Cable local damping evaluation method combining ultra-low frequency dielectric loss and broadband impedance spectroscopy test

Abstract

The invention relates to a cable local damping evaluation method combining ultra-low frequency dielectric loss and broadband impedance spectroscopy testing. The method comprises the steps that S1, the dielectric loss change rate, the dielectric loss stability along with time and the dielectric loss average value of a tested cable are obtained through VLF; s2, obtaining a time domain positioning map by using a BIS, and calculating the polarity deviation degree of each reflection peak; s3, calculating a damp risk index of the tested cable; s4, establishing a local damp assessment model; and S5, substituting the data of S1 to S3 into the local damping evaluation model of S4, calculating a damping state evaluation value, and evaluating the local damping degree of the tested cable. According to the method, indexes obtained by the ultra-low frequency dielectric loss test (VLF) and the broadband impedance spectroscopy (BIS) are comprehensively considered, the characteristics of the cable are combined, a new cable local damping evaluation model is established, and the accuracy of cable local damping state evaluation is improved.

Description

Technical Field

[0001] The invention belongs to the technical field of cable insulation defect detection, and in particular relates to a cable local moisture assessment method combining ultra-low frequency dielectric loss and broadband impedance spectrum testing. Background Art

[0002] With the acceleration of urbanization, power cables are gradually replacing traditional overhead lines and are widely used in urban power distribution networks due to their advantages such as high reliability, large power transmission and space saving. According to relevant statistics, the average annual growth rate of the length of power cable lines in my country has exceeded 10% in recent years, and the cableization rate in the central urban areas of cities such as Shanghai, Shenzhen and Xiamen has reached more than 90%. It can be seen that power cables occupy an important position in the modernization process of my country's power distribution network.

[0003] Cables are usually laid in cable trenches with long-term water accumulation, or directly buried in moist soil. When operating in a humid environment, if the cable itself has problems such as damaged outer sheath or insufficient protection measures for the intermediate joints, it is easy to get damp due to the intrusion of water, and then there will be problems such as excessive dielectric loss or low insulation resistance, threatening the safe operation of the cable. And as the service time of the cable increases, the dampness of the cable will further deteriorate, and in severe cases it will develop into permanent faults such as short circuit and open circuit. Once a cable fault occurs, it will cause the power distribution system to shut down or even lose control, causing huge economic losses and social impact. Therefore, timely detection of cable dampness, locating the local dampness position of the cable, and evaluating its dampness degree are of great significance to improving the safety and stability of the cable transmission system.

[0004] At present, among the commonly used cable moisture detection and positioning methods, the very low frequency dielectric loss test (VLF) can measure the overall insulation of the cable and judge the overall moisture status of the cable, but the sensitivity of identifying local moisture defects is low and cannot fully meet the testing requirements. Broadband impedance spectroscopy (BIS) is widely used in the field of cable defect positioning as a non-destructive testing method. It can locate the local moisture position of the cable, but the abnormal peak-to-peak value of the moisture position reflected in its positioning map is determined by the moisture position, moisture degree, cable characteristics and other factors, and cannot accurately reflect the moisture degree of the position. However, in the existing cable moisture detection and positioning methods, there is a lack of solutions for accurately evaluating the moisture degree.

[0005] Therefore, developing a cable local moisture assessment method that combines ultra-low frequency dielectric loss and broadband impedance spectrum testing is of great significance for the assessment of the cable's moisture status. Summary of the invention

[0006] The purpose of the present invention is to overcome the deficiencies of the prior art and provide a cable local moisture assessment method combining ultra-low frequency dielectric loss and broadband impedance spectrum testing.

