CN116643163B - Remote on-line monitoring system of vacuum circuit breaker - Google Patents
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Abstract
The invention relates to the technical field of electronic digital data processing, in particular to a remote on-line monitoring system of a vacuum circuit breaker, which comprises the following components: the collected current data is converted into frequency domain current data by utilizing Fourier transformation, the confidence coefficient of the harmonic data is obtained according to the amplitude corresponding to each frequency of the frequency domain current data in an analysis window, the influence degree of the harmonic data on the current data is obtained by combining the confidence coefficient of the harmonic data, the influence degree is corrected by the abnormal degree of the data points obtained by the difference among the data points in the current data, and the correction influence degree of the harmonic data is obtained. The correction influence degree of the harmonic data obtained by the invention can accurately reflect the influence degree of the harmonic data existing in the current data on the current data, so that the remote intelligent on-line monitoring of the vacuum circuit breaker can be realized according to the correction influence degree, the accurate reflection can be timely made when the current is abnormal, and the current overload phenomenon is avoided.
Description
Technical Field
The invention relates to the technical field of electronic digital data processing, in particular to a remote on-line monitoring system of a vacuum circuit breaker.
Background
The vacuum circuit breaker is generally configured in a centrally installed switchgear, a double-layer cabinet and a fixed cabinet for controlling and protecting high-voltage electrical equipment, but when current abnormality occurs in the vacuum circuit breaker, the circuit is easy to overload, so that electrical equipment in the circuit is damaged due to the current overload, and even potential safety hazards occur.
The invention provides a remote on-line monitoring system of a vacuum circuit breaker, which processes and analyzes current data by utilizing a remote on-line monitoring mode for acquiring the current data, ensures timely reflection when the current data in the vacuum circuit breaker is abnormal, and ensures the performance and safe operation of each device and electric equipment in a circuit.
It is often necessary to monitor the current change of the vacuum circuit breaker, the magnitude of the current through the vacuum circuit breaker, and the stability and ripple conditions of the current, which abnormal current ripple may indicate a fault or overload condition. If the current exceeds the rated current or the design load, an overload condition is indicated. The overload current may cause the device to overheat, damage or trigger the protective device action.
In the prior art, when a current signal is analyzed, a fourier transform algorithm is generally used for detecting the current signal, the fourier transform algorithm converts the current signal into a frequency domain space, and a change rule of the signal can be accurately observed, so that the current signal is accurately detected. However, because the current is influenced by the harmonic data and the abrupt current in the current signal influences the harmonic current, the influence degree of the harmonic data cannot be accurately judged only according to the distribution of the signals in the frequency domain, and therefore the method and the device correct the influence degree of the harmonic data by carrying out initial evaluation on the harmonic data and then carrying out correction according to the change of the original data.
Disclosure of Invention
The invention provides a remote on-line monitoring system of a vacuum circuit breaker, which aims to solve the existing problems.
The invention relates to a remote on-line monitoring system of a vacuum circuit breaker, which adopts the following technical scheme:
the invention provides a remote on-line monitoring system of a vacuum circuit breaker, which comprises the following modules:
and a data acquisition module: the method comprises the steps of collecting current data in a vacuum circuit breaker;
and a data decomposition module: carrying out frequency domain transformation processing on the current data to obtain frequency domain current data and harmonic data corresponding to any frequency; marking a window with a preset length as an analysis window, and obtaining the confidence coefficient of the harmonic data according to the amplitude value of the frequency in the analysis window and the difference between the amplitude values corresponding to the adjacent frequencies; obtaining the influence degree of the corresponding harmonic data according to the confidence level of the harmonic data and the amplitude values corresponding to all frequencies;
a data anomaly analysis module: obtaining abnormal degrees of data points in the current data according to differences among the data points in the current data and the amplitude of the frequency, and obtaining abnormal points according to the abnormal degrees;
and the data monitoring module is used for: obtaining the influence degree of abnormal harmonic data according to the abnormal points; acquiring a period of current data; obtaining correction influence degree of harmonic data according to the period of the current data, the influence degree of harmonic data, the influence degree of abnormal harmonic data and the extreme value in the current data; and the intelligent remote on-line monitoring of the vacuum circuit breaker is realized by utilizing the magnitude of the correction influence degree.
