Hydro-generator ultrahigh frequency partial discharge oscillation characteristic monitoring method and device

Abstract

The embodiment of the invention provides a hydro-generator ultrahigh frequency partial discharge oscillation characteristic monitoring method and device, and relates to the technical field of signal processing. The hydro-generator ultrahigh frequency partial discharge oscillation characteristic monitoring method comprises the following steps: acquiring a partial discharge signal; preprocessing the partial discharge signal to obtain a preprocessed signal; extracting a first-order envelope line of the preprocessed signal, and obtaining a second-order envelope line based on the first-order envelope line; and processing the pulse in the partial discharge signal based on the second-order envelope line to obtain a processed partial discharge signal. According to the implementation mode provided by the invention, subtle changes and attenuation behaviors in the partial discharge signal are better captured, the processing precision of the partial discharge signal is improved, and the rapid and real-time monitoring requirement of partial discharge and the interference resistance of a complex electromagnetic environment are met.

Description

Technical Field

[0001] The present application relates to the technical field of data compression, and specifically to a method for monitoring ultra-high frequency partial discharge oscillation characteristics of a hydro-turbine generator, a device for monitoring ultra-high frequency partial discharge oscillation characteristics of a hydro-turbine generator, an electronic device and a corresponding storage medium. Background Art

[0002] Partial discharge is accompanied by the rapid release of energy and excites local electromagnetic waves or mechanical vibrations. Since electrical equipment has complex inductance and capacitance (LC) circuits inside, based on the inherent resonant characteristics of the electrical system, when local discharge generates high-frequency pulse signals, these pulse signals will excite the natural resonant frequency in the equipment and form high-frequency oscillations. For the generator winding, multiple possible LC resonant circuits are formed between the inductance of the winding and the capacitance of the insulation layer. The natural frequencies of these circuits are usually between tens of kilohertz and hundreds of kilohertz. The pulse excitation of partial discharge will trigger the resonance of these LC circuits, resulting in the generation of oscillating signals. At the same time, the resistance and dielectric loss in the electrical equipment will dissipate the resonant energy, eventually causing the oscillation to gradually decay, which is manifested as the amplitude of the signal gradually decaying over time until it disappears completely, making the partial discharge signal have an oscillating decay phenomenon.

[0003] In addition, the electromagnetic waves generated by partial discharge will propagate along different paths in electrical equipment. During the propagation process, the electromagnetic waves will encounter the boundaries of different media, such as the interface between the winding and the insulation layer, the connection of the cable, etc., causing the reflection and refraction of the electromagnetic waves, forming a complex multi-path propagation phenomenon. Due to the different propagation speeds and impedances in different media, the signal is reflected at the interface of the medium. These reflected waves are superimposed on the original direct waves, further generating oscillation phenomena. The reflected waves will gradually weaken, but they will still interfere with the overall signal for a period of time, forming an oscillating waveform. Since partial discharge is essentially a transient phenomenon, the electromagnetic waves it generates have high frequency and short-term characteristics. The transient characteristics of partial discharge determine that the oscillation signal it excites is also transient and decays rapidly over time.

[0004] The traditional energy spectrum is to convert the signal from the time domain to the frequency domain through the frequency domain analysis tool, and analyze the frequency components of the signal and its corresponding energy distribution. Due to the oscillation attenuation characteristics of the partial discharge signal, the energy and frequency components of the signal will gradually decrease over time. The energy spectrum analysis can only provide the average frequency distribution of the signal in the entire time period, and cannot identify the details of the signal frequency change over time. This may cause the frequency components of the oscillation part to be ignored, or because the frequency components are relatively dispersed, it is difficult to obtain effective diagnostic information. The threshold processing method relies on the signal amplitude exceeding a certain set fixed threshold to determine whether partial discharge occurs. However, as the oscillation attenuation signal gradually decays, the signal amplitude may exceed the threshold in the initial stage, but as time goes by, the signal amplitude will quickly drop to a level below the threshold, resulting in the inability of the threshold processing method to effectively track and identify subsequent attenuation signals, and it is difficult to fully capture and identify partial discharge signals. At the same time, the threshold processing method is very sensitive to noise, especially when the amplitude of the partial discharge signal is close to the noise level, the noise may falsely trigger the detection system. When there is oscillation attenuation in the signal, the subsequent low-amplitude signal may be buried in the noise, and the fixed threshold is difficult to effectively distinguish between the signal and the noise, which may frequently trigger the threshold detection and generate a large number of false alarms.

