Method and device for generating excitation signal based on dielectric test of oil-paper insulation
By generating a sequence of characteristic signals that meet the component power density conditions at a specific frequency, using Fast Fourier Transform and periodogram method to filter out the target characteristic signals, and combining discrete sampling to obtain the target time-domain signal, the problem of long testing time and inaccurate test results of traditional oil-paper insulation testing methods is solved, realizing rapid measurement and efficient detection of oil-paper insulation dielectric test.
Patent Information
- Application Number
- CN202310464513.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2023-04-26
- Publication Date
- 2026-02-10
- Estimated Expiration
- 2043-04-26
AI Technical Summary
Traditional oil-paper insulation testing methods are complex to operate, time-consuming, and have inaccurate test results. Especially when the transformer is shut down for a limited time, the low-frequency detection time of the frequency domain dielectric spectroscopy method is too long, which affects the application efficiency.
By generating a characteristic signal sequence that satisfies the component power density condition at a specific frequency, the target characteristic signal sequence is selected using the fast Fourier transform and periodogram method. The target time-domain signal is then obtained by combining discrete sampling and used as the excitation signal for the dielectric test of oil-paper insulation.
This method enables rapid measurement of dielectric properties in oil-paper insulation, avoiding the problem of excessively long detection time in the low-frequency band and improving the application efficiency of frequency domain dielectric spectroscopy.
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Figure CN116559509B_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of power technology, and in particular to a method, apparatus, computer equipment, storage medium, and computer program product for generating excitation signals based on oil-paper insulation dielectric testing. Background Technology
[0002] For transformer insulation condition testing, traditional methods for detecting moisture in oil-paper insulation are difficult to sample, complex to operate, and time-consuming. In addition, manual sampling is required, which poses certain risks.
[0003] Time-frequency domain dielectric response testing is an important method currently used for non-destructive testing of oil-paper insulation, but it still has many shortcomings. Among them, the recovery voltage method and the polarization / depolarization current method have poor anti-interference ability in field testing and are easily affected by charge accumulation, leading to inaccurate test results. The frequency domain dielectric spectrum method has strong anti-interference ability and contains rich insulation information, but the detection time in the low-frequency range is relatively long, which has limitations under the condition of limited transformer power outage time in actual situations. Summary of the Invention
[0004] Therefore, it is necessary to provide a method, apparatus, computer equipment, storage medium, and computer program product for generating excitation signals based on oil-paper insulation dielectric testing, which can solve the above-mentioned technical problems.
[0005] In a first aspect, this application provides a method for generating an excitation signal based on an oil-paper insulation dielectric test, the method comprising:
[0006] Obtain preset sequence design information, and generate multiple feature signal sequences based on the preset sequence design information; the preset sequence design information is used to indicate the sequence generation method and the corresponding sequence generation parameters;
[0007] Obtain the target frequency, and take the feature signal sequence that satisfies the component power density condition at the target frequency from the plurality of feature signal sequences as the target feature signal sequence;
[0008] The target time-domain signal is obtained based on the target feature signal sequence and used as the excitation signal corresponding to the target frequency; the excitation signal is used to identify the oil-paper insulation system during the oil-paper insulation dielectric test.
[0009] In one embodiment, the step of obtaining preset sequence design information and generating multiple feature signal sequences based on the preset sequence design information includes:
[0010] Obtain preset sequence design information, determine the sequence generation method and corresponding sequence generation parameters; the sequence generation parameters include excitation amplitude parameters, initial value parameters and number of iterations;
[0011] According to the sequence generation method, the plurality of feature signal sequences are generated by combining the excitation amplitude parameter, the initial value parameter and the number of iterations.
[0012] In one embodiment, obtaining the target frequency, and taking the feature signal sequence that satisfies the component power density condition at the target frequency from the plurality of feature signal sequences as the target feature signal sequence, includes:
[0013] Perform a Fast Fourier Transform on the multiple feature signal sequences to obtain multiple transformed signal sequences;
[0014] Based on the multiple transformed signal sequences, the transformed signal sequence with the highest component power density at the target frequency is taken as the target feature signal sequence.
[0015] In one embodiment, the step of selecting the transformed signal sequence with the highest component power density at the target frequency as the target feature signal sequence based on the plurality of transformed signal sequences includes:
[0016] The power spectral density at the target frequency is determined using the periodogram method; the power spectral density is used to characterize the distribution of time-domain signal power with frequency.
[0017] Based on the power spectral density at the target frequency, the transformed signal sequence with the largest component power density at the target frequency is determined from the plurality of transformed signal sequences and used as the target feature signal sequence.
[0018] In one embodiment, obtaining the target time-domain signal based on the target feature signal sequence includes:
[0019] Obtain discrete sampling information; the discrete sampling information includes a discrete sampling interval parameter;
[0020] The target feature signal sequence is sampled according to the discrete sampling interval parameter to obtain the target time domain signal.
