CN111830405A - Load switch event detection method and system by using frequency difference - Google Patents

Load switch event detection method and system by using frequency difference Download PDF

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CN111830405A
CN111830405A CN202010671056.5A CN202010671056A CN111830405A CN 111830405 A CN111830405 A CN 111830405A CN 202010671056 A CN202010671056 A CN 202010671056A CN 111830405 A CN111830405 A CN 111830405A
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翟明岳
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Guangdong University of Petrochemical Technology
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/327—Testing of circuit interrupters, switches or circuit-breakers
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00032—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for
    • H02J13/00036—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for the elements or equipment being or involving switches, relays or circuit breakers

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Abstract

The embodiment of the invention discloses a load switch event detection method and a system by using frequency difference, wherein the method comprises the following steps: step 101, acquiring a signal sequence S acquired according to a time sequence; 102, generating N signal first-order difference sequences; step 103, generating N signal second-order difference sequences; 104, calculating a DFT transformation coefficient vector; step 105, obtaining a normalized DFT transform coefficient vector; step 106, obtaining N frequency difference quantities; step 107, calculating an event judgment threshold; step 108 determines a load switch event.

Description

Load switch event detection method and system by using frequency difference
Technical Field
The invention relates to the field of electric power, in particular to a load switch event detection method and system.
Background
With the development of smart grids, the analysis of household electrical loads becomes more and more important. Through the analysis of the power load, a family user can obtain the power consumption information of each electric appliance and a refined list of the power charge in time; the power department can obtain more detailed user power utilization information, can improve the accuracy of power utilization load prediction, and provides a basis for overall planning for the power department. Meanwhile, the power utilization behavior of the user can be obtained by utilizing the power utilization information of each electric appliance, so that the method has guiding significance for the study of household energy consumption evaluation and energy-saving strategies.
The current electric load decomposition is mainly divided into an invasive load decomposition method and a non-invasive load decomposition method. The non-invasive load decomposition method does not need to install monitoring equipment on internal electric equipment of the load, and can obtain the load information of each electric equipment only according to the total information of the electric load. The non-invasive load decomposition method has the characteristics of less investment, convenience in use and the like, so that the method is suitable for decomposing household load electricity.
In the non-invasive load decomposition algorithm, the detection of the switching event of the electrical equipment is the most important link. The initial event detection takes the change value of the active power P as the judgment basis of the event detection, and is convenient and intuitive. This is because the power consumed by any one of the electric devices changes, and the change is reflected in the total power consumed by all the electric devices. Besides the need to set a reasonable threshold for the power variation value, this method also needs to solve the problem of the event detection method in practical application: a large peak (for example, a motor starting current is much larger than a rated current) appears in an instantaneous power value at the starting time of some electric appliances, so that an electric appliance steady-state power change value is inaccurate, and the judgment of a switching event is influenced, and the peak is actually pulse noise; moreover, the transient process of different household appliances is long or short (the duration and the occurrence frequency of impulse noise are different greatly), so that the determination of the power change value becomes difficult; due to the fact that the active power changes suddenly when the quality of the electric energy changes (such as voltage drop), misjudgment is likely to happen. The intensity of (impulse) noise is large and background noise has a large impact on the correct detection of switching events.
Load switching events that are now commonly used are often determined using changes in power data: when the power change value exceeds a preset threshold value, a load switch event is considered to occur. This approach, while simple and easy to implement, results in a significant drop in the accuracy of the switching event detection due to the impulse noise and the common use of non-linear loads.
Therefore, in the switching event detection process, how to improve the switching event detection accuracy is very important. Load switch event detection is the most important step in energy decomposition, and can detect the occurrence of an event and determine the occurrence time of the event. However, the accuracy of the detection of the switching event is greatly affected by noise in the power signal (power sequence), and particularly, impulse noise generally exists in the power signal, which further affects the detection accuracy. Therefore, it is currently a very important task to effectively improve the detection accuracy of the load switch event.
