimated by frequency division. The processing method of the prior art has poor accuracy and dynamic response capability, and there is signal delay, which affects the control effect. Summary of the invention

[0003] In view of this, the embodiments of the present disclosure provide a synchronous sampling method and device to solve the problems in the prior art that the processing method of the prior art has poor accuracy and dynamic response capability, there is signal delay, and the control effect is affected.

[0004] A first aspect of an embodiment of the present disclosure provides a synchronous sampling method, comprising:

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

[0006] Calculate the real-time estimated angular frequency according to the real-time sampling data and a preset first calculation formula;

[0007] Calculating the next real-time sampling period based on the real-time estimated angular frequency and a preset second calculation formula;

[0008] The next real-time sampling period is determined as the real-time sampling period, and 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 is returned 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, and the initial value of the storage container is empty, wherein the step of performing the real-time sliding sampling once 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 a first threshold.

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

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

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

[0014] In some embodiments, calculating the real-time estimated angular frequency according to the real-time sampling data and a preset first calculation formula includes:

[0015] Performing discrete Fourier transform on the real-time sampling data to calculate the real-time component and the real-time imaginary component;

[0016] Calculate an error signal according to 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;

[0017] Comparing the error signal with a corresponding real-time signal to obtain an angular frequency error;

[0018] Adding the angular frequency error to the rated angular frequency of the real-time signal to obtain a real-time estimated angular frequency;

[0019] Performing an integration operation on the real-time estimated angular frequency to obtain a real-time estimated phase angle;

[0020] The real-time estimated phase angle is saved and updated.

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

[0022]

[0023] Among them, the u e represents the error signal, u re represents the real-time component, u im Indicates the real-time demand quantity. Indicates real-time estimation of the phase angle.

[0024] In some embodiments, before comparing the error signal with the real-time signal corresponding thereto, the method further includes:

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

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

[0027] Calculate the next sampling time point according to 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] Wherein, the second calculation formula includes:

[0030]

[0031] Among them, T s represents the next sampling time point, represents the real-time estimation of the angular frequency, and N represents the preset number.

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

[0033] A sampling module, used for performing a real-time sliding sampling on the real-time signal based on a real-time sampling period to obtain real-time sampling data, wherein an initial value of the real-time sampling period is a first preset value;

[0034] A first calculation module, used for calculating the real-time estimated angular frequency according to the real-time sampling data and a preset first calculation formula;

[0035] A second calculation module, used for calculating the next real-time sampling period based on the real-time estimated angular frequency and a preset second calculation formula;

[0036] The repeated 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 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.

[0037] In some embodiments, the sampling points obtained by real-time sliding sampling are stored in a preset storage container, and the initial value of the storage container is empty, wherein the step of performing the real-time sliding sampling once 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 a first threshold.

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

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

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

[0042] In some embodiments, calculating the real-time estimated angular frequency according to the real-time sampling data and a preset first calculation formula includes:

[0043] Performing discrete Fourier transform on the real-time sampling data to calculate the real-time component and the real-time imaginary component;

[0044] Calculate an error signal according to 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;

[0045] Comparing the error signal with a corresponding real-time signal to obtain an angular frequency error;

[0046] Adding the angular frequency error to the rated angular frequency of the real-time signal to obtain a real-time estimated angular frequency;

[0047] Performing an integration operation on the real-time estimated angular frequency to obtain a real-time estimated phase angle;

[0048] The real-time estimated phase angle is saved and updated.

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

[0050]

[0051] Among them, the u e represents the error signal, u re represents the real-time component, u im Indicates the real-time demand quantity. Indicates real-time estimation of the phase angle.

[0052] In some embodiments, before comparing the error signal with the real-time signal corresponding thereto, the method further includes:

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

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

[0055] Calculate the next sampling time point according to 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] Wherein, the second calculation formula includes:

[0058]

[0059] Among them, T s represents the next sampling time point, represents real-time estimation of angular frequency, and N represents the preset number.

[0060] According to a third aspect of an embodiment of the present disclosure, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the computer program.

[0061] According to a fourth aspect of the embodiments of the present disclosure, a computer-readable storage medium is provided, which stores a computer program, and when the computer program is executed by a processor, the steps of the above method are implemented.

[0062] According to a fifth aspect of the embodiments of the present disclosure, a computer program product is provided. The computer program product includes a computer program or instructions. When the computer program or instructions are executed by a processor, the steps of the above method are implemented.

