CN106324345B - Electrical equipment fault detection method and device - Google Patents

Abstract

The present invention relates to a method and device for fault detection of electrical equipment. Through the interference detection of discrete data, that is, detecting whether the preset interference condition is met, it can be known whether the discrete data is disturbed, and if disturbed, the disturbed discrete data is Update to ensure the accuracy of the data, and then perform Fourier transform on the discrete data to eliminate the interference component, obtain the fundamental wave component corresponding to the electrical parameter analog quantity, and according to the amplitude of the fundamental wave component, can Accurately calculate the effective value corresponding to the electrical parameters, and then obtain accurate fault detection results based on the accurate effective value, so as to improve the accuracy of fault detection, that is, it can accurately judge whether there is a fault or abnormal situation in the electrical equipment. Once a fault is found, Maintenance can be carried out, thereby increasing the safety of grid operation.

Description

Electrical equipment fault detection method and device

technical field

The invention relates to the technical field of power grids, in particular to a method and device for detecting electrical equipment faults.

Background technique

Distribution network automation terminal equipment is widely used in the market, including feeder automation terminal (FTU), distribution network automation measurement and control terminal (DTU), boundary switch controller, microcomputer relay protection device, and cable fault indicator. The rapid isolation of distribution network faults, the prevention of accident expansion, the improvement of power supply reliability and the safe and stable operation of the power grid play a key role. The above-mentioned distribution network automation terminal equipment needs to collect current and voltage and calculate the corresponding effective value, and then compare it with the set setting value to judge the fault and abnormal situation. The acquisition of current and voltage analog quantities is realized through an analog-to-digital converter. Because the original data collected are all discrete quantities, the actual current and voltage values need to be calculated. Fourier algorithm (referred to as Fourier algorithm) has the characteristics of fast operation speed, high precision, and can filter out periodic components. The analog calculation of existing distribution network automation terminal equipment is realized by Fourier algorithm.

The Fourier algorithm can filter out the periodic component, but it can't do anything about the non-periodic component, and the general interference data are random and non-periodic. Through the calculation and simulation of the Fourier algorithm, it is found that any interference data will have a very large impact on the calculation results, seriously deviating from the actual value. Therefore, for various distribution network automation terminal equipment using the Fourier algorithm, an interference signal may cause a malfunction of the terminal equipment or a wrong signal, resulting in unstable operation of the power grid and unsafe operation of the power grid.

Contents of the invention

Based on this, it is necessary to address the problem of unsafe operation of the power grid, and it is necessary to provide a method and device for detecting electrical equipment faults that enable the safe operation of the power grid.

A fault detection method for electrical equipment, comprising the following steps:

Obtain the electrical parameter analog quantity input to the electrical equipment, and sample the electrical parameter analog quantity according to a preset acquisition frequency, obtain a preset number of discrete data corresponding to the electrical parameter, and record and collect the discrete data The corresponding collection time point;

The initialization start time is the collection time point corresponding to the first collection of the discrete data;

Taking the start time as a reference and according to the sequence of the collection time points, three continuous discrete data are acquired from the preset number of discrete data, wherein the three continuous discrete data sequentially include the first discrete data, second discrete data, and third discrete data, the first discrete data being the discrete data collected at the start time;

When the first discrete data, the second discrete data, and the third discrete data meet a preset interference condition, update the second discrete data in the discrete data to the corresponding value of the second discrete data The data collected corresponding to the period before the collection time point;

Detecting whether the third discrete data is the last data in the discrete data;

If so, perform Fourier transform on the discrete data, obtain the fundamental wave component corresponding to the electrical parameter analog quantity, and calculate the effective value corresponding to the electrical parameter according to the amplitude of the fundamental wave component;

Obtain a fault detection result according to the effective value corresponding to the electrical parameter and the preset electrical parameter value.