Disclosure of Invention
Load switching events that are now commonly used are often determined using changes in power data: when the power change value exceeds a preset threshold value, a load switch event is considered to occur. This approach, while simple and easy to implement, results in a significant drop in the accuracy of the switching event detection due to the impulse noise and the common use of non-linear loads.
The invention aims to provide a load switch event detection method and system by using frequency difference, the proposed method utilizes the transient power signal difference generated when different loads are switched, and distinguishes different switch events of different loads and abnormal events caused by abnormal power signals by using the property of frequency difference. The method has good switching event detection performance and is simple in calculation.
In order to achieve the purpose, the invention provides the following scheme:
a method of load switch event detection using a frequency difference amount, comprising:
step 101, acquiring a signal sequence S acquired according to a time sequence;
step 102 generates N signal first-order difference sequences, specifically: the nth signal first order difference sequence is recorded as
Figure BDA0002582314070000021
The value of the ith element is s|i+1|N-si(ii) a Wherein, i is an element signal, and the value range of i is 1, ·, N; n is a sequence number of the difference sequence, and the value range of N is 1,2, ·, N; n is the length of the signal sequence S; siIs the ith element of the signal sequence S; s|i+1|NIs the | i +1| > th of the signal sequence SNAn element; i +1| non-woven hairNRepresenting the remainder operation modulo N;
step 103 generates N second-order difference sequences of signals, specifically: the nth signal second order difference sequence is recorded as
Figure BDA0002582314070000022
The value of the ith element is s|i+2|N-si(ii) a Wherein s is|i+2|NIs the | i +2 < th > of the signal sequence SNAn element;
step 104, calculating a DFT transform coefficient vector, specifically: the nth signal first order difference sequence
Figure BDA0002582314070000023
The DFT transform coefficient vector of
Figure BDA0002582314070000024
The formula is obtained as
Figure BDA0002582314070000025
The nth second order difference sequence of the signal
Figure BDA0002582314070000026
The DFT transform coefficient vector of
Figure BDA0002582314070000027
The formula is obtained as
Figure BDA0002582314070000028
Step 105 finds a normalized DFT transform coefficient vector, specifically: the nth signal first order difference sequence
Figure BDA0002582314070000029
DFT transform coefficient vector of
Figure BDA00025823140700000210
Is normalized as the DFT transform coefficient vector
Figure BDA00025823140700000211
The calculation formula is
Figure BDA00025823140700000212
The nth second order difference sequence of the signal
Figure BDA00025823140700000213
DFT transform coefficient vector of
Figure BDA00025823140700000214
Is normalized as the DFT transform coefficient vector
Figure BDA00025823140700000215
The calculation formula is
Figure BDA00025823140700000216
Step 106, obtaining N frequency differences, specifically: the nth frequency difference is recorded as HnThe calculation formula isWherein,
Figure BDA00025823140700000218
for the first order difference sequence of the signal
Figure BDA00025823140700000219
The center frequency of (d);
Figure BDA00025823140700000220
for the second order difference sequence of the signal
Figure BDA00025823140700000221
The center frequency of (d); d0Is a J difference factor which is calculated by the formula
Figure BDA00025823140700000222
Wherein, InIs a full 1 column vector of dimension n; Δ f is the sampling frequency of the signal sequence;
step 107, calculating an event judgment threshold, specifically: the event judgment threshold is recorded as0The calculation formula is
Figure BDA00025823140700000223
Figure BDA00025823140700000224
Step 108, judging a load switch event, specifically: if the nth frequency difference HnGreater than or equal to the event judgment threshold0Detecting a load switch event at the nth point of the signal sequence; otherwise, no load switch event is detected.