[0007] The present invention solves the technical problem by the following technical solutions:

[0008] A method for evaluating local moisture in a cable by combining ultra-low frequency dielectric loss and broadband impedance spectrum testing, the method comprising the following steps:

[0009] S1. Use the ultra-low frequency dielectric loss meter to measure the cable under test and obtain the dielectric loss change rate Δtanδ and dielectric loss stability σ of the cable under test. tanδ And the average dielectric loss tanδ a ;

[0010] S2. Measure the cable under test by broadband impedance spectroscopy to obtain a standardized time domain positioning spectrum. Record the reflection peak positions except the head end and tail end, label them in sequence according to their distance from the head end, and calculate the polarity deviation of each reflection peak δ p ;

[0011] S3. Query the record of the tested cable and calculate the moisture risk index DRI of the tested cable based on the laying environment and laying method;

[0012] S4. Process the measurement data of S1 to S3 by principal component analysis, establish a local moisture assessment model, and obtain the weight of each indicator ω j ;

[0013] S5. Substitute the measurement data of S1 to S3 into the local moisture assessment model, calculate the moisture state assessment value of the position, and assess the local moisture degree of the measured cable based on the value.

[0014] Moreover, the polarity deviation δ of the two reflection peaks at the same position in S2 is p The calculation formula is:

[0015]

[0016] Where: p(k) is the polarity deviation of the kth reflection peak;

[0017] α is the double peak correction coefficient, which is 0.4;

[0018] E r(k) is the extreme value of the right peak at the position of the kth reflection peak;

[0019] E l(k) is the extreme value of the left peak at the position of the kth reflection peak;

[0020] d(k) is the distance from the kth reflection peak to the tail reflection peak;

[0021] A is the extreme value of the end reflection peak;

[0022] For the polarity deviation δ of a single reflection peak at the same position p The calculation formula is:

[0023]

[0024] Where: E(k) is the extreme value of the kth reflection peak.

[0025] Moreover, the moisture risk index calculation formula of the S3 cable is:

[0026]

[0027] Where: I is the laying influence factor, which is determined according to the different laying methods of the tested cable;

[0028] T is the cable laying time;

[0029] The annual average relative humidity of the cable laying area;

[0030] IP is the cable waterproof grade. If IP=0, DRI=1.

[0031] Moreover, the weight of each index in S4 is j The calculation formula is:

[0032]

[0033] Where: j is the weight of the jth indicator;

[0034] m is the number of principal components of the data retained by the principal component analysis method;

[0035] p is the number of indicators;

[0036] λ i is the variance contribution rate of the i-th principal component;

[0037] a ji is the loading of the jth indicator in the i-th principal component.

[0038] Moreover, the calculation formula of the moisture state evaluation value G of S5 is:

[0039] G(k)=ω 1 Δtanδ+ω 2 tanδ a +ω 3 σ tanδ +ω 4 δ p(k) +ω 5 DRI (5)

[0040] Where:1 ,ω 2 ,ω 3 ,ω 4 and ω 5 They are the dielectric loss change rate Δtanδ and the dielectric loss average tanδ a , dielectric loss stability over time σ tanδ 、The polarity deviation of the position δ p(k) The influence weight of the cable moisture risk index DRI can be calculated and compared with the moisture status assessment reference table according to the value of G(k) to evaluate the moisture degree of the tested cable at that location.

[0041] The positive effects that the present invention can produce are:

[0042] 1. The present invention comprehensively considers the indicators obtained by ultra-low frequency dielectric loss test (VLF) and broadband impedance spectroscopy (BIS), combines the characteristics of the cable itself, and establishes a new cable local moisture assessment model to improve the accuracy of the assessment of the local moisture status of the cable.

[0043] 2. The present invention analyzes the tested cables at a wind farm test site and obtains the on-site disassembly and inspection results.

