CN110739986A - PLC channel impulse noise detection method and system using projection cumulant - Google Patents

PLC channel impulse noise detection method and system using projection cumulant Download PDF

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CN110739986A
CN110739986A CN201910997176.1A CN201910997176A CN110739986A CN 110739986 A CN110739986 A CN 110739986A CN 201910997176 A CN201910997176 A CN 201910997176A CN 110739986 A CN110739986 A CN 110739986A
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projection
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翟明岳
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Guangdong University of Petrochemical Technology
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B3/00—Line transmission systems
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    • H04B3/46—Monitoring; Testing
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Abstract

The embodiment of the invention discloses PLC channel impulse noise detection methods and systems utilizing projection cumulant, wherein the method comprises the steps of 1, inputting an actually measured PLC signal sequence S, 2, detecting PLC channel impulse noise according to the property of the projection cumulant, and concretely, if the K window projects cumulant HKSatisfies the judgment condition HK≥e0Detecting impulse noise at the Kth point of the signal sequence S; otherwise, impulse noise is not detected. Wherein e is0Is an impulse noise detection threshold.

Description

PLC channel impulse noise detection method and system using projection cumulant
Technical Field
The invention relates to the field of electric power, in particular to a method and a system for detecting pulse noise of PLC channels.
Background
The power line communication technology is divided into Narrowband over power line communication (NPL) and Broadband over power line communication (BPL), the Narrowband power line communication refers to a power line carrier communication technology with the bandwidth limited to 3 k-500 kHz, the power line communication technology comprises a specified bandwidth (3-148.5 kHz) of European CENELEC, a specified bandwidth (9-490 kHz) of the U.S. Federal Communications Commission (FCC), a specified bandwidth (9-450 kHz) of Japanese Wireless industry and trade Association (Association of Radio Industries and Business Industries, ARIB), and a specified bandwidth (3-500 kHz) of China, the Narrowband power line communication technology adopts multiple modulation technologies such as PSK technology, DSS technology and linear frequency modulation technology, the communication rate is less than 1Mbits/s, the Narrowband power line communication technology adopts multiple carrier communication technologies such as PSK technology, DSS technology and linear frequency modulation technology, the communication rate is less than 1Mbits/s, the Broadband power line communication technology is limited to more than 1.6 Mbps, and the bandwidth is generally larger than 1 Mbps.
Although the powerline communication system has been widely used and the technology is relatively mature, a great amount of noise is generated in the powerline channel by a great amount of branches and electrical devices in the powerline communication system, and random impulse noise has great randomness and high noise intensity, which causes serious damage to the powerline communication system, so that the suppression technology for the random impulse noise is the focus of research of researchers at home and abroad , and the noise model does not conform to gaussian distribution.
With the application and popularization of nonlinear electrical appliances, background noise in a medium and low voltage power transmission and distribution network presents obvious non-stationarity and non-Gaussian characteristics, pulse noise becomes more common and more serious, and to filter the pulse noise, the pulse noise is detected first, and then corresponding measures can be taken in the step , but the existing method and system lack sufficient attention on the detection of the pulse noise.
Disclosure of Invention
The invention aims to provide PLC channel impulse noise detection methods and systems by utilizing projection cumulant, the proposed method utilizes the difference of PLC modulation signal, impulse noise and background noise expressed in projection space, and detects impulse noise by a projection classification method.
In order to achieve the purpose, the invention provides the following scheme:
A PLC channel impulse noise detection method using projected cumulative quantities, comprising:
step 1, inputting an actually measured PLC signal sequence S;
and 2, detecting the PLC channel impulse noise according to the projection cumulant property. The method specifically comprises the following steps: if the Kth window projects the cumulative amount HKSatisfies the judgment condition HK≥e0Detecting impulse noise at the Kth point of the signal sequence S; otherwise, impulse noise is not detected. Wherein e is0Is an impulse noise detection threshold.
A PLC channel impulse noise detection system using projected cumulative quantities, comprising:
the acquisition module inputs an actually measured PLC signal sequence S;
and the detection module is used for detecting the PLC channel impulse noise according to the projection cumulant property. The method specifically comprises the following steps: if the Kth window projects the cumulative amount HKSatisfies the judgment condition HK≥e0Detecting impulse noise at the Kth point of the signal sequence S; otherwise, impulse noise is not detected. Wherein e is0Is an impulse noise detection threshold.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
although the power line communication system is widely applied in and the technology is relatively mature, a large amount of noise is generated in a power line channel by a large amount of branches and electrical equipment in the power line communication system, with the application and popularization of nonlinear electrical appliances, background noise in a medium and low voltage power transmission and distribution network presents obvious non-stationarity and non-Gaussian characteristics, pulse noise becomes more common and more serious, and to filter the pulse noise, the pulse noise is detected first and then corresponding measures can be taken in steps, but the existing method and system lack sufficient attention to the detection of the pulse noise.
