A direct current signal processing method, device, equipment and medium

Abstract

The embodiment of the application discloses a kind of processing method, device, equipment and medium of direct current signal, it is related to direct current measurement technical field.The method comprises: the number statistics of discrete signal sequence is carried out, and discrete integer counting result is obtained;Iterative calculation is carried out to the parameter in data distribution function based on discrete integer counting result, and data distribution function is determined according to the iterative result of parameter;In each data distribution function, the specific independent variable of selected data distribution function is determined as the direct current value of the direct current signal to be processed.The technical scheme is obtained by random sampling to the direct current signal to be processed, and the discrete integer counting result can truly reflect the distribution of current value, and then the direct current value is obtained according to the specific independent variable in the selected data distribution function, and the effect of obtaining direct current by only one processing mode under various interference environments is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of direct current measurement, in particular to a direct current signal processing method, device, equipment and medium. BACKGROUND

[0002] Lightning arrester resistance current measurement, equipment grounding resistance, equipment insulation characteristic measurement, etc. all involve direct current measurement. When direct current measurement is performed, diversified interference environments need to be faced. How to avoid environmental interference when measuring direct current is a technical problem that needs to be solved.

[0003] The current technical solution mainly sets an interference elimination scheme for interference environment characteristics for different interference environments. However, when dealing with rapidly changing interference signals or irregular interference signals, the detection result accuracy is poor. SUMMARY

[0004] The present application provides a direct current signal processing method, device, equipment and medium, which can accurately measure the direct current of the direct current signal in various interference environments by using a measurement method.

[0005] According to an aspect of the present application, a direct current signal processing method is provided, which comprises:

[0006] The number of the discrete signal sequence is counted to obtain a discrete integer count result. The discrete signal sequence is a signal sequence whose values are all integers, which is obtained by randomly sampling the to-be-processed direct current signal during receiving the to-be-processed direct current signal.

[0007] Based on the discrete integer count result, the parameters in the data distribution function are iteratively calculated, and the data distribution function is determined according to the iteration result of the parameters. Different data distribution functions correspond to different direct current signal influencing factors.

[0008] In each data distribution function, a specific independent variable of the selected data distribution function is determined as the direct current value of the to-be-processed direct current signal. The selected data distribution function is the data distribution function with the largest function value among the data distribution functions. The specific independent variable is the independent variable corresponding to the maximum value of the selected data distribution function.

[0009] According to another aspect of the present application, a direct current signal processing device is provided, which comprises:

[0010] The number of the discrete signal sequence is counted to obtain a discrete integer count result. The discrete signal sequence is a signal sequence whose values are all integers, which is obtained by randomly sampling the to-be-processed direct current signal during receiving the to-be-processed direct current signal.

[0011] The data distribution function determination module is configured to determine the parameters in the data distribution functions based on the discrete integer counting result, and determine the data distribution functions according to the iteration result of the parameters; different data distribution functions correspond to different direct current signal influencing factors.

[0012] The direct current value determination module is configured to determine the specific independent variable of the selected data distribution function as the direct current value of the direct current signal to be processed in each data distribution function; the selected data distribution function is the data distribution function with the largest function value among the data distribution functions; and the specific independent variable is the independent variable corresponding to the maximum value of the selected data distribution function.

[0013] According to another aspect of the present application, an electronic device is provided, which comprises:

[0014] at least one processor; and

[0015] a memory connected to the at least one processor in communication; wherein

[0016] the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the processing method of the direct current signal according to any one of the embodiments of the present application.

[0017] According to another aspect of the present application, a computer readable storage medium is provided, which stores computer instructions for enabling a processor to execute the processing method of the direct current signal according to any one of the embodiments of the present application when executed by the processor.