Further, the frequency domain transformation processing is performed on the current data to obtain frequency domain current data and harmonic data corresponding to any frequency, and the method comprises the following specific steps:
firstly, carrying out Fourier transform on current data, converting the current data into a frequency domain space, and recording the data after carrying out Fourier transform on the current data as frequency domain current data;
then, the amplitude corresponding to any frequency in the frequency domain current data is obtained, a sinusoidal signal is constructed, the frequency and the corresponding amplitude are used as the frequency and the amplitude of the sinusoidal signal, the sinusoidal signal and the current data are added, and the added result data are recorded as harmonic data.
Further, the method for obtaining the confidence coefficient of the harmonic data according to the difference between the amplitude of the frequency in the analysis window and the amplitude corresponding to the adjacent frequency comprises the following specific steps:
firstly, constructing a preset length for traversing frequency domain current data frequency by frequency asIs marked as an analysis window; acquiring the amplitude values corresponding to all frequencies in an analysis window;
then, combining an analysis window, and obtaining the confidence coefficient of the harmonic data according to the frequency domain current data obtained after Fourier transformation, wherein the specific calculation method comprises the following steps:
in the formula ,representing the%>Confidence of the frequency-corresponding harmonic data, +.>Representing the first in the analysis windowAmplitude corresponding to frequency, ++>Representing the%>Amplitude corresponding to frequency, ++>Representing a linear normalization function, ++>Representing a preset hyper-parameter.
Further, the method for obtaining the influence degree of the harmonic data comprises the following steps:
first, the analysis window is acquiredAt each frequency, corresponding to a maximum value of confidence of the harmonic data;
then, the specific calculation method of the influence degree of the harmonic data is as follows:
in the formula ,indicate->The individual frequencies correspond to the degree of influence of the harmonic data; />Representing the maximum value of the confidence coefficient of the corresponding harmonic data under all frequencies in an analysis window where the harmonic data are located; />Representing the +.>Confidence of the harmonic data corresponding to the frequencies; />Indicating within the analysis window>Corresponding amplitude values at the respective frequencies; />Indicating within the analysis window>Amplitude of the individual frequencies; />Indicate->Amplitude corresponding to frequency, and +.>Slope formed by amplitude values corresponding to the frequencies; />Representing preset super parameters; />Representing natural constants.
Further, the outlier acquisition method comprises the following steps:
first, the first current data is obtainedData points and->The data points are marked as amplitude differences corresponding to the amplitude differences of the frequencies, a plurality of amplitude differences are obtained, the amplitude differences with the values larger than 0 are marked as positive amplitude differences, and the number of all the positive amplitude differences is obtained;
then, the degree of abnormality of the data points is calculated by the following specific method:
wherein ,indicating the%>Degree of abnormality of data points +.>Indicating +.>The data points correspond to the magnitudes of the frequencies; />Indicate->A positive amplitude difference; />Indicating the number of positive amplitude differences,an exponential function based on a natural constant;
finally, presetting an abnormality degree threshold according to experience, and recording data points with the abnormality degree larger than the abnormality degree threshold as abnormal points to obtain a plurality of abnormal points.
Further, the correction influence degree obtaining method is as follows:
firstly, utilizing a period for obtaining current data according to the frequency of alternating current passing through a circuit in which a vacuum circuit breaker is positioned; acquiring the amplitude values of a plurality of maximum values and minimum value data points in any half period of current data; the time points corresponding to the maximum value and the minimum value are set; recording the influence degree of the harmonic data under the corresponding frequency in the frequency domain current data after Fourier transformation of any abnormal point in the current data as the influence degree of the abnormal harmonic data;
then, the difference between the influence degree of any harmonic data and the accumulated sum of the influence degrees of all abnormal harmonic data is recorded as an influence difference; recording the ratio of the difference between the maximum value and the minimum value and the difference between the corresponding time points of the maximum value and the minimum value as a reference period; the ratio of the reference period to the period of the current data is recorded as a first period factor, and the period factor is compared with the period of the current dataThe accumulated value of the absolute value of the difference is marked as a second periodic factor, and the result of the product between the influence difference and the second periodic factor is marked as the correction influence degree of the harmonic data.
