Signal noise reduction method and system for improving communication quality of power line

Abstract

The invention relates to the technical field of power line communication, in particular to a signal noise reduction method and system for improving power line communication quality, and the method comprises the steps: carrying out the filtering of a power line communication signal at different synchronization lengths; analyzing the volatility of the local range of each power line communication signal value; comparing the distances between the original extreme value signal sequences before and after filtering to obtain a filtering effect of each power line communication signal value based on different synchronization lengths; obtaining a denoising selection weight of each power line communication signal value; based on the prediction result of the filtering weight of a preset number of signal values before each power line communication signal value, combining the signal distribution similarity in the window corresponding to the power line communication signal values and the denoising selection weight to obtain the filtering weight of each power line communication signal value, and weighting the filtered signals to obtain the power line communication signal value. And obtaining a final filtering value of each power line communication signal value. The invention aims to improve the de-noising quality of the power line communication signal.

Description

Technical Field

[0001] The present application relates to the technical field of power line communication, and in particular to a signal noise reduction method and system for improving the quality of power line communication. Background Art

[0002] Power Line Communication (PLC) is a technology that uses existing power lines for data transmission. It has the advantages of no need for additional wiring, low cost, and wide coverage. However, as a communication medium, power lines have inherent noise interference and signal attenuation problems that have always been technical challenges. Power line communication channels are often interfered by various noises, such as switching noise of electrical equipment, lightning interference, background noise, etc. These noises will seriously affect the communication quality and reduce the reliability of signal transmission.

[0003] With the popularization of the Internet of Things and intelligent applications, the power line communication market is showing a rapid growth trend. It is expected that the power line carrier communication industry will continue to maintain a high growth rate in the next few years. At present, the performance of the power line communication system is still limited by noise interference. When using the traditional Gaussian filtering algorithm to reduce the noise of the power line communication signal, a Gaussian filter with a fixed window size is usually used. However, due to the complex and changeable noise interference in power line communication, the Gaussian filter with a fixed window size may not be able to adapt to the changes in different noise characteristics, and cannot effectively balance the relationship between noise and signal, thus affecting the quality of denoising. Summary of the invention

[0004] In view of the above, it is necessary to provide a signal noise reduction method and system for improving the quality of power line communication to solve the above problems.

[0005] A first aspect of the present application provides a signal noise reduction method for improving power line communication quality, the method comprising: filtering the power line communication signal with a first preset step size and a second preset step size respectively; Analyze the fluctuation characteristics of the envelope of the signal in the preset window of each power line communication signal value, and combine the signal difference distribution characteristics between adjacent signal values ​​to obtain the volatility of each power line communication signal value; Based on the type of the extreme point closest to each power line communication signal value, an original extreme value signal sequence of each power line communication signal value is obtained; the distance between the original extreme value signal sequence and the filtered original extreme value signal sequence is compared, and the first filtering effect and the second filtering effect of each power line communication signal value are obtained in combination with the abnormal detection result of the filtered original extreme value signal sequence; and a denoising selection weight value of each power line communication signal value is obtained in combination with the volatility; Based on the prediction results of the filtering weights of a preset number of signal values ​​before each power line communication signal value, combined with the signal distribution similarity in the window corresponding to the power line communication signal value and the denoising selection weight, the filtering weight of each power line communication signal value is obtained, and the filtered signal is weighted to obtain the final filtering value of each power line communication signal value.

[0006] The obtaining of the volatility of each power line communication signal value is specifically as follows: For each window of power line communication signal values, obtain the upper and lower envelopes of all signal values ​​in the window, and record the discreteness of the corresponding numerical values ​​of all signal values ​​on the upper envelope and the lower envelope as the first discreteness and the second discreteness respectively; Calculating a difference between the first discreteness and the second discreteness, recorded as a first difference; Calculate the average value of the differences between each signal value in the window and all its adjacent signal values, and calculate the mean value of the average values ​​of the differences of all signal values ​​in the window; accumulate the difference between the average value of the differences of all signal values ​​in the window and the mean value to obtain a second difference; The first discreteness, the second discreteness, the first difference, and the second difference are forward fused and normalized to obtain the volatility of each power line communication signal value.

