CN105811358A - Electric shock fault moment detection method and device - Google Patents

Abstract

The invention relates to an electric shock fault moment detection method and device. The method comprises following steps of sampling in real time by utilizing a zero sequence current transformer, thus obtaining total leakage current sampling signals; selecting an ith sampling point from the total leakage current sampling signals as a reference signal; by taking the reference signal as a reference, selecting the total leakage current sampling signals of a former period; obtaining the skewness of the total leakage current sampling signals of the former period by utilizing a data window, wherein the skewness indicates the degree of asymmetry of the total leakage current sampling signals and the average value of the signals; and judging that an electric shock fault occurs if the skewness exceeds a skewness set value and outputting a tripping signal to a surplus current protective device at this moment. According to the method and the device, the organism electric shock fault moment can be identified from the total leakage current sampling signals rapidly, and therefore, the action sensitivity and reliability of the surplus current protective device can be improved.

Description

A kind of electric shock fault moment detection method and device

Technical field

The present invention relates to Relay Protection Technology in Power System field, particularly relate to a kind of electric shock fault moment detection method and device.

Background technology

Aftercurrent protecting equipment is as important protection a kind of in low-voltage distribution system and control equipment, it is possible to situation about in time person electric shock, electrical fire and electrical equipment being damaged makes protection action, it is prevented that above-mentioned situation continued worsens.But malfunction and misaction often occurs in current Aftercurrent protecting equipment, reduce susceptiveness and the reliability of its operation, thus causing that its performance factor is not ideal.

For the problems referred to above; the Chinese patent literature that application number is CN201210134823.4A discloses a kind of shock current recognition methods and Aftercurrent protecting equipment; the method isolates shock current exactly by achieving based on small echo and sliding window mode from total leakage current; and judge whether to need tripping operation according to the amplitude of this shock current; but the method needs the described signal to M (M is even number) the individual cycle as current operation window; data volume is bigger; and move when moving described window successively and be spaced apart 1 cycle, the waiting time is also longer.The Chinese patent application that application number is CN201310520664.6A discloses a kind of electric shock signal time recognition method and residual current protection action criterion; by utilizing mathematical morphology to extract the transient characteristic of electric shock signal; using this one of transient characteristic quantity as the operating criterion of Aftercurrent protecting equipment; the method decreases amount of calculation to a certain extent, it also requires total leakage current signal in 2 cycles of real-time sampling carries out opening operation and the closed operation of mathematical morphology.

Summary of the invention

For defect of the prior art; the present invention provides a kind of electric shock fault moment detection method and device; organism electric shock fault moment can be picked out rapidly, thus improving susceptiveness and the reliability of Aftercurrent protecting equipment action from total leakage current sampled signal.

First aspect, the invention provides a kind of electric shock fault moment detection method, and described method includes:

Utilize zero sequence current mutual inductor real-time sampling to obtain total leakage current sampled signal；

Ith sample point is chosen as reference signal from described total leakage current sampled signal, and with total leakage current sampled signal that this reference signal is the selection of datum previous cycle；And utilize the degree of skewness of total leakage current sampled signal in data window acquisition previous cycle；Wherein, degree of skewness refers to the degree of asymmetry of total leakage current sampled signal and its meansigma methods；

If described degree of skewness exceedes degree of skewness setting valve, then there is electric shock fault, now output Aftercurrent protecting equipment trip signal.

Alternatively, Third order statistic is adopted to obtain degree of skewness.

Alternatively, described Third order statistic adopts below equation to represent:

$K_{X\left(i\right)}^3({\mathrm{\τ}}_1,{\mathrm{\τ}}_2)=E\left\{X\left(i\right)X(i+{\mathrm{\τ}}_1)X(i+{\mathrm{\τ}}_2)\right\};$

In formula, X (i) represents total leakage current sampled signal of ith sample point；X(i+τ₁) represent the i-th+τ₁Total leakage current sampled signal of individual sampled point；X(i+τ₂) represent the i-th+τ₂Total leakage current sampled signal of individual sampled point；E{} represents expectation computing；Represent the third moment of total leakage current sampled signal X (i).