The present invention also provides a fault detection device for electrical equipment, including:

a discrete data acquisition module, configured to acquire electrical parameter analog quantities input to electrical equipment, and sample the electrical parameter analog quantities according to a preset acquisition frequency to obtain a preset number of discrete data corresponding to the electrical parameters, And record the acquisition time point corresponding to the discrete data;

An initialization module, configured to initialize the start time as the collection time point corresponding to the first collection of the discrete data;

The continuous data acquisition module is used to acquire three continuous discrete data from the preset number of discrete data according to the sequence of the collection time points based on the starting time, wherein the three The continuous discrete data sequentially includes first discrete data, second discrete data and third discrete data, and the first discrete data is the discrete data collected at the start time;

An update module, configured to update the second discrete data in the discrete data to the first discrete data when the first discrete data, the second discrete data, and the third discrete data meet a preset interference condition The data collected corresponding to the previous period of the collection time point corresponding to the discrete data;

a detection module, configured to detect whether the third discrete data is the last data in the discrete data;

A calculation module, configured to perform Fourier transform on the discrete data when the detection result of the detection module is yes, to obtain the fundamental wave component corresponding to the electrical parameter analog quantity, and Value, calculate the effective value corresponding to the electrical parameter;

The fault detection module is configured to obtain a fault detection result according to the effective value corresponding to the electrical parameter and the preset electrical parameter value.

The above electrical equipment fault detection method and device, based on the start time, according to the sequence of the collection time points, acquire three continuous discrete data from the preset number of discrete data, when the first When the first discrete data, the second discrete data, and the third discrete data meet a preset interference condition, updating the second discrete data in the discrete data to be before the acquisition time point corresponding to the second discrete data One cycle corresponds to the collected data, and when it is detected whether the third discrete data is the last data in the discrete data, Fourier transform is performed on the discrete data to obtain the fundamental wave corresponding to the electrical parameter analog quantity component, and calculate the effective value corresponding to the electrical parameter according to the amplitude of the fundamental component, and obtain the fault detection result according to the effective value corresponding to the electrical parameter and the preset electrical parameter value. Through the interference detection of discrete data, that is, to detect whether the preset interference conditions are met, it can be known whether the discrete data has been disturbed. If it is disturbed, the disturbed discrete data will be updated to ensure the accuracy of the data, and then through the Perform Fourier transform on the discrete data to eliminate the interference component, obtain the fundamental wave component corresponding to the electrical parameter analog quantity, and accurately calculate the effective value corresponding to the electrical parameter according to the amplitude of the fundamental wave component, and then according to the accurate The ground effective value can obtain accurate fault detection results to improve the accuracy of fault detection, that is, it can accurately judge whether electrical equipment has faults and abnormal conditions, and once a fault is found, it can be maintained, thereby improving the safety of power grid operation.

Description of drawings

Fig. 1 is the flow chart of the electrical equipment fault detection method of an embodiment;

Fig. 2 is the flow chart of the electrical equipment fault detection method of another embodiment;

Fig. 3 is the waveform diagram of electrical parameter analog quantity;

Fig. 4 is a block diagram of an electrical equipment fault detection device according to an embodiment.

Detailed ways

Referring to Fig. 1, an embodiment of an electrical equipment fault detection method is provided, including the following steps:

S110: Obtain the electrical parameter analog input to the electrical equipment, and sample the electrical parameter analog according to the preset acquisition frequency, obtain a preset number of discrete data corresponding to the electrical parameter, and record the acquisition time corresponding to the discrete data acquisition point.

In the power grid system, it includes a variety of electrical equipment, such as feeder automation terminal (FTU), distribution network automation measurement and control terminal (DTU), boundary switch controller, microcomputer relay protection device and cable fault indicator, etc. These devices play a key role in quickly isolating grid faults, preventing accidents from expanding, improving power supply reliability, and ensuring safe and stable operation of the grid. In the process of fault detection of electrical equipment, it is usually necessary to obtain the waveform data of electrical parameters such as current and voltage input to electrical equipment, that is, analog quantities. These electrical parameter analog quantities input to electrical equipment are alternating current. In order to effectively detect electrical For fault detection of the equipment, it is necessary to know the effective value of the alternating current. In order to obtain the effective value, firstly, it is necessary to sample the electrical parameter analog quantity according to the preset acquisition frequency, obtain the preset number of discrete data corresponding to the electrical parameter, and record and collect Acquisition time points corresponding to discrete data.