[0007] The process of obtaining the original extreme value signal sequence of each power line communication signal value is as follows: For each power line communication signal value, the extreme value signal point closest to each power line communication signal value is obtained in the corresponding window, and all signal value points of the same type as the extreme value signal point are further obtained to form an original extreme value signal sequence.

[0008] The steps of obtaining the first filtering effect and the second filtering effect of each power line communication signal value are as follows: The original extreme value signal sequences of the power line communication signal after denoising by the first preset step length and the second preset step length are recorded as the first denoised extreme value signal sequence and the second denoised extreme value signal sequence respectively; Obtaining a metric distance between the original extreme value signal sequence and the first denoised extreme value signal sequence; Perform anomaly detection on the first denoised extreme value signal sequence and calculate the anomaly average of all elements; The negative correlation mapping result after the metric distance and the abnormal average value are positively fused as the first filtering effect corresponding to each power line communication signal value; Correspondingly, based on the original extreme value signal sequence and the second denoised extreme value signal sequence, a second filtering effect corresponding to each power line communication signal value is obtained.

[0009] The specific formula for obtaining the denoising selection weight of each power line communication signal value is as follows: ;in, represents a denoising selection weight for the i-th power line communication signal value; represents the volatility corresponding to the i-th power line communication signal value; represents a first filtering effect of the i-th power line communication signal value; The second filtering effect of the i-th power line communication signal value is represented.

[0010] The process of obtaining the filtering weight of each power line communication signal value is specifically as follows: Predicting the filter weights of a preset number of signal values ​​before each power line communication signal value to obtain a preferred weight for each power line communication signal value; Based on the filtering weights of a preset number of signal values ​​before each power line communication signal value and the signal distribution characteristics of the corresponding window, combined with the denoising selection weights, a signal filtering correction value for each power line communication signal value is obtained; The average of the signal filtering correction value and the preferred weight of each power line communication signal value is used as the filtering weight of each power line communication signal value.

[0011] Among them, the signal filtering correction value of each power line communication signal value is obtained, specifically: Analyze the signal distribution similarity between each power line communication signal value and the windows corresponding to the previously preset number of signal values ​​to obtain a similar window for each power line communication signal value; The signal filtering correction weight of the i-th power line communication signal value is recorded as , its formula form is: ;in, The number of similarity windows representing the value of the ith power line communication signal; represents the reference coefficient; represents the signal similarity between the window corresponding to the i-th power line communication signal value and its f-th similar window; The filtering weight of the center signal of the f-th similarity window representing the i-th power line communication signal value; Represents the denoising selection weight for the i-th power line communication signal value.

[0012] The obtaining of the similarity window of each power line communication signal value is specifically as follows: The signal similarity between each power line communication signal value and windows corresponding to a preset number of signal values ​​is calculated, and windows whose signal similarity is greater than a preset threshold are recorded as similar windows of each power line communication signal value.

[0013] Among them, the final filtered value of each power line communication signal value is obtained, and the specific formula is: ;in, a final filtered value representing each power line communication signal value; a filter weight representing each power line communication signal value; Indicates a filtered value of each power line communication signal value after using a first preset step size; Indicates that each power line communication signal value is filtered using the second preset step size.

[0014] In a second aspect, an embodiment of the present application also provides a signal noise reduction system for improving the quality of power line communication, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of any one of the above methods when executing the computer program.