Alternatively, the average utilizing total leakage current sampled signal of the sampled point in numerical aperture replaces expected value to obtain described degree of skewness:

$K_{X\left(i\right)}^3({\mathrm{\τ}}_1,{\mathrm{\τ}}_2)=\frac{1}{M}\underset{i=1}{\overset{M}{\Σ}}{\left(X\right(i)-\stackrel{\‾}{X}(i\left)\right)}^3;$

In formula,Represent the meansigma methods of total leakage current sampled signal in a numerical aperture；M represents the number of sampled point in a power frequency period；Represent the sum of the total leakage current sampled signal calculating M sampled point.

Alternatively, also include total leakage current sampled signal of sampled point in data window is gone meansigma methods computing:

$\tilde{X}\left(i\right)=X\left(i\right)-\stackrel{\‾}{X}\left(i\right),i=1,2,\mathrm{...},M,\mathrm{...},N;$

In formula,Represent the meansigma methods of sampled signal in the cycle.

Alternatively, the estimated value of described degree of skewness adopts below equation to represent:

$K_{X\left(i\right)}^3=\frac{1}{M}\underset{k=i-M+1}{\overset{k=i}{\Σ}}{\tilde{X}}^3\left(i\right).$

Second aspect, the embodiment of the present invention additionally provides a kind of electric shock fault moment detecting device, and described device includes:

Sampled signal acquisition module, is used for utilizing zero sequence current mutual inductor real-time sampling to obtain total leakage current sampled signal；

Degree of skewness acquisition module, for choosing ith sample point as reference signal, and with total leakage current sampled signal that this reference signal is the selection of datum previous cycle from described total leakage current sampled signal；And utilize the degree of skewness of total leakage current sampled signal in data window acquisition previous cycle；Wherein, degree of skewness refers to the degree of asymmetry of total leakage current sampled signal and its meansigma methods；

, for when described degree of skewness exceedes degree of skewness setting valve, then there is electric shock fault and export Aftercurrent protecting equipment trip signal in processing module.

Alternatively, described degree of skewness acquisition module adopts Third order statistic to obtain degree of skewness.

Alternatively, described degree of skewness acquisition module is used for adopting below equation to obtain described Third order statistic:

$K_{X\left(i\right)}^3({\mathrm{\τ}}_1,{\mathrm{\τ}}_2)=E\left\{X\left(i\right)X(i+{\mathrm{\τ}}_1)X(i+{\mathrm{\τ}}_2)\right\};$

In formula, X (i) represents total leakage current sampled signal of ith sample point；X(i+τ₁) represent the i-th+τ₁Total leakage current sampled signal of individual sampled point；X(i+τ₂) represent the i-th+τ₂Total leakage current sampled signal of individual sampled point；E{} represents expectation computing；Represent the third moment of total leakage current sampled signal X (i).

Alternatively, described degree of skewness acquisition module is additionally operable to utilize the average of total leakage current sampled signal of the sampled point in numerical aperture to replace expected value to obtain described degree of skewness:

$K_{X\left(i\right)}^3({\mathrm{\τ}}_1,{\mathrm{\τ}}_2)=\frac{1}{M}\underset{i=1}{\overset{M}{\Σ}}{\left(X\right(i)-\stackrel{\‾}{X}(i\left)\right)}^3;$

And, described degree of skewness module is additionally operable to total leakage current sampled signal of sampled point in data window is gone meansigma methods computing:

$\tilde{X}\left(i\right)=X\left(i\right)-\stackrel{\‾}{X}\left(i\right),i=1,2,...,M,...,N.$

As shown from the above technical solution, the present invention passes through the total leakage current sampled signal of zero sequence current mutual inductor Real-time Collection, then chooses the degree of skewness of the data window in one of them sampled point previous cycle；If this degree of skewness exceedes degree of skewness setting valve, then can pick out organism electric shock fault moment rapidly, thus improving susceptiveness and the reliability of Aftercurrent protecting equipment action.