[0005] Therefore, for the ultra-high frequency online monitoring of partial discharge in the stator winding bars of hydro-turbine generators, it is necessary to improve the time domain analysis method to better capture the subtle changes and attenuation behavior in the partial discharge signal, improve the accuracy of partial discharge signal processing, and meet the needs of rapid and real-time partial discharge monitoring and anti-interference in complex electromagnetic environments. Summary of the invention

[0006] The purpose of the embodiment of the present application is to provide a method and device for monitoring the ultra-high frequency partial discharge oscillation characteristics of a hydro-turbine generator. First, the noise and interference in the non-target frequency band in the ultra-high frequency partial discharge signal are filtered out by a bandpass filter, and the core frequency components of the ultra-high frequency partial discharge signal are retained. For pulse detection and envelope extraction, a time domain pulse detection algorithm is used to extract the transient pulse characteristics of the partial discharge signal. A second-order envelope analysis is used to obtain the envelope information of the signal through the Hilbert transform of the partial discharge signal, and the amplitude change characteristics of the oscillation attenuation signal are extracted, especially when the signal amplitude is small, the signal attenuation trend can also be identified. Then, in the extracted envelope signal, peak detection is performed, and the type and intensity of the partial discharge signal are identified through characteristic parameters such as the amplitude, duration and pulse interval of the time domain pulse, so as to at least solve some of the problems in the background technology.

[0007] In order to achieve the above-mentioned purpose, the present application provides a method for monitoring the ultra-high frequency partial discharge oscillation characteristics of a hydro-turbine generator, the method comprising: obtaining a partial discharge signal; preprocessing the partial discharge signal to obtain a preprocessed signal; extracting a first-order envelope of the preprocessed signal, and obtaining a second-order envelope based on the first-order envelope; processing pulses in the partial discharge signal based on the second-order envelope to obtain a processed partial discharge signal.

[0008] Optionally, obtaining a partial discharge signal includes: determining a sampling frequency according to a frequency range of the partial discharge signal; acquiring the partial discharge signal through a data acquisition card based on the sampling frequency; and converting the partial discharge signal acquired by the high-speed data acquisition card through an analog-to-digital converter.

[0009] Optionally, the preprocessing includes bandpass filtering and normalization; the bandpass filtering is implemented by constructing an impulse response of a filter; and the normalization is implemented by a ratio with a maximum absolute value amplitude of a signal.

[0010] Optionally, extracting the first-order envelope of the preprocessed signal includes: performing a Hilbert transform on the preprocessed signal to obtain an analytical signal; and extracting a modulus value of the analytical signal to obtain an envelope of the analytical signal as the first-order envelope of the preprocessed signal.

[0011] Optionally, obtaining a second-order envelope based on the first-order envelope includes: performing Hilbert transform on the first-order envelope of the preprocessed signal again to obtain a second-order analytical signal; and extracting the amplitude of the second-order analytical signal as the second-order envelope of the preprocessed signal.

[0012] Optionally, the pulses in the local discharge signal are processed based on the second-order envelope to obtain a processed local discharge signal, including: extracting the pulses in the local discharge signal to obtain an original data sequence; obtaining a second-order envelope sequence according to the maximum value of the second-order envelope of the original data sequence and an interpolation algorithm; searching the second-order envelope sequence for pulses with amplitudes higher than the white noise level of the local discharge signal, and determining the starting point and the ending point of each pulse to obtain a single pulse start and end index matrix; judging the interval time of adjacent pulses in the single pulse start and end index matrix, merging adjacent pulses whose interval time is less than a preset time threshold, to obtain an updated single pulse start and end index matrix; and using the updated single pulse start and end index matrix as the processed local discharge signal.