[0015] This application has at least the following beneficial effects: The embodiment of the present application first filters the power line communication signal, analyzes the signal fluctuations of each power line communication signal value and its surrounding signals, and obtains volatility. The beneficial effect is that the signal fluctuation characteristics around each power line communication signal value are analyzed, so as to facilitate the subsequent adaptive weighting of two filter values ​​based on the fluctuation characteristics; further, the distribution characteristics of the same type of extreme value points within the local range of each power line communication signal value before and after filtering are analyzed to obtain the filtering effect corresponding to each step size, so as to facilitate the subsequent comparison of the filtering effects of different step sizes to find the most suitable filtering weight, thereby maximizing the clarity of the signal and reducing noise interference; combined with the volatility, the denoising selection weight of each power line communication signal value is obtained, and the beneficial effect is that the denoising is flexibly adjusted according to the fluctuation characteristics of the signal. strength, thereby optimizing the clarity and stability of the signal; based on the prediction results of the filtering weights of a preset number of signal values ​​before each power line communication signal value, combined with the signal distribution similarity in the window corresponding to the power line communication signal value and the denoising selection weight, the filtering weight of each power line communication signal value is obtained, which has the beneficial effect of combining historical signal information, similarity between signals and denoising selection weight to more accurately predict the filtering weight of each signal value and avoid relying solely on a certain characteristic; the filtered signal is weighted to obtain the final filtering value of each power line communication signal value, and the filtering weight can be dynamically adjusted according to different signal conditions to effectively remove noise and retain useful signals, which greatly increases the flexibility of signal denoising and improves the signal denoising effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A flowchart of a signal noise reduction method for improving the quality of power line communication provided by an embodiment of the present application; Figure 2A flowchart for obtaining filtering weights provided in one embodiment of the present application. DETAILED DESCRIPTION

[0017] In the description of the embodiments of the present application, words such as "exemplary", "or", "for example" and the like are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary", "or", "for example" and the like is intended to present related concepts in a concrete manner.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art in the present application. The terms used in the specification of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application.

[0019] It should also be noted that the terms "first" and "second" in this application and the accompanying drawings are used to distinguish similar objects, rather than to describe a specific order or sequence. The method disclosed in the embodiments of the present application or the method shown in the flow chart includes one or more steps for implementing the method. Without departing from the scope of protection of the present application, the execution order of multiple steps can be interchanged with each other, and some steps can also be deleted.

[0020] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0021] The following is a detailed description of a signal noise reduction method and system for improving the quality of power line communication provided by the present application in conjunction with the accompanying drawings.

[0022] See also Figure 1 , which shows a flowchart of a signal noise reduction method for improving the quality of power line communication provided by an embodiment of the present application, the method comprising the following steps: Step 1: De-noising the power line communication signal using a first preset step size and a second preset step size respectively.

[0023] In smart grid and PLC technology, filtering technology is widely used in signal processing and transmission to overcome problems such as signal attenuation, interference and noise. Therefore, this application considers Gaussian filtering of power line communication signals. Since the existing Gaussian filtering algorithm has the problem that different step lengths have different effects on the filtering denoising algorithm, after using a fixed step length filtering algorithm to process it, there may still be a situation where the denoising effect is not ideal. Therefore, the denoising effect of the first preset step length and the second preset step length can be combined for analysis to better adapt to the complex characteristics of power line communication signals. In this embodiment, the first preset step length is 51, and the second preset step length is 11. The implementer can adjust the step length in the filtering algorithm according to the actual situation, and this application does not limit this.

[0024] Step 2: Analyze the fluctuation characteristics of the envelope of the signal in the preset window of each power line communication signal value, and combine the signal difference distribution characteristics between adjacent signal values ​​to obtain the volatility of each power line communication signal value.

[0025] This application analyzes each power line communication signal value to obtain its corresponding signal filtering selection weight. Specifically, a window is preset with each power line communication signal value as the center. In this embodiment, the length of the preset window is 1001, and the implementer can adjust it according to the actual situation; the fluctuation characteristics of the envelope of all power line communication signal values ​​in the window are analyzed, and the signal difference distribution characteristics between adjacent power line communication signal values ​​are combined to obtain the volatility of each power line communication signal value: For each window of power line communication signal values, the upper and lower envelopes of all signal values ​​in the window are obtained, and the discreteness of the corresponding numerical values ​​of all signal values ​​on the upper envelope and the lower envelope are recorded as the first discreteness and the second discreteness respectively; the difference between the first discreteness and the second discreteness is calculated, which is recorded as the first difference; the average value of the differences between each signal value in the window and all its adjacent signal values ​​is calculated, and the mean of the average values ​​of the differences of all signal values ​​in the window is calculated; the difference between the average value of the differences of all signal values ​​in the window and the mean is accumulated to obtain the second difference; the first discreteness, the second discreteness, the first difference and the second difference are forward fused and normalized to obtain the volatility of each power line communication signal value.