A load switch event detection system utilizing a frequency delta quantity, comprising:
the module 201 acquires a signal sequence S acquired in time sequence;
the module 202 generates N first-order difference sequences of signals, specifically: the nth signal first order difference sequence is recorded as
Figure BDA0002582314070000031
The value of the ith element is s|i+1|N-si(ii) a Wherein, i is an element signal, and the value range of i is 1, ·, N; n is a sequence number of the difference sequence, and the value range of N is 1,2, ·, N; n is the length of the signal sequence S; siIs the ith element of the signal sequence S; s|i+1|NIs the | i +1| > th of the signal sequence SNAn element; i +1| non-woven hairNRepresenting the remainder operation modulo N;
the module 203 generates N second-order differential sequences of signals, specifically: the nth signal second order difference sequence is recorded as
Figure BDA0002582314070000032
The value of the ith element is s|i+2|N-si(ii) a Wherein s is|i+2|NIs the | i +2 < th > of the signal sequence SNAn element;
the module 204 calculates a DFT transform coefficient vector, specifically: the nth signal first order difference sequence
Figure BDA0002582314070000033
The DFT transform coefficient vector of
Figure BDA0002582314070000034
The formula is obtained as
Figure BDA0002582314070000035
The nth second order difference sequence of the signal
Figure BDA0002582314070000036
The DFT transform coefficient vector of
Figure BDA0002582314070000037
The formula is obtained as
Figure BDA0002582314070000038
The module 205 finds a normalized DFT transform coefficient vector, specifically: the nth signal first order difference sequence
Figure BDA0002582314070000039
DFT transform coefficient vector of
Figure BDA00025823140700000310
Is normalized as the DFT transform coefficient vector
Figure BDA00025823140700000311
The calculation formula is
Figure BDA00025823140700000312
The nth second order difference sequence of the signal
Figure BDA00025823140700000313
DFT transform coefficient vector of
Figure BDA00025823140700000314
Is normalized as the DFT transform coefficient vector
Figure BDA00025823140700000315
The calculation formula is
Figure BDA00025823140700000316
The module 206 calculates N frequency differences, specifically: the nth frequency difference is recorded as HnThe calculation formula is
Figure BDA00025823140700000317
Wherein,
Figure BDA00025823140700000318
for the first order difference sequence of the signal
Figure BDA00025823140700000319
The center frequency of (d);
Figure BDA00025823140700000320
for the second order difference sequence of the signal
Figure BDA00025823140700000321
The center frequency of (d); d0Is a J difference factor which is calculated by the formula
Figure BDA00025823140700000322
Wherein, InIs a full 1 column vector of dimension n; Δ f is the sampling frequency of the signal sequence;
the module 207 calculates an event determination threshold, specifically: the event judgment threshold is recorded as0The calculation formula is
Figure BDA00025823140700000323
Figure BDA00025823140700000324
The module 208 determines a load switch event, specifically: if the nth frequency difference HnGreater than or equal to the event judgment threshold0Detecting a load switch event at the nth point of the signal sequence; otherwise, no load switch event is detected.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
load switching events that are now commonly used are often determined using changes in power data: when the power change value exceeds a preset threshold value, a load switch event is considered to occur. This approach, while simple and easy to implement, results in a significant drop in the accuracy of the switching event detection due to the impulse noise and the common use of non-linear loads.
The invention aims to provide a load switch event detection method and system by using frequency difference, the proposed method utilizes the transient power signal difference generated when different loads are switched, and distinguishes different switch events of different loads and abnormal events caused by abnormal power signals by using the property of frequency difference. The method has good switching event detection performance and is simple in calculation.
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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 used in the embodiments will be briefly described below. It is obvious that the drawings in the following description are only some embodiments of the invention, and that for a person skilled in the art, other drawings can be derived from them without inventive effort.
FIG. 1 is a schematic flow diagram of the process of the present invention;
FIG. 2 is a schematic flow chart of the system of the present invention;
FIG. 3 is a flow chart illustrating an embodiment of the present invention.