[0013] Optionally, determining the starting point and the ending point of each pulse includes: obtaining a maximum value sequence based on pulses in the second-order envelope sequence whose amplitudes are higher than the white noise level of the local discharge signal; taking the maximum amplitude of each pulse in the maximum value sequence as a starting point, searching for the second-order envelope zero point to the left and to the right respectively, and indexing the searched left-side second-order envelope zero point and right-side second-order envelope zero point as the starting point and the ending point of the single pulse.

[0014] The present application also provides a device for monitoring the ultra-high frequency partial discharge oscillation characteristics of a hydro-turbine generator, which includes: a signal acquisition module for acquiring a partial discharge signal; a preprocessing module for preprocessing the partial discharge signal to obtain a preprocessed signal; an envelope extraction module for extracting a first-order envelope of the preprocessed signal and obtaining a second-order envelope based on the first-order envelope; and a signal processing module for processing pulses in the partial discharge signal based on the second-order envelope to obtain a processed partial discharge signal.

[0015] The present application also provides an electronic device, comprising: at least one processor; a memory connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the at least one processor implements the aforementioned method for monitoring ultra-high frequency partial discharge oscillation characteristics of a hydro-turbine generator by executing the instructions stored in the memory.

[0016] The present application also provides a machine-readable storage medium on which instructions are stored. When the instructions are executed by a processor, the processor is configured to execute the aforementioned method for monitoring ultra-high frequency partial discharge oscillation characteristics of a hydro-turbine generator.

[0017] A computer program product is also provided in the present application, including a computer program, which, when executed by a processor, implements the aforementioned method for monitoring ultra-high frequency partial discharge oscillation characteristics of a hydro-generator.

[0018] The above technical solution has the following beneficial effects:

[0019] The implementation method of the present application better captures subtle changes and attenuation behaviors in partial discharge signals, improves the accuracy of partial discharge signal processing, meets the needs of fast and real-time monitoring of partial discharges, and has the advantage of anti-interference in complex electromagnetic environments.

[0020] Other features and advantages of the embodiments of the present application will be described in detail in the subsequent specific implementation section. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The accompanying drawings are used to provide a further understanding of the embodiments of the present application and constitute a part of the specification. Together with the following specific implementations, they are used to explain the embodiments of the present application, but do not constitute a limitation on the embodiments of the present application. In the accompanying drawings:

[0022] Figure 1 A schematic diagram of the steps of the method for monitoring ultra-high frequency partial discharge oscillation characteristics of a hydro-turbine generator according to an embodiment of the present application is schematically shown;

[0023] Figure 2 A diagram schematically shows the implementation process of the method for monitoring ultra-high frequency partial discharge oscillation characteristics of a hydro-turbine generator according to an embodiment of the present application;

[0024] Figure 3 A schematic diagram of the structure of a device for monitoring ultra-high frequency partial discharge oscillation characteristics of a hydro-turbine generator according to an embodiment of the present application is shown;

[0025] Figure 4 The internal structure of an electronic device according to an embodiment of the present application is schematically shown. DETAILED DESCRIPTION

[0026] The specific implementation of the embodiment of the present application is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described here is only used to illustrate and explain the embodiment of the present application, and is not used to limit the embodiment of the present application.

[0027] Figure 1 The following is a schematic diagram showing the steps of the method for monitoring the ultra-high frequency partial discharge oscillation characteristics of a hydro-turbine generator according to an embodiment of the present application. Figure 1 As shown, a method for monitoring ultra-high frequency partial discharge oscillation characteristics of a hydro-generator, the method comprising:

[0028] S01, obtaining a partial discharge signal;

[0029] S02, preprocessing the partial discharge signal to obtain a preprocessed signal;

[0030] S03, extracting the first-order envelope of the preprocessed signal, and obtaining a second-order envelope based on the first-order envelope;

[0031] S04. Processing the pulses in the partial discharge signal based on the second-order envelope to obtain a processed partial discharge signal.

