A distributed wave recording synchronization method, device and apparatus, and a medium

[0062] Example one

[0063] See figure 1 , A schematic flowchart of the distributed wave recording synchronization method provided by the first embodiment of the present invention;

[0064] S11. Obtain the reference recording curve and the to-be-synchronized recording curve;

[0065] It should be noted that the distributed recorder contains multiple recorder files from multiple control and protection equipment. Each control and protection device has a corresponding recorder file. Each recorder curve in each recorder file has the same Start and end time, sampling rate, that is to say, the internal recordings of each file are synchronized, but the internal recording curves of different recording files do not necessarily have the same start and end time, sampling rate, if you want to perform multiple different For the synchronization of the recording files, only one of the recording files is used as the reference recording file, and a certain recording curve a in the reference recording file is used as the reference recording curve, which is selected from the other recording files to be synchronized A recording curve b 1 , B 2 , B 3 ,..., b n Synchronize with the recording curve a respectively to realize the synchronization of all the recording files.

[0066] S12. Obtain a defined domain according to the reference recording curve and the to-be-synchronized recording curve;

[0067] Preferably, the acquiring the domain of definition based on the reference recording curve and the to-be-synchronized recording curve includes:

[0068] Obtain the condition that the reference recording curve and the to-be-synchronized recording curve have an intersection; wherein, the condition of the intersection is Where t b0 Is the left end point of the to-be-synchronized recording curve b, t bm Is the right end of the to-be-synchronized recording curve b, t aN Is the right end of the reference recording curve a, t a0 Is the left end point of the reference recording curve a, and τ is the optimal matching time;

[0069] The defined domain is obtained according to the conditions of intersection; wherein, the defined domain includes an optimal matching time domain and an effective domain; wherein, the optimal matching time domain is:

[0070] τ∈(t a0 -t bM ,t aN -t b0 )=(τ min ,τ max )=T τ

[0071] The valid domain is: t∈min(T a ,T b )=(t min ,t max )=T m; Where T a Is the domain of the reference recording curve a, T b Is the domain of the reference recording curve b.

[0072] Specifically, in this embodiment, the two recording curves that need to be synchronized are represented by a and b, respectively, a is the reference recording curve, and b is the recording curve to be synchronized, which is generally defined The domains are not inconsistent, let their definition domains be T a And T b :A=a(t),t∈T a , B=b(t),t∈T b; Construct b'(t), representing the recording curve formed by offsetting τ on the time axis of b(t): b'(t)=b(t+τ), t∈T b; The matching function is meaningful only when the domains of curve a and curve b have an intersection, so the matching function is defined as m(τ)=m(a,b'),τ∈T τ; 4 typical cases where the domains of curve a and curve b have intersections are as follows, and figure 2 As shown, (1) the right end point of curve b coincides with the left end point of curve a; (2) the right end point of curve b coincides with the right end point of curve a; (3) the left end point of curve b coincides with the left end point of curve a ; (4) The left end point of curve b coincides with the right end point of curve a; it can be seen that the condition for the intersection of curve a and curve b is

[0073] According to the intersecting conditions, we get:

[0074] τ∈(t a0 -t bM ,t aN -t b0 )=(τ min ,τ max )=T τ

[0075] So the valid domain of the corresponding curves a and b is:

[0076] t∈min(T a ,T b )=(t min ,t max )=T m.

[0077] S13. Obtain a continuous matching function according to the defined domain and the least square method;

[0078] It should be noted that in the prior art, the least squares method is commonly used to determine the matching degree of two recording curves: Satisfy τ∈T f The τ corresponding to the minimum value of m in the range is the optimal matching time. The least square method refers to integrating the square of the difference between the two curves. The larger the final integral, the more inconsistent the two curves. Obviously, when the two curves coincide, the integral is zero. The greater the difference and the greater the coincidence time, the greater the integral. In most cases, the least-squares method can meet the requirement that the τ corresponding to the minimum value of m is the optimal matching time. However, in practical applications, the inventor found that sometimes there may be a situation where the waveforms of the beginning and the end of the recording curve are basically the same. For example, the bus voltage and the line current in the case of a line fault restart are all normal operation waveforms before and after the fault. There will be obvious changes. At this time, if only the least squares method is used, the judgment will be wrong, and the wrong conclusion that the optimal matching time is before and after the fault is obtained, that is, there is a judgment error.