S120: The initialization start time is the collection time point corresponding to the first collection of discrete data.

S130: Based on the starting time, according to the order of collection time points, acquire three continuous discrete data from the preset number of discrete data.

Wherein, the three continuous discrete data sequentially include first discrete data, second discrete data and third discrete data, and the first discrete data is discrete data collected at a starting time.

S140: Detect whether the first discrete data, the second discrete data, and the third discrete data satisfy a preset interference condition.

Since these discrete data are obtained by sampling the alternating current input to the electrical equipment, these discrete data reflect the alternating current to a certain extent, and subsequent interference detection needs to be performed on each group of three continuous discrete data in the discrete data, that is, to detect whether the discrete data is affected interference. Specifically, according to the order of the collection time points, three continuous discrete data are sequentially obtained from the preset number of discrete data for interference detection and judgment, and according to the interference detection and judgment of three continuous discrete data each time, it is judged whether it is affected by Interference, until all the discrete data are interfered with and detected, the calculation of the effective value is carried out. For example, according to the order of the collection time points, the discrete data are 1, 4, 3, 4, 5, 6 in sequence. First, take the first three continuous data as 1, 2, 3, and perform interference detection on them, that is Judging whether the preset interference condition is met, if not, updating the second discrete data is about to update 4 to other data, for example, update to 2, at this time, the updated discrete data are 1, 2, 3, 4, 5, 6, Continue to select three consecutive data 2, 3, 4 for interference detection, and so on until all data interference detection is completed.

When the first discrete data, the second discrete data and the third discrete data meet the preset interference condition, perform the following steps:

S150: Updating the second discrete data in the discrete data to the data collected corresponding to a period before the collection time point corresponding to the second discrete data.

When the first discrete data, the second discrete data, and the third discrete data meet the preset interference conditions, it means that the second discrete data among the three continuous discrete data has been disturbed. In order to eliminate the interference, the second discrete data needs to be updated , specifically, the electrical parameter analog is generally a periodic signal, and the values corresponding to the time difference of one cycle are equal. If the second discrete data is disturbed at this time, the second discrete data in the discrete data is updated to the second discrete data corresponding to The data collected corresponding to the previous cycle of the collection time point can ensure the correctness of the updated second discrete data and ensure the accuracy of subsequent effective value calculations.

S160: Detect whether the third discrete data is the last data in the discrete data.

If yes, perform the following steps:

S170: Perform Fourier transform on the discrete data, obtain the fundamental wave component corresponding to the electrical parameter analog quantity, and calculate the effective value corresponding to the electrical parameter according to the amplitude of the fundamental wave component.

When it is detected that the third discrete data is the last data in the discrete data, that is to say, the interference detection of the last group of three continuous discrete data has been completed. The disturbed discrete data has also been updated, which means that all discrete data have been detected for interference and the disturbed discrete data has been updated, and the undisturbed discrete data keeps the original value unchanged. Fourier transform to calculate the effective value corresponding to the electrical parameter. After the discrete data is transformed by Fourier, the DC component, the fundamental component (amplitude and frequency of the fundamental wave) and the harmonic component (amplitude and frequency of the harmonic) corresponding to the electrical parameter analog can be obtained, that is, the signal Through Fourier decomposition into DC components and the superposition of sinusoidal signals of different frequencies, the frequency of the fundamental component is the same as that of the alternating current, the fundamental basically reflects the original shape of the signal, and the harmonic component can be considered as an interference noise signal. Performing Fourier transform on the discrete data can eliminate interference, and calculate the effective value corresponding to the electrical parameter according to the fundamental wave component.

S180: Obtain a fault detection result according to the effective value corresponding to the electrical parameter and the preset electrical parameter value.

After the effective value is obtained, it can be compared with the preset electrical parameter value to obtain the comparison result, and then the fault detection result can be known.