[0021] In one embodiment, the target frequency is a low-frequency band frequency. After the step of obtaining the target time-domain signal based on the target feature signal sequence as the excitation signal corresponding to the target frequency, the method further includes:
[0022] The excitation signal corresponding to the target frequency is used as the reference signal;
[0023] Obtain sampling interval information; the sampling interval information includes multiple different sampling interval parameters;
[0024] The reference signal is sampled and processed according to the sampling interval parameters to obtain the excitation signal corresponding to the frequency other than the target frequency in the low frequency band.
[0025] Secondly, this application also provides an excitation signal generation device based on oil-paper insulation dielectric testing, the device comprising:
[0026] A signal sequence design module is used to acquire preset sequence design information and generate multiple feature signal sequences based on the preset sequence design information; the preset sequence design information is used to indicate the sequence generation method and the corresponding sequence generation parameters.
[0027] The target signal sequence determination module is used to obtain the target frequency and take the feature signal sequence that satisfies the component power density condition at the target frequency from the plurality of feature signal sequences as the target feature signal sequence;
[0028] The excitation signal acquisition module is used to obtain a target time-domain signal based on the target feature signal sequence, which serves as the excitation signal corresponding to the target frequency; the excitation signal is used to identify the oil-paper insulation system during the oil-paper insulation dielectric test.
[0029] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of the excitation signal generation method based on oil-paper insulation dielectric testing as described above.
[0030] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, implements the steps of the excitation signal generation method based on the oil-paper insulation dielectric test as described above.
[0031] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the steps of the excitation signal generation method based on the oil-paper insulation dielectric test as described above.
[0032] The aforementioned method, apparatus, computer equipment, storage medium, and computer program product for generating excitation signals based on oil-paper insulation dielectric testing, acquires preset sequence design information, generates multiple characteristic signal sequences based on the preset sequence design information, which indicates the sequence generation method and corresponding sequence generation parameters, then acquires the target frequency, and selects the characteristic signal sequence that satisfies the component power density condition at the target frequency from among the multiple characteristic signal sequences as the target characteristic signal sequence, and then obtains the target time-domain signal based on the target characteristic signal sequence as the excitation signal corresponding to the target frequency. This excitation signal is used to identify the oil-paper insulation system during oil-paper insulation dielectric testing, realizing rapid measurement excitation signal design for oil-paper insulation dielectric testing, avoiding the problem of excessively long detection time in the low-frequency band, and improving the application efficiency of the frequency domain dielectric spectrum method. Attached Figure Description
[0033] Figure 1 This is a flowchart illustrating an excitation signal generation method based on oil-paper insulation dielectric testing in one embodiment.
[0034] Figure 2 This is a schematic diagram of a white noise sequence generation process in one embodiment;
[0035] Figure 3 This is a schematic diagram of a signal time-domain waveform in one embodiment;
[0036] Figure 4 This is a schematic diagram of a signal power density spectrum in one embodiment;
[0037] Figure 5 This is a flowchart illustrating another method for generating excitation signals based on oil-paper insulation dielectric testing in one embodiment;
[0038] Figure 6 This is a structural block diagram of an excitation signal generation device based on oil-paper insulation dielectric testing in one embodiment;
[0039] Figure 7 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation
[0040] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.
[0041] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for display, data used for analysis, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties; correspondingly, this application also provides a corresponding user authorization entry point for users to choose to authorize or refuse.
[0042] Oil-paper insulation, as an insulating material, possesses excellent heat dissipation, stable insulation performance, and low cost, making it widely used in the insulation of oil-immersed electrical equipment such as transformers. The moisture content of transformer oil-paper insulation affects the transformer's lifespan and operational stability; therefore, accurately assessing the moisture content of oil-paper insulation is of great significance.
[0043] Traditional methods for detecting moisture in oil-paper insulation are difficult to operate and time-consuming. Novel dielectric response testing methods are currently important methods used for non-destructive testing of oil-paper insulation. Among them, time-domain non-destructive testing techniques mainly include the return voltage method (RVM) and polarization and depolarization current (PDC), while frequency-domain non-destructive testing techniques mainly include the frequency domain dielectric spectrometry (FDS).
[0044] The recovery voltage method and polarization / depolarization current method have poor anti-interference capabilities during field testing and are easily affected by charge accumulation, leading to inaccurate test results. While the frequency domain dielectric spectroscopy method has strong anti-interference capabilities and contains rich insulation information, its long detection time in the low-frequency range limits its application under conditions of limited transformer downtime. For example, when performing frequency domain dielectric response testing on oil-paper insulation systems, the applied sinusoidal excitation voltage needs to be scanned frequency-by-frequency from high to low, resulting in a lengthy testing process. In special operating conditions, limited maintenance time further restricts the application of the frequency domain dielectric response method in practical engineering due to the limited transformer downtime. This application's excitation signal generation method for oil-paper insulation dielectric testing improves upon the frequency domain dielectric spectroscopy method, addressing the problem of excessively long detection time in the low-frequency range and enabling rapid measurement.