Further, the intelligent remote on-line monitoring of the vacuum circuit breaker is realized by utilizing the correction of the influence degree, and the method comprises the following specific steps:
and when the correction influence degree of the harmonic data is larger than the correction influence degree threshold, the harmonic current corresponding to the harmonic data in the vacuum circuit breaker is indicated, and the influence degree of the harmonic data on the current in the vacuum circuit breaker is larger, so that the circuit is closed and an alarm is given when the vacuum circuit breaker is abnormal, the running state of the current in the vacuum circuit breaker is detected by a remote on-line monitoring method, and the intelligent remote on-line monitoring of the vacuum circuit breaker is realized.
The technical scheme of the invention has the beneficial effects that: when the current data of the vacuum circuit breaker is monitored, the operating state of the vacuum circuit breaker is abnormal because the current is influenced by the harmonic data, so that the influence degree of the current data is judged according to the change of the harmonic data by monitoring the harmonic data in the current data, and further the remote monitoring of the vacuum circuit breaker is realized. In judging the degree of influence of the harmonic data, since the harmonic data is different from the frequency of the original current signal, it is converted into the frequency domain space by fourier transform, and then the initial degree of influence of the harmonic data is obtained from the distribution of the different frequency signals in the frequency domain space. However, because the harmonic data is affected by the abrupt signal, the influence of the abrupt signal is removed according to the change of the data amplitude in the original signal, and then the influence degree of the harmonic data is corrected, so that the influence degree of the obtained harmonic data can accurately reflect the influence of the harmonic data existing in the original signal, and further the monitoring of the vacuum circuit breaker is more accurate.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a block flow diagram of a remote on-line monitoring system for a vacuum circuit breaker according to the present invention.
Detailed Description
In order to further describe the technical means and effects adopted by the invention to achieve the preset aim, the following is a detailed description of a remote on-line monitoring system for a vacuum circuit breaker according to the invention, which is provided by combining the accompanying drawings and the preferred embodiment, wherein the detailed description is as follows. In the following description, different "one embodiment" or "another embodiment" means that the embodiments are not necessarily the same. Furthermore, the particular features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
The following specifically describes a specific scheme of the remote on-line monitoring system for the vacuum circuit breaker provided by the invention with reference to the accompanying drawings.
Referring to fig. 1, a block flow diagram of a remote on-line monitoring system for a vacuum circuit breaker according to an embodiment of the invention is shown, the system includes the following blocks:
and a data acquisition module: for acquiring current data in a vacuum circuit breaker by means of a current sensor.
Firstly, a current sensor or a current transformer is arranged on a circuit where a vacuum circuit breaker is arranged, wherein the sensor can be a non-contact current sensor such as a magnetic sensor or a contact current sensor such as a clamp sensor;
then, collecting current data in the vacuum circuit breaker by using an installed current sensor or a current transformer;
and finally, transmitting the detected current data to a signal receiver through a built-in WiFi module of the current sensor, and transmitting the current data to a processor containing a subsequent module by the signal receiver through a wired transmission method to perform remote processing analysis on the current data.
The current data is time series data.
And a data decomposition module: the method is used for decomposing the current data and analyzing the decomposed data to obtain the influence degree of the harmonic data on the current data.
In order to analyze current data of a vacuum circuit breaker, it is determined whether the current data is abnormal. Anomalies in current data are typically due to current exceeding a rated current or design load, causing the device to overheat, damage or trigger a protective device action.