Detailed Description
The technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
FIG. 1 is a flow chart of a load switch event detection method using frequency difference
Fig. 1 is a flow chart illustrating a load switch event detection method using frequency difference according to the present invention. As shown in fig. 1, the method for detecting a load switch event by using a frequency difference specifically includes the following steps:
step 101, acquiring a signal sequence S acquired according to a time sequence;
step 102 generates N signal first-order difference sequences, specifically: the nth signal first order difference sequence is recorded as
Figure BDA0002582314070000041
The value of the ith element is s|i+1|N-si(ii) a Wherein, i is an element signal, and the value range of i is 1, ·, N; n is a sequence number of the difference sequence, and the value range of N is 1,2, ·, N; n is the length of the signal sequence S; siIs the ith element of the signal sequence S; s|i+1|NIs the | i +1| > th of the signal sequence SNAn element; i +1| non-woven hairNRepresenting the remainder operation modulo N;
step 103 generates N second-order difference sequences of signals, specifically: the nth signal second order difference sequence is recorded as
Figure BDA0002582314070000042
The value of the ith element is s|i+2|N-si(ii) a Wherein s is|i+2|NIs the | i +2 < th > of the signal sequence SNAn element;
step 104, calculating a DFT transform coefficient vector, specifically: the nth signal first order difference sequence
Figure BDA0002582314070000043
The DFT transform coefficient vector of
Figure BDA0002582314070000044
The formula is obtained as
Figure BDA0002582314070000045
The nth second order difference sequence of the signal
Figure BDA0002582314070000046
The DFT transform coefficient vector of
Figure BDA0002582314070000047
The formula is obtained as
Figure BDA0002582314070000048
Step 105 finds a normalized DFT transform coefficient vector, specifically: the nth signal first order difference sequence
Figure BDA0002582314070000049
DFT transform coefficient vector of
Figure BDA00025823140700000410
Is normalized as the DFT transform coefficient vector
Figure BDA00025823140700000411
The calculation formula is
Figure BDA00025823140700000412
The nth second order difference sequence of the signal
Figure BDA00025823140700000413
DFT transform coefficient vector of
Figure BDA00025823140700000414
Is normalized as the DFT transform coefficient vector
Figure BDA00025823140700000415
The calculation formula is
Figure BDA00025823140700000416
Step 106, obtaining N frequency differences, specifically: the nth frequency difference is recorded as HnThe calculation formula is
Figure BDA0002582314070000051
Wherein,
Figure BDA0002582314070000052
for the first order difference sequence of the signal
Figure BDA0002582314070000053
The center frequency of (d);
Figure BDA0002582314070000054
for the second order difference sequence of the signal
Figure BDA0002582314070000055
The center frequency of (d); d0Is a J difference factor which is calculated by the formula
Figure BDA0002582314070000056
Wherein, InIs a full 1 column vector of dimension n; Δ f is the sampling frequency of the signal sequence;
step 107, calculating an event judgment threshold, specifically: the event judgment threshold is recorded as0The calculation formula is
Figure BDA0002582314070000057
Figure BDA0002582314070000058
Step 108, judging a load switch event, specifically: if the nth frequency difference HnGreater than or equal to the event judgment threshold0Detecting a load switch event at the nth point of the signal sequence; otherwise, no load switch event is detected.