[0079] Preferably, see image 3 , The obtaining the continuous matching function according to the domain and the least square method includes:

[0080] S21: Form a time reverse weight according to the overlapping time length of the reference recording curve and the to-be-synchronized recording curve;

[0081] S22. Obtain the least squares method with inverse time weight according to the time inverse weight and the least square method;

[0082] S23. Obtain a continuous matching function according to the domain and the least squares method with inverse time weight Where τ is the optimal matching time, a(t) is the reference recording curve, b(t) is the to-be-synchronized recording curve, t max Is the maximum value of the valid domain of the reference recording curve and the to-be-synchronized recording curve, t min The minimum value of the effective domain of the reference recording curve and the to-be-synchronized recording curve; τ∈T τ ,T∈T m.

[0083] In this embodiment, the greater the difference of the least square method and the greater the coincidence time, the greater the integral. The length of the coincidence time is variable, which may cause the least squares integration to be mainly affected by the length of the coincidence time and not affected by the difference. For example, see Figure 4 , The least squares method may judge that when the upper curve head and the lower curve tail intersect a small part, the integral is the smallest, so that the difference is the smallest. This is unreasonable, so it is necessary to construct a quantity related to the coincidence time length, that is, divide by t max -t min , The formation of time reverse weights can ensure that the weights during comparison are mainly within a reasonable range of the long overlap time. To construct a dead zone, it is roughly considered that t∈T m =(t min ,t max ) Are all reasonable. Actually, this interval can be reduced to eliminate the obvious small-scale connection between the end and end. In fact, the recordings are basically triggered within the range of 10% to 30%, that is to say, the last aligned point should be within the range of 10-30% of each recording. If the recordings meet this requirement, then you can It is reasonable to stipulate that each curve is aligned within the range of 5% to 35%, and the value beyond the range is unreasonable.

[0084] It should be noted that the number of times to change the time reverse weight, (t max -t min ) h , H is a real number greater than 0, which can be optimized and set according to different occasions, which is not specifically limited in the present invention.

[0085] S14. Obtain the optimal matching time of the continuous matching function according to the simulated annealing algorithm based on global pre-traversal;

[0086] In this embodiment, the traversal method is first used to obtain a full range of traversal curves, and within the range of the smaller value of the traversal curve, a simulated annealing algorithm with a faster temperature T decay is performed, thereby improving the simulated annealing algorithm. Under the premise of ensuring accuracy, the amount of calculation is reduced and the search for the optimal value is accelerated.

[0087] S15. Discretize the continuous matching function according to a discrete integral formula to obtain a discrete matching function;

[0088] It should be noted that the actual recording curves are all discrete functions, so the curves of the continuous discrete functions that need to be obtained are discretized. There are many discrete integral formulas, such as rectangular method, trapezoidal method, Simpson integral method, etc., with similar principles and accuracy. However, the present invention does not specifically limit this.

[0089] Preferably, the discretizing the continuous matching function according to a discrete integral formula, and obtaining the discrete matching function includes:

[0090] Discretize the continuous matching function according to the discrete integral formula to obtain the discrete matching function Where g(t i )=a(t i )-b(t i +τ), τ∈T τ ,t∈T m.

[0091] Preferably, the discrete integral formula is a trapezoidal integral formula;

[0092] The trapezoidal integral formula is Where f(t i ) Is the trapezoid upper base; f(t i+1 ) Is the bottom of the trapezoid; (t i+1 -t i ) Is the trapezoidal height.

[0093] S16. Synchronize the reference recording curve and the to-be-synchronized recording curve according to the optimal matching time and the discrete matching function.

[0094] Specifically, the pole bus current IDLH of S1P1PPR obtained in the Northwest Yunnan Engineering Experiment is used as the reference recording curve a, and the pole bus current IDLH of S1P1CCP1 is used as the to-be-synchronized recording curve b, wherein the to-be-synchronized recording curve b is more The reference recording curve a lags 1s, see Figure 5 with Image 6 , The matching function m(τ) presents a form of low in the middle and high on both sides. When τ=-1s, m is the smallest. At this time, τ is the optimal matching point, see Figure 7 with Figure 8 , The curves differ by 1s before synchronization, and the curves almost completely coincide after synchronization.