In addition, when the current is monitored, transient current can impact or instability to equipment and a power grid by analyzing changes of the transient current, such as starting current or current abrupt change in a short time, and the transient current needs to be recognized and processed in time; meanwhile, harmonic current needs to be monitored, namely harmonic components in the monitored current, particularly higher harmonics, the harmonic current is possibly caused by nonlinear loads, overheat, vibration or other faults of equipment are caused, voltage distortion can be caused when the harmonic current passes through reactive elements, stability of a power grid is affected, voltage fluctuation is large, adverse effects are generated on equipment of other users, additional loss of windings and conductors are caused, the electric equipment is overheated, ageing and service life of the equipment are shortened, the higher the frequency of the harmonic current is, the damage degree of components is larger, and therefore current data of a circuit where a vacuum circuit breaker is located needs to be monitored to judge whether abrupt current and harmonic current exist or not.
The current harmonic wave is an alternating current circuit, the current comprises a plurality of frequency-doubled sine wave components besides a fundamental wave, the fundamental wave is power grid power frequency, the frequencies of the sine wave components are integer multiples of the fundamental wave frequency respectively, the frequency is called the current harmonic wave, the current harmonic distortion (THD) is one of indexes reflecting the degree of the current harmonic wave, and the effective value of the current of all non-fundamental wave components in the alternating current is divided by the effective value of the current fundamental wave.
In general, the larger the current harmonic distortion rate is, the higher the proportion of harmonic components in the total current is, the worse the load capacity and stability of a circuit are, and when analyzing current data, since harmonic data is a high-frequency signal based on fundamental waves, when noise exists in the current data, noise signals are added to the fundamental wave data, and erroneous judgment on the harmonic data is caused, so that it is necessary to distinguish the harmonic data from the noise according to the characteristics of the harmonic data.
Because the harmonic wave refers to each sub-component which is obtained by carrying out Fourier series decomposition on the periodic non-sinusoidal alternating current and is larger than integral multiple of fundamental wave frequency, and the noise signal is randomly changed, amplitude deviation of harmonic wave data can be caused, and judgment on abrupt current is influenced, the current data is processed by utilizing Fourier transformation, and the processed data is analyzed, and the method specifically comprises the following steps:
firstly, carrying out Fourier transform on current data, converting the current data into a frequency domain space, and recording the data after carrying out Fourier transform on the current data as frequency domain current data;
the distribution of different frequency signals in the current data can be clearly obtained in the frequency domain space, and the corresponding amplitude values under different frequencies in the frequency domain current data show that the more the number of data components of the current data under the corresponding frequencies in the current data; in addition, in the current data, the harmonic data always accompanies the fundamental wave data, and the frequency of the harmonic data is higher than that of the fundamental wave data, so that in the current data, in the frequency domain current data after fourier transformation, a plurality of continuous spectrum peaks exist, and at the same time, a spectrum peak corresponding to a noise signal exists;
then, acquiring amplitude corresponding to any frequency in the frequency domain current data, constructing a sinusoidal signal, taking the frequency and the corresponding amplitude as the frequency and the amplitude of the sinusoidal signal, adding the sinusoidal signal and the current data, and recording the added result data as harmonic data corresponding to the frequency;
in addition, any one frequency in the frequency current data corresponds to one harmonic data, and any one frequency corresponds to one amplitude.
Step (2), constructingA preset length for traversing frequency domain current data one by one isThe window is marked as an analysis window, and the confidence coefficient of the harmonic data is obtained according to the frequency domain current data obtained after Fourier transformation by combining the analysis window, and the specific calculation method comprises the following steps:
in the formula ,representing the%>Confidence of the frequency-corresponding harmonic data, +.>Representing the first in the analysis windowAmplitude corresponding to frequency, ++>Representing the%>Amplitude corresponding to frequency, ++>Representing a linear normalization function, ++>Representing preset super parameters;
and obtaining the confidence coefficient of the corresponding harmonic data under all frequencies in the frequency domain current data.
