CN114924110A - Electric shock detection system and method based on self-adaptive threshold - Google Patents
Electric shock detection system and method based on self-adaptive threshold Download PDFInfo
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- CN114924110A CN114924110A CN202210255557.4A CN202210255557A CN114924110A CN 114924110 A CN114924110 A CN 114924110A CN 202210255557 A CN202210255557 A CN 202210255557A CN 114924110 A CN114924110 A CN 114924110A
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- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R19/00—Arrangements for measuring currents or voltages or for indicating presence or sign thereof
- G01R19/165—Indicating that current or voltage is either above or below a predetermined value or within or outside a predetermined range of values
- G01R19/16566—Circuits and arrangements for comparing voltage or current with one or several thresholds and for indicating the result not covered by subgroups G01R19/16504, G01R19/16528, G01R19/16533
- G01R19/16571—Circuits and arrangements for comparing voltage or current with one or several thresholds and for indicating the result not covered by subgroups G01R19/16504, G01R19/16528, G01R19/16533 comparing AC or DC current with one threshold, e.g. load current, over-current, surge current or fault current
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Abstract
The invention provides an electric shock detection system and method based on an adaptive threshold, which comprises the following steps: the acquisition module is used for acquiring a first total residual current and a second total residual current of the power distribution network in real time; the first processing module is used for respectively performing wavelet transformation on the first total residual current and the second total residual current to obtain a first low-frequency component and a second low-frequency component and processing the first low-frequency component and the second low-frequency component to obtain a period variable quantity; the statistical module is used for obtaining the average value of the period variable quantity of one period before the first reference point and the extreme value of the wavelet coefficient through statistics; the second processing module is used for processing the average value of the period variation and the extreme value of the wavelet coefficient to obtain an adaptive threshold; and the third processing module is used for processing according to the period variation, the self-adaptive threshold and the out-of-limit threshold to obtain an electric shock detection result. The system and the method have the advantages that the system and the method amplify the fault characteristics by performing wavelet transformation on the total residual current, judge whether the electric shock accident happens according to the period variation and the self-adaptive threshold, and are more accurate and quicker.
Description
Technical Field
The invention relates to the technical field of electric shock detection, in particular to an electric shock detection system and method based on an adaptive threshold.
Background
When a low-voltage distribution network is subjected to an electric shock accident, the total residual current is suddenly changed, but is generally weak in the distribution network, and the amplitude of the total residual current is small and ranges from dozens of milliamperes to several amperes. Therefore, the sudden change characteristics of the fault current are often not obvious enough, and the sudden change characteristics are easily mixed with the tiny sudden change caused by line interference and are difficult to distinguish, so that great difficulty is brought to electric shock detection work.
Meanwhile, the traditional earth leakage protection device is started by a threshold value method, and the threshold value is required to be readjusted in different installation occasions and is inconvenient to use. Therefore, after an electric shock accident occurs, the sudden change current meter is not obvious enough, the threshold value is not flexible enough in the starting process, and the like, and a reasonable judgment method is needed to improve the accuracy of electric shock accident judgment.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides an electric shock detection system based on an adaptive threshold, which comprises:
the acquisition module is used for acquiring a first total residual current corresponding to a first reference point and a second total residual current corresponding to a second reference point of a power distribution network in real time;
the first processing module is connected with the acquisition module and used for respectively performing wavelet transformation on the first total residual current and the second total residual current to obtain a first low-frequency component corresponding to the first reference point and a second low-frequency component corresponding to the second reference point, and processing according to the first low-frequency component and the second low-frequency component to obtain a periodic variable quantity;
the statistic module is used for counting to obtain a period variable quantity average value of a period before the first reference point and a wavelet coefficient extreme value of the period before the first reference point;
the second processing module is connected with the statistical module and used for processing according to the average value of the period variation and the extreme value of the wavelet coefficient to obtain a self-adaptive threshold;
and the third processing module is respectively connected with the first processing module and the second processing module and used for processing according to the period variation, the self-adaptive threshold and a preset out-of-limit threshold to obtain a corresponding electric shock detection result.