[0026] In this embodiment, variance is used to measure the discreteness of signal values ​​on the upper and lower envelope lines; the difference between the discreteness is calculated using the absolute value of the difference; the multiplication method is used for forward fusion of multiple variables; the maximum and minimum value normalization method is used for normalization, and the implementer can select the appropriate normalization method according to the actual situation.

[0027] It should be understood that the first discreteness and the second discreteness are used to measure the stationarity characteristics of the signal distribution in the window of each power line communication signal value, the first difference is used to measure the stationarity difference between the upper and lower envelopes, and the second difference is used to measure the difference distribution between the signal in the window and the adjacent signal values; further, when the difference between adjacent signal values ​​of the signal curve in the window is smaller, and the stationarity of the upper and lower envelope curves is stronger, and the stationarity difference between the upper and lower envelopes is smaller, it means that the signal volatility in the window is smaller, and a longer filter should be used to denoise the signal; otherwise, a shorter filter should be used to denoise the signal.

[0028] Step three: based on the type of the extreme point closest to each power line communication signal value, obtain the original extreme value signal sequence of each power line communication signal value; compare the distance between the original extreme value signal sequence and the filtered original extreme value signal sequence, and combine the abnormality detection result of the filtered original extreme value signal sequence to obtain the first filtering effect and the second filtering effect of each power line communication signal value; combine the volatility to obtain the denoising selection weight value of each power line communication signal value.

[0029] For each power line communication signal value, the extreme value signal point closest to each power line communication signal value is obtained in the corresponding window, and all signal value points of the same type as the extreme value signal point are further obtained to form an original extreme value signal sequence, and the type includes a maximum value point and a minimum value point; for ease of understanding, an example is given, if the extreme value signal point closest to the i-th power line communication signal value is a maximum value point, then a sequence composed of all maximum value points in the window of the i-th power line communication signal value is obtained, which is recorded as the original extreme value signal sequence of the i-th power line communication signal value. The original extreme value signal sequence after denoising the i-th power line communication signal value by the first preset step size and the second preset step size is recorded as the first denoised extreme value signal sequence and the second denoised extreme value signal sequence, respectively.

[0030] Obtain the metric distance between the original extreme value signal sequence and the first denoised extreme value signal sequence; perform anomaly detection on the first denoised extreme value signal sequence and calculate the abnormal average value of all elements; use the negative correlation mapping result after positive fusion of the metric distance and the abnormal average value as the first filtering effect corresponding to each power line communication signal value. Based on the original extreme value signal sequence and the second denoised extreme value signal sequence, the same calculation method as the first filtering effect is used to obtain the second filtering effect corresponding to each power line communication signal value.

[0031] In this embodiment, the dynamic time warping (DTW) distance is used to measure the metric distance between two sequences, which is recorded as A; the algorithm for detecting anomalies in the sequence adopts the local outlier factor (LOF) anomaly detection algorithm, and the abnormal average value is recorded as B; the multiplication calculation method is used for forward fusion of multiple variables, and the formula form of the first filtering effect is: ;in, Represents an exponential function with a natural constant as the base. Among them, the DTW distance and the LOF anomaly detection algorithm are both well-known technologies, and this application will not go into details.

[0032] It should be understood that when the distance measure of the extreme value signal sequence before and after filtering is closer and the abnormal average value of all signal values ​​after filtering is smaller, it means that the filtering effect obtained by using the corresponding length filtering is better.

[0033] Based on the volatility corresponding to each power line communication signal value and the first and second filtering effects, a denoising selection weight value for each power line communication signal value is obtained, and its formula form is: ;in, represents a denoising selection weight for the i-th power line communication signal value; represents the volatility corresponding to the i-th power line communication signal value; represents a first filtering effect of the i-th power line communication signal value; The second filtering effect of the i-th power line communication signal value is represented.