[0063] The real-time sampling data is obtained by performing a real-time sliding sampling on the real-time signal based on the real-time sampling period; the real-time estimated angular frequency is calculated according to 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 step of performing a real-time sliding sampling on the real-time signal based on the real-time sampling period to obtain the real-time sampling data is returned to cyclically update the real-time sampling period, so that the sampling period of the present invention changes in real time with the change of the power grid period, thereby improving the phase acquisition accuracy, making the sampling time more accurate, and greatly reducing the delay, thereby obtaining a higher control accuracy and achieving a better harmonic control level. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

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

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

[0067] Figure 3 is a flow chart of some other embodiments of another synchronous sampling method provided according to an embodiment of the present disclosure;

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

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

[0070] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments set forth herein. On the contrary, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0071] It should also be noted that, for ease of description, only the parts related to the present disclosure are shown in the drawings. In the absence of conflict, the embodiments and features in the embodiments of the present disclosure can be combined with each other.

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

[0073] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

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

[0075] The present disclosure will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

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

[0077] exist Figure 1 In the application scenario, first, 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 may calculate the real-time estimated angular frequency 106 according to the real-time sampling data 104 and a preset first calculation formula 105 .

[0079] Again, the computing device 101 may 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 may determine the next real-time sampling period 108 as the real-time sampling period 102 , and return to execute 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 102 .

[0081] It should be noted that the computing device 101 can be 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 embodied as software, it can be installed in the hardware devices listed above. It can be implemented as multiple software or software modules for providing distributed services, or as a single software or software module. No specific limitation is made here.

[0082] It should be understood that Figure 1 The number of computing devices in the embodiment is only illustrative. Any number of computing devices may be provided according to implementation requirements.

[0083] Continue to refer Figure 2 , shows a process 200 of some embodiments of the synchronous sampling method according to the present disclosure. The method can be Figure 1 The synchronous sampling method comprises the following steps:

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

[0085] In some embodiments, the execution body of the synchronous sampling method (such as Figure 1The computing device 101 shown can be connected to the target device via a wired connection or a wireless connection, and then a real-time sliding sampling is performed on the real-time signal based on a 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.

[0086] In the present disclosure, the sampling period is based on calculations and may change at each sampling to achieve higher accuracy, so the real-time sampling period may refer to the sampling period of the current time that changes over time. In addition, when running for the first time, the real-time sampling period may be set to a value that relatively meets the requirements, that is, a first preset value. The first preset value may be a sampling period set based on experience, but is not limited thereto. Real-time sliding sampling may refer to discarding some of the last sampling points and adding at least one newly added sampling point when sampling.

[0087] In some optional implementations, the sampling points obtained by real-time sliding sampling are stored in a preset storage container, and the initial value of the storage container is empty. The step of performing the real-time sliding sampling once includes: if the storage container is empty, obtaining 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, discard the first preset number of sampling points with the longest storage time, and store the first preset number of sampling points of the latest sampling, wherein the first preset number is a positive integer. Obviously, the more data added each time the real-time sliding sampling is performed, the lower the accuracy. Therefore, preferably, the first preset number is 1.

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

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

[0090] In some embodiments, the execution subject may calculate the real-time estimated angular frequency according to the real-time sampling data and the 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 component and the real-time imaginary component. The real-time component may refer to the real number part of the sampled data obtained after calculation. The real-time imaginary component may refer to the imaginary number part of the sampled data obtained after calculation.

[0092] In the second step, an error signal is calculated 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. The real-time estimated phase angle may refer to a phase angle calculated from real-time sampled data. Since the real-time sampled data is composed of a plurality of time-stamped data, a signal may be formed, and after processing the signal based on the first calculation formula, an error signal may be obtained, i.e., a signal representing the error data between the calculated signal and the actual signal. The first calculation formula may refer to a calculation formula for calculating the error signal.

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

[0094]

[0095] Among them, the u e represents the error signal at that time, u re Indicates the real-time component of the current time, u im Indicates the real-time demand quantity of the current time. Indicates the current real-time estimated phase angle (or initial phase angle).

[0096] The third step is to compare the error signal with the corresponding real-time signal to obtain an angular frequency error, wherein the angular frequency error may refer to the difference between the calculated angular frequency and the angular frequency of the actual real-time signal (or rated angular frequency).

[0097] In the fourth step, the angular frequency error is added to the rated angular frequency of the real-time signal to obtain a real-time estimated angular frequency. The grid angular frequency may refer to the calculated estimated real-time angular frequency of the grid.

[0098] In the fifth step, an integration operation is performed on the real-time estimated angular frequency to obtain a real-time estimated phase angle. The real-time estimated phase angle may refer to an estimated real-time phase angle obtained by calculation.

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

[0100] In some optional embodiments, before comparing the error signal and the corresponding real-time signal, the method further includes: low-pass filtering the error signal to reduce interference from abnormal signals, thereby increasing the accuracy of the calculation of the present disclosure.