Preferably, the first processing module includes:
the first acquisition unit is used for acquiring a period number between the first reference point and the second reference point and a sampling point number corresponding to one period;
the first processing unit is connected with the first acquisition unit and used for performing wavelet transformation on the first total residual current to obtain the first low-frequency component corresponding to the first reference point and performing wavelet transformation on the second total residual current based on the periodicity and the number of sampling points to obtain the second low-frequency component corresponding to the second reference point;
and the second processing unit is connected with the first processing unit and used for processing according to the first low-frequency component and the second low-frequency component to obtain the period variable quantity.
Preferably, the period variation is obtained by processing according to the following calculation formula:
wherein the content of the first and second substances,
Δ c (i) representing the period variation;
i represents a variable parameter;
n represents the number of cycles;
l represents the number of sampling points.
Preferably, the average value of the period variation is obtained by processing according to the following calculation formula:
wherein the content of the first and second substances,
λ c represents the average value of the period variation;
l represents the number of sampling points;
N P representing a length between the first reference point and the second reference point;
i represents a variable parameter;
Δ c representing the amount of cyclic variation.
Preferably, the wavelet coefficient extremum is obtained by processing according to the following calculation formula:
ε c ＝max[|Δ c (2*L-N P )|,...,|Δ c (L-N P )|]
wherein the content of the first and second substances,
ε c representing the wavelet coefficient extremum;
l represents the number of sampling points;
N P representing the length between the first reference point and the second reference point;
Δ c representing the amount of cyclic variation.
Preferably, the adaptive threshold is obtained by processing according to the following calculation formula:
λ s_c ＝λ c +K ε_c *ε c
wherein the content of the first and second substances,
λ s_c representing the adaptive threshold;
λ c representing the average value of the period variation;
ε c representing the wavelet coefficient extremum;
K ε_c a maximum utilization coefficient of a low frequency component is represented.
Preferably, the third processing module includes:
the third processing unit is used for comparing the period variation with the self-adaptive threshold, controlling the second processing module to stop running when the period variation is larger than the self-adaptive threshold, and counting the corresponding out-of-limit times in a waiting time;
the fourth processing unit is connected with the third processing unit and used for comparing the out-of-limit times with the out-of-limit threshold and generating a contact detection result representing the occurrence of electric shock accidents when the out-of-limit times are larger than the out-of-limit threshold;
and generating a contact detection result representing that no electric shock accident occurs when the number of times of the threshold crossing is not greater than the threshold crossing value, and controlling the second processing module to operate again.
Preferably, an electric shock detection method based on an adaptive threshold is applied to the electric shock detection system, and specifically includes the following steps:
step S1, collecting a first total residual current corresponding to a first reference point and a second total residual current corresponding to a second reference point of a power distribution network in real time, and counting to obtain a period variable quantity average value of a period before the first reference point and a wavelet coefficient extreme value of the period before the first reference point;
step S2, performing wavelet transformation on the first total residual current and the second total residual current to obtain a first low-frequency component corresponding to the first reference point and a second low-frequency component corresponding to the second reference point, and processing according to the first low-frequency component and the second low-frequency component to obtain a periodic variation;
step S3, processing according to the average value of the period variation and the extreme value of the wavelet coefficient to obtain an adaptive threshold;
and step S4, processing according to the period variation, the adaptive threshold and a preset out-of-limit threshold to obtain a corresponding electric shock detection result.
Preferably, the step S2 includes:
step S21, collecting a period number between the first reference point and the second reference point and a sampling point number corresponding to one period;
step S22, performing wavelet transform on the first total residual current to obtain the first low frequency component corresponding to the first reference point, and performing wavelet transform on the second total residual current based on the number of cycles and the number of sampling points to obtain the second low frequency component corresponding to the second reference point;
step S23, processing the first low frequency component and the second low frequency component to obtain the period variation.
