DC insulation resistance detection method and detection device

Abstract

The invention relates to a direct current insulation resistance detection method and a detection device. The method comprises the following steps: establishing a mathematical model of insulation resistance and bus voltage of a direct current bus to be measured, acquiring voltage to ground values of positive and negative buses when a positive bridge arm and a negative bridge arm of an unbalanced bridge are not connected and when the negative bridge arm of the unbalanced bridge is connected, introducing noise influence, and establishing a calculation method for eliminating the noise influence based on the acquired measurement values. And performing iterative calculation to obtain a to-be-identified parameter theta. And theta is substituted into the mathematical model to solve the insulation resistance value of the direct current system to be measured. According to the method, environment noise generally existing in the test process and pulse noise caused by circuit switch switching are fully considered, so that the insulation resistance detection error of the direct current system to be detected is reduced, and the reliability of a detection result is improved.

Description

Technical Field

[0001] The invention relates to the field of insulation detection of power systems, and in particular to a direct current insulation resistance detection method and a detection device. Background Art

[0002] With the increasing complexity of modern power systems and the increasing demand for high reliability, insulation monitoring of DC systems plays a vital role in ensuring equipment safety, extending service life, and preventing equipment failures. The health of the insulation system directly affects the stable operation and safety of the equipment, especially in key areas such as power transmission, rail transportation, and communications. For insulation problems in DC systems, accurate monitoring and diagnostic technology is particularly important.

[0003] At present, the insulation detection of DC system mainly relies on the structure formed by the combination of balanced bridge and unbalanced bridge. The balanced bridge is used to clamp the positive and negative bus voltages to the ground and control the fluctuation range of the bus voltage to the ground during the switching process of the unbalanced bridge. The main function of the unbalanced bridge is to form bus voltage fluctuations by switching the bridge arms, and to perform circuit analysis and solve the voltage fluctuations to calculate the insulation resistance of the DC bus to the ground. For example, the Chinese invention patent application "An Unbalanced Bridge Insulation Resistance Detection Circuit and Calculation Method for Rail Transit" with the publication number CN112540226A realizes the switching of unbalanced bridge resistance through a single control switch, uses sampling circuit and signal conditioning circuit to collect voltage signals, and finally calculates the insulation resistance through Ohm's law and Kirchhoff's voltage and current law. However, this method does not take into account the environmental noise that is prevalent in the measurement process, nor does it take into account the pulse noise caused by the switching of circuit switches, resulting in large errors in the calculation of insulation resistance. Summary of the invention

[0004] The technical problem to be solved by the present invention is how to reduce the detection error of DC insulation resistance.

[0005] The present invention solves the above technical problems through the following technical means:

[0006] The present invention provides a method for detecting direct current insulation resistance, the method comprising the following steps:

[0007] S1. When the positive bridge arm and the negative bridge arm of the unbalanced bridge are not connected, the mathematical model of the bus insulation resistance and bus voltage to be measured is: Among them, U p1 is the voltage between positive busbar and ground, U n1 is the voltage of negative busbar to ground; R b is the voltage clamp balance bridge resistance, R x is the insulation resistance of the positive busbar to be tested, R y is the insulation resistance value of the negative busbar to be tested;

[0008] S2. When the negative arm of the unbalanced bridge is connected, the mathematical model of the bus insulation resistance and bus voltage to be measured is:

[0009] Among them, U p2 This is the voltage between the positive busbar and the ground, U n2 This is the voltage between the negative busbar and the ground; R bn is the equivalent resistance of the voltage clamped balanced bridge and the unbalanced bridge, and the calculation formula is R bn =R b R n / (R b +R n ), where R n is the resistance value of the unbalanced bridge;

[0010] S3, when the positive and negative bridge arms of the unbalanced bridge are not connected, the voltages of the positive bus and the negative bus to ground are measured n times, and recorded as

[0011] U p1 =[u p1 (1),...,u p1 (i),...,u p1 (n)] T , U n1 =[u n1 (1),...,u n1 (i),...,u n1 (n)] T ;That

[0012] in, u p1 (i) is the positive bus voltage to ground at the i-th measurement, u n1 (i) is the voltage between the negative busbar and the ground during the i-th measurement;

[0013] S4, when connected to the negative arm of the unbalanced bridge, measure the voltages of the positive bus and the negative bus to ground n times, and record them as U p2 =[u p2 (1),...,u p2 (i),...,u p2 (n)] T , U n2 =[u n2 (1),...,u n2 (i),...,u n2 (n)] T ; Among them, u p2 (i) is the positive bus voltage to ground at the i-th measurement, u n2 (i) is the voltage between the negative busbar and the ground during the i-th measurement;