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

[0102] In some embodiments, the execution subject can calculate the next real-time sampling period according to the following steps based on the real-time estimated angular frequency and the preset second calculation formula: the first step is to calculate the next sampling time point according to the real-time estimated phase angle, the real-time estimated angular frequency, and the preset second calculation formula; the second step is to calculate the real-time sampling period according to the next sampling time point and the most recent sampling time point. The second calculation formula may refer to a formula for calculating 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 optional implementations, the second calculation formula includes:

[0104]

[0105] Among them, T s represents the next sampling time point, represents real-time estimation of angular frequency, and N represents the preset number.

[0106] Step 204, 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 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.

[0107] In some embodiments, the execution subject may determine the next real-time sampling period as the real-time sampling period, and return to perform a real-time sliding sampling of the real-time signal based on the real-time sampling period to obtain the step of real-time sampling 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 operation environment of the power grid, it is necessary to cyclically execute steps 201-203 to continuously update the real-time sampling period to improve the control accuracy.

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

[0109] Continue to refer Figure 3 , shows a process 300 of another embodiment of the synchronous sampling method according to the present disclosure, which can be Figure 1 The synchronous sampling method includes:

[0110] Step 301, based on the real-time sampling period, a real-time sliding sampling is performed on the real-time signal to obtain real-time sampling data, wherein the initial value of the real-time sampling period is a first preset value, wherein the sampling points obtained by the real-time sliding sampling are stored in a preset storage container, the initial value of the storage container is empty, and the step of performing the real-time sliding sampling once includes: if the storage container is empty, a sampling point carrying a time tag is obtained 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, the first preset number of sampling points with the longest storage time are discarded, and the first preset number of sampling points of the latest sampling are stored, wherein the first preset number is a positive integer. Preferably, the first preset number is 1.

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

[0112] Step 303, calculating an error signal according to 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.

[0113] Step 304: perform comparison processing based on the error signal and the corresponding real-time signal to obtain an angular frequency error.

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

[0115] Step 306, performing an integration operation on the real-time estimated angular frequency to obtain a real-time estimated phase angle.

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

[0117] Step 308, calculating the next sampling time point according to the real-time estimated phase angle, the real-time estimated angular frequency, and a preset second calculation formula.

[0118] Step 309, calculating the real-time sampling period according to the next sampling time point and the most recent sampling time point.

[0119] Step 310, 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 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.

[0120] In some embodiments, the specific implementation of steps 301-310 and the technical effects brought about can be referred to Figure 2 The steps in the corresponding embodiments will not be repeated here.

[0121] All the above optional technical solutions can be arbitrarily combined to form optional embodiments of the present application, which will not be described one by one here.

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

[0123] Further references Figure 4 As an implementation of the above methods in the above figures, the present disclosure provides some embodiments of synchronous sampling devices, which are similar to Figure 2 The above method embodiments correspond.

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

[0125] The sampling module 401 is used to perform a real-time sliding sampling on the real-time signal based on a 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 according to the real-time sampling data and a 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 a preset second calculation formula.

[0128] The module 404 is repeatedly executed, and 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 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 some embodiments, the sampling points obtained by the real-time sliding sampling are stored in a preset storage container, and the initial value of the storage container is empty, wherein the step of performing the real-time sliding sampling once 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 a first threshold.

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

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

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

[0134] In some optional implementations of some embodiments, calculating the real-time estimated angular frequency according to the real-time sampling data and a preset first calculation formula includes:

[0135] Performing discrete Fourier transform on the real-time sampling data to calculate the real-time component and the real-time imaginary component;

[0136] Calculate an error signal according to 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;

[0137] Comparing the error signal with a corresponding real-time signal to obtain an angular frequency error;

[0138] Adding the angular frequency error to the rated angular frequency of the real-time signal to obtain a real-time estimated angular frequency;

[0139] Performing an integration operation on the real-time estimated angular frequency to obtain a real-time estimated phase angle;

[0140] The real-time estimated phase angle is saved and updated.

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

[0142]

[0143] Among them, the u e represents the error signal, u re represents the real-time component, u im Indicates the real-time demand quantity. Indicates real-time estimation of the phase angle.

[0144] In some optional implementations of some embodiments, before comparing the error signal and the real-time signal corresponding thereto, the method further includes:

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

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

[0147] Calculate the next sampling time point according to 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] Wherein, the second calculation formula includes:

[0150]

[0151] Among them, T s represents the next sampling time point, represents real-time estimation of angular frequency, and N represents the preset number.