The invention aims to provide PLC channel impulse noise detection methods and systems by utilizing projection cumulant, the proposed method utilizes the difference of PLC modulation signal, impulse noise and background noise expressed in projection space, and detects impulse noise by a projection classification method.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed in the embodiments will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a schematic flow diagram of the process of the present invention;
FIG. 2 is a schematic diagram of the system of the present invention;
FIG. 3 is a flow chart illustrating an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, it is obvious that the described embodiments are only partial embodiments of the of the present invention, rather than all embodiments.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, a more detailed description is provided below in conjunction with the accompanying drawings and the detailed description.
FIG. 1 is a flow chart of 1 PLC channel impulse noise detection method using projection cumulant
Fig. 1 is a schematic flow chart of PLC channel impulse noise detection methods using projected cumulative quantities according to the present invention, as shown in fig. 1, PLC channel impulse noise detection methods using projected cumulative quantities specifically include the following steps:
step 1, inputting an actually measured PLC signal sequence S;
and 2, detecting the PLC channel impulse noise according to the projection cumulant property. The method specifically comprises the following steps: if the Kth window projects the cumulative amount HKSatisfies the judgment condition HK≥e0Detecting impulse noise at the Kth point of the signal sequence S; otherwise, impulse noise is not detected. Wherein e is0Is an impulse noise detection threshold.
Before the step 2, the method further comprises:
step 3, calculating the projection cumulant H of the Kth windowKAnd the impulse noise detection threshold e0。
The step 3 comprises the following steps:
step 301, generating the nth signal difference sequence Δ SnThe method specifically comprises the following steps:
ΔSn＝[ΔSn-D,ΔSn-D+1,…,ΔSn,ΔSn+1,…,ΔSn+D]
wherein:
ΔSi＝Si-Si-1: the nth signal differential sequence Delta SnThe ith element [ i ═ n-D, n-D +1, …, n + D]Si: the ith element in the signal sequence S, if element SiSubscript i of>N or i<1, then Si＝0S＝[S1，S2，…，SN]The length of the signal sequence is N
Figure BDA0002240141520000041
Length of window
Figure BDA0002240141520000042
Represents the lower rounding of
SNR: signal-to-noise ratio of the signal sequence S
Step 302, iteratively calculating the nth signal difference sequence Δ SnThe category center of (1) is specifically:
, initializing iteration, specifically:
Figure BDA0002240141520000051
Figure BDA0002240141520000052
wherein:
maxΔSn: the nth signal differential sequence Delta SnMaximum element of (2)
minΔSn: the nth signal differential sequence Delta SnMinimum element of (2)
Initialization value of class center
Figure BDA0002240141520000054
Initialization value of second class center
Figure BDA0002240141520000055
Figure BDA0002240141520000056
k＝0
Wherein:
Figure BDA0002240141520000057
initialization value of Category element set
Figure BDA0002240141520000058
Initialization value of second category element set
Figure BDA0002240141520000059
Beginning of class determination thresholdInitialization value
k: iterative control parameter
And step two, iterative updating, which specifically comprises the following steps:
Figure BDA00022401415200000510
Figure BDA00022401415200000511
wherein:
Figure BDA00022401415200000512
step k-1, category
Figure BDA00022401415200000513
The ith element in
Figure BDA00022401415200000514
Step k-1, second class
Figure BDA00022401415200000515
The j (th) element of (1)
N1The th category
Figure BDA00022401415200000516
Number of middle element
N2: the second class
Figure BDA00022401415200000517
Number of middle element
Figure BDA00022401415200000518
Step k, category
Figure BDA00022401415200000519
Class center of
Figure BDA00022401415200000520
Step k second class
Figure BDA00022401415200000521
Class center of
Figure BDA0002240141520000061
Figure BDA0002240141520000062
Wherein:
Figure BDA0002240141520000063
step k value of the th category element set
Step k value of the second class element set
Figure BDA0002240141520000065
The kth step value of the category judgment threshold value
k: iterative control parameter
Thirdly, iterative judgment, specifically comprising:
adding 1 to the iteration control parameter K, returning to the second step for re-iteration until the difference between two adjacent iteration values is less than thousandths, wherein the iteration control parameter K is equal to K, and obtaining the nth signal difference sequence delta SnSaid category center of the th category