Accompanying drawing explanation

Being more clearly understood from the features and advantages of the present invention by reference accompanying drawing, accompanying drawing is schematic and should not be construed as and the present invention is carried out any restriction, in the accompanying drawings:

Fig. 1 is the schematic flow sheet of a kind of fault moment detection method of getting an electric shock that the embodiment of the present invention provides；

The oscillogram of total leakage current when Fig. 2 is electric shock accidents in one embodiment of the invention；

Fig. 3 is the schematic diagram of the degree of skewness of total leakage current shown in Fig. 2；

Fig. 4 is the block diagram of a kind of fault moment detecting device that gets an electric shock that the embodiment of the present invention provides.

Detailed description of the invention

For making the purpose of the embodiment of the present invention, technical scheme and advantage clearly, below in conjunction with the accompanying drawing in the embodiment of the present invention, technical scheme in the embodiment of the present invention is clearly and completely described, obviously, described embodiment is a part of embodiment of the present invention, rather than whole embodiments.Based on the embodiment in the present invention, the every other embodiment that those of ordinary skill in the art obtain under not making creative work premise, broadly fall into the scope of protection of the invention.

In the process realizing the present invention, the inventors found that: when low-voltage distribution system normal operation, total leakage current signal only comprises the sinusoidal signal with cyclic symmetry and gaussian random noise signal, and the degree of skewness of both component of signals is zero.But, if adopting the estimated value of degree of skewness to calculate, can make the degree of skewness of total leakage current collection signal that null value has a less skew.When after organism generation electric shock accidents, fundamental voltage amplitude and the phase place of total leakage current sampled signal can change, total leakage current sampled signal also comprises the transient state component such as high frequency transient component and exponential damping DC component so that the degree of skewness of total leakage current sampled signal offsets null value (skew that more above-mentioned employing estimated value calculates is very big) significantly simultaneously.

Based on above-mentioned principle, embodiments provide a kind of electric shock fault moment detection method, as it is shown in figure 1, the method includes:

S1, utilize zero sequence current mutual inductor real-time sampling to obtain total leakage current sampled signal；

S2, from described total leakage current sampled signal, choose ith sample point as reference signal, and with total leakage current sampled signal that this reference signal is the selection of datum previous cycle；And utilize the degree of skewness of total leakage current sampled signal in data window acquisition previous cycle；Wherein, degree of skewness refers to the degree of asymmetry of total leakage current sampled signal and its meansigma methods；

If the described degree of skewness of S3 exceedes degree of skewness setting valve, then there is electric shock fault, now output Aftercurrent protecting equipment trip signal.

For embodying the superiority of the electric shock fault moment detection method that the embodiment of the present invention provides, below said method is described further with accompanying drawing in conjunction with the embodiments.

First, introduce S1, utilize zero sequence current mutual inductor real-time sampling to obtain the step of total leakage current sampled signal.

In the embodiment of the present invention, total leakage current refers to the conjunction electric current on three-phase line.The embodiment of the present invention adopt zero sequence current mutual inductor obtain total leakage current.Such as can installing a current transformer respectively on each phase line, the electric current sum of the three-phase line then gathered by synchronization is as total leakage current.Three-phase line can also allowed also cross zero sequence current mutual inductor, now can record total leakage current.It is of course also possible to by above-mentioned zero line through zero sequence inductance transformer, equally possible get total leakage current.

It should be noted that above describe only zero sequence current mutual inductor to obtain the situation of total leakage current, naturally it is also possible to adopting other current transformer or other electronic equipments to obtain leakage current, the present invention is not construed as limiting.