In this embodiment, the super parameters are empirically determinedThe preset value is 7, and the adjustment can be performed according to the actual application condition, and the embodiment is not particularly limited;
in the traversal process of the analysis window, one frequency in the frequency domain current data corresponds to one analysis window, and the analysis window is used as the analysis window of the first frequency in the window;
first confidence factorRepresenting the continuity of the frequency domain current data>The frequency corresponds to the product of the magnitudes, because the fundamental wave data and the harmonic wave data exist simultaneously in the current data, and the frequency of the harmonic wave data is higher than that of the fundamental wave data, for example, the frequency of the third harmonic wave, the fifth harmonic wave, the seventh harmonic wave and the like is higher than that of the fundamental wave data; in the spectrogram of the frequency domain current data, the amplitude of the data under the continuous frequency is analyzed to represent possible harmonic data, and if the confidence factor is larger, the +.>Continuous after each frequency point->The amplitudes corresponding to the frequencies are larger, so that the possibility of harmonic data or noise signals is higher;
second confidence factorThe absolute value of the difference representing the corresponding amplitude at two consecutive frequencies is assumed to be the +.>When the frequency correspondence data is fundamental wave data of the current signal, then +.>Frequency and->The difference of the frequency signals is relatively large, but the signal of the next frequency is harmonic data, so the change degree of the signal in a section of frequency interval is reflected according to the change of the continuous frequency signal. Here->The empirical value was taken to be 7 (empirical value).
And (3) analyzing the frequency domain harmonic data, and combining the confidence level of the harmonic data to obtain the influence degree of the harmonic data.
The more the number of frequencies corresponding to the harmonic data in the current data, the greater the influence degree on the current data, the influence degree of the harmonic data is obtained to reflect the difference between the harmonic data and the noise data, and the interference of the noise data on the harmonic data is eliminated.
According to the distribution of the frequency domain current data, the influence degree of the harmonic data on the current data is obtained and is recorded as the influence degree of the harmonic data, and the specific obtaining method comprises the following steps:
first, the arbitrary analysis window is acquiredThe maximum value of the confidence of the corresponding harmonic data at each frequency is recorded as；
Then, the influence degree of any frequency corresponding harmonic data in the frequency domain current data is obtained, and the specific calculation method comprises the following steps:
in the formula ,indicate->Shadow of harmonic data corresponding to each frequencyThe degree of ringing; />Representing the maximum value of the confidence coefficient of the corresponding harmonic data under all frequencies in an analysis window where the harmonic data are located; />Representing the +.>Confidence of the harmonic data corresponding to the frequencies; />Indicating within the analysis window>Corresponding amplitude values at the respective frequencies; />Indicating within the analysis window>Amplitude of the individual frequencies; />Indicate->Amplitude corresponding to frequency, and +.>Slope formed by amplitude values corresponding to the frequencies; />Representing preset super parameters; />Representing natural constants;
indicate->The distribution characteristics of the frequency domain current data are that the waveform continuously changes within a certain frequency range, and the amplitude corresponding to the frequency is gradually increased along with the increase of the frequency, so that the influence degree of any frequency in the frequency domain current data corresponding to the harmonic data is obtained by using the maximum confidence;
representing the degree of variation in amplitude among all the data in the analysis window;
representing the accumulated value of the slope formed by the amplitude values corresponding to all adjacent frequencies in the analysis window, and if harmonic data exist, the accumulated value of the slope is a positive number; if noise data exist, the accumulated value in the analysis window is a negative number; therefore, the influence degree of the harmonic is judged according to the change of the slope, and the more higher harmonics are, the larger the accumulated value of the slope is, and therefore the influence degree of the harmonic on the current data is larger.
A data anomaly analysis module: and obtaining the degree of abnormality according to the difference of the amplitude values at different positions in the current signal, and removing the abnormal data according to the degree of the abnormality.