[0045] In one embodiment, such as Figure 1 As shown, a method for generating excitation signals based on oil-paper insulation dielectric testing is provided. This embodiment illustrates the application of this method to a terminal. It is understood that this method can also be applied to a server, and further to a system including both a terminal and a server, and implemented through interaction between the terminal and the server. In this embodiment, the method includes the following steps:
[0046] Step 101: Obtain preset sequence design information, and generate multiple feature signal sequences based on the preset sequence design information;
[0047] Among them, the preset sequence design information can be used to indicate the sequence generation method and the corresponding sequence generation parameters.
[0048] As an example, the feature signal sequence can be a white noise excitation sequence; the sequence generation method can be the multiplicative congruence method, such as obtaining multiple sets of white noise excitation sequences by the multiplicative congruence method; the sequence generation parameters can include excitation amplitude parameters, initial value parameters, and number of cycles, and can also include other sequence generation parameters, which are not specifically limited in this embodiment.
[0049] In practical applications, preset sequence design information can be obtained. Based on this preset sequence design information, the sequence generation method and corresponding sequence generation parameters can be obtained, such as excitation amplitude parameters, initial value parameters and number of cycles. Then, according to the sequence generation method, combined with the excitation amplitude parameters, initial value parameters and number of cycles, multiple characteristic signal sequences can be generated. For example, multiple white noise excitation sequences can be obtained by multiplying congruents.
[0050] In one example, since white noise sequence is a typical random sequence and an ideal system identification excitation signal, white noise sequence can be selected as excitation signal. The mean of the white noise sequence is zero, and the power spectral density after FFT (fast Fourier transform) is a non-zero constant. For white noise sequence w(k), the following equations (1) and (2) need to be satisfied.
[0051] E{w(k)}=0 (1)
[0052] Cov{w(k),w(k+i)}=Rδ i (2)
[0053] Where R is the regularity constant matrix, δ i The Kronecker notation represents a unit diagonal matrix, for δ in equation (2) i It can be represented as:
[0054]
[0055] In another example, since ideal white noise sequences are difficult to obtain directly, a pseudo-random sequence satisfying the definition of white noise can be generated by computer as the excitation signal for system identification. To identify the dynamic characteristics of oil-paper insulation under different amplitude excitations, an excitation signal with a high power density of its characteristic frequency components after Fourier transform can be designed for system identification.
[0056] Specifically, taking the rapid measurement of nonlinear coefficients under sinusoidal excitation with a frequency of 0.01Hz and an amplitude of 100V to 2000V as an example, when designing the white noise excitation sequence, in order to excite the nonlinear characteristics of the 100V to 2000V sinusoidal excitation, the amplitude can be set to 2000V, and multiple sets of (-2000, 2000) sequences (i.e., multiple characteristic signal sequences) can be arbitrarily generated by the multiplication congruence method.
[0057] Step 102: Obtain the target frequency, and take the feature signal sequence that satisfies the component power density condition at the target frequency from the plurality of feature signal sequences as the target feature signal sequence;
[0058] In a practical implementation, multiple feature signal sequences can be subjected to Fast Fourier Transform to obtain multiple transformed signal sequences. Then, based on the multiple transformed signal sequences, the transformed signal sequence with the highest component power density at the target frequency can be used as the target feature signal sequence.
[0059] In an optional embodiment, the periodogram method can be used to determine the power spectral density at the target frequency. This power spectral density can be used to characterize the distribution of time-domain signal power with frequency. Then, based on the power spectral density at the target frequency, the transformed signal sequence with the largest component power density at the target frequency can be determined from multiple transformed signal sequences, such as obtaining the excitation signal with a high characteristic frequency component power density after Fourier transform (i.e., the target characteristic signal sequence).
[0060] For example, after obtaining multiple sets of white noise excitation sequences (i.e., multiple characteristic signal sequences) using the congruential multiplication method, time-domain white noise signals can be obtained by designing different sampling intervals. Taking the rapid measurement of nonlinear coefficients under sinusoidal excitation with a frequency of 0.01Hz and an amplitude of 100V to 2000V as an example, the target frequency can be selected as 0.01Hz, and the excitation signal with a higher frequency component at 0.01Hz can be selected (i.e., the characteristic signal sequence that satisfies the component power density condition at the target frequency). Since the power spectral density can be used to describe the distribution of time-domain signal power with frequency in practical engineering, the periodogram method can be selected to calculate the power spectral density for the designed white noise excitation sequence.