Figure BDA0002240141520000066
And a class center of the second class
Step 303, find outThe nth signal difference sequence Delta SnThe optimal projection factor χ specifically is:
Figure BDA0002240141520000068
wherein:
W＝[ΔSn-μ1][ΔSn-μ2]T: the nth signal differential sequence Delta SnProjected value of
Step 304, calculating the cumulative projection H of the Kth windowKThe method specifically comprises the following steps:
Figure BDA0002240141520000069
step 305, obtaining the impulse noise detection threshold e0The method specifically comprises the following steps:
Figure BDA00022401415200000610
FIG. 2 structural intention of PLC channel impulse noise detection system using projection accumulation
Fig. 2 is a schematic structural diagram of PLC channel impulse noise detection systems using projected cumulative quantities according to the present invention, as shown in fig. 2, the PLC channel impulse noise detection systems using projected cumulative quantities include the following structures:
the acquisition module 401 inputs an actually measured PLC signal sequence S;
and the detection module 402 detects the PLC channel impulse noise according to the projection cumulant property. The method specifically comprises the following steps: if the Kth window projects the cumulative amount HKSatisfies the judgment condition HK≥e0Detecting impulse noise at the Kth point of the signal sequence S; otherwise, impulse noise is not detected. Wherein e is0Is an impulse noise detection threshold.
The system further comprises:
a calculating module 403, for obtaining the K-th window projection accumulation HKAnd the impulse noiseDetection threshold e0。
The calculation module 403 further includes the following units:
calculation unit 4031 at generates nth signal difference sequence Δ SnThe method specifically comprises the following steps:
ΔSn＝[ΔSn-D,ΔSn-D+1,…,ΔSn,ΔSn+1,…,ΔSn+D]
wherein:
ΔSi＝Si-Si-1: the nth signal differential sequence Delta SnThe ith element [ i ═ n-D, n-D +1, …, n + D]Si: the ith element in the signal sequence S, if element SiSubscript i of>N or i<1, then Si＝0S＝[S1，S2，…，SN]The length of the signal sequence is N
Figure BDA0002240141520000071
Length of window
Figure BDA0002240141520000072
Represents the lower rounding of
SNR: signal-to-noise ratio of the signal sequence S
An iteration unit 4032 for iteratively calculating the nth signal difference sequence Δ SnThe category center of (1) is specifically:
, initializing iteration, specifically:
Figure BDA0002240141520000081
Figure BDA0002240141520000082
wherein:
maxΔSn: the nth signal differential sequence Delta SnMaximum element of (2)
minΔSn: the nth signal differential sequence Delta SnMinimum element of (2)
Figure BDA0002240141520000083
Initialization value of class center
Figure BDA0002240141520000084
Initialization value of second class center
Figure BDA0002240141520000085
Figure BDA0002240141520000086
k＝0
Wherein:
Figure BDA0002240141520000087
initialization value of Category element set
Initialization value of second category element set
Figure BDA0002240141520000089
Initialization value of class judgment threshold value
k: iterative control parameter
And step two, iterative updating, which specifically comprises the following steps:
Figure BDA0002240141520000091
Figure BDA0002240141520000092
wherein:
step k-1, category
Figure BDA0002240141520000094
The ith element in
Figure BDA0002240141520000095
Step k-1, second class
Figure BDA0002240141520000096
The j (th) element of (1)
N1The th category
Figure BDA0002240141520000097
Number of middle element
N2: the second class
Figure BDA0002240141520000098
Number of middle element
Step k, category
Figure BDA00022401415200000910
Class center of
Figure BDA00022401415200000911
Step k second classClass center of
Figure BDA00022401415200000913
Figure BDA00022401415200000914
Wherein:
step k value of the th category element set
Figure BDA00022401415200000916
Step k value of the second class element set
The kth step value of the category judgment threshold value
k: iterative control parameter
Thirdly, iterative judgment, specifically comprising:
adding 1 to the iteration control parameter K, returning to the second step for re-iteration until the difference between two adjacent iteration values is less than thousandths, wherein the iteration control parameter K is equal to K, and obtaining the nth signal difference sequence delta SnSaid category center of the th category
Figure BDA00022401415200000918
And a class center of the second class
Figure BDA00022401415200000919
Second calculation unit 4033, which finds the nth signal difference sequence Δ SnThe optimal projection factor χ specifically is:
Figure BDA0002240141520000101
wherein:
W＝[ΔSn-μ1][ΔSn-μ2]T: the nth signal differential sequence Delta SnProjected value of
A third calculation unit 4034 for obtaining the KthCumulative amount of window projection HKThe method specifically comprises the following steps:
Figure BDA0002240141520000102
fourth calculation unit 4035, which calculates impulse noise detection threshold e0The method specifically comprises the following steps:
Figure BDA0002240141520000103
the following provides embodiments, and illustrates the present invention
FIG. 3 is a flow chart illustrating an embodiment of the present invention. As shown in fig. 3, the method specifically includes the following steps:
1. inputting measured PLC signal sequence
S＝[S1,S2,…,SN-1,SN]
Wherein:
s: measured PLC signal data sequence with length N
SiI is 1,2, …, N is measured PLC signal with serial number i
2. Determining a signal difference sequence
ΔSn＝[ΔSn-D,ΔSn-D+1,…,ΔSn,ΔSn+1,…,ΔSn+D]
Wherein:
ΔSi＝Si-Si-1: the nth signal differential sequence Delta SnThe ith element [ i ═ n-D, n-D +1, …, n + D]Si: the ith element in the signal sequence S, if element SiSubscript i of>N or i<1, then Si＝0S＝[S1，S2，…，SN]The length of the signal sequence is N
Figure BDA0002240141520000111
Length of window
Represents the lower rounding of
SNR: signal-to-noise ratio of the signal sequence S
3. Iterative determination of class centers of signal difference sequences
, initializing iteration, specifically:
Figure BDA0002240141520000113
Figure BDA0002240141520000114
wherein:
maxΔSn: the nth signal differential sequence Delta SnMaximum element of (2)
minΔSn: the nth signal differential sequence Delta SnMinimum element of (2)
Figure BDA0002240141520000115
Initialization value of class center
Figure BDA0002240141520000116
Initialization value of second class center
Figure BDA0002240141520000121
Figure BDA0002240141520000122
k＝0
Wherein:
Figure BDA0002240141520000123
initialization value of Category element set
Initialization value of second category element set
Figure BDA0002240141520000125
Initialization value of class judgment threshold value
k: iterative control parameter
And step two, iterative updating, which specifically comprises the following steps:
Figure BDA0002240141520000126
Figure BDA0002240141520000127
wherein:
Figure BDA0002240141520000128
step k-1, category
Figure BDA0002240141520000129
The ith element in
Figure BDA00022401415200001210
Step k-1, second class
Figure BDA00022401415200001211
The j (th) element of (1)
N1The th categoryNumber of middle element
N2: the second class
Figure BDA00022401415200001213
Number of middle element
Figure BDA00022401415200001214
Step k, category
Figure BDA00022401415200001215
Class center of
Step k second class
Figure BDA00022401415200001217
Class center of
Figure BDA0002240141520000131
Figure BDA0002240141520000132
Wherein:
Figure BDA0002240141520000133
step k value of the th category element set
Figure BDA0002240141520000134
Step k value of the second class element set
Figure BDA0002240141520000135
The kth step value of the category judgment threshold value
k: iterative control parameter
Thirdly, iterative judgment, specifically comprising:
adding 1 to the iteration control parameter K, returning to the second step for re-iteration until the difference between two adjacent iteration values is less than thousandths, wherein the iteration control parameter K is equal to K, and obtaining the nth signal difference sequence delta SnSaid category center of the th category
Figure BDA0002240141520000136
And a class center of the second class
4. Finding the best projection factor
Figure BDA0002240141520000138
Wherein:
W＝[ΔSn-μ1][ΔSn-μ2]T: the nth signal differential sequence Delta SnProjected value of
5. Calculating the cumulative amount of window projection
Figure BDA0002240141520000139
6. Calculating impulse noise detection threshold
Figure BDA00022401415200001310
7. Detecting impulse noise
And detecting the PLC channel impulse noise according to the projection cumulant property. The method specifically comprises the following steps: if the Kth window projects the cumulative amount HKSatisfies the judgment condition HK≥e0Detecting impulse noise at the Kth point of the signal sequence S; otherwise, impulse noise is not detected. Wherein e is0Is an impulse noise detection threshold.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is simple because the system corresponds to the method disclosed by the embodiment, and the relevant part can be referred to the method part for description.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core idea of the present invention, and to those skilled in the art with variations in the specific embodiments and applications of the invention.