Preferably, the step S4 includes:
step S41, determining whether the period variation is greater than the adaptive threshold:
if yes, counting corresponding out-of-limit times in a waiting time and turning to the step S42;
if not, returning to the step S1;
step S42, determining whether the number of times of crossing is greater than the threshold value:
if yes, generating a contact detection result for representing the occurrence of the electric shock accident and quitting;
if not, the process returns to the step S1.
The technical scheme has the following advantages or beneficial effects: the system and the method amplify the fault characteristics by performing wavelet transformation on the total residual current, calculate the period variation according to the low-frequency components of the two reference points, and compare the period variation with the self-adaptive threshold to judge whether the electric shock accident occurs, so that the protection action is more accurate and rapid.
Drawings
FIG. 1 is a schematic diagram of the system in accordance with the preferred embodiment of the present invention;
FIG. 2 is a flow chart of the steps of the method according to the preferred embodiment of the present invention;
FIG. 3 is a flowchart illustrating the detailed procedure of step S2 according to the preferred embodiment of the present invention;
FIG. 4 is a flowchart illustrating the step S4 according to the preferred embodiment of the present invention.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments. The present invention is not limited to the embodiment, and other embodiments may be included in the scope of the present invention as long as the gist of the present invention is satisfied.
In view of the above problems in the prior art, there is provided in a preferred embodiment of the present invention an adaptive threshold based shock detection system, as shown in fig. 1, comprising:
the acquisition module 1 is used for acquiring a first total residual current corresponding to a first reference point and a second total residual current corresponding to a second reference point of a power distribution network in real time;
the first processing module 2 is connected with the acquisition module 1 and is used for respectively performing wavelet transformation on the first total residual current and the second total residual current to obtain a first low-frequency component corresponding to the first reference point and a second low-frequency component corresponding to the second reference point, and processing according to the first low-frequency component and the second low-frequency component to obtain a periodic variation;
a statistical module 3, configured to statistically obtain a mean value of a period variation of a period before the first reference point and a wavelet coefficient extremum of the period before the first reference point;
the second processing module 4 is connected with the statistical module 3 and is used for processing according to the average value of the period variation and the extreme value of the wavelet coefficient to obtain a self-adaptive threshold;
and the third processing module 5 is respectively connected with the first processing module 2 and the second processing module 4 and is used for processing according to the period variation, the self-adaptive threshold and a preset out-of-limit threshold to obtain a corresponding electric shock detection result.
Specifically, in this embodiment, in order to amplify the fault feature, wavelet transform is performed on the first total residual current and the second total residual current based on a maratt algorithm to obtain a corresponding first low-frequency component and a corresponding second low-frequency component, the first low-frequency component and the second low-frequency component are further processed to obtain a period variation between the first low-frequency component and the second low-frequency component, so that the variation of the low-frequency component waveform is amplified to be a variation of the period variation, and under a normal operation condition, the period variation of the low-frequency component generally fluctuates around zero, and only when a disturbance or an electric shock accident occurs, a sudden change occurs, so that the detection of the original total residual current sudden change in the conventional method is finally converted into the detection of a waveform sudden change, so that in addition to amplifying the fault feature, the problem that the conventional electric shock detection method has a fault protection dead zone can be eliminated, meanwhile, the protection action is more accurate and rapid.
Specifically, in this embodiment, the adaptive threshold and the period variation change amount change correspondingly with changes of the first reference point and the second reference point, that is, the calculation of the adaptive threshold and the period variation amount are both real-time calculation processes, so that the calculated adaptive threshold has strong sensitivity to changes of the operation state of the power distribution network line, and can be adjusted correspondingly in real time according to the operation state of the line.
Preferably, when the total residual current in the line gradually increases with the increase of the load, the value of the period variation is also set to a higher level, and at this time, the adaptive threshold can be adjusted in real time according to the waveform data of the period variation, so as to correspondingly increase the value of the adaptive threshold, thereby avoiding the occurrence of misjudgment.