[0018] The technical scheme of the embodiments of the present application comprises: performing quantity statistics on a discrete signal sequence to obtain a discrete integer counting result; the discrete signal sequence is a signal sequence in which the values obtained by randomly sampling the direct current signal to be processed are all integers in the process of receiving the direct current signal to be processed; determining the parameters in the data distribution functions based on the discrete integer counting result, and determining the data distribution functions according to the iteration result of the parameters; different data distribution functions correspond to different direct current signal influencing factors; determining the specific independent variable of the selected data distribution function as the direct current value of the direct current signal to be processed in each data distribution function; the selected data distribution function is the data distribution function with the largest function value among the data distribution functions; and the specific independent variable is the independent variable corresponding to the maximum value of the selected data distribution function. The technical scheme can truly reflect the distribution of the current value by randomly sampling the direct current signal to be processed to obtain the discrete integer counting result, and then determine the direct current value by determining the specific independent variable in the selected data distribution function, thereby achieving the effect of obtaining the direct current value by only one processing method in various interference environments.

[0019] It should be understood that nothing in this section is intended to limit the scope of the embodiments of the present application nor are they intended to represent key or essential features of the embodiments of the present application. Other features of the present application will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiments description. Obviously, the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained from these drawings without creative effort.

[0021] Figure 1 is a flow chart of a direct current signal processing method according to the embodiment one of the present application;

[0022] Figure 2 is a flow chart of a direct current signal processing method according to the embodiment two of the present application;

[0023] Figure 3 is a data distribution function diagram according to the embodiment two of the present application;

[0024] Figure 4 is a structural schematic diagram of a direct current signal processing device according to the embodiment three of the present application;

[0025] Figure 5 is a structural schematic diagram of an electronic device for implementing a direct current signal processing method according to the embodiment of the present application. DETAILED DESCRIPTION

[0026] In order to make the technical personnel in the art better understand the present application scheme, the following will combine the drawings in the embodiments of the present application, and the technical solutions in the embodiments of the present application will be described clearly and completely. Obviously, the described embodiments are only some embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative effort should belong to the scope of protection of the present application.

[0027] It should be noted that the terms "first", "second", "target", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not necessarily limit to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0028] Embodiment one

[0029] Figure 1 A flowchart of a direct current signal processing method is provided for the first embodiment of the present application. The first embodiment of the present application can be applied to the case of measuring direct current. The method can be executed by a direct current signal processing device, which can be realized in the form of hardware and / or software, and can be configured in an electronic device with data processing capability. As shown in Figure 1 The method comprises:

[0030] S110, counting the discrete signal sequence to obtain a discrete integer counting result.

[0031] The discrete signal sequence is a signal sequence in which the values obtained by randomly sampling the to-be-processed direct current signal are all integers during the process of receiving the to-be-processed direct current signal. Since the discrete signal sequence is obtained by randomly sampling the to-be-processed direct current signal, the values in the discrete signal sequence are discrete. Since the to-be-processed direct current signal is all integers, the values in the discrete signal sequence are all integers.

[0032] For example, the discrete integer counting result includes integer values and counting results corresponding to the integer values, which reflect the number of integer values. For example, the integer values are 5, 8, 10, 11 and 12; the counting result corresponding to the integer value 5 is 14, the counting result corresponding to the integer value 8 is 18, the counting result corresponding to the integer value 10 is 20, the counting result corresponding to the integer value 11 is 14, and the counting result corresponding to the integer value 12 is 10. It should be noted that the above discrete integer counting result is only a specific example, and the actual data amount is usually much larger than the above example.

[0033] Optionally, in the embodiment, the determination process of the discrete signal sequence comprises: amplifying the analog signal continuously received from the direct current sensor, and performing analog-digital conversion on the amplified signal to obtain a time-series to-be-processed direct current signal; and performing random sampling on the time-series to-be-processed direct current signal based on a random pulse sequence to obtain the discrete signal sequence whose values are all integers.

[0034] Specifically, the analog signal continuously received from the direct current sensor is amplified, and the amplified signal is subjected to analog-digital conversion to obtain a time-series to-be-processed direct current signal, wherein the digital signal converted in the analog-digital conversion is an integer value; a random pulse sequence is obtained, wherein each pulse appears randomly with the passage of time, and the time-series to-be-processed direct current signal is obtained at each pulse occurrence to achieve random sampling, thereby obtaining the discrete signal sequence whose values are all integers.

[0035] In this way, the discrete signal sequence is extracted randomly from the to-be-processed direct current signal, and the extraction process is random, thereby avoiding the influence caused by the extraction mode (for example, periodic extraction).