[0061] Step 103: Obtain the target time-domain signal based on the target feature signal sequence, and use it as the excitation signal corresponding to the target frequency; the excitation signal is used to identify the oil-paper insulation system during the oil-paper insulation dielectric test.
[0062] After obtaining the target feature signal sequence, discrete sampling information can be acquired. This discrete sampling information may include discrete sampling interval parameters. Then, the target feature signal sequence can be sampled according to these discrete sampling interval parameters to obtain the target time domain signal, which can be used as the excitation signal for identifying the oil-paper insulation system.
[0063] In one example, based on preset sequence design information, a time interval of 25s can be selected to generate 1000 white noise signals with a duration of 400s each, such as multiple white noise excitation sequences (i.e., multiple feature signal sequences). After generating multiple white noise excitation sequences, the white noise signal with the highest power density of the 0.01Hz (i.e., target frequency) component (i.e., the target feature signal sequence) can be selected, and then discretized into a time-domain signal with a sampling interval of 0.1ms (i.e., the target time-domain signal) as the excitation signal for system identification.
[0064] In another example, the target frequency can be a low-frequency band frequency, such as 0.01Hz. After obtaining the excitation signal corresponding to the target frequency, the excitation signal corresponding to the target frequency can be used as a reference signal. Then, the sampling interval information can be obtained. This sampling interval information can include multiple different sampling interval parameters. Then, the reference signal can be sampled according to each sampling interval parameter to obtain the excitation signal corresponding to frequencies other than the target frequency in the low-frequency band. For example, based on the design of the excitation signal for quickly measuring the 0.01Hz nonlinear coefficient, the excitation signal for quickly measuring the nonlinear coefficient of other frequencies can be obtained by stretching or shortening the signal.
[0065] In the above-mentioned excitation signal generation method based on oil-paper insulation dielectric testing, multiple feature signal sequences are generated by acquiring preset sequence design information. The preset sequence design information is used to indicate the sequence generation method and corresponding sequence generation parameters. Then, the target frequency is obtained, and the feature signal sequence that meets the component power density condition at the target frequency among the multiple feature signal sequences is taken as the target feature signal sequence. Then, the target time domain signal is obtained based on the target feature signal sequence and used as the excitation signal corresponding to the target frequency. This excitation signal is used to identify the oil-paper insulation system during oil-paper insulation dielectric testing. This realizes the design of a rapid measurement excitation signal for oil-paper insulation dielectric testing, avoids the problem of excessively long detection time in the low-frequency band, and improves the application efficiency of the frequency domain dielectric spectrum method.
[0066] In one embodiment, obtaining preset sequence design information and generating multiple feature signal sequences based on the preset sequence design information may include the following steps:
[0067] Obtain preset sequence design information, determine the sequence generation method and corresponding sequence generation parameters; the sequence generation parameters include excitation amplitude parameters, initial value parameters and number of iterations; generate the multiple feature signal sequences according to the sequence generation method, combining the excitation amplitude parameters, the initial value parameters and the number of iterations.
[0068] As an example, the sequence generation method can be the multiplicative congruence method, such as obtaining multiple sets of white noise excitation sequences through the multiplicative congruence method.
[0069] The sequence generation parameters can include excitation amplitude parameters, initial value parameters, and number of iterations. For example, the amplitude can be set to 2000V, and the initial value and number of iterations can be set for the multiplicative congruence method.
[0070] In practical applications, the process of generating white noise excitation sequences using the congruential multiplication method can be as follows: Figure 2 As shown, the sequence length can be determined based on a set initial value (i.e., initial value parameter) and the number of iterations, which can be used to determine the sequence length. This initial value can be obtained by... Figure 2 The operation involves using the remainder as the new dividend and repeating the process until the desired pseudo-random number array is obtained as a white noise sequence (i.e., a characteristic signal sequence).
[0071] To enable those skilled in the art to better understand the above steps, the process of designing a white noise excitation sequence is illustrated below, but it should be understood that the embodiments of this application are not limited thereto.
[0072] For example, based on the set initial value 'a' and the number of loops, the initial value 'a' can be divided by 255 and the remainder 'b' can be taken. Then, the remainder 'b' can be divided by 256 to obtain a random number 'c'. For this random number 'c', 0.5 can be subtracted from the random number 'c' and then multiplied by 4000 to obtain 'd'. It can then be determined whether the number of loops has been reached. If the number of loops has been reached, all 'd's can be output to form a white noise signal. If the number of loops has not been reached, based on a preset condition, such as letting 'a = ads(d)', the process can return to the step of dividing the initial value 'a' by 255 and taking the remainder 'b'.
[0073] In one example, taking the rapid measurement of nonlinear coefficients under sinusoidal excitation with a frequency of 0.01Hz and an amplitude of 100V to 2000V as an example, when designing the white noise excitation sequence, in order to excite the nonlinear characteristics of the sinusoidal excitation of 100V to 2000V, the amplitude can be set to 2000V (i.e., the excitation amplitude parameter), and multiple sets of (-2000, 2000) sequences, i.e. multiple characteristic signal sequences, can be arbitrarily generated by the congruential multiplication method.