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

[0153] like Figure 5 As shown, the electronic device 500 may include a processing device (e.g., a central processing unit, a graphics processing unit, 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. In the RAM 503, various programs and data required for the operation of the electronic device 500 are also stored. The processing device 501, the ROM 502, and the RAM 503 are connected to each other via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0154] Typically, the following devices may be connected to the I / O interface 505: an input device 506 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 507 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 508 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 509. The communication device 509 may allow the electronic device 500 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 5The electronic device 500 is shown with various devices, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead. Figure 5 Each block shown in the figure may represent one device, or may represent multiple devices as required.

[0155] In particular, according to some embodiments of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, some embodiments of the present disclosure include a computer program product, which includes a computer program or instruction carried on a computer-readable medium, and the computer program or instruction contains a program code for executing the method shown in the flowchart. In some such embodiments, the computer program can be downloaded and installed from the network through the communication device 509, or installed from the storage device 508, or installed from the ROM 502. When the computer program is executed by the processing device 501, the above-mentioned functions defined in the method of some embodiments of the present disclosure are executed.

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

[0157] In some embodiments, the client and the server may communicate using any currently known or future developed network protocol such as HTTP (HyperText Transfer Protocol), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or future developed network.

[0158] The computer-readable medium may be included in the device; or it may exist independently without being assembled into the electronic device. The computer-readable medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device: performs 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; calculates the real-time estimated angular frequency based on the real-time sampling data and the preset first calculation formula; calculates the next real-time sampling period based on the real-time estimated angular frequency and the preset second calculation formula; determines the next real-time sampling period as the real-time sampling period, and returns to perform 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.

[0159] Computer program code for performing the operations of some embodiments of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate 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 a remote computer, the remote computer may 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 may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0160] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0161] The modules described in some embodiments of the present disclosure may be implemented in software or hardware. The modules described may also be set in a processor, for example, may be described as:

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

[0163] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0164] The above descriptions are only some preferred embodiments of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the embodiments of the present disclosure is not limited to the technical solutions formed by a specific combination of the above-mentioned technical features, but should also cover other technical solutions formed by any combination of the above-mentioned technical features or their equivalent features without departing from the above-mentioned inventive concept. For example, the above-mentioned features are replaced with the technical features with similar functions disclosed in the embodiments of the present disclosure (but not limited to) and the technical solutions formed.

Claims

1. A synchronous sampling method, characterized in that: include: Performing a real-time sliding sampling on the real-time signal based on a real-time sampling period to obtain real-time sampling data, wherein an initial value of the real-time sampling period is a first preset value; Calculate the real-time estimated angular frequency according to the real-time sampling 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; The next real-time sampling period is determined as the real-time sampling period, and 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 is returned 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, and the initial value of the storage container is empty. The steps of performing the real-time sliding sampling once 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 a first threshold.

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

4. The method according to claim 1, characterized in that: Calculating the real-time estimated angular frequency according to the real-time sampling data and a preset first calculation formula includes: Performing discrete Fourier transform on the real-time sampling data to calculate the real-time component and the real-time imaginary component; Calculate an error signal according to 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; Comparing the error signal with a corresponding real-time signal to obtain an angular frequency error; Adding the angular frequency error to the rated angular frequency of the real-time signal to obtain a real-time estimated angular frequency; Performing an integration operation on the real-time estimated angular frequency to obtain a real-time estimated phase angle; The real-time estimated phase angle is saved and updated.

5. The method according to claim 4, characterized in that The first calculation formula includes: Among them, the u e represents the error signal, u re represents the real-time component, u im Indicates the real-time demand quantity. Indicates real-time estimation of the phase angle.

6. The method according to claim 4, characterized in that Before comparing the error signal with the real-time signal corresponding thereto, the method further includes: The error signal is low pass filtered.

7. The method according to claim 1, characterized in that The step of calculating the next real-time sampling period based on the real-time estimated angular frequency and a preset second calculation formula includes: Calculate the next sampling time point according to the real-time estimated phase angle, the real-time estimated angular frequency, and the preset second calculation formula; Calculate the real-time sampling period based on the next sampling time point and the most recent sampling time point; Wherein, the second calculation formula includes: Among them, T s represents the next sampling time point, represents real-time estimation of angular frequency, and N represents the preset number.

8. A synchronous sampling device, characterized in that: include: A sampling module, used for performing a real-time sliding sampling on the real-time signal based on a real-time sampling period to obtain real-time sampling data, wherein an initial value of the real-time sampling period is a first preset value; A first calculation module, used for calculating the real-time estimated angular frequency according to the real-time sampling data and a preset first calculation formula; A second calculation module, used for calculating the next real-time sampling period based on the real-time estimated angular frequency and a preset second calculation formula; The repeated 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 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.

9. 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, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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