[0036] Optionally, in the embodiment, the determination process of the random pulse sequence comprises: generating a pseudo-random number sequence; if a pseudo-random number in the pseudo-random number sequence is greater than a specified constant, the pseudo-random number is assigned a value of 1; otherwise, the pseudo-random number is assigned a value of 0; and the pseudo-random number sequence is determined as the random pulse sequence.

[0037] Specifically, a pseudo-random number sequence is generated, and then each value in the pseudo-random number sequence is compared with a specified constant; if a pseudo-random number in the pseudo-random number sequence is greater than the specified constant, the pseudo-random number is assigned a value of 1; otherwise, the pseudo-random number is assigned a value of 0, thereby obtaining the random pulse sequence, which can obtain the to-be-processed direct current signal when the value is 1.

[0038] Further, the specified constant can be preset, and if the discrete integer counting result presents a non-regular distribution (for example, not a normal distribution), the value of the specified constant can be increased to reduce the sampling frequency, that is, the time for obtaining the discrete signal sequence is lengthened, and if the current is affected by the external environment in a period of time, the influence of the external environment on the discrete signal sequence can be reduced due to the decrease in the number of samples in this period of time.

[0039] In S120, the parameter in the data distribution function is iteratively calculated based on the discrete integer counting result, and the data distribution function is determined according to the iteration result of the parameter.

[0040] Different data distribution functions correspond to different direct current signal influencing factors.

[0041] Specifically, the discrete integer counting result reflects the result of the comprehensive action of various direct current signal influencing factors, for example, including the real current, noise, etc., different data distribution functions corresponding to different direct current signal influencing factors can be determined, and then the specific data distribution function is determined based on the discrete integer counting result, so that the real current can be calculated through subsequent steps. For example, the data distribution function can be a Gaussian function.

[0042] In each data distribution function, a specific independent variable of the selected data distribution function is determined as the direct current value of the direct current signal to be processed.

[0043] The selected data distribution function is the data distribution function with the largest function value among the data distribution functions; and the specific independent variable is the independent variable corresponding to the maximum value of the selected data distribution function.

[0044] Specifically, in the data distribution function, the independent variable reflects the current size, the function value reflects the number of times the current is detected, and the real current is sampled more times, i.e., the function value corresponding to the real current in the data distribution function is larger. Therefore, in each data distribution function, the maximum value of each data distribution function is determined, and then the function corresponding to the maximum value among the maximum values is determined as the selected data distribution function, and the independent variable corresponding to the maximum value of the selected data distribution function is determined as the specific independent variable. The specific independent variable can be determined as the direct current value of the direct current signal to be processed. It should be noted that since the current value is within a certain range, the independent variable range can be limited according to the current value range.

[0045] The technical scheme of the embodiment of the present application comprises: performing quantity statistics on a discrete signal sequence to obtain a discrete integer counting result; the discrete signal sequence is a signal sequence in which the values obtained by randomly sampling the direct current signal to be processed are all integers; iteratively calculating the parameters in the data distribution function based on the discrete integer counting result, and determining the data distribution function according to the iteration result of the parameters; different data distribution functions correspond to different direct current signal influencing factors; in each data distribution function, a specific independent variable of the selected data distribution function is determined as the direct current value of the direct current signal to be processed; the selected data distribution function is the data distribution function with the largest function value among the data distribution functions; and the specific independent variable is the independent variable corresponding to the maximum value of the selected data distribution function. The technical scheme can truly reflect the distribution of the current value by randomly sampling the direct current signal to be processed, and then the direct current value is obtained by determining the specific independent variable in the selected data distribution function, thereby realizing the effect of obtaining the direct current by only one processing method in various interference environments.

[0046] Embodiment Two

[0047] Figure 2 A flowchart of a direct current signal processing method provided for Embodiment Two of the present application is based on the above-mentioned embodiments and is optimized.

[0048] As shown in Figure 2 , the method of the present embodiment specifically includes the following steps:

[0049] S210, when performing quantity statistics on the discrete signal sequence, if it is determined that the count number of integer values in the current statistical result is greater than a preset number threshold, the current statistical result is determined as a discrete integer count result.