Specifically, in this embodiment, a spacer is disposed between the first reference point and the second reference point, the spacer is close to a failure point of an electric shock accident, the periodic variation of the low frequency component may oscillate, and the influence of the oscillation is avoided by setting the spacer.
Preferably, the first reference point and the second reference point are located on a current waveform, and the number of cycles of the current waveform between the first reference point and the second reference point is the number of cycles of the current waveform.
In a preferred embodiment of the present invention, the first processing module 2 comprises:
a first collecting unit 21, configured to collect a period number between the first reference point and the second reference point and a sampling point number corresponding to one period;
the first processing unit 22 is connected with the first acquisition unit 21 and is used for performing wavelet transformation on the first total residual current to obtain a first low-frequency component corresponding to the first reference point and performing wavelet transformation on the second total residual current based on the periodicity and the number of sampling points to obtain a second low-frequency component corresponding to the second reference point;
and the second processing unit 23 is connected to the first processing unit 22 and configured to obtain the period variation according to the processing of the first low-frequency component and the second low-frequency component.
In a preferred embodiment of the present invention, the period variation is obtained by processing according to the following calculation formula:
wherein the content of the first and second substances,
Δ c (i) represents a period variation amount;
i represents a variable parameter;
n represents the number of cycles;
l represents the number of sample points.
In a preferred embodiment of the present invention, the average value of the period variation is obtained by the following calculation formula:
wherein the content of the first and second substances,
λ c represents the average value of the period variation;
l represents the number of sampling points;
N P representing a length between the first reference point and the second reference point;
i denotes a variable parameter.
In a preferred embodiment of the present invention, the wavelet coefficient extremum is obtained by processing according to the following calculation formula:
ε c ＝max[|Δ c (2*L-N P )|,...,|Δ c (L-N P )|]
wherein the content of the first and second substances,
ε c representing wavelet coefficient extreme values;
l represents the number of sampling points;
N P indicating the length between the first reference point and the second reference point.
In a preferred embodiment of the present invention, the adaptive threshold is obtained by processing according to the following calculation formula:
λ s_c ＝λ c +K ε_c *ε c
wherein, the first and the second end of the pipe are connected with each other,
λ s_c represents an adaptive threshold;
λ c represents the average value of the period variation;
ε c representing wavelet coefficient extreme values;
K ε_c a maximum utilization coefficient of a low frequency component is represented.
In a preferred embodiment of the present invention, the third processing module 5 includes:
a third processing unit 51, configured to compare the period variation with the adaptive threshold, control the second processing module to stop operating when the period variation is greater than the adaptive threshold, and count corresponding number of times of violation in a waiting time;
the fourth processing unit 52 is connected with the third processing unit 51 and used for comparing the out-of-limit times with the out-of-limit threshold and generating a contact detection result representing the occurrence of the electric shock accident when the out-of-limit times are greater than the out-of-limit threshold;
and when the number of times of exceeding the limit is not more than the threshold value of exceeding the limit, generating a contact detection result representing that no electric shock accident occurs, and controlling the second processing module 4 to operate again.
In this embodiment, specifically, when the value of the period variation exceeds the adaptive threshold corresponding to the period variation, namely, the disturbance is judged to occur at the moment, the first out-of-limit time is recorded, meanwhile, the calculation of the self-adaptive threshold value is stopped, the self-adaptive threshold value is kept as the value calculated at the first out-of-limit time until the judgment flow is finished, but the value of the period variable is still calculated in real time and compared with the self-adaptive threshold, if the number of times of exceeding the threshold exceeds the corresponding threshold within the waiting time after the first threshold-crossing time, judging that the electric shock accident occurs at the moment, outputting a fault starting signal and generating a contact detection result representing the occurrence of the electric shock accident, if the number of the out-of-limit times in the waiting time does not reach the out-of-limit threshold value, the out-of-limit time is cleared, a fault judgment program is skipped, the normal monitoring state is returned, and the calculation of the self-adaptive threshold value is restarted.