[0074] In this embodiment, by acquiring preset sequence design information, the sequence generation method and corresponding sequence generation parameters are determined. Then, according to the sequence generation method, combined with the excitation amplitude parameters, initial value parameters and the number of iterations, multiple feature signal sequences are generated. This can effectively obtain multiple sets of white noise sequences, providing data support for further screening of excitation signals with high power density of feature frequency components after Fourier transform.
[0075] In one embodiment, obtaining the target frequency, and taking the feature signal sequence that satisfies the component power density condition at the target frequency from the plurality of feature signal sequences as the target feature signal sequence, may include the following steps:
[0076] Perform a Fast Fourier Transform on the multiple feature signal sequences to obtain multiple transformed signal sequences; based on the multiple transformed signal sequences, the transformed signal sequence with the highest component power density at the target frequency is taken as the target feature signal sequence.
[0077] In practical implementation, multiple characteristic signal sequences can be subjected to Fast Fourier Transform (FFT) to obtain multiple transformed signal sequences. Then, the periodogram method can be used to determine the power spectral density at the target frequency. This power spectral density can be used to characterize the distribution of time-domain signal power with frequency. Furthermore, based on the power spectral density at the target frequency, the transformed signal sequence with the largest component power density at the target frequency can be determined from multiple transformed signal sequences. For example, an excitation signal with a high characteristic frequency component power density after Fourier transform can be obtained.
[0078] In one example, taking the rapid measurement of the nonlinear coefficient under sinusoidal excitation at a frequency of 0.01 Hz as an example, a time interval of 25 s can be selected to generate 1000 white noise signals with a duration of 400 s, such as multiple sets of white noise excitation sequences (i.e. multiple feature signal sequences). Then, after generating multiple sets of white noise excitation sequences, the white noise signal with the highest power density of the 0.01 Hz (i.e. target frequency) component can be selected as the target feature signal sequence.
[0079] In this embodiment, multiple transformed signal sequences are obtained by performing fast Fourier transform on multiple characteristic signal sequences. Then, based on the multiple transformed signal sequences, the transformed signal sequence with the highest component power density at the target frequency is taken as the target characteristic signal sequence. This helps to identify the dynamic characteristics of oil-paper insulation under different amplitude excitations and improves the application efficiency of the frequency domain dielectric spectroscopy method.
[0080] In one embodiment, selecting the transformed signal sequence with the highest component power density at the target frequency as the target feature signal sequence based on the plurality of transformed signal sequences may include the following steps:
[0081] The power spectral density at the target frequency is determined using the periodogram method. The power spectral density is used to characterize the distribution of time-domain signal power with frequency. Based on the power spectral density at the target frequency, the transformed signal sequence with the largest component power density at the target frequency is determined from the plurality of transformed signal sequences and used as the target feature signal sequence.
[0082] In one example, after obtaining multiple sets of white noise excitation sequences (i.e., multiple characteristic signal sequences) using the congruential multiplication method, time-domain white noise signals can be obtained by designing different sampling intervals. Taking the rapid measurement of nonlinear coefficients under sinusoidal excitation with a frequency of 0.01Hz and an amplitude of 100V to 2000V as an example, the target frequency can be selected as 0.01Hz, and the excitation signal with a higher frequency component at 0.01Hz can be selected, i.e., the transformed signal sequence with the largest component power density at the target frequency. Since the power spectral density can be used to describe the distribution of time-domain signal power with frequency in practical engineering, the periodogram method can be selected to calculate the power spectral density for the designed white noise excitation sequence.
[0083] In another example, regarding the periodogram method, the time-domain signal can be treated as a sequence with finite power. By performing a DFFT transform on the time-domain signal, taking the square of the amplitude, and then dividing by the total amount of data, the power density at different frequencies can be obtained. As can be seen from the power density spectrum calculation method, for the same white noise sequence, different power density spectra can be obtained by setting different sampling intervals, and their spectral lines are identical. For example, the longer the sampling interval, the spectral lines can be shifted to lower frequencies; the shorter the sampling interval, the spectral lines can be shifted to higher frequencies. Therefore, based on the design of an excitation signal for rapidly measuring the 0.01Hz nonlinear coefficient, by lengthening or shortening the signal, corresponding excitation signals for rapidly measuring the nonlinear coefficients at other frequencies can be obtained.
[0084] In this embodiment, the power spectral density at the target frequency is determined by using the periodogram method. Then, based on the power spectral density at the target frequency, the transformed signal sequence with the largest component power density at the target frequency is determined from multiple transformed signal sequences and used as the target feature signal sequence, which enables rapid measurement excitation signal design.