Claims (5)

1, PLC channel impulse noise detection method using projection accumulation, characterized by comprising:
step 1, inputting an actually measured PLC signal sequence S;
and 2, detecting the PLC channel impulse noise according to the projection cumulant property. The method specifically comprises the following steps: if the Kth window projects the cumulative amount HKSatisfies the judgment condition HK≥e0Detecting impulse noise at the Kth point of the signal sequence S; otherwise, impulse noise is not detected. Wherein e is0Is an impulse noise detection threshold.
2. The method of claim 1, wherein prior to step 2, the method further comprises:
step 3, calculating the projection cumulant H of the Kth windowKAnd the impulse noise detection threshold e0。
3. The method of claim 2, wherein step 3 comprises:
step 301, generating the nth signal difference sequence Δ SnThe method specifically comprises the following steps:
ΔSn＝[ΔSn-D,ΔSn-D+1,…,ΔSn,ΔSn+1,…,ΔSn+D]
wherein:
ΔSi＝Si-Si-1: the nth signal differential sequence Delta SnThe ith element [ i ═ n-D, n-D +1, …, n + D]
Si: the ith element in the signal sequence SIf the element SiSubscript i of>N or i<1, then Si＝0。
S＝[S1，S2，…，SN]The length of the signal sequence is N
Figure FDA0002240141510000011
Length of window
Figure FDA0002240141510000012
Represents the lower rounding of
SNR: signal-to-noise ratio of the signal sequence S
Step 302, iteratively calculating the nth signal difference sequence Δ SnThe category center of (1) is specifically:
, initializing iteration, specifically:
Figure FDA0002240141510000021
Figure FDA0002240141510000022
wherein:
maxΔSn: the nth signal differential sequence Delta SnMaximum element of (2)
minΔSn: the nth signal differential sequence Delta SnMinimum element of (2)
Figure FDA0002240141510000023
Initialization value of class center
Figure FDA0002240141510000024
Initialization value of second class center
Figure FDA0002240141510000025
Figure FDA0002240141510000026
k＝0
Wherein:
Figure FDA0002240141510000027
initialization value of Category element set
Figure FDA0002240141510000028
Initialization value of second category element set
Figure FDA0002240141510000029
Initialization value of class judgment threshold value
k: iterative control parameter
And step two, iterative updating, which specifically comprises the following steps:
Figure FDA00022401415100000210
wherein:
Figure FDA00022401415100000212
step k-1, category
Figure FDA00022401415100000213
The ith element in
Figure FDA00022401415100000214
Step k-1 of the second classClip for fixing
Figure FDA00022401415100000215
The j (th) element of (1)
N1The th category
Figure FDA00022401415100000216
Number of middle element
N2: the second classNumber of middle element
Figure FDA00022401415100000218
Step k, category
Figure FDA00022401415100000219
Class center of
Figure FDA00022401415100000220
Step k second classClass center of
Figure FDA0002240141510000031
Figure FDA0002240141510000032
Wherein:
Figure FDA0002240141510000033
step k value of the th category element set
Figure FDA0002240141510000034
Step k value of the second class element set
Figure FDA0002240141510000035
The kth step value of the category judgment threshold value
k: iterative control parameter
Thirdly, iterative judgment, specifically comprising:
adding 1 to the iteration control parameter K, returning to the second step for re-iteration until the difference between two adjacent iteration values is less than thousandths, wherein the iteration control parameter K is equal to K, and obtaining the nth signal difference sequence delta SnSaid category center of the th category
Figure FDA0002240141510000036
And a class center of the second class
Figure FDA0002240141510000037
Step 303, obtaining the nth signal difference sequence Δ SnThe optimal projection factor χ specifically is:
Figure FDA0002240141510000038
wherein:
W＝[ΔSn-μ1][ΔSn-μ2]T: the nth signal differential sequence Delta SnProjected value of
Step 304, calculating the cumulative projection H of the Kth windowKThe method specifically comprises the following steps:
Figure FDA0002240141510000039
step 305, obtaining the operation state judgment threshold e0The method specifically comprises the following steps:
Figure FDA00022401415100000310
the system for detecting impulse noise of PLC channel by using projection accumulation amount is 4, , which is characterized by comprising:
the acquisition module inputs an actually measured PLC signal sequence S;
and the detection module is used for detecting the PLC channel impulse noise according to the projection cumulant property. The method specifically comprises the following steps: if the Kth window projects the cumulative amount HKSatisfies the judgment condition HK≥e0Detecting impulse noise at the Kth point of the signal sequence S; otherwise, impulse noise is not detected. Wherein e is0Is an impulse noise detection threshold.
5. The system of claim 4, further comprising:
a calculation module for calculating the Kth window projection cumulant HKAnd the impulse noise detection threshold e0。
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