In a preferred embodiment of the present invention, an electric shock detection method based on adaptive threshold is applied to the electric shock detection system, as shown in fig. 2, and specifically includes the following steps:
step S1, collecting a first total residual current corresponding to a first reference point and a second total residual current corresponding to a second reference point of a power distribution network in real time, and counting to obtain a periodic variation average value of a period before a first reference point and a wavelet coefficient extreme value of the period before the first reference point;
step S2, respectively performing wavelet transformation on the first total residual current and the second total residual current to obtain a first low-frequency component corresponding to the first reference point and a second low-frequency component corresponding to the second reference point, and processing according to the first low-frequency component and the second low-frequency component to obtain a periodic variation;
step S3, processing according to the average value of the period variation and the extreme value of the wavelet coefficient to obtain an adaptive threshold;
step S4, a corresponding electric shock detection result is obtained according to the period variation, the adaptive threshold and a preset out-of-limit threshold.
In a preferred embodiment of the present invention, as shown in fig. 3, step S2 includes:
step S21, collecting a period number between the first reference point and the second reference point and a sampling point number corresponding to one period;
step S22, performing wavelet transformation on the first total residual current to obtain a first low-frequency component corresponding to the first reference point, and performing wavelet transformation on the second total residual current based on the periodicity and the number of sampling points to obtain a second low-frequency component corresponding to the second reference point;
in step S23, the period variation is obtained by processing according to the first low-frequency component and the second low-frequency component.
In a preferred embodiment of the present invention, as shown in fig. 4, step S4 includes:
step S41, determining whether the period variation is greater than the adaptive threshold:
if yes, counting corresponding out-of-limit times in a waiting time and turning to the step S42;
if not, returning to the step S1;
step S42, determining whether the number of times of violation is greater than the violation threshold:
if yes, generating a contact detection result for representing the occurrence of the electric shock accident and quitting;
if not, the process returns to step S1.
While the invention has been described with reference to a preferred embodiment, it will be understood by those skilled in the art that various changes in form and detail may be made without departing from the spirit and scope of the invention.
Claims (10)
1. An adaptive threshold-based electrocution detection system, comprising:
the acquisition module is used for acquiring a first total residual current corresponding to a first reference point and a second total residual current corresponding to a second reference point of a power distribution network in real time;
the first processing module is connected with the acquisition module and used for respectively performing wavelet transformation on the first total residual current and the second total residual current to obtain a first low-frequency component corresponding to the first reference point and a second low-frequency component corresponding to the second reference point, and processing according to the first low-frequency component and the second low-frequency component to obtain a periodic variable quantity;
the statistical module is used for obtaining a mean value of a period variable quantity of a period before the first reference point and a wavelet coefficient extreme value of the period before the first reference point through statistics;
the second processing module is connected with the statistical module and used for processing according to the average value of the period variation and the extreme value of the wavelet coefficient to obtain a self-adaptive threshold;
and the third processing module is respectively connected with the first processing module and the second processing module and used for processing according to the period variation, the self-adaptive threshold and a preset out-of-limit threshold to obtain a corresponding electric shock detection result.
2. The electrocution detection system of claim 1, wherein the first processing module comprises:
the first acquisition unit is used for acquiring a period number between the first reference point and the second reference point and a sampling point number corresponding to one period;
the first processing unit is connected with the first acquisition unit and used for performing wavelet transformation on the first total residual current to obtain the first low-frequency component corresponding to the first reference point and performing wavelet transformation on the second total residual current based on the periodicity and the number of sampling points to obtain the second low-frequency component corresponding to the second reference point;
and the second processing unit is connected with the first processing unit and used for processing according to the first low-frequency component and the second low-frequency component to obtain the period variation.