[0032] Through the above implementation, the second-order envelope analysis is adopted to obtain the envelope information of the signal through the Hilbert transform of the partial discharge signal, and the amplitude change characteristics of the oscillation attenuation signal are extracted, especially when the signal amplitude is small, the signal attenuation trend can also be identified. Then, in the extracted envelope signal, peak detection is performed, and the type and intensity of the partial discharge signal are identified through characteristic parameters such as the amplitude, duration and pulse interval of the time domain pulse. Combined with the multi-threshold judgment method, it is ensured that the partial discharge signal can be effectively distinguished from the background noise.

[0033] This embodiment is preferably applied to a hydro-generator, especially to ultra-high frequency monitoring of partial discharge of stator winding bars.

[0034] In some optional embodiments of the present application, obtaining a partial discharge signal includes: determining a sampling frequency according to a frequency range of the partial discharge signal; the partial discharge signal is usually transmitted in the form of a high-frequency pulse, with a frequency range of 300MHz to 3GHz, and is manifested as a short-time signal with oscillation characteristics in the time domain. The partial discharge signal is obtained by collecting the partial discharge signal through a data acquisition card based on the sampling frequency; and the partial discharge signal collected by the high-speed data acquisition card is converted by an analog-to-digital converter. The signal acquisition device includes a data acquisition card and a high-speed ADC (analog-to-digital converter) for sampling the signal to ensure that the acquisition frequency is high enough to capture the details of the high-frequency partial discharge signal. The partial discharge signal is generally expressed as:

[0035] x(t)=A(t)·cos(2πfct+φ(t))+n(t) (1)

[0036] Among them, A(t) is the envelope of the signal, reflecting the amplitude change of the signal; fc is the carrier frequency (the center frequency of the partial discharge signal); φ(t) is the instantaneous phase of the signal; and n(t) is the noise.

[0037] In some optional implementations of the present application, the preprocessing includes bandpass filtering and normalization; the bandpass filtering is implemented by constructing an impulse response of a filter; specifically, bandpass filtering can be implemented by constructing an impulse response of a filter, assuming that the transfer function of the filter is H(f), the filtered signal y(t) can be expressed as:

[0038] y(t)=x(t)*h(t) (2)

[0039] Wherein, h(t) is the time domain impulse response of the bandpass filter, and * represents the convolution operation. The frequency response of the filter can be designed to meet the bandpass characteristics and filter out frequency components below 300 MHz and above 3 GHz. This embodiment uses a bandpass filter to filter out noise and interference in non-target frequency bands in the UHF PD signal, retain the core frequency components of the UHF PD signal, and improve the accuracy of subsequent extraction of the PD signal.

[0040] The normalization process is implemented by the ratio of the maximum absolute value amplitude of the signal. Specifically, the normalization process is performed using the following formula:

[0041]

[0042] Wherein, max(|x(t)|) is the maximum absolute value amplitude of the signal x(t). The normalized signal xb(t) is in the range of [-1,1]. The normalization processing in this embodiment can improve the standardization of the signal x(t).

[0043] In some optional embodiments of the present application, extracting the first-order envelope of the preprocessed signal includes: performing Hilbert transform on the preprocessed signal to obtain an analytical signal; for the partial discharge signal x(t), performing Hilbert transform on the analytical signal Z(t):

[0044]

[0045] in, is the Hilbert transform of the signal x(t), which is defined as:

[0046]

[0047] "PV" stands for Cauchy principal value integration to handle singular points in the integral.

[0048] Then, the modulus of the analytical signal is extracted to obtain the envelope of the analytical signal as the first-order envelope of the preprocessed signal. The envelope A(t) of the analytical signal is the modulus of the analytical signal, which represents the instantaneous amplitude of the partial discharge signal, that is, the first-order envelope of the signal, and the calculation formula is:

[0049]

[0050] In some optional embodiments of the present application, obtaining a second-order envelope based on the first-order envelope includes: performing Hilbert transformation on the first-order envelope of the preprocessed signal again to obtain a second-order analytical signal; after extracting the first-order envelope A(t), performing a second Hilbert transformation on the first-order envelope to extract a higher-order instantaneous amplitude change, i.e., a second-order envelope. The second-order envelope can be obtained by performing Hilbert transformation on A(t) again to obtain a second-order analytical signal z2(t).