[0050] The preset number threshold can be determined according to actual conditions, and the present embodiment does not limit this.

[0051] The method further includes: if it is determined that the discrete integer count result is a non-Gaussian distribution, increasing the preset number threshold.

[0052] The method further includes: if the initial function value corresponding to the integer value obtained through the subsequent step A2 satisfies the following condition:

[0053]

[0054] Wherein, k is an influencing factor, K is the number of influencing factors, f k (n) is the initial function value corresponding to the integer n, and ε is a small constant, for example, 10 -4 .

[0055] The integer value is determined as a discrete point, and then a part of the discrete signal sequence is obtained, so that the number of integer values in the statistical result is equal to the preset number threshold.

[0056] S220, based on the discrete integer count result, iteratively calculating the parameters in the data distribution function, and determining the data distribution function according to the iteration result of the parameters.

[0057] In the present embodiment, iteratively calculating the parameters in the data distribution function based on the discrete integer count result, and determining the data distribution function according to the iteration result of the parameters, includes: iteratively calculating the standard deviation, the center value and the selection probability in the Gaussian function based on the discrete integer count result, and determining the Gaussian function according to the iteration result of the parameters; different Gaussian functions correspond to different direct current signal influencing factors.

[0058] Specifically, in the embodiment of the present application, the data distribution functions corresponding to different influence factors are Gaussian distribution, and the Gaussian distributions corresponding to different influence factors are different. Since the standard deviation, center value and selection probability (which can be called weight) in the Gaussian distribution can determine the specific Gaussian function, the parameters are determined as the standard deviation, center value and selection probability in the present solution.

[0059] Specifically, the Gaussian function can be expressed as:

[0060] {f k (t,φ k )} k＝1,2,…,K ;

[0061] wherein, φ k =(σ k ,μ k ,w k ), σ k is the standard deviation, μ k is the center value, w k is the selection probability, t is the independent variable, and k is the influence factor.

[0062]

[0063] Since w k is the coefficient of the function, it can also be called weight.

[0064] In the embodiment of the present application, when determining the Gaussian function, the following constraint condition can be optionally met:

[0065]

[0066] wherein, n is the integer value in the discrete integer counting result, N-1 is the upper limit of the integer value, i.e., the integer value is less than or equal to N-1, and h n is the counting result of the integer value n.

[0067] In the embodiment of the present application, the standard deviation, center value and selection probability in the Gaussian function can be iteratively calculated based on the discrete integer counting result, including steps A1-A6:

[0068] Step A1, initializing the standard deviation, center value and selection probability in the target Gaussian function to obtain the initialized standard deviation, initialized center value and initialized selection probability; the target Gaussian function is the Gaussian function corresponding to the target influence factor.

[0069] Step A2, determining the initialized target Gaussian function according to the initialized standard deviation, initialized center value and initialized selection probability, and substituting the target integer value in the discrete integer counting result into the initialized target Gaussian function to obtain the target initial function value corresponding to the target integer value.

[0070] Step A3, determining the probability of the target integer value being classified as the target impact factor according to the ratio of the target function value corresponding to the target integer value and the total function value; the total function value is the sum of the initial function values corresponding to the target integer value under each impact factor.

[0071] Step A4, determining the target calculation value based on the probability of each integer value being classified as the target impact factor and the counting result of the integer value.

[0072] Step A5, determining the updated standard deviation, updated center value and updated selection probability after this iteration according to the target calculation value and the counting result of the discrete integer.

[0073] Step A6, if the updated standard deviation, updated center value and updated selection probability meet the iteration end condition, then the updated standard deviation, updated center value and updated selection probability are determined as the final standard deviation, final center value and final selection probability; otherwise, the updated standard deviation, updated center value and updated selection probability are determined as the initial standard deviation, initial center value and initial selection probability for the next iteration.

[0074] Correspondingly, the Gaussian function is determined according to the iteration result of the parameter, comprising:

[0075] The target Gaussian function is determined according to the final standard deviation, final center value and final selection probability.