[0034] It should be understood that, when the volatility of the signal value within the window of each power line communication signal value is smaller and the corresponding denoising effect using the first preset step size is better, the corresponding signal denoising selection weight value is more biased towards the signal value after denoising by the first preset step size, and thus the denoising selection weight value is larger.

[0035] Step 4: Based on the prediction results of the filtering weights of a preset number of signal values ​​before each power line communication signal value, combined with the signal distribution similarity in the window corresponding to the power line communication signal value and the denoising selection weight, the filtering weight of each power line communication signal value is obtained, and the filtered signal is weighted to obtain the final filtering value of each power line communication signal value.

[0036] This application analyzes discrete power line communication signals. It should be noted that when filtering these discrete data, the changes in weights should not be too drastic: if the weights of adjacent signal values ​​change too much, it may cause abnormal fluctuations in the filtering results. Especially when the signal is interfered by noise, the filtering process may tend to be over-smoothed, causing the results to tend toward an abnormal stable trend. In order to ensure the rationality of signal changes, although it is discrete data, the adjustment of weights during the filtering process should be as smooth and continuous as possible to avoid sudden changes or discontinuities, so as to better reflect the changing trend of the real signal.

[0037] Therefore, prediction is performed based on the filter weights of the preset number of signal values ​​before each power line communication signal value to obtain the preferred weight of each power line communication signal value, thereby ensuring that the weight changes dynamically while the change of the signal value is smooth, continuous and reasonable; this embodiment adopts a time series prediction algorithm. The signal distribution similarity of each power line communication signal value and the window corresponding to each previous signal value is analyzed to obtain a similar window for each power line communication signal value: the signal similarity of each power line communication signal value and the window corresponding to the preset number of signal values ​​before is calculated, and the window with the signal similarity greater than the preset threshold is recorded as the similar window for each power line communication signal value. In this embodiment, the preset number is 10000. It should be noted that if a power line communication signal value is less than the preset number of signal values ​​before, only all signal values ​​before each power line communication signal value are considered; the signal similarity between two windows is determined by calculating the Pearson correlation coefficient, and the preset threshold value is 0.8.

[0038] Furthermore, based on the denoising selection weight of each power line communication signal value and the filtering weight of the previous signal, combined with the signal similarity, the signal filtering correction value of each power line communication signal value is obtained, and its formula form is: ;in, A signal filtering correction weight representing the i-th power line communication signal value; The number of similarity windows representing the value of the ith power line communication signal; represents the reference coefficient, which is 0.5 in this embodiment; represents the signal similarity between the window corresponding to the i-th power line communication signal value and its f-th similar window; The filtering weight of the center signal of the f-th similarity window representing the i-th power line communication signal value; Represents the denoising selection weight for the i-th power line communication signal value.

[0039] Further, the average of the signal filtering correction value and the preferred weight of each power line communication signal value is used as the filtering weight of each power line communication signal value, wherein the flowchart for obtaining the filtering weight is as follows: Figure 2 As shown; based on the filtering weight of each power line communication signal value, combined with the filtering algorithm, the denoised power line communication signal is obtained. Specifically, ;in, a final filtered value representing each power line communication signal value; a filter weight representing each power line communication signal value; Indicates a filtered value of each power line communication signal value after using a first preset step size; Indicates that each power line communication signal value is filtered using the second preset step size.

[0040] At this point, the noise reduction of the power line communication signal is completed.

[0041] Based on the same inventive concept as the above method, an embodiment of the present application also provides a signal noise reduction system for improving the quality of power line communication, including a memory, a processor, and a computer program stored in the memory and running on the processor, and when the processor executes the computer program, the steps of any one of the above-mentioned signal noise reduction methods for improving the quality of power line communication are implemented.