For simplifying subsequent calculations amount, in the embodiment of the present invention, the mode by sampling obtains total leakage current.Gathering in preset time period once, the total leakage current gathered at this sampled point is called total leakage current sampled signal.When sample frequency is sufficiently large, total leakage current sampled signal is identical with actual total leakage current signal waveform, does not therefore affect the accuracy rate of subsequent calculations.

The total leakage current sampled signal in the embodiment of the present invention, each sampled point gathered be stored in sample sequence X (i), i=1,2,3 ..., in N}, wherein N is positive integer.

Secondly, introduce and from described total leakage current sampled signal, choose ith sample point as reference signal, and with total leakage current sampled signal that this reference signal is the selection of datum previous cycle；And utilize the step of the degree of skewness of total leakage current sampled signal in data window acquisition previous cycle.

It should be noted that degree of skewness refers to the degree of asymmetry of total leakage current sampled signal and its meansigma methods in the embodiment of the present invention.Meansigma methods refers to the meansigma methods of the total leakage current sampled signal in a data window herein.

In the embodiment of the present invention, degree of skewness adopts Third order statistic to obtain, the dimensionless number evidence that so degree of skewness can be made to be Third order statistic.Assume sample sequence X (i), i=1,2,3 ..., the meansigma methods of N} is zero, and its Third order statistic is defined as:

$K_{X\left(i\right)}^3({\mathrm{\τ}}_1,{\mathrm{\τ}}_2)=E\left\{X\left(i\right)X(i+{\mathrm{\τ}}_1)X(i+{\mathrm{\τ}}_2)\right\};---\left(1\right)$

In formula (1), X (i) represents total leakage current sampled signal of ith sample point；X(i+τ₁) represent the i-th+τ₁Total leakage current sampled signal of individual sampled point；X(i+τ₂) represent the i-th+τ₂Total leakage current sampled signal of individual sampled point；E{} represents expectation computing；Represent the third moment of total leakage current sampled signal X (i).

In practical application, relating to sample sequence is carried out expectation computing in formula (1), adopt estimator to be similar in the embodiment of the present invention, namely the estimator of degree of skewness replaces expected value to calculate by the meansigma methods of total leakage current sampled signal:

$K_{X\left(i\right)}^3({\mathrm{\τ}}_1,{\mathrm{\τ}}_2)=\frac{1}{M}\underset{i=1}{\overset{M}{\Σ}}{\left(X\right(i)-\stackrel{\‾}{X}(i\left)\right)}^3;---\left(2\right)$

In formula (2),Represent the meansigma methods of total leakage current sampled signal in a numerical aperture；M represents the number of sampled point in a power frequency period；Represent the sum of the total leakage current sampled signal calculating M sampled point.

Then from sample sequence, total leakage current sampled signal of an ith sample point is chosen as reference signal, and with total leakage current sampled signal that this reference signal is the selection of datum previous cycle；And utilize data window to obtain the degree of skewness of total leakage current sampled signal in previous cycle, calculate the estimated sequence of its meansigma methods:

$\{\begin{array}{c}\stackrel{\‾}{X}\left(i\right)=\frac{1}{M}\underset{k=i-M+1}{\overset{k=i}{\Σ}}X\left(k\right),i=M,M+1,\mathrm{...},N\\ \stackrel{\‾}{X}\left(i\right)=\stackrel{\‾}{X}\left(M\right),i=1,2,\mathrm{...},M\end{array}---\left(3\right)$

In formula (3),Represent the meansigma methods of total leakage current sampled signal in a numerical aperture.Such as, in the cycle, sampled point number is 200, then in the 200th sampled point that is first cycle, the average of signal isSignal average in the previous cycle of the 201st sampled point is

Then according to formula (4), the sample sequence shown in formula (3) is gone meansigma methods computing, to obtain new data sequence

$\tilde{X}\left(i\right)=X\left(i\right)-\stackrel{\‾}{X}\left(i\right),i=1,2,...,M,...,N;---\left(4\right)$

Finally calculate the estimated value of the degree of skewness of the total leakage current sampled signal corresponding to ith sample point:

$K_{X\left(i\right)}^3=\frac{1}{M}\underset{k=i-M+1}{\overset{k=i}{\Σ}}{\tilde{X}}^3\left(i\right)---\left(5\right)$

Finally, if introducing the described degree of skewness of S3 to exceed degree of skewness setting valve, then there is electric shock fault, now export the step of Aftercurrent protecting equipment trip signal.