According to the degree of influence of the harmonic wave obtained by the calculation on the current, the abnormality of the harmonic wave is reflected according to the change of the harmonic wave in the current data, and because harmonic data and abrupt data exist in the current data, and when the abrupt data and the harmonic data occur simultaneously, the harmonic data are distorted due to the existence of the abrupt data, the degree of influence of the harmonic data needs to be corrected according to the change of the current data.
When the influence degree of the harmonic data is corrected according to the change of the current data, the change condition of the current data is changed due to the existence of the harmonic data, so that the waveform of the current data loses the sine characteristic of alternating current, and the waveform of the current data may have characteristics such as distortion, asymmetry or saw tooth.
The magnitude of the obtained degree of influence of the harmonic current is actually smaller than the original degree of influence of the harmonic current according to the change of different frequencies in the frequency domain current data after the fourier transform, so that it is necessary to obtain an accurate degree of influence of the harmonic current according to the degree of abnormality of the data points in the current data.
First, the first current data is obtainedData points and->Data points, the difference value of the amplitude of the corresponding frequency is recorded as the amplitude difference, a plurality of amplitude differences are obtained, and the amplitude difference with the value larger than 0 is recorded as positive amplitude difference +.>The number of all positive amplitude differences is recorded as +.>The abnormal degree of the data points in the current data is obtained according to the change of the current data, and the specific calculation method comprises the following steps:
wherein ,indicating the%>Degree of abnormality of data points +.>Indicating +.>The data points correspond to the magnitudes of the frequencies; />Indicate->A positive amplitude difference; />Indicating the number of positive amplitude differences,an exponential function based on a natural constant is represented.
When the current in the circuit is unstable, the current can be changed greatly, so that the change degree of the current is represented by acquiring the difference value of the current between the continuous data points, and when the numerical value of the adjacent data points in the current data always presents a rising state, the amplitude difference is positive, and the current abnormality degree of the circuit where the vacuum circuit breaker is larger; in addition, the larger the number of positive amplitude differences, the larger the abnormal value of the current data in the circuit, and the larger the number of occurrences of data points of the same frequency in the current data, the more the current data in the frequency domainThe larger the amplitude corresponding to the frequency, the unstable current of the circuit where the vacuum circuit breaker is located.
Then presetting an abnormality degree threshold value as 1 according to experience, marking data points with the abnormality degree larger than the abnormality degree threshold value as abnormal points, and obtaining a plurality of abnormal points;
it should be noted that, the preset threshold value of the degree of abnormality is an empirical value, and may be adjusted according to the actual application, and the embodiment is not limited specifically.
And the data monitoring module is used for: and obtaining the correction influence degree of the harmonic data according to the influence degree of the harmonic data, and realizing the on-line monitoring of the current data.
First, according to the electricity of the vacuum breakerIn the road, the frequency of the passing alternating current obtains the period of the current data；
The domestic standard AC frequencyIs->According to the conversion relation between frequency and periodCycle of obtaining current data +.>；
In addition, the amplitude values of a plurality of maximum values and minimum value data points in any half period in the current data are respectively recorded as and />The method comprises the steps of carrying out a first treatment on the surface of the The time points corresponding to the maximum value and the minimum value are respectively marked as +.> and />The method comprises the steps of carrying out a first treatment on the surface of the Recording the influence degree of the harmonic data under the corresponding frequency in the frequency domain current data after Fourier transformation of any abnormal point in the current data as the influence degree of the abnormal harmonic data;
then, since the harmonic data causes waveform distortion of the current data, the correction influence degree of any harmonic data is obtained according to the abnormal degree of the data points in the current data, and the specific calculation method is as follows:
in the formula ,representing the degree of correction influence of harmonic data, +.>Representing the extent of influence of harmonic data, +.>Indicate->The degree of influence of abnormal harmonic data at each frequency; />The number of corresponding frequencies of abnormal points in the current data after Fourier transformation is represented; />Indicating the%>Amplitude of each maximum data point, +.>Indicating the%>The magnitudes of the individual minima data points; />Indicating the%>Time points corresponding to the maximum data points, < ->Indicating the%>A time point corresponding to the minimum data point; />Representing the number of maximum or minimum data points; />A period representing current data;
influence of differencesThe difference between the influence degree of any harmonic data and all abnormal harmonic data on the current data is reflected, and the larger the difference is, the larger the correction influence degree of the harmonic data is, the larger the influence of the harmonic data on the current data is, and the more the current data is likely to be abnormal.