The above electrical equipment fault detection method uses the starting time as a reference and according to the sequence of the collection time points, acquires three continuous discrete data from the preset number of discrete data, when the first discrete When the data, the second discrete data, and the third discrete data meet a preset interference condition, updating the second discrete data in the discrete data to a period preceding the acquisition time point corresponding to the second discrete data Corresponding to the collected data, when it is detected whether the third discrete data is the last data in the discrete data, Fourier transform is performed on the discrete data to obtain the fundamental wave component corresponding to the electrical parameter analog quantity, And calculate the effective value corresponding to the electrical parameter according to the amplitude of the fundamental wave component, and obtain the fault detection result according to the effective value corresponding to the electrical parameter and the preset electrical parameter value. Through the interference detection of discrete data, that is, to detect whether the preset interference conditions are met, it can be known whether the discrete data has been disturbed. If it is disturbed, the disturbed discrete data will be updated to ensure the accuracy of the data, and then through the Perform Fourier transform on the discrete data to eliminate the interference component, obtain the fundamental wave component corresponding to the electrical parameter analog quantity, and accurately calculate the effective value corresponding to the electrical parameter according to the amplitude of the fundamental wave component, and then according to the accurate The ground effective value can obtain accurate fault detection results to improve the accuracy of fault detection, that is, it can accurately judge whether electrical equipment has faults and abnormal conditions, and once a fault is found, it can be maintained, thereby improving the safety of power grid operation.

In one embodiment, the preset interference condition includes that when the second discrete data is larger than the first discrete data and larger than the third discrete data, a preset multiple of the second discrete data is larger than the first discrete data and larger than the third discrete data. Alternatively, the preset interference condition includes that when the second discrete data is smaller than the first discrete data and smaller than the third discrete data, dividing the second discrete data by a preset multiple is larger than the first discrete data and larger than the third discrete data.

That is to say, as long as the first discrete data, the second discrete data and the third discrete data meet one of the preset interference conditions mentioned above, it is considered to be interfered. When the second discrete data is greater than the first discrete data and greater than the third discrete data, the preset multiple of the second discrete data is greater than the first discrete data and greater than the third discrete data, it is considered that the interference appears near the peak, when the second discrete data When it is smaller than the first discrete data and smaller than the third discrete data, the second discrete data divided by the preset multiple is larger than the first discrete data and larger than the third discrete data, and it is considered that the interference appears near the trough.

Please refer to Fig. 2, in one of the embodiments, the above-mentioned electrical equipment fault detection method also includes the steps:

When the third discrete data is not the last data in the discrete data, execute:

S290: Update the start time to the next collection time point according to the sequence of the collection time points. And return to step S230 of acquiring three continuous discrete data from the preset number of discrete data according to the sequence of collection time points based on the starting time.

When the third discrete data is not the last data in the discrete data, it means that there are still discrete data without interference detection, and the interference detection of the next group of three continuous discrete data needs to be performed. Specifically, the start time is newly updated as At the next collection time point, based on the start time, according to the order of the collection time points, three continuous discrete data are obtained from the preset number of discrete data, and the interference detection is continued.

In one of the embodiments, before the step of detecting whether the third discrete data is the last data in the discrete data, the step further includes:

When the first discrete data, the second discrete data and the third discrete data do not meet the preset interference condition, enter the step of detecting whether the third discrete data is the last data in the discrete data.

When the first discrete data, the second discrete data, and the third discrete data do not meet the preset interference conditions, it means that the corresponding three continuous discrete data are not disturbed, and there is no need to update them, and directly enter the detection third The step of whether the discrete data is the last data in the discrete data, that is, if it is detected that the third discrete data is not the last data in the discrete data, the interference detection of the next group of three continuous discrete data will also be continued, Until all discrete data disturbances are detected.

The above-mentioned electrical equipment fault detection method will be described below with a specific embodiment.

The acquisition of analog quantities (AC data) of electrical parameters such as current and voltage is realized through an analog-to-digital converter. Since the original data collected are all discrete quantities, the actual current and voltage values need to be calculated. Fourier algorithm (referred to as Fourier algorithm) has the characteristics of fast operation speed, high precision, and can filter out periodic components. The analog calculation of existing distribution network automation terminal equipment is realized by Fourier algorithm.