[0076] Specifically, an initial initial standard deviation, initial center value and initial selection probability can be given first to obtain an initial target Gaussian function, the target integer value in the counting result of the discrete integer is substituted into the initial target Gaussian function to obtain a target initial function value corresponding to the target integer value, and after each integer value is substituted, an initial function value corresponding to each integer value is obtained. The following formula is the expression of the initial function value:

[0077] f k (n,φ k );

[0078] n is the integer value, and φ k comprising: initial standard deviation, initial center value and initial selection probability, and k is the impact factor.

[0079] Further, the total function value is determined according to the following formula:

[0080] Σ k f k (n,φ k );

[0081] The formula reflects the cumulative summation of the initial function values corresponding to the target integer value under each impact factor.

[0082] The probability of classifying the target integer value n as the target influence factor k is determined according to the following formula:

[0083]

[0084] wherein r k,n is the probability of classifying the target integer value n as the target influence factor k.

[0085] The target calculation value is determined according to the following formula:

[0086] r k =∑ n h n r k,n ;

[0087] wherein r k is the target calculation value, ∑ n is the cumulative summation, and h n is the counting result corresponding to the target integer value n.

[0088] In the embodiments of the present application, the updated standard deviation, the updated center value, and the updated selection probability after this iteration are determined according to the target calculation value and the discrete integer counting result, including:

[0089] The updated selection probability is determined according to the following formula:

[0090]

[0091] wherein p is the updated selection probability, r k is the target calculation value, and h n is the counting result corresponding to the integer value n in the discrete integer counting result.

[0092] The updated center value is determined according to the following formula:

[0093]

[0094] wherein n is the updated center value, n is the integer value n in the discrete integer counting result, and r k,n is the probability of classifying the integer value n as the influence factor k.

[0095] The updated standard deviation is determined according to the following formula:

[0096]

[0097] wherein σ is the updated standard deviation.

[0098] ​If the updated standard deviation, the updated center value, and the updated selection probability satisfy the following formula:

[0099]

[0100] wherein δ is a small positive number artificially specified, such as (but not limited to) 10 -6 .

[0101] The updated standard deviation, the updated center value, and the updated selection probability are determined as the final standard deviation, the final center value, and the final selection probability; otherwise, the updated standard deviation, the updated center value, and the updated selection probability are determined as the initialized standard deviation, the initialized center value, and the initialized selection probability for the next iteration.

[0102] In S230, the specific independent variable of the selected data distribution function is determined as the direct current value of the direct current signal in each data distribution function.

[0103] Exemplarily, Figure 3 is a schematic diagram of a data distribution function, as Figure 3 indicated, is a selected data distribution function.

[0104] The present scheme is thus configured to accurately calculate each Gaussian function, i.e., each data distribution function, and further accurately determine the direct current value according to the specific independent variable. Since the digital signal is an integer value output, but the specific independent variable can be a decimal number, the effect of improving the current measurement accuracy is achieved.

[0105] Embodiment Three

[0106] Figure 4 is a structural schematic diagram of a direct current signal processing device provided by Embodiment Three of the present application. The device can execute the direct current signal processing method provided by any embodiment of the present application, and has the corresponding function modules and beneficial effects of the execution method. As Figure 4 indicated, the device comprises:

[0107] The quantity statistical module 310 is configured to perform quantity statistics on the discrete signal sequence to obtain a discrete integer counting result. The discrete signal sequence is a signal sequence in which the values obtained by randomly sampling the to-be-processed direct current signal during the process of receiving the to-be-processed direct current signal are all integers.

[0108] The data distribution function determination module 320 is configured to iteratively calculate the parameters in the data distribution function based on the discrete integer counting result, and determine the data distribution function according to the iterative result of the parameters. Different data distribution functions correspond to different direct current signal influencing factors.

[0109] The direct current value determination module 330 is configured to determine a specific independent variable of a selected data distribution function as the direct current value of the direct current signal to be processed in each data distribution function, the selected data distribution function being a data distribution function with the largest function value in each data distribution function, and the specific independent variable being an independent variable corresponding to the maximum value of the selected data distribution function.