[0095] The implementation of this embodiment has the following beneficial effects: acquiring the reference recording curve and the to-be-synchronized recording curve; acquiring the definition domain according to the reference recording curve and the to-be-synchronizing recording curve; acquiring according to the definition domain and the least square method Continuous matching function; the optimal matching time of the continuous matching function is obtained according to the simulated annealing algorithm based on global pre-traversal. Under the premise of ensuring accuracy, the amount of calculation is reduced, and the speed of searching for the optimal value is accelerated, which can be realized quickly The optimal matching time is obtained, the continuous matching function is discretized according to the discrete integral formula to obtain the discrete matching function; the reference recording curve and the to-be-synchronized are realized according to the optimal matching time and the discrete matching function Recording curve synchronization. With the least amount of calculation and space occupation, the calculation of the discrete matching function is realized, and the synchronization of different time length and sampling frequency curves is finally realized.

[0096] The second embodiment, on the basis of the first embodiment, see Picture 9 It is a schematic flow diagram of another distributed wave recording synchronization method provided by the second embodiment of the present invention;

[0097] Preferably, the obtaining the optimal matching time of the continuous matching function according to the simulated annealing algorithm based on global pre-traversal includes:

[0098] S31. Obtain a full-range low-density traversal curve of the continuous matching function according to the traversal method of small equal division n;

[0099] S32: When the continuous matching function value is small, obtain the corresponding range of the low-density traversal curve;

[0100] S33. Within the range, obtain the optimal matching time of the continuous matching function according to a simulated annealing algorithm with a faster attenuation of the temperature T.

[0101] It should be noted that in the matching function domain range T τ The τ corresponding to the minimum value of m in the range is the optimal matching time. The commonly used algorithm for searching the optimal value is as follows:

[0102] (1) Traversal method

[0103] The domain of the matching function is the domain of the optimal matching time T τ It is equally divided into n cells, and the endpoints of all sections are: τ i =(i-1)(τ max -τ min )/n, i=1, 2, 3...n. Let τ = τ in turn i , I=1,2,3,...,n+1, and find the corresponding matching function m(τ) to get the optimal matching time τ. The advantage of the traversal method is that it can traverse the entire effective range. The fitting accuracy depends on the size of the equal division n. The larger the n, the finer the division and the more accurate the matching. However, the disadvantage is that as the accuracy increases, the amount of calculation will increase significantly. Big.

[0104] (2) Mountain climbing method

[0105] Set the initial value τ of τ 0 And the initial direction s=1, each time τ is increased by an increment sΔτ, where s represents the direction, and there are only two values ​​of 1 and -1, 1 represents the direction in which τ increases, and -1 represents the direction in which τ decreases. Δτ represents the increment interval and is a positive number. sΔτ represents the increment of τ. Calculate the corresponding m(τ 0 +sΔτ), if m(τ 0 +sΔτ) increment Δm <0, keep s unchanged and continue to increase sΔτ; if m(τ 0 +sΔτ) increment Δm> 0, then multiply s by (-1) and continue to increase sΔτ, and repeat, that is, one is that s is unchanged, and the other is s is multiplied (-1). Such repetition refers to the judgment process of these two cases. repeatedly. Finally make m(τ 0 +sΔτ) reaching the minimum means that all the quantities involved are considered to have found the minimum after several rounds of cycles, and the algorithm ends. The advantage of mountain climbing method makes it possible to find its extreme value for any recorded curve, but its disadvantage is that it is easy to fall into the trap of local optimum and it is impossible to find the global optimum value.

[0106] In the embodiment of the present invention, in order to improve the climbing method and avoid falling into the local optimal trap, a simulated annealing algorithm may be used. The simulated annealing algorithm has the ability to jump out of the local optimal trap, that is, adding a random amount to each step increment of the mountaineering method, and the mountaineering has the probability to proceed in the "wrong direction" according to the random amount, even if it falls into the local optimal trap, after a period of time After time, the algorithm can jump out of the trap again and will eventually converge towards the global optimal value. The simulated annealing algorithm is described in detail as follows:

[0107] Set the initial value τ of τ 0 And initial direction s=1, temperature T∈[T min ,T max ] Is the initial temperature T 0. Each time τ is increased by the increment sΔτ, the corresponding m(τ 0 +sΔτ), if m(τ 0 +sΔτ) increment Δm <0, keep s unchanged and continue to increase sΔτ; if m(τ 0 +sΔτ) increment Δm> 0, keep s unchanged according to probability P and continue to increase sΔτ, otherwise, multiply s by (-1) and continue to increase sΔτ, and so on, finally make m(τ 0 +sΔτ) reaches the minimum. The expression of probability P is as follows: Among them, Δm is the increment of the matching function; T max Is the highest temperature; T i Is the current temperature, which decreases as i increases; i is the current number of calculation steps; the simulated annealing algorithm accepts a solution that is worse than the current solution with a certain probability, so it may jump out of this local optimal solution. Reach the global optimal solution. After the simulated annealing algorithm has searched for the local optimal solution, it will accept the movement of m to a larger value with a certain probability. Maybe after several such moves that are not local optimal, it will reach the global optimal point, so it jumps out Local optimal value. In the formula Ti becomes smaller with i, the specific formula is T(i+1)=r*Ti, where r is a fixed real number and 0 <1, the larger the r, the slower the search, but the easier it is to find the optimal value.

[0108] It should be noted that the calculation amount of the simulated annealing algorithm is related to the accuracy. When the T decay of the simulated annealing algorithm is faster, the speed is faster but the accuracy is lower. Conversely, when the T decays slowly, the accuracy is higher but the speed is slower. .

[0109] In this embodiment, first use the traversal method with a smaller equal division n to obtain a full range of low-density traversal curves. Within the range of the low-density traversal curve m with a smaller value, perform the simulated annealing algorithm with faster T decay , Thereby improving the simulated annealing algorithm, reducing the amount of calculation under the premise of ensuring accuracy, and speeding up the search for the optimal value.

[0110] The implementation of this embodiment has the following beneficial effects: under the premise of ensuring accuracy, the amount of calculation is reduced, the speed of searching for the optimal value is accelerated, the optimal matching time can be found more quickly, and the local optimal trap can be avoided. Unable to find the global optimal value.

[0111] The third embodiment, on the basis of the first embodiment, see Picture 10 It is a schematic flow diagram of another distributed wave recording synchronization method provided by the third embodiment of the present invention;

[0112] The achieving synchronization of the reference recording curve and the to-be-synchronized recording curve according to the optimal matching time and the discrete matching function includes:

[0113] S41. Obtain the original sampling points of the reference recording curve and the to-be-synchronized recording curve;

[0114] S42. Calculate the discrete matching function respectively according to the original sampling points, and obtain a discrete matching function after the calculation;

[0115] S43. Synchronize the reference recording curve and the to-be-synchronized recording curve according to the optimal matching time and the calculated discrete matching function.

[0116] It should be noted that for the two curves to be synchronized, the recording time and sampling frequency are generally inconsistent, and there is no one-to-one correspondence between the sampling points, so direct calculation is impossible. The commonly used method in the past is the constant frequency Lagrangian interpolation algorithm, that is, the two curves are resampled with a constant sampling rate to obtain a new curve, and then the calculation is performed. However, there is a problem with this algorithm. In order to ensure that the sampling can cover all the points of the two curves, the sampling period will be less than or equal to the minimum time interval between the discrete points of the two recording curves. The sampling frequency is generally high, which is very important for storage space and computing speed. Both have a greater impact; and if a lower sampling frequency is used, all the original recording points cannot be covered, resulting in distortion of the sampling waveform.

[0117] In this embodiment, in order to reduce the sampling frequency while preserving all the original data points to reduce the complexity of subsequent calculations, this paper proposes an unfixed frequency sampling curve fusion algorithm, which covers only the original sampling points of the two recording curves in the sampling The position that appears, for the convenience of description, the following basis Picture 11 Detailed description:

[0118] Picture 11 The first and second curves in the curve respectively represent the distribution of the recording curves a and b on the time axis. The expression of curve a is as follows:

[0119]

[0120] The expression of curve b is as follows:

[0121]

[0122] Among them, the time length and sampling rate of the recording curves a and b are inconsistent, so the calculation cannot be directly performed. Therefore, this article will convert the recording curves a and b into the recording curves a` and b` with the same domain of definition. Picture 11 The 3rd and 4th curves in the middle represent the recording curves a` and b` respectively. Picture 11 The fifth curve in shows the distribution of the recorded wave y on the time axis after a` and b` operations:

[0123]