As shown in Figure 3 above, d1, d2, and d3 are three continuous discrete data obtained by sampling the analog quantity by the analog-to-digital converter. Since the sinusoidal AC waveform is continuous and smooth, the value of point d2 is normally at The values of points d1 and d3 are in the middle (see (a) and (b) in Figure 3). Only when point d2 is near the peak (see (c) in Figure 3), its sampling value will be larger than the values of two adjacent sampling points d1 and d3, and the sampling value of point d2 will be larger than that of the two adjacent sampling points when it is near the wave trough. The values of the adjacent two sampling points d1 and d3 are small.

The existing distribution network automation terminal equipment all adopt 32-bit CPU and high-speed AD converter. In order to improve the terminal acquisition accuracy, in this embodiment, the calculation is based on 64 points of one cycle acquisition, that is, the preset number of discrete data is 64, then The sampling interval between two points is 20/64=0.3125 milliseconds, and the phase difference between the two points is 360/64=5.625 degrees. Take the middle point d2 near the peak (the situation is the same near the trough) as an example, satisfy the condition that point d2 is greater than point d1 and point d3, when point d2 is equal to point d1 (or d3), the difference between point d2 and point d3 (or d1) The value is the largest, and the largest difference is: sin(90-5.625/2)-sin(90-5.625/2-5.625)=0.0096. That is, if point d2 is greater than point d1 and point d3, the minimum value of point d1 and point d3 is 99.04% of point d1. Considering the conversion error of the analog-to-digital converter and the maximum allowable 5% error of relay protection, set the crest factor to 97% is more appropriate, that is, the preset multiple is 0.97. If the value of point d2 multiplied by 0.97 is still greater than the value of point d1 and point d3, then d2 is replaced by the value of one cycle of wave front to filter out the interference data.

Utilizing the smooth and continuous characteristics of the AC waveform, using the sampling values of three consecutive points to judge, filter out transient interference signals, and improve the anti-interference performance of the Fourier algorithm. Through the analysis and calculation and the actual test of the immunity of a large number of electrical fast transient bursts, when the sampling point is at the peak and valley, the preset multiple of 0.97 is used for calculation, which can not only ensure that the normal AC calculation is not affected, but also ensure that Effectively filter out disturbing data. Applying the above method to the integrated fault control terminal of the distribution network line, the algorithm has a small amount of calculation, is simple and practical. The AC sampling speed and sampling accuracy test before and after the application and the electrical fast transient burst immunity test were carried out. The AC sampling speed and sampling accuracy did not change before and after the application, while the anti-fast transient burst interference ability was improved. There is a substantial improvement, which can improve the anti-interference ability of 1KV.

Referring to Fig. 4, an embodiment of an electrical equipment fault detection device is also provided, including:

The discrete data acquisition module 410 is configured to acquire the electrical parameter analog quantities input to the electrical equipment, and sample the electrical parameter analog quantities according to a preset acquisition frequency to obtain a preset number of discrete data corresponding to the electrical parameters , and record the collection time point corresponding to the discrete data collection;

The initialization module 420 is configured to initialize the start time as the collection time point corresponding to the first collection of the discrete data;

The continuous data acquisition module 430 is configured to acquire three continuous discrete data from the preset number of discrete data according to the sequence of the collection time points based on the starting time, wherein the three A continuous discrete data sequentially includes first discrete data, second discrete data and third discrete data, and the first discrete data is the discrete data collected at the start time;

An updating module 440, configured to update the second discrete data in the discrete data to the The data collected corresponding to the collection time point corresponding to the second discrete data in the previous cycle;

A detection module 450, configured to detect whether the third discrete data is the last data in the discrete data;

The calculation module 460 is used to perform Fourier transform on the discrete data when the detection result of the detection module is yes, to obtain the fundamental wave component corresponding to the electrical parameter analog quantity, and to Amplitude, calculate the effective value corresponding to the electrical parameter;

The fault detection module 470 is configured to obtain a fault detection result according to the effective value corresponding to the electrical parameter and the preset electrical parameter value.