[0110] The technical scheme of the embodiment of the present application comprises: a quantity statistical module 310 configured to perform quantity statistics on a discrete signal sequence to obtain a discrete integer counting result, the discrete signal sequence being a signal sequence with integer values obtained by randomly sampling the direct current signal to be processed in the process of receiving the direct current signal to be processed; a data distribution function determination module 320 configured to perform iterative calculation on parameters in a data distribution function based on the discrete integer counting result, and determine the data distribution function according to the iterative result of the parameters; different data distribution functions correspond to different direct current signal influencing factors; and a direct current value determination module 330 configured to determine a specific independent variable of a selected data distribution function as the direct current value of the direct current signal to be processed in each data distribution function, the selected data distribution function being a data distribution function with the largest function value in each data distribution function, and the specific independent variable being an independent variable corresponding to the maximum value of the selected data distribution function. The technical scheme can truly reflect the distribution of the current value by randomly sampling the direct current signal to be processed to obtain a discrete integer counting result, and then determine the direct current value by determining the specific independent variable in the selected data distribution function, thereby realizing the effect of obtaining the direct current by only one processing method in various interference environments.

[0111] In the embodiment of the present application, the data distribution function determination module 320 comprises:

[0112] The Gaussian function determination unit is configured to perform iterative calculation on the standard deviation, the central value and the selection probability in a Gaussian function based on the discrete integer counting result, and determine the Gaussian function according to the iterative result of the parameters; different Gaussian functions correspond to different direct current signal influencing factors.

[0113] In the embodiment of the present application, the Gaussian function determination unit is specifically configured to:

[0114] initialize the standard deviation, the central value and the selection probability in the target Gaussian function to obtain an initialized standard deviation, an initialized central value and an initialized selection probability; the target Gaussian function being a Gaussian function corresponding to the target influencing factor;

[0115] determine an initialized target Gaussian function according to the initialized standard deviation, the initialized central value and the initialized selection probability, and substitute the target integer value in the discrete integer counting result into the initialized target Gaussian function to obtain a target initial function value corresponding to the target integer value.

[0116] determine a probability that the target integer value is classified as the target influence factor according to a ratio of a target function value corresponding to the target integer value and a total function value; the total function value is a sum of initial function values corresponding to the target integer value under each influence factor;

[0117] determine the target calculation value based on the probability that each integer value is classified as the target influence factor and a counting result of the integer value;

[0118] determine an updated standard deviation, an updated center value and an updated selection probability after this iteration according to the target calculation value and the counting result of the discrete integer;

[0119] If the updated standard deviation, the updated center value and the updated selection probability satisfy an iteration end condition, the updated standard deviation, the updated center value and the updated selection probability are determined as a final standard deviation, a final center value and a final selection probability;

[0120] Otherwise, the updated standard deviation, the updated center value and the updated selection probability are determined as an initialization standard deviation, an initialization center value and an initialization selection probability for next iteration;

[0121] Correspondingly, the Gaussian function is determined according to the iteration result of the parameter, comprising:

[0122] The target Gaussian function is determined according to the final standard deviation, the final center value and the final selection probability.

[0123] In the embodiments of the application, the updated standard deviation, the updated center value and the updated selection probability after this iteration are determined according to the target calculation value and the counting result of the discrete integer, comprising:

[0124] The updated selection probability is determined according to the following formula:

[0125]

[0126] wherein, is the updated selection probability, r k is the target calculation value, h n is a counting result corresponding to an integer value n in the counting result of the discrete integer;

[0127] The updated center value is determined according to the following formula:

[0128]

[0129] wherein, is the updated center value, n is an integer value n in the counting result of the discrete integer, r k,n is a probability that the integer value n is classified as the influence factor k;

[0130] The update standard deviation is determined according to the following formula:

[0131]

[0132] wherein, is the update standard deviation.

[0133] In the embodiments of the present application, the device further comprises, comprising:

[0134] The analog-to-digital conversion module is configured to amplify the analog signal continuously received from the direct current sensor and perform analog-to-digital conversion on the amplified signal to obtain a time series of the to-be-processed direct current signal.

[0135] The random sampling module is configured to perform random sampling on the time series of the to-be-processed direct current signal based on the random pulse sequence to obtain a discrete signal sequence in which all values are integers.