[0124] In order to calculate the domain of the recording curves a` and b` and y, first take the time period when the recording curves a and b overlap as the effective time period of y, namely In the effective time period, the domains of the recording curves a`, b` and y are the union of the domains of a and b:

[0125] In domain T y Within, a'(t), b'(t) can be expressed as: with Where f Inter (a,t) represents the interpolation of a at time t, f Inter (b,t) represents the interpolation of b at time t. The interpolation can use Lagrangian linear interpolation, cubic spline interpolation and other interpolation algorithms. For simplicity of description, Lagrangian linear interpolation is used. Taking curve a as an example, let the interval of t be t∈[t ai ,t a(i+1) ],then: In domain T y , The y curve can be expressed as

[0126] The implementation of this embodiment has the following beneficial effects: with the least amount of calculation and space occupation, the synchronization of curves of different time lengths and sampling frequencies is realized, and the calculation of the discrete matching function is finally realized.

[0127] See Picture 12 , Picture 12 It is a distributed wave recording synchronization device provided by the fourth embodiment of the present invention, including:

[0128] The curve acquisition module 11 is used to acquire the reference recording curve and the to-be-synchronized recording curve;

[0129] The definition domain acquisition module 12 is configured to acquire the definition domain according to the reference recording curve and the to-be-synchronized recording curve;

[0130] The continuous matching function obtaining module 13 is configured to obtain the continuous matching function according to the domain and the least square method;

[0131] The optimal matching time obtaining module 14 is configured to obtain the optimal matching time of the continuous matching function according to a simulated annealing algorithm based on global pre-traversal;

[0132] The discrete matching function obtaining module 15 is configured to discretize the continuous matching function according to a discrete integral formula to obtain a discrete matching function;

[0133] The synchronization module 16 is configured to realize synchronization of the reference recording curve and the to-be-synchronized recording curve according to the optimal matching time and the discrete matching function.

[0134] Preferably, the domain acquiring module 12 includes: acquiring a condition that the reference recording curve and the to-be-synchronized recording curve have an intersection; wherein the condition of the intersection is Where t b0 Is the left end point of the to-be-synchronized recording curve b, t bm Is the right end of the to-be-synchronized recording curve b, t aN Is the right end of the reference recording curve a, t a0 Is the left end point of the reference recording curve a, and τ is the optimal matching time;

[0135] The defined domain is obtained according to the conditions of intersection; wherein, the defined domain includes an optimal matching time domain and an effective domain; wherein, the optimal matching time domain is:

[0136] τ∈(t a0 -t bM ,t aN -t b0 )=(τ min ,τ max )=T τ

[0137] The valid domain is: t∈min(T a ,T b )=(t min ,t max )=T m; Where T a Is the domain of the reference recording curve a, T b Is the domain of the reference recording curve b.

[0138] Preferably, the continuous matching function acquisition module 13 includes:

[0139] A reverse weight acquisition unit, configured to form a time reverse weight according to the overlapping time length of the reference recording curve and the to-be-synchronized recording curve;

[0140] The square method obtaining unit is configured to obtain the least square method with inverse time weight according to the time reverse weight and the least square method;

[0141] The continuous matching function obtaining unit is used to obtain the continuous matching function according to the domain and the least square method with inverse time weight Where τ is the optimal matching time, a(t) is the reference recording curve, b(t) is the to-be-synchronized recording curve, t max Is the maximum value of the valid domain of the reference recording curve and the to-be-synchronized recording curve, t min The minimum value of the effective domain of the reference recording curve and the to-be-synchronized recording curve; τ∈T τ ,T∈T m.

[0142] Preferably, the optimal matching time obtaining module 14 includes:

[0143] A curve obtaining unit, configured to obtain a full-range low-density traversal curve of the continuous matching function according to a traversal method of small equal division n;

[0144] A range obtaining unit, configured to obtain the corresponding range of the low-density traversal curve when the continuous matching function value is small;

[0145] The time obtaining unit is configured to obtain the optimal matching time of the continuous matching function according to a simulated annealing algorithm with a faster temperature decay within the range.

[0146] Preferably, the discrete matching function acquisition module 15 includes:

[0147] A discrete matching function obtaining unit, configured to discretize the continuous matching function according to a discrete integral formula to obtain the discrete matching function Where g(t i )=a(t i )-b(t i +τ), τ∈T τ ,t∈T m.