[0042] To summarize, the present application first filters the power line communication signal, analyzes the signal fluctuations of each power line communication signal value and its surrounding signals, and obtains volatility. The beneficial effect is that the signal fluctuation characteristics around each power line communication signal value are analyzed, so as to facilitate the subsequent adaptive weights of the two filter values ​​based on the fluctuation characteristics; further, the distribution characteristics of the same type of extreme points in the local range of each power line communication signal value before and after filtering are analyzed to obtain the filtering effect corresponding to each step size, so as to facilitate the subsequent comparison of the filtering effects of different step sizes, so as to find the most suitable filtering weight, thereby maximizing the clarity of the signal and reducing noise interference; combined with the volatility, the denoising selection weight of each power line communication signal value is obtained, and the beneficial effect is that the denoising can be flexibly adjusted according to the fluctuation characteristics of the signal. strength, thereby optimizing the clarity and stability of the signal; based on the prediction results of the filtering weights of a preset number of signal values ​​before each power line communication signal value, combined with the signal distribution similarity in the window corresponding to the power line communication signal value and the denoising selection weight, the filtering weight of each power line communication signal value is obtained, and its beneficial effect is that by combining historical signal information, similarity between signals and denoising selection weight, the filtering weight of each signal value can be predicted more accurately to avoid relying solely on a certain characteristic; the filtered signal is weighted to obtain the final filtering value of each power line communication signal value, and the filtering weight can be dynamically adjusted according to different signal conditions, effectively removing noise and retaining useful signals, greatly increasing the flexibility of signal denoising and improving the signal denoising effect.

[0043] The flowchart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system, method and computer program product according to the embodiment of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of the 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. In some alternative implementations, the function marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two continuous boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. In the description corresponding to the flowchart and the block diagram in the accompanying drawings, the operations or steps corresponding to different boxes can also occur in a different order from the order disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two continuous operations or steps can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. Each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented by a dedicated hardware-based system that performs the specified functions or actions, or may be implemented by a combination of dedicated hardware and computer instructions.

[0044] For those skilled in the art, it is obvious that the present application is not limited to the details of the above exemplary embodiments, and the present application can be implemented in other specific forms without departing from the basic features of the present application. Therefore, no matter from which point of view, the above embodiments of the present application should be regarded as exemplary and non-restrictive; the technical solutions recorded in the above embodiments are modified, or some of the technical features are replaced by equivalents, which does not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application.

Claims

1. A signal noise reduction method for improving the quality of power line communication, characterized in that: The method comprises the following steps: filtering the power line communication signal with a first preset step size and a second preset step size respectively; Analyze the fluctuation characteristics of the envelope of the signal in the preset window of each power line communication signal value, and combine the signal difference distribution characteristics between adjacent signal values ​​to obtain the volatility of each power line communication signal value; Based on the type of the extreme point closest to each power line communication signal value, an original extreme value signal sequence of each power line communication signal value is obtained; the distance between the original extreme value signal sequence and the filtered original extreme value signal sequence is compared, and the first filtering effect and the second filtering effect of each power line communication signal value are obtained in combination with the abnormal detection result of the filtered original extreme value signal sequence; and a denoising selection weight value of each power line communication signal value is obtained in combination with the volatility; Based on the prediction results of the filtering weights of a preset number of signal values ​​before each power line communication signal value, combined with the signal distribution similarity in the window corresponding to the power line communication signal value and the denoising selection weight, the filtering weight of each power line communication signal value is obtained, and the filtered signal is weighted to obtain the final filtering value of each power line communication signal value.

2. A signal noise reduction method for improving the quality of power line communication according to claim 1, characterized in that: The volatility of each power line communication signal value is obtained as follows: For each window of power line communication signal values, obtain the upper and lower envelopes of all signal values ​​in the window, and record the discreteness of the corresponding numerical values ​​of all signal values ​​on the upper envelope and the lower envelope as the first discreteness and the second discreteness respectively; Calculating a difference between the first discreteness and the second discreteness, recorded as a first difference; Calculate the average value of the differences between each signal value in the window and all its adjacent signal values, and calculate the mean value of the average values ​​of the differences of all signal values ​​in the window; accumulate the difference between the average value of the differences of all signal values ​​in the window and the mean value to obtain a second difference; The first discreteness, the second discreteness, the first difference, and the second difference are forward fused and normalized to obtain the volatility of each power line communication signal value.