[0136] In the embodiments of the present application, the device further comprises:

[0137] The pseudo-random number sequence generation module is configured to generate a pseudo-random number sequence.

[0138] The pseudo-random number sequence adjustment module is configured to, if a pseudo-random number in the pseudo-random number sequence is greater than a specified constant, assign the pseudo-random number in the pseudo-random number sequence to 1.

[0139] Otherwise, assign it to 0.

[0140] The pseudo-random number sequence is determined as the random pulse sequence.

[0141] In the embodiments of the present application, the quantity counting module 310 comprises:

[0142] The quantity counting unit is configured to, when counting the discrete signal sequence, if it is determined that the count of integer values in the current counting result is greater than a preset quantity threshold, determine the current counting result as a discrete integer counting result.

[0143] The direct current signal processing device provided in the embodiments of the present application can execute the direct current signal processing method provided in any of the embodiments of the present application, and has the corresponding function modules and beneficial effects of the execution method.

[0144] Embodiment Four

[0145] Figure 5A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0146] like Figure 5 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., which is communicatively connected to the at least one processor 11. The memory stores a computer program that can be executed by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. Various programs and data required for the operation of the electronic device 10 can also be stored in the RAM 13. The processor 11, ROM 12, and RAM 13 are connected to each other via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0147] Multiple components in the electronic device 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0148] The processor 11 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The processor 11 performs the various methods and processes described above, such as the DC signal processing method.

[0149] In some embodiments, the processing method of the direct current signal can be implemented as a computer program tangibly embodied in a computer readable storage medium, e.g., storage unit 18. In some embodiments, parts or all of the computer program can be loaded onto the electronic device 10 via, e.g., ROM 12 and / or communication unit 19. When the computer program is loaded onto RAM 13 and executed by processor 11, one or more steps of the processing method of the direct current signal described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the processing method of the direct current signal by any other suitable means, e.g., by means of firmware.

[0150] The various implementations of the system and techniques described above can be realized in digital electronic circuitry, integrated circuitry, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on a chip (SOC), a complex programmable logic device (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0151] Computer programs used to implement the processes of the present application can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the computer program, when executed, implements the functions / acts specified in the flowcharts and / or block diagrams. The computer program can be executed entirely on a machine, partially on a machine, partially on a machine as part of a standalone software package, or entirely on a remote machine or server.

[0152] In the context of the present application, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. A computer-readable storage medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of a machine-readable storage medium will include one or more lines of a program of instructions in a transitory signal, a portable computer diskette, 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 disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0153] To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0154] The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by 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), a blockchain network, and the Internet.

[0155] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system, to solve the defects of large management difficulty and weak business scalability in traditional physical host and VPS service.

[0156] It should be understood that the various forms of flow shown above can be reordered, added to, or have steps deleted. For example, the steps described in the present application can be performed in parallel, in series, or in a different order, as long as the desired results of the technical solutions of the present application can be achieved, which are not limited herein.

[0157] The above detailed description does not constitute a limitation on the protection scope of the present application. Those skilled in the art should understand that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method for processing a DC signal, characterized in that: include: Perform quantity statistics on discrete signal sequences to obtain discrete integer counting results; The discrete signal sequence is a signal sequence in which the values ​​obtained by randomly sampling the DC signal to be processed in the process of receiving the DC signal to be processed are all integers; Iteratively calculate the parameters in the data distribution function based on the discrete integer counting result, and determine the data distribution function according to the iterative result of the parameters; different data distribution functions correspond to different DC signal influencing factors; Among the data distribution functions, the specific independent variable of the selected data distribution function is determined to be the DC current value of the DC signal to be processed; the selected data distribution function is the data distribution function with the largest function value among the data distribution functions; the specific independent variable is the independent variable corresponding to the maximum value of the selected data distribution function.

2. The method according to claim 1, characterized in that Iteratively calculating parameters in the data distribution function based on the discrete integer counting result, and determining the data distribution function according to the iterative results of the parameters, including: The standard deviation, central value and selection probability of the Gaussian function are iteratively calculated based on the discrete integer counting results, and the Gaussian function is determined according to the iterative results of the parameters; different Gaussian functions correspond to different DC signal influencing factors.