[0051]

[0052] Then, the amplitude is extracted as the second-order envelope A2(t), that is, the amplitude of the second-order analytical signal is extracted as the second-order envelope of the preprocessed signal. The calculation formula of the second-order envelope A2(t) is:

[0053]

[0054] Since the partial discharge signal has the characteristic of attenuation and oscillation, the second-order envelope processing can reflect the more subtle oscillation and attenuation process of the signal, thereby improving the detection sensitivity of the discharge signal.

[0055] In some optional embodiments of the present application, the pulses in the local discharge signal are processed based on the second-order envelope to obtain a processed local discharge signal, including: extracting the pulses in the local discharge signal to obtain an original data sequence; obtaining a second-order envelope sequence according to the maximum value of the second-order envelope of the original data sequence and the interpolation algorithm; searching for pulses in the second-order envelope sequence with an amplitude higher than the white noise level of the local discharge signal, and determining the starting point and the ending point of each pulse to obtain a single pulse start-end index matrix; judging the interval time of adjacent pulses in the single pulse start-end index matrix, merging adjacent pulses whose interval time is less than a preset time threshold, and obtaining an updated single pulse start-end index matrix; using the updated single pulse start-end index matrix as the processed local discharge signal. Specifically, let the original data sequence be A N×1 , A i is the signal amplitude, N is the original data length, and the data length is determined by the pulse interval:

[0056] Δt=t i+1 -t i (9)

[0057] First, remove the mean of the original data and take the absolute value, and search for the maximum value twice in succession to obtain the sequence P peak , and then for the sequence P peak Perform linear interpolation to obtain a second-order envelope sequence P of length N N×1 .

[0058] P peak (t i )=max(A2(t))for t∈[t i , t i+1 ] (10)

[0059] Among them, P peak (t i ) means that in the interval [t i , t i+1] The peak value detected within . The amplitude of the pulse is determined by measuring the peak value of the pulse, and the duration of the pulse is determined by measuring the half-height width of the pulse. Search for the maximum value sequence P′ whose second-order envelope amplitude is higher than the white noise level of the original signal m×1 , m is the number of maximum values ​​of the second-order envelope that are higher than the white noise level, and P′ i (i∈[1,2,…,m]) is the starting point, and the second-order envelope zero point is searched to the left and right respectively, and its index is recorded as the single pulse starting point P si With the end point P ei , get the single pulse start and end index matrix: P Index =[P s1 , P e1 ;P s2 , P e2 ;…;P sm , P em ]. Since the same pulse has multiple second-order peak points, the edge search results in repeated start and end points of the single pulse, and the repeated rows need to be deleted. If a single pulse has a discontinuous second-order envelope, the single pulse will be Index In the form of two lines, P ei With P si+1 The phase difference is small, so the extracted pulse interval distance d pluse When the interval between two pulses is d pluse >0.125μs (10 data points, which can be set manually), it is determined as two pulses, otherwise it is considered as the same pulse. Then update the single pulse index matrix P Index =[P s1 , P e1 ;P Max1 ;P s2 , P e2 , P Max2 ;…;P sm , P em , P Maxn ].

[0060] Optionally, in the previous embodiment, determining the starting point and the ending point of each pulse includes: obtaining a maximum value sequence based on pulses in the second-order envelope sequence whose amplitude is higher than the white noise level of the partial discharge signal; starting from the maximum amplitude of each pulse in the maximum value sequence, searching for the second-order envelope zero point to the left and to the right respectively, and indexing the searched left second-order envelope zero point and right second-order envelope zero point as the starting point and the ending point of the single pulse. This embodiment provides a method for determining the starting point and the ending point of a single pulse based on the second-order envelope, which has the advantage of extracting the pulse duration more accurately.

[0061] Through the above implementation, the method in this implementation is combined with a multi-threshold determination method to ensure that the partial discharge signal and the background noise can be effectively distinguished, thereby improving the accuracy of the partial discharge signal during the extraction process.