[0014] S5. Combine the matrix augmentations obtained in step S4 and step S5 to obtain the following formula:

[0015] U y =U x θ, where, U y =(U p1 U p2 ) T , θ=(θ1θ2) T ,θ

[0016] is the parameter matrix to be identified, where

[0017] S6, based on the voltage data obtained in step S4 and step S5, initial parameters are set based on the standard deviation weighted recursive least squares method, and iterative calculation is performed considering noise factors to update the parameter to be identified θ;

[0018] S7. Calculate the insulation resistance values ​​of the positive and negative buses of the DC system to be measured by using the parameters θ1 and θ2 to be identified.

[0019] Furthermore, the initial parameters in step S6 include: a parameter to be identified θ, a covariance matrix P, an adaptive weight factor W, a forgetting factor λ, and an adjustment factor μ.

[0020] Furthermore, step S6 includes the following steps:

[0021] S61, using the i-th measurement data, generate an augmented input matrix Output matrix U y (i)=(u p1 (i) u p2 (i)) T , calculate the model prediction error e(i);

[0022] S62, calculating and updating an adaptive weight factor W based on a standard deviation of the measurement data;

[0023] S63, calculating and updating the gain factor K;

[0024] S64, calculating and updating the covariance matrix P;

[0025] S65, calculating and updating the parameter θ to be identified;

[0026] S66. If the measurement stops, the parameter matrix θ to be identified is output and step S7 is continued; if the measurement continues, the measurement data is updated and the process returns to step S61 to continue iterative calculation.

[0027] Furthermore, the specific calculation formula of the model prediction error is:

[0028] e(i)=U y (i)-U x (i)θ.

[0029] Furthermore, the adaptive weight factor is:

[0030] The calculation formula is:

[0031]

[0032] in, is the standard deviation between the i-th measurement data and the mean of historical data; is the mean of historical data; a=n,p; j=1,2; μ is the adjustment factor.

[0033] Furthermore, the specific calculation formula of the gain factor K is:

[0034] Where λ is the forgetting factor.

[0035] Furthermore, the specific calculation formula of the covariance matrix P is:

[0036] Furthermore, the specific updating formula of the parameter θ to be identified is: θ=θ+Ke(i).

[0037] Furthermore, the step S7 is specifically as follows:

[0038] The parameters to be identified θ1 and θ2 obtained in step S6 are compared with the insulation resistance R x , R y The mathematical relationship is solved together to obtain the calculation formula for the insulation resistance of the negative busbar to be measured:

[0039] R y =(θ1-θ2)R bn R b / (θ2R bn -θ1R b );

[0040] The calculation formula for the positive electrode insulation resistance to be measured is:

[0041] R x =R by θ1R b / (R b -R by θ1);

[0042] Among them, R by It is the equivalent resistance obtained by connecting the voltage clamping balance bridge resistance in parallel with the negative electrode insulation resistance to be measured. The resistance calculation formula is: R by=R b R y / (R b +R y ).

[0043] The present invention also provides a DC insulation resistance detection device, which detects the insulation resistance of a DC system according to the above method, comprising:

[0044] A main control MCU module, including a built-in memory and a chip, is used to execute the DC insulation resistance detection method described in any of the above schemes to calculate the insulation resistance value of the DC system to be tested;

[0045] The balanced bridge unbalanced bridge module is used to collect the voltage values ​​of the positive and negative busbars to the ground when the positive and negative bridge arms of the unbalanced bridge are not connected, and when the negative bridge arm of the unbalanced bridge is connected;

[0046] The AD analog-to-digital conversion module is used to convert the collected analog voltage signal into a digital signal and input it into the main control MCU module.

[0047] The advantages of the present invention are:

[0048] The present invention fully considers the environmental noise and pulse noise caused by circuit switch switching that are commonly present in the measurement process, creates a calculation method to reduce the influence of noise, and reduces the DC insulation resistance detection error through iterative calculation. Moreover, by repeatedly measuring the DC system to be tested through this detection method, the insulation resistance value obtained is more stable, that is, the data reliability of a single test is stronger. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a schematic flow chart of a DC insulation resistance detection method according to an embodiment of the present invention;

[0050] Figure 2 It is a schematic flow chart of sub-steps of step S6 of a method for detecting direct current insulation resistance according to an embodiment of the present invention;

[0051] Figure 3 is a schematic diagram comparing simulation results of the embodiment of the present invention and the traditional Ohm's method detection method;