FIG. 2 is a schematic diagram of a load switch event detection system using frequency difference
Fig. 2 is a schematic diagram of a load switch event detection system using frequency difference according to the present invention. As shown in fig. 2, the load switch event detection system using the frequency difference amount includes the following structure:
the module 201 acquires a signal sequence S acquired in time sequence;
the module 202 generates N first-order difference sequences of signals, specifically: the nth signal first order difference sequence is recorded as
Figure BDA0002582314070000059
The value of the ith element is s|i+1|N-si(ii) a Wherein, i is an element signal, and the value range of i is 1, ·, N; n is a sequence number of the difference sequence, and the value range of N is 1,2, ·, N; n is the length of the signal sequence S; siIs the ith element of the signal sequence S; s|i+1|NIs the | i +1| > th of the signal sequence SNAn element; i +1| non-woven hairNRepresenting the remainder operation modulo N;
the module 203 generates N second-order differential sequences of signals, specifically: the nth signal second order difference sequence is recorded as
Figure BDA00025823140700000510
The value of the ith element is s|i+2|N-si(ii) a Wherein s is|i+2|NIs the | i +2 < th > of the signal sequence SNAn element;
the module 204 calculates a DFT transform coefficient vector, specifically: the nth signal first order difference sequence
Figure BDA00025823140700000511
The DFT transform coefficient vector of
Figure BDA00025823140700000512
The formula is obtained as
Figure BDA00025823140700000513
The nth second order difference sequence of the signal
Figure BDA00025823140700000514
The DFT transform coefficient vector of
Figure BDA00025823140700000515
The formula is obtained as
Figure BDA00025823140700000516
The module 205 finds a normalized DFT transform coefficient vector, specifically: the nth signal first order difference sequence
Figure BDA00025823140700000517
DFT transform coefficient vector of
Figure BDA00025823140700000518
Is normalized as the DFT transform coefficient vector
Figure BDA00025823140700000519
The calculation formula is
Figure BDA00025823140700000520
The nth second order difference sequence of the signal
Figure BDA00025823140700000521
DFT transform coefficient vector of
Figure BDA00025823140700000522
Is normalized as the DFT transform coefficient vector
Figure BDA00025823140700000523
The calculation formula is
Figure BDA00025823140700000524
The module 206 calculates N frequency differences, specifically: the nth frequency difference is recorded as HnThe calculation formula is
Figure BDA00025823140700000525
Wherein,
Figure BDA00025823140700000526
for the first order difference sequence of the signal
Figure BDA00025823140700000527
The center frequency of (d);
Figure BDA00025823140700000528
for the second order difference sequence of the signal
Figure BDA00025823140700000529
The center frequency of (d); d0Is a J difference factor which is calculated by the formula
Figure BDA00025823140700000530
Wherein, InIs a full 1 column vector of dimension n; Δ f is the sampling frequency of the signal sequence;
the module 207 calculates an event determination threshold, specifically: the event judgment threshold is recorded as0The calculation formula is
Figure BDA0002582314070000061
Figure BDA0002582314070000062
The module 208 determines a load switch event, specifically: if the nth frequency difference HnGreater than or equal to the event judgment threshold0Detecting a load switch event at the nth point of the signal sequence; otherwise, no load switch event is detected.
The following provides an embodiment for further illustrating the 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:
step 301, acquiring a signal sequence S acquired according to a time sequence;
step 302 generates N signal first order difference sequences, specifically: the nth signal first order difference sequence is recorded as
Figure BDA0002582314070000063
The value of the ith element is s|i+1|N-si(ii) a WhereinI is an element signal, and the value range of i is 1, ·, N; n is a sequence number of the difference sequence, and the value range of N is 1,2, ·, N; n is the length of the signal sequence S; siIs the ith element of the signal sequence S; s|i+1|NIs the | i +1| > th of the signal sequence SNAn element; i +1| non-woven hairNRepresenting the remainder operation modulo N;
step 303 generates N second order differential sequences of signals, specifically: the nth signal second order difference sequence is recorded as
Figure BDA0002582314070000064
The value of the ith element is s|i+2|N-si(ii) a Wherein s is|i+2|NIs the | i +2 < th > of the signal sequence SNAn element;
step 304, calculating a DFT transform coefficient vector, specifically: the nth signal first order difference sequence
Figure BDA0002582314070000065
The DFT transform coefficient vector of
Figure BDA0002582314070000066
The formula is obtained as
Figure BDA0002582314070000067
The nth second order difference sequence of the signal
Figure BDA0002582314070000068
The DFT transform coefficient vector of
Figure BDA0002582314070000069
The formula is obtained as
Figure BDA00025823140700000610
Step 305 finds a normalized DFT transform coefficient vector, specifically: the nth signal first order difference sequence
Figure BDA00025823140700000611
DFT transform system ofNumber vector
Figure BDA00025823140700000612
Is normalized as the DFT transform coefficient vector
Figure BDA00025823140700000613
The calculation formula is
Figure BDA00025823140700000614
The nth second order difference sequence of the signal
Figure BDA00025823140700000615
DFT transform coefficient vector of
Figure BDA00025823140700000616
Is normalized as the DFT transform coefficient vector
Figure BDA00025823140700000617
The calculation formula is
Figure BDA00025823140700000618
Step 306, obtaining N frequency differences, specifically: the nth frequency difference is recorded as HnThe calculation formula is
Figure BDA00025823140700000619
Wherein,
Figure BDA00025823140700000620
for the first order difference sequence of the signal
Figure BDA00025823140700000621
The center frequency of (d);
Figure BDA00025823140700000622
for the second order difference sequence of the signal
Figure BDA00025823140700000623
The center frequency of (d); d0Is a J difference factor whichIs calculated by the formula
Figure BDA00025823140700000624
Wherein, InIs a full 1 column vector of dimension n; Δ f is the sampling frequency of the signal sequence;
step 307, obtaining an event judgment threshold, specifically: the event judgment threshold is recorded as0The calculation formula is
Figure BDA00025823140700000625
Figure BDA00025823140700000626
Step 308, judging a load switch event, specifically: if the nth frequency difference HnGreater than or equal to the event judgment threshold0Detecting a load switch event at the nth point of the signal sequence; otherwise, no load switch event is detected.