The electrical equipment failure detection device above acquires three continuous discrete data from the preset number of discrete data according to the sequence of the collection time points based on the starting time, when the first discrete When the data, the second discrete data, and the third discrete data meet a preset interference condition, updating the second discrete data in the discrete data to a period preceding the acquisition time point corresponding to the second discrete data Corresponding to the collected data, when it is detected whether the third discrete data is the last data in the discrete data, Fourier transform is performed on the discrete data to obtain the fundamental wave component corresponding to the electrical parameter analog quantity, And calculate the effective value corresponding to the electrical parameter according to the amplitude of the fundamental wave component, and obtain the fault detection result according to the effective value corresponding to the electrical parameter and the preset electrical parameter value. Through the interference detection of discrete data, that is, to detect whether the preset interference conditions are met, it can be known whether the discrete data has been disturbed. If it is disturbed, the disturbed discrete data will be updated to ensure the accuracy of the data, and then through the Perform Fourier transform on the discrete data to eliminate the interference component, obtain the fundamental wave component corresponding to the electrical parameter analog quantity, and accurately calculate the effective value corresponding to the electrical parameter according to the amplitude of the fundamental wave component, and then according to the accurate The ground effective value can obtain accurate fault detection results to improve the accuracy of fault detection, that is, it can accurately judge whether electrical equipment has faults and abnormal conditions, and once a fault is found, it can be maintained, thereby improving the safety of power grid operation.

In one of the embodiments, the preset interference condition includes that when the second discrete data is larger than the first discrete data and larger than the third discrete data, the preset multiple of the second discrete data is larger than the The first discrete data is larger than the third discrete data, or, the preset interference condition includes when the second discrete data is smaller than the first discrete data and smaller than the third discrete data, the first discrete data Dividing the second discrete data by the preset multiple is larger than the first discrete data and larger than the third discrete data.

In one of the embodiments, the electrical equipment fault detection device further includes:

A time updating module, configured to update the start time to the next collection time point according to the order of the collection time points when the third discrete data is not the last data in the discrete data , and return to the continuous data acquisition module to execute taking the start time as a reference and according to the order of the acquisition time points, acquire three continuous discrete data from the preset number of discrete data.

In one of the embodiments, the electrical equipment fault detection device further includes:

Enter the module, when the first discrete data, the second discrete data and the third discrete data do not meet the preset interference condition, enter the detection module to perform detection whether the third discrete data is the discrete The last data in the data.

Since the above-mentioned electrical equipment fault detection device is a device for executing the above-mentioned electrical equipment fault detection method, there is a one-to-one correspondence, and its specific details and features are also one-to-one correspondence, so details are not repeated here.

The technical features of the above embodiments can be combined arbitrarily. To make the description concise, all possible combinations of the technical features in the above embodiments are not described. However, as long as there is no contradiction in the combination of these technical features, they should be It is considered to be within the range described in this specification.

The above examples only express several implementation modes of the present invention, and the description thereof is relatively specific and detailed, but it should not be construed as limiting the scope of the patent for the invention. It should be pointed out that those skilled in the art can make several modifications and improvements without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent for the present invention should be based on the appended claims.

Claims (8)

1. a kind of electrical equipment malfunction detection method, which comprises the following steps:

The electric parameter analog quantity for being input to electrical equipment is obtained, and according to default frequency acquisition, the electric parameter is simulated Amount is sampled, and obtains the discrete data of the corresponding predetermined number of the electric parameter, and record and acquire the discrete data pair The acquisition time answered；

Initialization initial time is to acquire the discrete data corresponding acquisition time at first；

On the basis of the initial time, according to the sequencing of the acquisition time, from the dispersion number of predetermined number According to three continuous discrete datas of middle acquisition, wherein described three continuous discrete datas successively include the first discrete data, second from It dissipates data and third discrete data, first discrete data is the discrete data acquired with the initial time；

When first discrete data, second discrete data and the third discrete data meet default disturbed condition When, it is previous that the second discrete data described in the discrete data is updated to second discrete data corresponding acquisition time The data of period corresponding acquisition；

Detect whether the third discrete data is the last one data in the discrete data；