[0148] Preferably, the discrete matching function acquisition unit includes:

[0149] The discrete integral formula is a trapezoidal integral formula;

[0150] The trapezoidal integral formula is Where f(t i ) Is the trapezoid upper base; f(t i+1 ) Is the bottom of the trapezoid; (t i+1 -t i ) Is the trapezoidal height.

[0151] Preferably, the synchronization module 16 includes:

[0152] An original sampling point acquiring unit, configured to acquire the original sampling points of the reference recording curve and the to-be-synchronized recording curve;

[0153] An arithmetic function obtaining unit, configured to calculate the discrete matching function according to the original sampling point, and obtain the discrete matching function after the operation;

[0154] The synchronization unit is configured to synchronize the reference recording curve and the to-be-synchronized recording curve according to the optimal matching time and the calculated discrete matching function.

[0155] The implementation of this embodiment has the following beneficial effects:

[0156] Obtain the reference recording curve and the to-be-synchronized recording curve; obtain the definition domain according to the reference recording curve and the to-be-synchronized recording curve; obtain the continuous matching function according to the definition domain and the least square method; according to the global pre-traversal The simulated annealing algorithm obtains the optimal matching time of the continuous matching function. Under the premise of ensuring accuracy, the amount of calculation is reduced, the speed of searching for the optimal value is accelerated, and the optimal matching time can be obtained quickly. According to the discrete integral The formula discretizes the continuous matching function to obtain a discrete matching function; realizes synchronization of the reference recording curve and the to-be-synchronized recording curve according to the optimal matching time and the discrete matching function. With the least amount of calculation and space occupation, the calculation of the discrete matching function is realized, and the synchronization of different time length and sampling frequency curves is finally realized.

[0157] See Figure 13 , Figure 13 It is a schematic diagram of the distributed recorder synchronization device provided by the fifth embodiment of the present invention, which is used to execute the distributed recorder synchronization method provided by the embodiment of the present invention, such as Figure 13 As shown, the terminal device for distributed wave recording synchronization includes: at least one processor 11, such as a CPU, at least one network interface 14 or other user interfaces 13, memory 15, at least one communication bus 12, and the communication bus 12 is used to implement these Connection communication between components. Among them, the user interface 13 may optionally include a USB interface, other standard interfaces, and wired interfaces. The network interface 14 may optionally include a Wi-Fi interface and other wireless interfaces. The memory 15 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory. The memory 15 may optionally include at least one storage device located far away from the aforementioned processor 11.

[0158] In some embodiments, the memory 15 stores the following elements, executable modules or data structures, or their subsets, or their extended sets:

[0159] The operating system 151 contains various system programs for implementing various basic services and processing hardware-based tasks;

[0160] Procedure 152.

[0161] Specifically, the processor 11 is configured to call the program 152 stored in the memory 15 to execute the distributed wave recording synchronization method described in the foregoing embodiment.

[0162] The so-called processor can be a central processing unit (Central Processing Unit, CPU), other general-purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), ready-made Field-Programmable Gate Array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The processor is the control center of the distributed recording synchronization method, and various interfaces and lines are used to connect the entire distribution The various parts of the recording synchronization method.

[0163] The memory may be used to store the computer program and/or module, and the processor can realize distributed recording by running or executing the computer program and/or module stored in the memory and calling the data stored in the memory. Various functions of wave-synchronized electronic devices. The memory may mainly include a storage program area and a storage data area. The storage program area may store an operating system, an application program required by at least one function (such as a sound playback function, a text conversion function, etc.), etc.; the storage data area may store Data (such as audio data, text message data, etc.) created based on the use of mobile phones. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart memory card (Smart Media Card, SMC), Secure Digital (SD) card, Flash Card, at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device.

[0164] Wherein, if the distributed wave recording synchronization integrated module is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiments and methods, and can also be completed by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the program is executed by the processor, it can implement the steps of the foregoing method embodiments. Wherein, the computer program includes computer program code, and the computer program code may be in the form of source code, object code, executable file, or some intermediate forms. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory) , Random Access Memory (RAM, Random Access Memory), electrical carrier signal, telecommunications signal, and software distribution media. It should be noted that the content contained in the computer-readable medium can be appropriately added or deleted according to the requirements of the legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to the legislation and patent practice, the computer-readable medium Does not include electrical carrier signals and telecommunication signals.