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 concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.

Claims (2)

1. A method for load switch event detection using a frequency difference, comprising:
step 101, acquiring a signal sequence S acquired according to a time sequence;
step 102 generates N signal first-order difference sequences, specifically: the nth signal first order difference sequence is recorded as
Figure FDA0002582314060000011
The value of the ith element thereof is
Figure FDA0002582314060000012
Wherein, i is an element signal, and the value range of i is 1, ·, N; n is a sequence number of the difference sequence, and the value range of N is 1,2, ·, N; n is the length of the signal sequence S; siIs the ith element of the signal sequence S;
Figure FDA0002582314060000013
is the | i +1| > th of the signal sequence SNAn element; i +1| non-woven hairNRepresenting the remainder operation modulo N;
step 103 generates N second-order difference sequences of signals, specifically: the nth signal second order difference sequence is recorded as
Figure FDA0002582314060000014
The value of the ith element thereof is
Figure FDA0002582314060000015
Wherein,
Figure FDA0002582314060000016
is the | i +2 < th > of the signal sequence SNAn element;
step 104, calculating a DFT transform coefficient vector, specifically: the nth signal first order difference sequence
Figure FDA0002582314060000017
The DFT transform coefficient vector of
Figure FDA0002582314060000018
The formula is obtained as
Figure FDA0002582314060000019
The nth second order difference sequence of the signal
Figure FDA00025823140600000110
The DFT transform coefficient vector of
Figure FDA00025823140600000111
The formula is obtained as
Figure FDA00025823140600000112
Step 105 finds a normalized DFT transform coefficient vector, specifically: the nth signal first order difference sequence
Figure FDA00025823140600000113
DFT transform coefficient vector of
Figure FDA00025823140600000114
Is normalized as the DFT transform coefficient vector
Figure FDA00025823140600000115
The calculation formula is
Figure FDA00025823140600000116
The nth second order difference sequence of the signal
Figure FDA00025823140600000117
DFT transform coefficient vector of
Figure FDA00025823140600000118
Is normalized as the DFT transform coefficient vector
Figure FDA00025823140600000119
The calculation formula is
Figure FDA00025823140600000120
Step 106, obtaining N frequency differences, specifically: the nth frequency difference is recorded as HnThe calculation formula is
Figure FDA00025823140600000121
Wherein,
Figure FDA00025823140600000122
for the first order difference sequence of the signal
Figure FDA00025823140600000123
The center frequency of (d);
Figure FDA00025823140600000124
for the second order difference sequence of the signal
Figure FDA00025823140600000125
The center frequency of (d); d0Is a J difference factor which is calculated by the formula
Figure FDA00025823140600000126
Wherein, InIs a full 1 column vector of dimension n; Δ f is the sampling frequency of the signal sequence;
step 107, calculating an event judgment threshold, specifically: the event judgment threshold is recorded as0The calculation formula is
Figure FDA00025823140600000127
Step 108, judging a load switch event, specifically: if the nth frequency difference HnGreater than or equal to the event judgment threshold0Detecting a load switch event at the nth point of the signal sequence; otherwise, no load switch event is detected.