Reference periodReflects the actual period size after the current data is affected by the harmonic data; minus->In the method for calculating the correction influence degree of the harmonic data, the amplitude values and the time points of the maximum value and the minimum value data points are acquired in a half period of the current data, so that when the period of the current data is more similar to the reference period, the reference period of the current data is more likely to be a normal period, and the smaller the influence of the harmonic data on the current data in the period is, the more normal the current data is; otherwise, the current data is abnormal.
Finally, presetting a correction influence degree threshold value to be 0.1 according to experience according to the correction influence degree of the harmonic data, and when the correction influence degree of the harmonic data is larger than the correction influence degree threshold value, indicating that harmonic current corresponding to the harmonic data in the vacuum circuit breaker has larger influence degree on current in the vacuum circuit breaker, so that the vacuum circuit breaker is abnormal, closing a circuit and alarming, and detecting the running state of the current in the vacuum circuit breaker by a remote on-line monitoring method to ensure the normal and safe running of the vacuum circuit breaker and the circuit.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.
Claims (4)
1. A remote on-line monitoring system for a vacuum circuit breaker, comprising the following modules:
and a data acquisition module: the method comprises the steps of collecting current data in a vacuum circuit breaker;
and a data decomposition module: carrying out frequency domain transformation processing on the current data to obtain frequency domain current data and harmonic data corresponding to any frequency; marking a window with a preset length as an analysis window, and obtaining the confidence coefficient of the harmonic data according to the amplitude value of the frequency in the analysis window and the difference between the amplitude values corresponding to the adjacent frequencies; obtaining the influence degree of the corresponding harmonic data according to the confidence level of the harmonic data and the amplitude values corresponding to all frequencies;
a data anomaly analysis module: obtaining abnormal degrees of data points in the current data according to differences among the data points in the current data and the amplitude of the frequency, and obtaining abnormal points according to the abnormal degrees;
and the data monitoring module is used for: obtaining the influence degree of abnormal harmonic data according to the abnormal points; acquiring a period of current data; obtaining correction influence degree of harmonic data according to the period of the current data, the influence degree of harmonic data, the influence degree of abnormal harmonic data and the extreme value in the current data; the intelligent remote on-line monitoring of the vacuum circuit breaker is realized by utilizing the correction influence degree;
the method for obtaining the confidence coefficient of the harmonic data according to the amplitude value of the frequency in the analysis window and the difference between the amplitude values corresponding to the adjacent frequencies comprises the following specific steps:
first, a pair of frequency domain current numbers is constructedThe preset length according to the frequency-by-frequency traversal isIs marked as an analysis window; acquiring the amplitude values corresponding to all frequencies in an analysis window;
then, combining an analysis window, and obtaining the confidence coefficient of the harmonic data according to the frequency domain current data obtained after Fourier transformation, wherein the specific calculation method comprises the following steps:
in the formula ,representing the +.>Confidence of the frequency-corresponding harmonic data, +.>Representing the amplitude of the frequency corresponding to v in the analysis window corresponding to i frequency in the frequency domain current data,/v>Representing the v +.sup.th in the analysis window corresponding to the i-th frequency in the frequency domain current data>Amplitude corresponding to the frequency, < >>Representing a linear normalization function;
the method for acquiring the influence degree of the harmonic data comprises the following steps:
first, the analysis window is acquiredFrequency of personalAt the rate, the maximum value of the confidence coefficient of the harmonic data is corresponding;
then, the specific calculation method of the influence degree of the harmonic data is as follows:
in the formula ,representing the +.>The individual frequencies correspond to the degree of influence of the harmonic data; />Representing the maximum value of the confidence coefficient of the corresponding harmonic data under all frequencies in an analysis window where the harmonic data are located; />Representing the +.>Confidence of the harmonic data corresponding to the frequencies; />Representing the corresponding amplitude value of the ith frequency in the frequency domain current data in an analysis window corresponding to the ith frequency; />Representing the ith frequency in the frequency domain current data within the analysis window corresponding to the ith frequencyAmplitude of the individual frequencies; />Representing the frequency domain currentAmplitude corresponding to the ith frequency in the analysis window corresponding to the ith frequency in the data, is equal to the +.>Slope formed by amplitude values corresponding to the frequencies; />Representing natural constants;
the abnormal point acquisition method comprises the following steps:
first, the first current data is obtainedData points and->The data points are marked as amplitude differences corresponding to the amplitude differences of the frequencies, a plurality of amplitude differences are obtained, the amplitude differences with the values larger than 0 are marked as positive amplitude differences, and the number of all the positive amplitude differences is obtained;
then, the degree of abnormality of the data points is calculated by the following specific method:
wherein ,indicating the%>Degree of abnormality of data points +.>Indicating +.>The data points correspond to the magnitudes of the frequencies; />Indicate->A positive amplitude difference; />Indicating the number of positive amplitude differences,an exponential function based on a natural constant;
finally, presetting an abnormality degree threshold according to experience, and recording data points with the abnormality degree larger than the abnormality degree threshold as abnormal points to obtain a plurality of abnormal points.
2. The remote on-line monitoring system of a vacuum circuit breaker according to claim 1, wherein the frequency domain transformation processing is performed on the current data to obtain frequency domain current data and harmonic data corresponding to any frequency, and the method comprises the following specific steps:
firstly, carrying out Fourier transform on current data, converting the current data into a frequency domain space, and recording the data after carrying out Fourier transform on the current data as frequency domain current data;
then, the amplitude corresponding to any frequency in the frequency domain current data is obtained, a sinusoidal signal is constructed, the frequency and the corresponding amplitude are used as the frequency and the amplitude of the sinusoidal signal, the sinusoidal signal and the current data are added, and the added result data are recorded as harmonic data.
3. The remote on-line monitoring system of a vacuum circuit breaker according to claim 1, wherein the correction influence degree obtaining method comprises the following steps:
firstly, utilizing a period for obtaining current data according to the frequency of alternating current passing through a circuit in which a vacuum circuit breaker is positioned; acquiring the amplitude values of a plurality of maximum values and minimum value data points in any half period of current data; the time points corresponding to the maximum value and the minimum value are set; recording the influence degree of the harmonic data under the corresponding frequency in the frequency domain current data after Fourier transformation of any abnormal point in the current data as the influence degree of the abnormal harmonic data;
then, the difference between the influence degree of any harmonic data and the accumulated sum of the influence degrees of all abnormal harmonic data is recorded as an influence difference; recording the ratio of the difference between the maximum value and the minimum value and the difference between the corresponding time points of the maximum value and the minimum value as a reference period; the ratio of the reference period to the period of the current data is recorded as a first period factor, and the period factor is compared with the period of the current dataThe accumulated value of the absolute value of the difference is marked as a second periodic factor, and the result of the product between the influence difference and the second periodic factor is marked as the correction influence degree of the harmonic data.
4. The remote on-line monitoring system for vacuum circuit breaker according to claim 1, wherein the intelligent remote on-line monitoring for vacuum circuit breaker is realized by utilizing the correction of the influence degree, comprising the following specific steps:
and when the correction influence degree of the harmonic data is larger than the correction influence degree threshold, the harmonic current corresponding to the harmonic data in the vacuum circuit breaker is indicated, and the influence degree of the harmonic data on the current in the vacuum circuit breaker is larger, so that the circuit is closed and an alarm is given when the vacuum circuit breaker is abnormal, the running state of the current in the vacuum circuit breaker is detected by a remote on-line monitoring method, and the intelligent remote on-line monitoring of the vacuum circuit breaker is realized.
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