[0044] The results are consistent with the evaluation of the present invention, while the use of VLF or BIS method alone to judge the moisture condition of the tested cable cannot make an accurate evaluation of the moisture condition of the cable. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 is a flow chart of the present invention;

[0046] Figure 2 This is a schematic diagram of a wind farm test site of the present invention;

[0047] Figure 3 This is the positioning spectrum obtained by the BIS method of the present invention;

[0048] Figure 4 This is a schematic diagram of the on-site dismantling and inspection of the intermediate joint at 715m according to the present invention. DETAILED DESCRIPTION

[0049] The present invention is further described in detail below through specific examples. The following examples are only illustrative and not restrictive, and the protection scope of the present invention cannot be limited thereto.

[0050] like Figure 1 As shown, a cable local moisture assessment method combining ultra-low frequency dielectric loss and broadband impedance spectrum testing is innovative in that the steps of the method are:

[0051] S1. Use an ultra-low frequency dielectric loss meter to measure the cable under test and obtain three indicators: dielectric loss change rate, dielectric loss stability over time and dielectric loss average value;

[0052] S2. Measure the tested cable by BIS method, obtain the positioning spectrum, determine the position of the abnormal peak, and calculate its polarity deviation;

[0053] S3. Check the cable inventory and calculate the cable moisture risk index based on the laying environment and laying method;

[0054] S4, processing the field test data including the indicators in S1 to S3 by principal component analysis (PCA) to obtain a local moisture assessment model;

[0055] S5. Substitute the various indicators obtained in S1 to S3 into the local moisture assessment model, calculate the moisture status assessment value of the location, and evaluate the local moisture degree of the cable based on this.

[0056] The specific contents of each process are as follows:

[0057] 1. Determine the cable to be tested, open the electrical connection between the cable terminal and the switch cabinet, transformer and other equipment, check whether the cable terminal is clean and in good condition, put a voltage equalizing ring on the nose of the cable terminal, connect one end of the high-voltage connecting cable to the cable terminal to be tested, and the other end to the test host, and ground the other phase cable terminals to the detection device.

[0058] Before testing, enter the cable name, length, cable insulation type, laying method and other information on the test host, and select the oil-paper cable or cross-linked cable test program. After clicking Start Test, pressurize the cable under test, set the frequency to 0.1Hz, and test at 0.5U 0 ,1.0U 0 , 1.5U 0 The relevant dielectric loss data under these three voltages, among which U 0 is the rated voltage of the tested cable. After obtaining the dielectric loss value and the test curve, calculate the dielectric loss change rate Δtanδ and the dielectric loss average value tanδ a , dielectric loss stability over time σ tanδ , can be calculated as follows:

[0059]

[0060] In the formula, n is the number of detections, is 0.5U 0 The dielectric loss value of the ith test under and Similarly, tanδ can be calculated as follows:

[0061]

[0062] Where δ is the dielectric loss angle, I R is the resistor leakage current value, I Cis the capacitive current value, R is the DC leakage resistance, and C is the equivalent capacitance.

[0063] 2. Connect one end of the cable under test to Port 1 of the vector network analyzer (VNA) through an alligator clip, and use the S11 mode to measure the impedance spectrum of the first end of the cable under test. Keep the other end of the cable under test open. During measurement, set the test frequency of the VHA to 100kHz~100MHz and the sampling interval to 10kHz.

[0064] The measured first-end impedance is converted into the first-end reflection coefficient. The two have the following relationship:

[0065]

[0066] Where: v (0) is the reflection coefficient of the first end, Z(0) is the measured impedance spectrum of the first end, and Z a is the characteristic impedance of the line.

[0067] The Gaussian pulse incident signal is simulated by computer, and the reflection coefficient and the spectrum of the Gaussian pulse are used to obtain the time domain reflection signal of the Gaussian pulse. The reflection signal is converted into the time-space domain to obtain the positioning map of the tested cable, and the positioning map is compensated according to linear regression to obtain a standardized time domain positioning map.

[0068] The positions of the reflection peaks except the head and tail are determined by the peak-finding algorithm, and the polarity deviation δ of each reflection peak is calculated after being numbered in sequence according to their distance from the head. p .