[0052] Figure 4 is a schematic diagram comparing simulation results of an embodiment of the present invention and a traditional least squares detection method; DETAILED DESCRIPTION

[0053] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described in combination with the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0054] Example 1

[0055] like Figure 1 As shown, the present invention provides a DC insulation resistance detection method, which calculates the insulation resistance of the positive and negative busbars based on the standard deviation weighted recursive least squares method, and includes the following steps:

[0056] S1. When the positive bridge arm and the negative bridge arm of the unbalanced bridge are not connected, the mathematical model of the bus insulation resistance and bus voltage to be measured is: Among them, U p1 is the voltage between positive busbar and ground, U n1 is the voltage between the negative busbar and the ground. b is the voltage clamp balance bridge resistance, R x is the insulation resistance of the positive busbar to be tested, R y is the insulation resistance value of the negative busbar to be tested;

[0057] S2. When the negative arm of the unbalanced bridge is connected, the mathematical model of the bus insulation resistance and bus voltage to be measured is:

[0058] Among them, U p2 This is the voltage between the positive busbar and the ground, U n2 This is the voltage between the negative busbar and the ground; R bn is the equivalent resistance of the voltage clamped balanced bridge and the unbalanced bridge, and the calculation formula is R bn =R b R n / (R b +R n ), where R n is the resistance value of the unbalanced bridge;

[0059] S3, when the positive and negative bridge arms of the unbalanced bridge are not connected, the voltages of the positive bus and the negative bus to ground are measured n times, and recorded as

[0060] U p1 =[u p1 (1),...,u p1 (i),...,u p1 (n)] T , U n1 =[un1 (1),...,u n1 (i),...,u n1 (n)] T ;That

[0061] in, u p1 (i) is the positive bus voltage to ground at the i-th measurement, u n1 (i) is the voltage between the negative busbar and the ground during the i-th measurement;

[0062] S4, when connected to the negative arm of the unbalanced bridge, measure the voltages of the positive bus and the negative bus to ground n times, and record them as U p2 =[u p2 (1),...,u p2 (i),...,u p2 (n)] T , U n2 =[u n2 (1),...,u n2 (i),...,u n2 (n)] T ; Among them, u p2 (i) is the positive bus voltage to ground at the i-th measurement, u n2 (i) is the voltage between the negative busbar and the ground during the i-th measurement;

[0063] S5. Combine the matrix augmentations obtained in step S4 and step S5 to obtain the following formula:

[0064] U y =U x θ, where, U y =(U p1 U p2 ) T , θ=(θ1θ2) T ,θ

[0065] is the parameter matrix to be identified, where

[0066] S6, based on the voltage data obtained in step S4 and step S5, initial parameters are set based on the standard deviation weighted recursive least squares method, and iterative calculation is performed considering noise factors to update the parameter to be identified θ;

[0067] The initial parameters in step S6 include: parameter θ to be identified, covariance matrix P, adaptive weight factor W, forgetting factor λ, and adjustment factor μ.

[0068] S7. Calculate the insulation resistance values ​​of the positive and negative buses of the DC system to be measured by using the parameters θ1 and θ2 to be identified.

[0069] like Figure 2 As shown, step S6 includes the following steps:

[0070] S61, using the i-th measurement data, generate an augmented input matrix Output matrix U y (i)=(u p1 (i) u p2 (i)) T , calculate the model prediction error e(i);

[0071] S62, calculating and updating the adaptive weight factor W based on the standard deviation of the measurement data; this step fully considers the environmental noise commonly present in the measurement process and the impulse noise caused by the switching of the circuit switch.

[0072] S63, calculating and updating the gain factor K;

[0073] S64, calculating and updating the covariance matrix P;

[0074] S65, calculating and updating the parameter θ to be identified;

[0075] S66. If the measurement stops, the parameter matrix θ to be identified is output and step S7 is continued; if the measurement continues, the measurement data is updated and the process returns to step S61 to continue iterative calculation.

[0076] The specific calculation formula of the model prediction error is:

[0077] e(i)=U y (i)-U x (i)θ

[0078] The adaptive weight factor is:

[0079] The calculation formula is:

[0080]

[0081] in, is the standard deviation between the i-th measurement data and the mean of historical data. is the mean of historical data; a=n,p. j=1,2; μ is the adjustment factor;

[0082] The specific calculation formula of the gain factor K is: Where λ is the forgetting factor.

[0083] The specific calculation formula of the covariance matrix P is:

[0084] The specific updating formula of the parameter θ to be identified is: θ=θ+Ke(i).