When obtaining the estimated value of degree of skewness, compare with default degree of skewness setting valve.If the estimated value of this degree of skewness exceedes above-mentioned degree of skewness setting valve, ith sample point moment low-voltage distribution system generation electric shock accidents is described, now needs to export trip signal to Aftercurrent protecting equipment, so that its timely protection act.

It should be noted that when the estimated value of above-mentioned degree of skewness is not less than default degree of skewness setting valve, ith sample point moment low-voltage distribution system normal operation is described, now this method also includes:

S4, extract total leakage current sampled signal of next sampled point, repeat step S1～S3 or repeat step S1, S2 and S4.

It should be noted that the order of step S3 and step S4 is not fixing in the embodiment of the present invention, and it not simultaneous.

As in figure 2 it is shown, run the electric shock accidents moment detection method that the embodiment of the present invention provides in low-voltage distribution system, electric shock accidents occurring when 0.06 second, now total leakage current sampled signal changes.Obtain 0.0602 second moment degree of skewness according to said method to occur significantly increasing, as it is shown on figure 3, and exceed default degree of skewness setting valve, then judge that this 0.0602 second moment, electric shock accidents moment, time delay only 0.0002 second occurred.And export trip signal to Aftercurrent protecting equipment, low-voltage distribution system is protected in time.

It should be noted that the degree of skewness setting valve preset in Fig. 3 in the embodiment of the present invention can be very little, it is usually arranged as less than 1.Default degree of skewness setting valve in Fig. 3, more than 500, simply conveniently skilled artisan understands that the technical scheme of the application is arranged.

The embodiment of the present invention additionally provides a kind of electric shock fault moment detecting device, and as shown in Figure 4, described device includes:

Sampled signal acquisition module M1, is used for utilizing zero sequence current mutual inductor real-time sampling to obtain total leakage current sampled signal；

Degree of skewness acquisition module M2, for choosing ith sample point as reference signal, and with total leakage current sampled signal that this reference signal is the selection of datum previous cycle from described total leakage current sampled signal；And utilize the degree of skewness of total leakage current sampled signal in data window acquisition previous cycle；Wherein, degree of skewness refers to the degree of asymmetry of total leakage current sampled signal and its meansigma methods；

, for when described degree of skewness exceedes degree of skewness setting valve, then there is electric shock fault and export Aftercurrent protecting equipment trip signal in processing module M3.

Alternatively, described degree of skewness acquisition module M2 adopts Third order statistic to obtain degree of skewness.

Alternatively, described degree of skewness acquisition module M2 is used for adopting below equation to obtain described Third order statistic:

$K_{X\left(i\right)}^3({\mathrm{\τ}}_1,{\mathrm{\τ}}_2)=E\left\{X\left(i\right)X(i+{\mathrm{\τ}}_1)X(i+{\mathrm{\τ}}_2)\right\};$

In formula, X (i) represents total leakage current sampled signal of ith sample point；X(i+τ₁) represent the i-th+τ₁Total leakage current sampled signal of individual sampled point；X(i+τ₂) represent the i-th+τ₂Total leakage current sampled signal of individual sampled point；E{} represents expectation computing；Represent the third moment of total leakage current sampled signal X (i).