If so, carrying out Fourier transformation to the discrete data, the corresponding fundametal compoment of the electric parameter analog quantity is obtained, and According to the amplitude of the fundametal compoment, the corresponding virtual value of electric parameter is calculated；

According to the corresponding virtual value of the electric parameter and default electrical parameters, failure detection result is obtained；

Above-mentioned electrical equipment malfunction detection method, further comprises the steps of:

When the third discrete data is not the last one data in the discrete data, according to the elder generation of the acquisition time The initial time is updated to next acquisition time by sequence afterwards, and is returned described using the initial time as base Standard obtains three continuous dispersion numbers according to the sequencing of the acquisition time from the discrete data of predetermined number According to the step of.

2. electrical equipment malfunction detection method according to claim 1, which is characterized in that the default disturbed condition includes When second discrete data is greater than first discrete data and is greater than the third discrete data, second dispersion number According to presupposition multiple be greater than first discrete data and be greater than the third discrete data.

3. electrical equipment malfunction detection method according to claim 1, which is characterized in that the default disturbed condition includes When second discrete data is less than first discrete data and is less than the third discrete data, second dispersion number Greater than first discrete data and it is greater than third discrete data according to divided by presupposition multiple.

4. electrical equipment malfunction detection method according to claim 1, which is characterized in that the detection third is discrete Before the step of whether data are the last one data in the discrete data, further comprise the steps of:

When first discrete data, second discrete data and the third discrete data are unsatisfactory for default disturbed condition When, into the step of whether the third discrete data is the last one data in the discrete data detected.

5. a kind of electrical equipment malfunction detection device characterized by comprising

Discrete data obtains module, for obtaining the electric parameter analog quantity for being input to electrical equipment, and according to default acquisition frequency Rate samples the electric parameter analog quantity, obtains the discrete data of the corresponding predetermined number of the electric parameter, and remember Record acquires the discrete data corresponding acquisition time；

Initialization module is to acquire the discrete data corresponding acquisition time at first for initializing initial time；

Continuous data obtains module, on the basis of the initial time, according to the sequencing of the acquisition time, from Three continuous discrete datas are obtained in the discrete data of predetermined number, wherein described three continuous discrete datas are successively wrapped The first discrete data, the second discrete data and third discrete data are included, first discrete data is with the initial time The discrete data of acquisition；

Update module, for meeting when first discrete data, second discrete data and the third discrete data When default disturbed condition, the second discrete data described in the discrete data is updated to second discrete data is corresponding to adopt Collect the data of the corresponding acquisition of time point previous cycle；

Detection module, for detecting whether the third discrete data is the last one data in the discrete data；

Computing module, for carrying out Fourier transformation to the discrete data when the testing result of the detection module, which is, is, The corresponding fundametal compoment of the electric parameter analog quantity is obtained, and according to the amplitude of the fundametal compoment, calculates electric parameter pair The virtual value answered；

Fault detection module, for obtaining according to the corresponding virtual value of the electric parameter and default electrical parameters Failure detection result；

Above-mentioned electrical equipment malfunction detection device, further includes:

Time update module, for when the third discrete data is not the last one data in the discrete data, according to The initial time is updated to next acquisition time by the sequencing of the acquisition time, and described in return Continuous data obtains module and executes on the basis of the initial time, according to the sequencing of the acquisition time, from default Three continuous discrete datas are obtained in the discrete data of number.

6. electrical equipment malfunction detection device according to claim 5, which is characterized in that the default disturbed condition includes When second discrete data is greater than first discrete data and is greater than the third discrete data, second dispersion number According to presupposition multiple be greater than first discrete data and be greater than the third discrete data.

7. electrical equipment malfunction detection device according to claim 5, which is characterized in that the default disturbed condition includes When second discrete data is less than first discrete data and is less than the third discrete data, second dispersion number Greater than first discrete data and it is greater than third discrete data according to divided by presupposition multiple.

8. electrical equipment malfunction detection device according to claim 5, which is characterized in that further include:

Into module, when first discrete data, second discrete data and the third discrete data be unsatisfactory for it is pre- If when disturbed condition, being executed into the detection module and detecting whether the third discrete data is last in the discrete data One data.