[0085] In one embodiment, obtaining the target time-domain signal based on the target feature signal sequence may include the following steps:
[0086] Obtain discrete sampling information; the discrete sampling information includes a discrete sampling interval parameter; sample the target feature signal sequence according to the discrete sampling interval parameter to obtain the target time domain signal.
[0087] In practical applications, after generating multiple white noise excitation sequences, the white noise signal with the highest power density of the 0.01Hz component can be selected. Then, the discrete sampling interval parameter can be determined based on the discrete sampling information. For example, if the sampling interval is 0.1ms, the white noise signal with the highest power density of the 0.01Hz component can be discretized into a time-domain signal (i.e., the target time-domain signal) with a sampling interval of 0.1ms, which can be used as the excitation signal for system identification.
[0088] For example, the time-domain waveform of this signal can be as follows: Figure 3As shown, the power density spectrum of this signal can be expressed as follows: Figure 4 As shown. For the measurement of nonlinear coefficients at different frequencies, by... Figure 3 By adjusting the sampling interval of the time-domain signal, signals of different durations can be obtained as excitations, thereby obtaining excitation signals for rapid measurement of nonlinear coefficients at other frequencies.
[0089] In this embodiment, by acquiring discrete sampling information and then sampling the target feature signal sequence according to the discrete sampling interval parameter, the target time-domain signal is obtained, which provides data support for further obtaining the excitation signal for rapidly measuring other frequency nonlinear coefficients.
[0090] In one embodiment, the target frequency is a low-frequency band frequency. After the step of obtaining the target time-domain signal based on the target feature signal sequence as the excitation signal corresponding to the target frequency, the following steps may be included:
[0091] The excitation signal corresponding to the target frequency is used as a reference signal; sampling interval information is obtained; the sampling interval information includes multiple different sampling interval parameters; the reference signal is sampled and processed according to each of the sampling interval parameters to obtain the excitation signal corresponding to frequencies other than the target frequency in the low-frequency band.
[0092] In one example, as can be seen from the power density spectrum calculation method, for the same white noise sequence, different power density spectra can be obtained by setting different sampling intervals, and their spectral lines are the same. For example, the longer the sampling interval, the spectral lines can be shifted to the lower frequency band; the shorter the sampling interval, the spectral lines can be shifted to the higher frequency band. Therefore, based on the design of the excitation signal for quickly measuring the 0.01Hz nonlinear coefficient, the excitation signal for quickly measuring the nonlinear coefficient of other frequencies can be obtained by lengthening or shortening the signal.
[0093] In another example, taking the rapid measurement of the nonlinear coefficient under sinusoidal excitation with a frequency of 0.01Hz and an amplitude of 100V to 2000V as an example, based on, for instance... Figure 3 The time-domain waveform of the signal shown (i.e., the reference signal) can be used to measure nonlinear coefficients at different frequencies by... Figure 3 By adjusting the sampling interval (i.e., multiple different sampling interval parameters) of the time-domain signal, signals of different durations can be obtained as excitations, thereby obtaining excitation signals for rapid measurement of nonlinear coefficients of other frequencies.
[0094] In this embodiment, by using the excitation signal corresponding to the target frequency as a reference signal, obtaining the sampling interval information, and then sampling the reference signal according to each sampling interval parameter, the excitation signal corresponding to frequencies other than the target frequency in the low-frequency band can be obtained. This enables the design of a rapid measurement excitation signal for the dielectric test of oil-paper insulation, and improves the application efficiency of the frequency domain dielectric spectrum method.
[0095] In one embodiment, such as Figure 5 The diagram illustrates another method for generating excitation signals based on oil-paper insulation dielectric testing. In this embodiment, the method includes the following steps:
[0096] In step 501, preset sequence design information is obtained, and the sequence generation method and corresponding sequence generation parameters are determined. According to the sequence generation method, combined with excitation amplitude parameters, initial value parameters, and the number of iterations, multiple characteristic signal sequences are generated. In step 502, a Fast Fourier Transform is performed on the multiple characteristic signal sequences to obtain multiple transformed signal sequences. In step 503, the periodogram method is used to determine the power spectral density at the target frequency; the power spectral density is used to characterize the distribution of time-domain signal power with frequency. In step 504, based on the power spectral density at the target frequency, the transformed signal sequence with the largest component power density at the target frequency is determined from the multiple transformed signal sequences and used as the target characteristic signal sequence. In step 505, discrete sampling information is obtained; the discrete sampling information includes discrete sampling interval parameters; the target characteristic signal sequence is sampled according to the discrete sampling interval parameters to obtain the target time-domain signal. In step 506, the excitation signal corresponding to the target frequency is used as a reference signal; sampling interval information is obtained, which includes multiple different sampling interval parameters. In step 507, the reference signal is sampled and processed according to the sampling interval parameters to obtain the excitation signal corresponding to the frequencies other than the target frequency in the low-frequency band. It should be noted that the specific limitations of the above steps can be found in the specific limitations of the excitation signal generation method based on oil-paper insulation dielectric testing described above, and will not be repeated here.