[0069] The present invention defines the polarity deviation δ p To characterize the tendency of the insulating material to undergo dipole polarization under the action of an electric field. A value of 0 indicates a stable state, and a value greater than 0 indicates that polarization is prone to occur. When the cable is partially damp, the cable insulation material is prone to thermal oxidation and thermal degradation reactions, forming various small molecules, causing the current position polarity deviation δ p Increase.

[0070] In the localization spectrum, the reflection peak usually presents a single peak or a double peak. For the double peak reflection peak, its polarity deviation δ p It depends on the difference between the extreme values ​​of the double peaks, so the value is generally greater than the single peak reflection peak, and numerical correction is required. The Gaussian pulse signal is input from the head end, so the left peak of the double peak changes polarity first. In addition, considering the differences in the frequency and power of the input signal, the material and length of the cable in different tests, the end reflection peak and the length from the reflection peak to the end are introduced. The calculation formula is as follows:

[0071]

[0072] Where:p(k) is the polarity deviation of the kth reflection peak, α is the polarity correction index, α=0.4, E r(k) is the extreme value of the right peak in the kth reflection peak, E l(k) is the extreme value of the left peak in the kth reflection peak, l(k) is the length from the kth reflection peak to the tail reflection peak, and A is the extreme value of the tail reflection peak. If it is a single reflection peak, the calculation formula is as follows:

[0073]

[0074] Where: E(k) is the extreme value of the kth reflection peak.

[0075] 3. After determining the tested cable, the cable characteristics, cable laying method, time and environment are important factors affecting the cable's moisture. The present invention defines a cable moisture risk index DRI, which characterizes the ease with which the cable is affected by moisture. As a reference indicator for evaluating the degree of moisture in the cable, the value is between 0 and 1. The larger the DRI value, the more susceptible the cable is to moisture.

[0076] The second characteristic of the cable protection level indicates the protection level of the cable in liquid, ranging from 0 to 8, representing protection from no protection to continuous immersion. The larger the number, the stronger the moisture resistance. Combined with the statistical data of on-site inspections, it was found that in the judgment of damp cables, the proportion of different cable laying methods was significantly different, among which direct burial laying accounted for the highest proportion and overhead laying accounted for the lowest proportion. At the same time, the cable laying time and the average humidity of the surrounding environment are also important factors affecting the cable moisture. Based on this, the calculation formula of the cable moisture risk index DRI is proposed:

[0077]

[0078] Wherein, I is the laying influence factor defined in the present invention, which is determined according to the laying mode of the tested cable and with reference to the cable laying mode moisture influence factor table described in Table 1, T is the cable laying time, DRI is the annual average relative humidity of the cable laying site, IP is the cable waterproof grade, if IP = 0, then DRI = 1.

[0079] Table 1 Cable laying method moisture influence factors

[0080] Laying method Direct burial Cable trench Pipe Bridge overhead Impact Factor 1.0 0.8 0.6 0.4 0.2

[0081] 4. To discover the internal relationship between the indicators in the above steps and determine their role in evaluating the local moisture of the cable

[0082] The present invention uses principal component analysis (PCA) to process the field test data, establishes a local moisture assessment model, and obtains the moisture status assessment value G.

[0083] The present invention proposes 5 indicators in total and uses 104 sets of field test data. For the convenience of explanation, they are abbreviated as n samples and p indicators. A sample matrix x of size n×p can be constructed:

[0084]

[0085] After standardizing the sample matrix, calculate its covariance matrix R

[0086]

[0087] The eigenvalue λ can be calculated from the covariance matrix R 1 ≥λ 2 …λ p ≥0 and eigenvector a 1 ,a 2 …a n ,in

[0088]

[0089] Each principal component F i The proportion of the corresponding eigenvalue in the eigenvalue is the contribution rate of the principal component. i Arrange from large to small, and take the first and second eigenvalues ​​corresponding to the eigenvalues ​​whose cumulative contribution rate exceeds 80%.