3. The electric shock detection system according to claim 2, wherein the period change amount is obtained by processing according to the following calculation formula:
wherein the content of the first and second substances,
Δ c (i) representing the period variation;
i represents a variable parameter;
n represents the number of cycles;
l represents the number of sampling points.
4. The electric shock detection system according to claim 1, wherein the average value of the cyclic variation is obtained by processing according to the following calculation formula:
wherein the content of the first and second substances,
λ c represents the average value of the period variation;
l represents the number of sampling points;
N P representing a length between the first reference point and the second reference point;
i represents a variable parameter;
Δ c representing the amount of cyclic variation.
5. The electrocution detection system of claim 1, wherein the wavelet coefficient extremum is processed by the following calculation:
ε c ＝max[|Δ c (2*L-N P )|,...,|Δ c (L-N P )|]
wherein the content of the first and second substances,
ε c representing the wavelet coefficient extremum;
l represents the number of sampling points;
N P representing the length between the first reference point and the second reference point;
Δ c representing the amount of cyclic variation.
6. The electrocution detection system of claim 1 wherein the adaptive threshold is processed by the following calculation:
λ s_c ＝λ c +K ε_c *ε c
wherein the content of the first and second substances,
λ s_c representing the adaptive threshold;
λ c represents the average value of the period variation;
ε c representing the wavelet coefficient extremum;
K ε_c a maximum utilization coefficient of a low frequency component is represented.
7. The electrocution detection system of claim 1, wherein the third processing module includes:
the third processing unit is used for comparing the period variation with the self-adaptive threshold, controlling the second processing module to stop running when the period variation is larger than the self-adaptive threshold, and counting the corresponding out-of-limit times in a waiting time;
the fourth processing unit is connected with the third processing unit and used for comparing the out-of-limit times with the out-of-limit threshold and generating a contact detection result representing the occurrence of electric shock accidents when the out-of-limit times are larger than the out-of-limit threshold;
and generating a contact detection result representing that no electric shock accident occurs when the out-of-limit times are not greater than the out-of-limit threshold, and controlling the second processing module to operate again.
8. An electric shock detection method based on an adaptive threshold value, which is applied to the electric shock detection system as claimed in any one of claims 1 to 7, and specifically comprises the following steps:
step S1, collecting a first total residual current corresponding to a first reference point and a second total residual current corresponding to a second reference point of a power distribution network in real time, and counting to obtain a period variable quantity average value of a period before the first reference point and a wavelet coefficient extreme value of the period before the first reference point;
step S2, performing wavelet transformation on the first total residual current and the second total residual current to obtain a first low-frequency component corresponding to the first reference point and a second low-frequency component corresponding to the second reference point, and processing according to the first low-frequency component and the second low-frequency component to obtain a periodic variation;
step S3, processing according to the average value of the period variation and the extreme value of the wavelet coefficient to obtain an adaptive threshold;
and step S4, processing according to the period variation, the adaptive threshold and a preset out-of-limit threshold to obtain a corresponding electric shock detection result.
9. The electric shock detection method according to claim 8, wherein the step S2 includes:
step S21, collecting a period number between the first reference point and the second reference point and a sampling point number corresponding to one period;
step S22, performing wavelet transform on the first total residual current to obtain the first low-frequency component corresponding to the first reference point, and performing wavelet transform on the second total residual current based on the number of cycles and the number of sampling points to obtain the second low-frequency component corresponding to the second reference point;
step S23, processing the first low frequency component and the second low frequency component to obtain the period variation.
10. The electric shock detection method according to claim 8, wherein the step S4 includes:
step S41, determining whether the period change is greater than the adaptive threshold:
if yes, counting corresponding out-of-limit times in a waiting time and turning to the step S42;
if not, returning to the step S1;
step S42, determining whether the number of times of crossing is greater than the threshold value:
if so, generating a contact detection result representing the occurrence of the electric shock accident and quitting;
if not, the process returns to the step S1.
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