3. A signal noise reduction method for improving the quality of power line communication according to claim 1, characterized in that: The process of obtaining the original extreme value signal sequence of each power line communication signal value is as follows: For each power line communication signal value, the extreme value signal point closest to each power line communication signal value is obtained in the corresponding window, and all signal values ​​of the same type as the extreme value signal point are further obtained to form an original extreme value signal sequence.

4. A signal noise reduction method for improving the quality of power line communication according to claim 1, characterized in that: The steps of obtaining the first filtering effect and the second filtering effect of each power line communication signal value are: The original extreme value signal sequences of the power line communication signal after denoising by the first preset step length and the second preset step length are recorded as the first denoised extreme value signal sequence and the second denoised extreme value signal sequence respectively; Obtaining a metric distance between the original extreme value signal sequence and the first denoised extreme value signal sequence; Perform anomaly detection on the first denoised extreme value signal sequence and calculate the anomaly average of all elements; The negative correlation mapping result after the metric distance and the abnormal average value are positively fused as the first filtering effect corresponding to each power line communication signal value; Correspondingly, based on the original extreme value signal sequence and the second denoised extreme value signal sequence, a second filtering effect corresponding to each power line communication signal value is obtained.

5. A signal noise reduction method for improving the quality of power line communication according to claim 1, characterized in that: The specific formula for obtaining the denoising selection weight of each power line communication signal value is: ;in, represents a denoising selection weight for the i-th power line communication signal value; represents the volatility corresponding to the i-th power line communication signal value; represents a first filtering effect of the i-th power line communication signal value; The second filtering effect of the i-th power line communication signal value is represented.

6. A signal noise reduction method for improving the quality of power line communication according to claim 1, characterized in that: The process of obtaining the filtering weight of each power line communication signal value is specifically as follows: Predicting the filter weights of a preset number of signal values ​​before each power line communication signal value to obtain a preferred weight for each power line communication signal value; Based on the filtering weights of a preset number of signal values ​​before each power line communication signal value and the signal distribution characteristics of the corresponding window, combined with the denoising selection weights, a signal filtering correction value for each power line communication signal value is obtained; The average of the signal filtering correction value and the preferred weight of each power line communication signal value is used as the filtering weight of each power line communication signal value.

7. A signal noise reduction method for improving the quality of power line communication according to claim 6, characterized in that: The signal filtering correction value of each power line communication signal value is obtained as follows: Analyze the signal distribution similarity between each power line communication signal value and the windows corresponding to the previously preset number of signal values ​​to obtain a similar window for each power line communication signal value; The signal filtering correction weight of the i-th power line communication signal value is recorded as , its formula form is: ;in, The number of similarity windows representing the value of the ith power line communication signal; represents the reference coefficient; represents the signal similarity between the window corresponding to the i-th power line communication signal value and its f-th similar window; The filtering weight of the center signal of the f-th similarity window representing the i-th power line communication signal value; Represents the denoising selection weight for the i-th power line communication signal value.

8. A signal noise reduction method for improving the quality of power line communication according to claim 7, characterized in that: The similarity window of each power line communication signal value is obtained as follows: The signal similarity between each power line communication signal value and windows corresponding to a preset number of signal values ​​is calculated, and windows whose signal similarity is greater than a preset threshold are recorded as similar windows of each power line communication signal value.

9. A signal noise reduction method for improving the quality of power line communication according to claim 1, characterized in that: The final filtering value of each power line communication signal value is obtained by the following specific formula: ;in, a final filtered value representing each power line communication signal value; a filter weight representing each power line communication signal value; Indicates a filtered value of each power line communication signal value after using a first preset step size; Indicates that each power line communication signal value is filtered using the second preset step size.

10. A signal noise reduction system for improving the quality of power line communication, comprising a memory, a processor, and a computer program stored in the memory and running 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 9 are implemented.

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