[0085] The step S7 is specifically as follows:

[0086] The parameters to be identified θ1 and θ2 obtained in step S6 are compared with the insulation resistance R x , R y The mathematical relationship is solved together to obtain the calculation formula for the insulation resistance of the negative busbar to be measured:

[0087] R y =(θ1-θ2)R bn R b / (θ2R bn -θ1R b );

[0088] The calculation formula for the positive electrode insulation resistance to be measured is:

[0089] R x =R by θ1R b / (R b -R by θ1);

[0090] Among them, R by It is the equivalent resistance obtained by connecting the voltage clamping balance bridge resistance in parallel with the negative electrode insulation resistance to be measured. The resistance calculation formula is: R by =R b R y / (R b +R y ).

[0091] In order to verify the effectiveness of the present invention, the embodiment is simulated and verified. In this example, the DC insulation resistance detection method simulation and the noise parameters applied are shown in Table 1:

[0092] Table 1

[0093]

[0094]

[0095] In this example, the initial parameter settings of the standard deviation weighted recursive least squares method are shown in Table 2:

[0096] Table 2

[0097]

[0098] During the simulation, the random seeds of white noise and impulse noise applied each time are different, and the intensity of impulse noise is different, so as to increase the diversity of the experiment and verify the robustness of the algorithm. According to the parameters in Table 1 and Table 2, the above detection method of this embodiment was used, and a total of 20 experiments were conducted, and the detection results were compared with the detection results based on other algorithms.

[0099] like Figure 3 As shown in the figure, the simulation results show that the positive and negative insulation resistance mean square errors of the detection method based on the traditional Ohm method are 3.83 and 4.32 respectively. Figure 4 As shown, the positive and negative insulation resistance mean square errors of the detection method based on the traditional least square method are 3.90 and 4.40, respectively. The positive and negative insulation resistance mean square errors of the detection method of this embodiment are 1.76 and 2.03, respectively.

[0100] The data table of 20 comparative experiments is as follows:

[0101] Comparison table of Ohm's method and this method.

[0102]

[0103]

[0104]

[0105] Comparison table of least squares method and this method.

[0106]

[0107]

[0108]

[0109] It can be seen from the comparison chart that the resistance value result obtained by the DC system insulation resistance detection method of the embodiment of the present invention is less affected by noise interference, which improves the calculation accuracy. The fluctuation of the insulation resistance calculation results of multiple experiments is much smaller than that of the traditional Ohm's method and the least squares method, and has higher stability.

[0110] Example 2

[0111] It should be further explained that, based on the same inventive concept, the present invention also provides a DC insulation resistance detection device, which detects the insulation resistance of a DC system according to the method described in Example 1, including:

[0112] A main control MCU module, including a built-in memory and a chip, is used to execute the DC insulation resistance detection method described in Example 1 to calculate the insulation resistance value of the DC system to be tested;

[0113] Balanced bridge and unbalanced bridge module, the balanced bridge part is used to clamp the bus voltage to ground, ensuring that the bus voltage fluctuation is within the allowable range when the unbalanced bridge part is working; this module is used to collect the positive and negative bus voltage values ​​to ground when the positive and negative bridge arms of the unbalanced bridge are not connected, and when the negative bridge arm of the unbalanced bridge is connected;

[0114] The AD analog-to-digital conversion module is used to convert the collected analog voltage signal into a digital signal and input it into the main control MCU module.