[0097] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.
[0098] Based on the same inventive concept, this application also provides an excitation signal generation device for implementing the excitation signal generation method based on oil-paper insulation dielectric testing as described above. The solution provided by this device is similar to the implementation described in the above method. Therefore, the specific limitations of one or more embodiments of the excitation signal generation device based on oil-paper insulation dielectric testing provided below can be found in the limitations of the excitation signal generation method based on oil-paper insulation dielectric testing described above, and will not be repeated here.
[0099] In one embodiment, such as Figure 6 As shown, an excitation signal generation device based on oil-paper insulation dielectric testing is provided, comprising:
[0100] The signal sequence design module 601 is used to acquire preset sequence design information and generate multiple feature signal sequences based on the preset sequence design information; the preset sequence design information is used to indicate the sequence generation method and the corresponding sequence generation parameters.
[0101] The target signal sequence determination module 602 is used to obtain the target frequency and take the feature signal sequence that satisfies the component power density condition at the target frequency from the plurality of feature signal sequences as the target feature signal sequence;
[0102] The excitation signal acquisition module 603 is used to obtain a target time-domain signal based on the target feature signal sequence, which serves as the excitation signal corresponding to the target frequency; the excitation signal is used to identify the oil-paper insulation system during the oil-paper insulation dielectric test.
[0103] In one embodiment, the signal sequence design module 601 includes:
[0104] The design information acquisition submodule is used to acquire preset sequence design information, determine the sequence generation method and corresponding sequence generation parameters; the sequence generation parameters include excitation amplitude parameters, initial value parameters and number of iterations;
[0105] The signal sequence generation submodule is used to generate the plurality of feature signal sequences according to the sequence generation method, in combination with the excitation amplitude parameter, the initial value parameter and the number of iterations.
[0106] In one embodiment, the target signal sequence determination module 602 includes:
[0107] The transformation processing submodule is used to perform a fast Fourier transform on the multiple feature signal sequences to obtain multiple transformed signal sequences;
[0108] The signal sequence filtering submodule is used to select the transformed signal sequence with the highest component power density at the target frequency as the target feature signal sequence based on the plurality of transformed signal sequences.
[0109] In one embodiment, the signal sequence filtering submodule includes:
[0110] A power spectral density determination unit is used to determine the power spectral density at the target frequency using the periodogram method; the power spectral density is used to characterize the distribution of time-domain signal power with frequency.
[0111] The target signal sequence obtaining unit is used to determine, from the plurality of transformed signal sequences, the transformed signal sequence with the largest component power density at the target frequency, based on the power spectral density at the target frequency, as the target feature signal sequence.
[0112] In one embodiment, the excitation signal obtaining module 603 includes:
[0113] A discrete sampling information acquisition submodule is used to acquire discrete sampling information, including discrete sampling interval parameters.
[0114] The target time-domain signal acquisition submodule is used to sample the target feature signal sequence according to the discrete sampling interval parameter to obtain the target time-domain signal.
[0115] In one embodiment, the target frequency is a low-frequency band frequency, and the device further includes:
[0116] The reference signal determination module is used to use the excitation signal corresponding to the target frequency as the reference signal;
[0117] A sampling interval information acquisition module is used to acquire sampling interval information; the sampling interval information includes multiple different sampling interval parameters;
[0118] Multiple excitation signal acquisition modules are used to sample and process the reference signal according to the sampling interval parameters to obtain excitation signals corresponding to frequencies other than the target frequency in the low-frequency band.
[0119] Each module in the excitation signal generation device based on the dielectric test of oil-paper insulation described above can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.
[0120] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 7 As shown, the computer device includes a processor, memory, communication interface, display screen, and input device connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage medium. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When executed by the processor, the computer program implements a method for generating excitation signals based on oil-paper insulation dielectric testing.
[0121] Those skilled in the art will understand that Figure 7 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.
[0122] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:
[0123] Obtain preset sequence design information, and generate multiple feature signal sequences based on the preset sequence design information; the preset sequence design information is used to indicate the sequence generation method and the corresponding sequence generation parameters;
[0124] Obtain the target frequency, and take the feature signal sequence that satisfies the component power density condition at the target frequency from the plurality of feature signal sequences as the target feature signal sequence;
[0125] The target time-domain signal is obtained based on the target feature signal sequence and used as the excitation signal corresponding to the target frequency; the excitation signal is used to identify the oil-paper insulation system during the oil-paper insulation dielectric test.
[0126] In one embodiment, when the processor executes the computer program, it also implements the steps of the excitation signal generation method based on the oil-paper insulation dielectric test in the other embodiments described above.