[0090] 2. The mth (m≤p) principal component F i .in

[0091] F i =a 1i X 1 +a 2i X 2 +…+a pi X p (14)

[0092] In the formula, X j is the normalized x in formula (9) j Indicator, a ji is the indicator X j In the principal component F i The load in .

[0093] For the principal component F i For each indicator X j The load a ji The larger the value is, the greater the influence of the index on the principal component is. Based on this, each index X j The weight of the moisture state assessment value G is calculated as follows:

[0094]

[0095] Thus, a local moisture assessment model was established, and the moisture state assessment value G(k) of the point was obtained. This assessment value comprehensively considers the advantages of ultra-low frequency dielectric loss test (VLF) for the overall cable assessment, the sensitive response of broadband impedance spectroscopy (BIS) to the local cable, and the moisture risk of the cable itself, and makes an assessment of the local moisture condition of the tested cable with a high degree of confidence.

[0096] 5. After the local moisture assessment model is established, the subsequent field test data can be directly substituted into the model to calculate the moisture

[0097] The tide state assessment value G(k) is calculated as follows:

[0098] G(k)=ω 1 Δtanδ+ω 2 tanδ a +ω 3 σ tanδ +ω 4 δ p(k) +ω 5 DRI (5)

[0099] The accuracy of the evaluation model continues to improve with the continuous accumulation of sample data. After comparing the obtained moisture state evaluation value G(k) with the moisture state evaluation reference table in Table 2, the moisture degree of the point on the tested cable can be evaluated.

[0100] Table 2 Reference table for moisture status assessment

[0101] Cable Status Intact cable Slightly damp Moderately damp Severe dampness Numerical range G(k)≤0.2 0.2<G(k)≤0.6 0.6<G(k)≤1.0 G(k)>1.0

[0102] In the disclosed invention patents, the use of VLF or BIS methods to determine the moisture condition of the tested cable has been mentioned, but the two methods alone cannot make an accurate assessment of the moisture condition of the cable. The VLF method detects the abnormality of the overall cable dielectric loss factor, rather than evaluating the local situation, and cannot determine the location of the local moisture. And the abnormality is affected by two factors: the local aging degree of the cable and the proportion of local aging. When the local aging length accounts for a small proportion of the total cable length, it will lead to a misjudgment of the local aging degree. The BIS method can obtain the positioning map of the tested cable, and the local moisture position of the cable can be determined by the abnormal reflection peak that appears. However, the size of the abnormal reflection peak is affected by factors such as the input signal frequency, the total length of the cable, the local moisture position and the local moisture degree, and the local moisture degree cannot be simply evaluated based on this.

[0103] Therefore, the present invention combines the VLF and BIS methods, comprehensively considers the indicators obtained by the two methods, and combines the characteristics of the cable itself to establish a new cable local moisture assessment model, so as to improve the accuracy of the assessment of the local moisture status of the cable.

[0104] Figure 2 The test site of a wind farm is presented. The cable under test is a 35kV XLPE cable with a length of 1866m. The middle joint 715m away from the head end is seriously damp. Figure 3 The positioning spectrum obtained by the BIS method, the frequency range is selected from 100kHz to 50MHz, and the frequency sampling interval is set to 2kHz. Table 3 shows the test data results.

[0105] Table 3 Test data table

[0106] Dielectric loss change rate Average dielectric loss Dielectric loss stability over time Polarity Deviation Moisture risk index Moisture status assessment value 37.96 0.01 0.01 1.11 0.36 1.39

[0107] Comparing the results of ultra-low frequency dielectric loss detection with the international standard IEEE400.2-2013, only the dielectric loss change rate is in a warning state, and the other two indicators are in a normal state.

[0108] The moisture state evaluation value proposed by the present invention is referred to Table 2, and it is considered that the intermediate joint at this position has been seriously damp. According to the test results, the staff dismantled and inspected the intermediate joint at 715m. The results are as follows Figure 4 The inspection results show that the intermediate joint at 715m has a serious moisture failure, which seriously affects the safety and reliability of cable operation. The on-site inspection results are consistent with the evaluation of the present invention.