[0115] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A DC insulation resistance detection method, characterized in that: The following steps are involved: S1. When the positive bridge arm and the negative bridge arm of the unbalanced bridge are not connected, the mathematical model of the bus insulation resistance and bus voltage to be measured is: Among them, U p1 is the voltage between positive busbar and ground, U n1 is the voltage between negative busbar and ground; R b is the voltage clamp balance bridge resistance, R x is the insulation resistance of the positive busbar to be tested, R y is the insulation resistance value of the negative busbar to be tested; S2. When the negative arm of the unbalanced bridge is connected, the mathematical model of the bus insulation resistance and bus voltage to be measured is: Among them, U p2 This is the voltage between the positive busbar and the ground, U n2 This is the voltage between the negative busbar and the ground; R bn is the equivalent resistance of the voltage clamped balanced bridge and the unbalanced bridge, and the calculation formula is R bn =R b R n / (R b +R n ), where R n is the resistance value of the unbalanced bridge; S3, when the positive and negative bridge arms of the unbalanced bridge are not connected, the voltages of the positive bus and the negative bus to ground are measured n times, and recorded as U p1 = [u p1 (1),..., u p1 (i),..., u p1 (n)] T 、U n1 = [u n1 (1),..., u n1 (i),..., u n1 (n)] T ; wherein in, u p1 (i) is the positive bus voltage to ground at the i-th measurement, u n1 (i) is the voltage between the negative busbar and the ground during the i-th measurement; S4, when connected to the negative arm of the unbalanced bridge, measure the voltages of the positive bus and the negative bus to ground n times, and record them as U p2 =[u p2 (1),...,u p2 (i),...,u p2 (n)] T , U n2 =[u n2 (1),...,u n2 (i),...,u n2 (n)] T ; Among them, u p2 (i) is the positive bus voltage to ground at the i-th measurement, u n2 (i) is the voltage between the negative busbar and the ground during the i-th measurement; S5. Combine the matrix augmentations obtained in step S4 and step S5 to obtain the following formula: U y =U x i, among them, U y =(U p1 U p2 ) T , θ=(θ1θ2) T ,the is the parameter matrix to be identified, where S6, based on the voltage data obtained in step S4 and step S5, initial parameters are set based on the standard deviation weighted recursive least squares method, and iterative calculation is performed considering noise factors to update the parameter to be identified θ; S7. Calculate the insulation resistance values ​​of the positive and negative buses of the DC system to be measured by using the parameters θ1 and θ2 to be identified.

2. A DC insulation resistance detection method according to claim 1, characterized in that: The initial parameters in step S6 include: parameter θ to be identified, covariance matrix P, adaptive weight factor W, forgetting factor λ, and adjustment factor μ.

3. A DC insulation resistance detection method according to claim 1, characterized in that: The step S6 comprises the following steps: S61, using the i-th measurement data, generate an augmented input matrix Output matrix U y (i)=(u p1 (i)u p2 (i)) T , calculate the model prediction error e(i); S62, calculating and updating an adaptive weight factor W based on a standard deviation of the measurement data; S63, calculating and updating the gain factor K; S64, calculating and updating the covariance matrix P; S65, calculating and updating the parameter θ to be identified; S66. If the measurement stops, the parameter matrix θ to be identified is output and step S7 is continued; if the measurement continues, the measurement data is updated and the process returns to step S61 to continue iterative calculation.

4. A DC insulation resistance detection method according to claim 3, characterized in that: The specific calculation formula of the model prediction error is: e(i)=U y (i)-U x (i)θ.

5. A DC insulation resistance detection method according to claim 3, characterized in that: The adaptive weight factor is: The calculation formula is: in, is the standard deviation between the i-th measurement data and the mean of historical data; is the mean of historical data; a=n,p; j=1,2; μ is the adjustment factor.

6. A DC insulation resistance detection method according to claim 3, characterized in that: The specific calculation formula of the gain factor K is: Where λ is the forgetting factor.

7. A DC insulation resistance detection method according to claim 3, characterized in that: The specific calculation formula of the covariance matrix P is:

8. A DC insulation resistance detection method according to claim 3, characterized in that: The specific updating formula of the parameter θ to be identified is: θ=θ+Ke(i).

9. A DC insulation resistance detection method according to claim 1, characterized in that: The step S7 is specifically as follows: The parameters to be identified θ1 and θ2 obtained in step S6 are compared with the insulation resistance R x , R y The mathematical relationship is solved together to obtain the calculation formula for the insulation resistance of the negative busbar to be measured: R y =(θ1-θ2)R bn R b / (θ2R bn -θ1R b ); The calculation formula for the positive electrode insulation resistance to be measured is: R x =R by θ1R b / (R b -R by θ1); Among them, R by It is the equivalent resistance obtained by connecting the voltage clamping balance bridge resistance in parallel with the negative electrode insulation resistance to be measured. The resistance calculation formula is: R by =R b R y / (R b +R y ).

10. A DC insulation resistance detection device, characterized in that: The device comprises: A main control MCU module, including a built-in memory and a chip, is used to execute the DC insulation resistance detection method according to claims 1-9 to calculate the insulation resistance value of the DC system to be tested; Balanced bridge and unbalanced bridge module, the balanced bridge part is used to clamp the bus voltage to ground, ensuring that the bus voltage fluctuation is within the allowable range when the unbalanced bridge part is working; this module is used to collect the positive and negative bus voltage values ​​to ground when the positive and negative bridge arms of the unbalanced bridge are not connected, and when the negative bridge arm of the unbalanced bridge is connected; The AD analog-to-digital conversion module is used to convert the collected analog voltage signal into a digital signal and input it into the main control MCU module.

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