2. A load switch event detection system that utilizes a frequency difference, comprising:
the module 201 acquires a signal sequence S acquired in time sequence;
the module 202 generates N first-order difference sequences of signals, specifically: the nth signal first order difference sequence is recorded as
Figure FDA00025823140600000128
The value of the ith element thereof is
Figure FDA00025823140600000129
Wherein, i is an element signal, and the value range of i is 1, ·, N; n is a sequence number of the difference sequence, and the value range of N is 1,2, ·, N; n is the length of the signal sequence S; siIs the ith element of the signal sequence S;
Figure FDA0002582314060000021
is the | i +1| > th of the signal sequence SNAn element; i +1| non-woven hairNRepresenting the remainder operation modulo N;
the module 203 generates N second-order differential sequences of signals, specifically: the nth signal second order difference sequence is recorded as
Figure FDA0002582314060000022
The value of the ith element thereof is
Figure FDA0002582314060000023
Wherein,
Figure FDA0002582314060000024
is the | i +2 < th > of the signal sequence SNAn element;
the module 204 calculates a DFT transform coefficient vector, specifically: the nth signal first order difference sequence
Figure FDA0002582314060000025
The DFT transform coefficient vector of
Figure FDA0002582314060000026
The formula is obtained as
Figure FDA0002582314060000027
The nth second order difference sequence of the signal
Figure FDA0002582314060000028
The DFT transform coefficient vector of
Figure FDA0002582314060000029
The formula is obtained as
Figure FDA00025823140600000210
The module 205 finds a normalized DFT transform coefficient vector, specifically: the nth signal first order difference sequence
Figure FDA00025823140600000211
DFT transform coefficient vector of
Figure FDA00025823140600000212
Is normalized as the DFT transform coefficient vector
Figure FDA00025823140600000213
The calculation formula is
Figure FDA00025823140600000214
The nth second order difference sequence of the signal
Figure FDA00025823140600000215
DFT transform coefficient vector of
Figure FDA00025823140600000216
Is normalized as the DFT transform coefficient vector
Figure FDA00025823140600000217
It calculatesIs given by the formula
Figure FDA00025823140600000218
The module 206 calculates N frequency differences, specifically: the nth frequency difference is recorded as HnThe calculation formula is
Figure FDA00025823140600000219
Wherein,
Figure FDA00025823140600000220
for the first order difference sequence of the signal
Figure FDA00025823140600000221
The center frequency of (d);
Figure FDA00025823140600000222
for the second order difference sequence of the signal
Figure FDA00025823140600000223
The center frequency of (d); d0Is a J difference factor which is calculated by the formula
Figure FDA00025823140600000224
Wherein, InIs a full 1 column vector of dimension n; Δ f is the sampling frequency of the signal sequence;
the module 207 calculates an event determination threshold, specifically: the event judgment threshold is recorded as0The calculation formula is
Figure FDA00025823140600000225
The module 208 determines a load switch event, specifically: if the nth frequency difference HnGreater than or equal to the event judgment threshold0Detecting a load switch event at the nth point of the signal sequence; otherwise, no load switch event is detected.
CN202010671056.5A 2020-07-14 2020-07-14 Load switch event detection method and system by using frequency difference Withdrawn CN111830405A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113721103A (en) * 2021-11-01 2021-11-30 广东电网有限责任公司东莞供电局 Online fault diagnosis method and system for high-voltage switch cabinet

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113721103A (en) * 2021-11-01 2021-11-30 广东电网有限责任公司东莞供电局 Online fault diagnosis method and system for high-voltage switch cabinet
CN113721103B (en) * 2021-11-01 2022-02-11 广东电网有限责任公司东莞供电局 Online fault diagnosis method and system for high-voltage switch cabinet

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Application publication date: 20201027