3. The method according to claim 2, characterized in that Iteratively calculate the standard deviation, central value, and selection probability of the Gaussian function based on the discrete integer counting results, including: Initializing the standard deviation, center value, and selection probability of the target Gaussian function to obtain an initialized standard deviation, an initialized center value, and an initialized selection probability; the target Gaussian function is a Gaussian function corresponding to the target influencing factor; Determine the initialization target Gaussian function according to the initialization standard deviation, the initialization center value, and the initialization selection probability, and substitute the target integer value in the discrete integer counting result into the initialization target Gaussian function to obtain the target initial function value corresponding to the target integer value; Determining the probability that the target integer value is classified as a target influencing factor based on the ratio of the target function value corresponding to the target integer value to the total function value; the total function value is the sum of the initial function values ​​corresponding to the target integer value under each influencing factor; Determining a target calculation value based on the probability of each integer value being classified as a target influencing factor and the counting result of the integer values; Determine the updated standard deviation, updated center value, and updated selection probability after this iteration based on the target calculation value and the discrete integer counting result; If the updated standard deviation, updated center value, and updated selection probability meet the iteration end condition, the updated standard deviation, updated center value, and updated selection probability are determined as the final standard deviation, final center value, and final selection probability; Otherwise, the updated standard deviation, updated center value, and updated selection probability are determined as the initialization standard deviation, initialization center value, and initialization selection probability for the next iteration; Accordingly, the Gaussian function is determined according to the iterative results of the parameters, including: The target Gaussian function is determined based on the final standard deviation, the final center value, and the final selection probability.

4. The method according to claim 3, characterized in that The updated standard deviation, updated center value, and updated selection probability after this iteration are determined based on the target calculation value and the discrete integer counting result, including: The update selection probability is determined according to the following formula: in, is the update selection probability, r k Calculate the target value, h n is the counting result corresponding to the integer value n in the discrete integer counting result; The update center value is determined according to the following formula: in, To update the center value, n is the integer value in the discrete integer counting result, r k,n is the probability of an integer value n being classified as influencing factor k; The updated standard deviation is determined according to the following formula: in, is the updated standard deviation.

5. The method according to claim 1, wherein The process of determining the discrete signal sequence includes: Amplify the analog signal continuously received from the DC sensor, and perform analog-to-digital conversion on the amplified signal to obtain a time series DC signal to be processed; Based on the random pulse sequence, the DC signal to be processed in the time series is randomly sampled, and the obtained values ​​are all discrete signal sequences with integer values.

6. The method according to claim 5, characterized in that The process of determining the random pulse sequence includes: Generate a pseudo-random number sequence; If the pseudo-random number in the pseudo-random number sequence is greater than the specified constant, the pseudo-random number in the pseudo-random number sequence is assigned a value of 1; Otherwise, assign a value of 0; A pseudo-random number sequence is determined as a random pulse sequence.

7. The method according to claim 1, characterized in that Perform quantitative statistics on discrete signal sequences to obtain discrete integer counting results, including: When performing quantity statistics on a discrete signal sequence, if it is determined that the count quantity of integer values ​​in a current statistical result is greater than a preset quantity threshold, the current statistical result is determined as a discrete integer counting result.

8. A DC signal processing device, characterized in that: include: The quantity statistics module is used to perform quantity statistics on discrete signal sequences to obtain discrete integer counting results; The discrete signal sequence is a signal sequence in which the values ​​obtained by randomly sampling the DC signal to be processed in the process of receiving the DC signal to be processed are all integers; A data distribution function determination module is used to iteratively calculate the parameters in the data distribution function based on the discrete integer counting results, and determine the data distribution function according to the iterative results of the parameters; different data distribution functions correspond to different DC signal influencing factors; A DC current value determination module is used to determine a specific independent variable of a selected data distribution function among each data distribution function as the DC current value of the DC signal to be processed; the selected data distribution function is the data distribution function with the largest function value among each data distribution function; and the specific independent variable is the independent variable corresponding to the maximum value of the selected data distribution function.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor. The computer program is executed by the at least one processor so that the at least one processor can perform the direct current signal processing method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the direct current signal processing method according to any one of claims 1 to 7 when executed.

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