[0109] Although the embodiments and drawings of the present invention are disclosed for illustrative purposes, those skilled in the art will appreciate that various substitutions, changes and modifications are possible without departing from the spirit and scope of the present invention and the appended claims. Therefore, the scope of the present invention is not limited to the contents disclosed in the embodiments and drawings.

Claims

1. A method for evaluating local moisture in a cable by combining ultra-low frequency dielectric loss and broadband impedance spectrum testing, characterized in that: The steps of the method are: S1. Use the ultra-low frequency dielectric loss meter to measure the cable under test and obtain the dielectric loss change rate Δtanδ and dielectric loss stability σ of the cable under test. tanδ And the average dielectric loss tanδ a ; S2. Measure the cable under test by broadband impedance spectroscopy to obtain a standardized time domain positioning spectrum. Record the reflection peak positions except the head end and tail end, label them in sequence according to their distance from the head end, and calculate the polarity deviation of each reflection peak δ p ; S3. Query the record of the tested cable and calculate the moisture risk index DRI of the tested cable based on the laying environment and laying method; S4. Use principal component analysis to process the data from S1 to S3, establish a local moisture assessment model, and obtain the weight of each indicator ω j ; S5. Substitute the measurement data of S1 to S3 into the local moisture assessment model, calculate the moisture state assessment value of the position, and assess the local moisture degree of the measured cable based on the value.

2. The cable local moisture assessment method of combined ultra-low frequency dielectric loss and broadband impedance spectrum testing according to claim 1 is characterized in that: The polarity deviation δ of the two reflection peaks at the same position in S2 is p The calculation formula is: Where: p(k) is the polarity deviation of the kth reflection peak; α is the double peak correction coefficient, which is 0.4; E r(k) is the extreme value of the right peak at the position of the kth reflection peak; E l(k) is the extreme value of the left peak at the position of the kth reflection peak; d(k) is the distance from the kth reflection peak to the tail reflection peak; A is the extreme value of the end reflection peak; For the polarity deviation δ of a single reflection peak at the same position p The calculation formula is: Where: E(k) is the extreme value of the kth reflection peak.

3. The cable local moisture assessment method of combined ultra-low frequency dielectric loss and broadband impedance spectrum testing according to claim 1 is characterized in that: The calculation formula for the moisture risk index of the S3 cable is: Where: I is the laying influence factor, which is determined according to the different laying methods of the tested cable; T is the cable laying time; The annual average relative humidity of the cable laying area; IP is the cable waterproof grade. If IP=0, DRI=1.

4. The cable local moisture assessment method of combined ultra-low frequency dielectric loss and broadband impedance spectrum testing according to claim 1 is characterized in that: The weight of each indicator in S4 j The calculation formula is: Where: j is the weight of the jth indicator; m is the number of principal components of the data retained by the principal component analysis method; p is the number of indicators; λ i is the variance contribution rate of the i-th principal component; a ji is the loading of the jth indicator in the i-th principal component.

5. The cable local moisture assessment method of combined ultra-low frequency dielectric loss and broadband impedance spectrum testing according to claim 1 is characterized in that: The calculation formula of the moisture state evaluation value G of S5 is: G(k)=ω1Δtanδ+ω2tanδ a +ω3σ tanδ +ω4d p(k) +ω5DRI (5) Among them: ω1, ω2, ω3, ω4 and ω5 are the dielectric loss change rate Δtanδ, the dielectric loss average value tanδ a , dielectric loss stability over timeσ tanδ 、The polarity deviation of the position δ p(k) The influence weight of the cable moisture risk index DRI can be calculated and compared with the moisture status assessment reference table according to the value of G(k) to evaluate the moisture degree of the tested cable at that location.

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