Alternatively, described degree of skewness acquisition module M2 is additionally operable to utilize the average of total leakage current sampled signal of the sampled point in numerical aperture to replace expected value to obtain described degree of skewness:

$K_{X\left(i\right)}^3({\mathrm{\τ}}_1,{\mathrm{\τ}}_2)=\frac{1}{M}\underset{i=1}{\overset{M}{\Σ}}{\left(X\right(i)-\stackrel{\‾}{X}(i\left)\right)}^3;$

And, described degree of skewness module M2 is additionally operable to total leakage current sampled signal of sampled point in data window is gone meansigma methods computing:

$\tilde{X}\left(i\right)=X\left(i\right)-\stackrel{\‾}{X}\left(i\right),i=1,2,...,M,...,N.$

As seen from the above, the electric shock fault moment detecting device that the above embodiment of the present invention provides realizes based on electric shock fault moment detection method mentioned above, thus can solve same technical problem, and obtains identical technique effect, and this is no longer going to repeat them.

Should be noted that, in all parts of device disclosed in the present embodiment, according to its function to realize, parts therein are carried out logical partitioning, but, the disclosure is not only restricted to this, it is possible to as required all parts is repartitioned or combines, for instance, can be single parts by some unit constructions, or some parts can be further broken into more subassembly.

The all parts embodiment of the disclosure can realize with hardware, or realizes with the software module run on one or more processor, or realizes with their combination.It will be understood by those of skill in the art that the some or all functions that microprocessor or digital signal processor (DSP) can be used in practice to realize the some or all parts in the system according to disclosure embodiment.The disclosure is also implemented as part or all the equipment for performing method as described herein or device program (such as, computer program and computer program).Such program realizing the disclosure can store on a computer-readable medium, or can have the form of one or more signal.Such signal can be downloaded from internet website and obtain, or provides on carrier signal, or provides with any other form.

It should be noted that the disclosure is illustrated rather than by above-described embodiment, the disclosure is limited, and those skilled in the art can design alternative embodiment without departing from the scope of the appended claims.In the claims, any reference marks that should not will be located between bracket is configured to limitations on claims.Word " comprises " and does not exclude the presence of the element or step not arranged in the claims.Word "a" or "an" before being positioned at element does not exclude the presence of multiple such element.The disclosure by means of including the hardware of some different elements and can realize by means of properly programmed computer.In the unit claim listing some devices, several in these devices can be through same hardware branch and specifically embody.Word first, second and third use do not indicate that any order.Can be title by these word explanations.

Embodiment of above is only suitable to the disclosure is described; and not restriction of this disclosure; those of ordinary skill about technical field; when without departing from the spirit and scope of the disclosure; can also make a variety of changes and modification; therefore all equivalent technical schemes fall within the category of the disclosure, and the scope of patent protection of the disclosure should be defined by the claims.

Claims (10)

1. an electric shock fault moment detection method, it is characterised in that described method includes:

Utilize zero sequence current mutual inductor real-time sampling to obtain total leakage current sampled signal；

Ith sample point is chosen as reference signal from described total leakage current sampled signal, and with total leakage current sampled signal that this reference signal is the selection of datum previous cycle；And utilize the degree of skewness of total leakage current sampled signal in data window acquisition previous cycle；Wherein, degree of skewness refers to the degree of asymmetry of total leakage current sampled signal and its meansigma methods；

If described degree of skewness exceedes degree of skewness setting valve, then there is electric shock fault, now output Aftercurrent protecting equipment trip signal.

2. electric shock fault moment detection method according to claim 1, it is characterised in that adopt Third order statistic to obtain degree of skewness.

3. electric shock fault moment detection method according to claim 2, it is characterised in that described Third order statistic adopts below equation to represent:

$K_{X\left(i\right)}^3({\mathrm{\τ}}_1,{\mathrm{\τ}}_2)=E\left\{X\left(i\right)X(i+{\mathrm{\τ}}_1)X(i+{\mathrm{\τ}}_2)\right\};$

In formula, X (i) represents total leakage current sampled signal of ith sample point；X(i+τ₁) represent the i-th+τ₁Total leakage current sampled signal of individual sampled point；X(i+τ₂) represent the i-th+τ₂Total leakage current sampled signal of individual sampled point；E{} represents expectation computing；Represent the third moment of total leakage current sampled signal X (i).