[0127] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:
[0128] Obtain preset sequence design information, and generate multiple feature signal sequences based on the preset sequence design information; the preset sequence design information is used to indicate the sequence generation method and the corresponding sequence generation parameters;
[0129] Obtain the target frequency, and take the feature signal sequence that satisfies the component power density condition at the target frequency from the plurality of feature signal sequences as the target feature signal sequence;
[0130] The target time-domain signal is obtained based on the target feature signal sequence and used as the excitation signal corresponding to the target frequency; the excitation signal is used to identify the oil-paper insulation system during the oil-paper insulation dielectric test.
[0131] In one embodiment, when the computer program is executed by a processor, it also implements the steps of the excitation signal generation method based on the oil-paper insulation dielectric test in the other embodiments described above.
[0132] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps:
[0133] Obtain preset sequence design information, and generate multiple feature signal sequences based on the preset sequence design information; the preset sequence design information is used to indicate the sequence generation method and the corresponding sequence generation parameters;
[0134] Obtain the target frequency, and take the feature signal sequence that satisfies the component power density condition at the target frequency from the plurality of feature signal sequences as the target feature signal sequence;
[0135] The target time-domain signal is obtained based on the target feature signal sequence and used as the excitation signal corresponding to the target frequency; the excitation signal is used to identify the oil-paper insulation system during the oil-paper insulation dielectric test.
[0136] In one embodiment, when the computer program is executed by a processor, it also implements the steps of the excitation signal generation method based on the oil-paper insulation dielectric test in the other embodiments described above.
[0137] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.
[0138] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
[0139] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.
Claims
1. A method for generating excitation signals based on oil-paper insulation dielectric testing, characterized in that, The method includes: Obtain preset sequence design information, and generate multiple feature signal sequences based on the preset sequence design information; the preset sequence design information is used to indicate the sequence generation method and the corresponding sequence generation parameters; Perform a Fast Fourier Transform on the multiple feature signal sequences to obtain multiple transformed signal sequences; The power spectral density at the target frequency is determined using the periodogram method; the power spectral density is used to characterize the distribution of time-domain signal power with frequency. Based on the power spectral density at the target frequency, the transformed signal sequence with the largest component power density at the target frequency is determined from the plurality of transformed signal sequences and used as the target feature signal sequence. The target time-domain signal is obtained based on the target feature signal sequence and used as the excitation signal corresponding to the target frequency; the excitation signal is used to identify the oil-paper insulation system during the oil-paper insulation dielectric test.
2. The method according to claim 1, characterized in that, The step of obtaining preset sequence design information and generating multiple feature signal sequences based on the preset sequence design information includes: Obtain preset sequence design information, determine the sequence generation method and corresponding sequence generation parameters; the sequence generation parameters include excitation amplitude parameters, initial value parameters and number of iterations; According to the sequence generation method, the plurality of feature signal sequences are generated by combining the excitation amplitude parameter, the initial value parameter and the number of iterations.
3. The method according to claim 1, characterized in that, The process of obtaining the target time-domain signal based on the target feature signal sequence includes: Obtain discrete sampling information; the discrete sampling information includes a discrete sampling interval parameter; The target feature signal sequence is sampled according to the discrete sampling interval parameter to obtain the target time domain signal.
4. The method according to any one of claims 1 to 3, characterized in that, The target frequency is a low-frequency band frequency. After the step of obtaining the target time-domain signal based on the target feature signal sequence as the excitation signal corresponding to the target frequency, the method further includes: The excitation signal corresponding to the target frequency is used as the reference signal; Obtain sampling interval information; the sampling interval information includes multiple different sampling interval parameters; The reference signal is sampled and processed according to the sampling interval parameters to obtain the excitation signal corresponding to the frequency other than the target frequency in the low frequency band.
5. An excitation signal generation device based on oil-paper insulation dielectric testing, characterized in that, The device includes: A signal sequence design module is used to acquire preset sequence design information and generate multiple feature signal sequences based on the preset sequence design information; the preset sequence design information is used to indicate the sequence generation method and the corresponding sequence generation parameters. The target signal sequence determination module is used to perform a fast Fourier transform on the multiple feature signal sequences to obtain multiple transformed signal sequences; to determine the power spectral density at the target frequency using the periodogram method; the power spectral density is used to characterize the distribution of time-domain signal power with frequency; and based on the power spectral density at the target frequency, to determine the transformed signal sequence with the largest component power density at the target frequency from the multiple transformed signal sequences, as the target feature signal sequence. The excitation signal acquisition module is used to obtain a target time-domain signal based on the target feature signal sequence, which serves as the excitation signal corresponding to the target frequency; the excitation signal is used to identify the oil-paper insulation system during the oil-paper insulation dielectric test.
6. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 4.
7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 4.
8. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 4.