4. electric shock fault moment detection method according to claim 3, it is characterised in that utilize the average of total leakage current sampled signal of the sampled point in numerical aperture to replace expected value to obtain described degree of skewness:

$K_{X\left(i\right)}^3({\mathrm{\τ}}_1,{\mathrm{\τ}}_2)=\frac{1}{M}\underset{i=1}{\overset{M}{\Σ}}{\left(X\right(i)-\stackrel{\‾}{X}(i\left)\right)}^3;$

In formula,Represent the meansigma methods of total leakage current sampled signal in a numerical aperture；M represents the number of sampled point in a power frequency period；Represent the sum of the total leakage current sampled signal calculating M sampled point.

5. electric shock fault moment detection method according to claim 4, it is characterised in that also include total leakage current sampled signal of sampled point in data window is gone meansigma methods computing:

$\tilde{X}\left(i\right)=X\left(i\right)-\stackrel{\‾}{X}\left(i\right),i=1,2,...,M,...,N;$

In formula,Represent the meansigma methods of sampled signal in the cycle.

6. electric shock fault moment detection method according to claim 5, it is characterised in that the estimated value of described degree of skewness adopts below equation to represent:

$K_{X\left(i\right)}^3=\frac{1}{M}\underset{k=i-M+1}{\overset{k=i}{\Σ}}{\tilde{X}}^3\left(i\right).$

7. an electric shock fault moment detecting device, it is characterised in that described device includes:

Sampled signal acquisition module, is used for utilizing zero sequence current mutual inductor real-time sampling to obtain total leakage current sampled signal；

Degree of skewness acquisition module, for choosing ith sample point as reference signal, and with total leakage current sampled signal that this reference signal is the selection of datum previous cycle from described total leakage current sampled signal；And utilize the degree of skewness of total leakage current sampled signal in data window acquisition previous cycle；Wherein, degree of skewness refers to the degree of asymmetry of total leakage current sampled signal and its meansigma methods；

, for when described degree of skewness exceedes degree of skewness setting valve, then there is electric shock fault and export Aftercurrent protecting equipment trip signal in processing module.

8. electric shock fault moment detecting device according to claim 7, it is characterised in that described degree of skewness acquisition module adopts Third order statistic to obtain degree of skewness.

9. electric shock fault moment detecting device according to claim 8, it is characterised in that described degree of skewness acquisition module is used for adopting below equation to obtain described Third order statistic:

$K_{X\left(i\right)}^3({\mathrm{\τ}}_1,{\mathrm{\τ}}_2)=E\left\{X\left(i\right)X(i+{\mathrm{\τ}}_1)X(i+{\mathrm{\τ}}_2)\right\};$

In formula, X (i) represents total leakage current sampled signal of ith sample point；X(i+τ₁) represent the i-th+τ₁Total leakage current sampled signal of individual sampled point；X(i+τ₂) represent the i-th+τ₂Total leakage current sampled signal of individual sampled point；E{} represents expectation computing；Represent the third moment of total leakage current sampled signal X (i).

10. electric shock fault moment detecting device according to claim 9, it is characterised in that described degree of skewness acquisition module is additionally operable to utilize the average of total leakage current sampled signal of the sampled point in numerical aperture to replace expected value to obtain described degree of skewness:

$K_{X\left(i\right)}^3({\mathrm{\τ}}_1,{\mathrm{\τ}}_2)=\frac{1}{M}\underset{i=1}{\overset{M}{\Σ}}{\left(X\right(i)-\stackrel{\‾}{X}(i\left)\right)}^3;$

And, described degree of skewness module is additionally operable to total leakage current sampled signal of sampled point in data window is gone meansigma methods computing:

$\tilde{X}\left(i\right)=X\left(i\right)-\stackrel{\‾}{X}\left(i\right),i=1,2,...,M,...,N.$