[0062] Figure 2 The following diagram schematically shows the implementation process of the method for monitoring the ultra-high frequency partial discharge oscillation characteristics of a hydro-turbine generator according to the embodiment of the present application. Figure 2 As shown, the method includes: acquiring the original pulse signal, preprocessing the collected signal, the preprocessing includes bandpass filtering and normalization processing, then performing first-order envelope extraction and second-order envelope extraction, and finally extracting the processed partial discharge signal through pulse monitoring.

[0063] Based on the same inventive concept, the present application also provides a device for monitoring ultra-high frequency partial discharge oscillation characteristics of a hydro-turbine generator. Figure 3 The schematic diagram of the structure of the ultra-high frequency partial discharge oscillation characteristic monitoring device of a hydro-turbine generator according to the embodiment of the present application is shown schematically. Figure 3 As shown, the device includes: a signal acquisition module for acquiring a local discharge signal; a preprocessing module for preprocessing the local discharge signal to obtain a preprocessed signal; an envelope extraction module for extracting a first-order envelope and a second-order envelope of the preprocessed signal; and a signal processing module for processing a pulse in the local discharge signal based on the first-order envelope and the second-order envelope to obtain a processed local discharge signal.

[0064] In some optional embodiments of the present application, obtaining a local discharge signal includes: determining a sampling frequency according to a frequency range of the local discharge signal; acquiring the local discharge signal through a data acquisition card based on the sampling frequency; and converting the local discharge signal acquired by the high-speed data acquisition card through an analog-to-digital converter.

[0065] In some optional embodiments of the present application, the preprocessing includes bandpass filtering and normalization; the bandpass filtering is achieved by constructing an impulse response of the filter; and the normalization is achieved by the ratio with the maximum absolute value amplitude of the signal.

[0066] In some optional embodiments of the present application, extracting the first-order envelope of the preprocessed signal includes: obtaining an analytical signal by Hilbert transforming the preprocessed signal; extracting the modulus of the analytical signal to obtain the envelope of the analytical signal as the first-order envelope of the preprocessed signal.

[0067] In some optional embodiments of the present application, a second-order envelope is obtained based on the first-order envelope, including: performing a Hilbert transform on the first-order envelope of the preprocessed signal to obtain a second-order analytical signal; and extracting the amplitude of the second-order analytical signal as the second-order envelope of the preprocessed signal.

[0068] In some optional embodiments of the present application, the pulses in the local discharge signal are processed based on the second-order envelope to obtain a processed local discharge signal, including: extracting the pulses in the local discharge signal to obtain an original data sequence; obtaining a second-order envelope sequence according to the maximum value of the second-order envelope of the original data sequence and an interpolation algorithm; searching the second-order envelope sequence for pulses with amplitudes higher than the white noise level of the local discharge signal, and determining the starting point and the ending point of each pulse to obtain a single pulse start and end index matrix; judging the interval time of adjacent pulses in the single pulse start and end index matrix, merging adjacent pulses whose interval time is less than a preset time threshold, to obtain an updated single pulse start and end index matrix; and using the updated single pulse start and end index matrix as the processed local discharge signal.

[0069] In some optional embodiments of the present application, the starting point and the ending point of each pulse are determined, including: obtaining a maximum value sequence based on pulses in the second-order envelope sequence whose amplitudes are higher than the white noise level of the local discharge signal; taking the maximum amplitude of each pulse in the maximum value sequence as the starting point, searching for the second-order envelope zero point to the left and to the right respectively, and indexing the searched left-side second-order envelope zero point and right-side second-order envelope zero point as the starting point and the ending point of the single pulse.

[0070] The specific definition of each functional module in the above-mentioned ultra-high frequency partial discharge oscillation characteristics monitoring device of the hydro-turbine generator can be found in the definition of the ultra-high frequency partial discharge oscillation characteristics monitoring method of the hydro-turbine generator mentioned above, which will not be repeated here. Each module in the above-mentioned system can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the electronic device in the form of hardware, or can be stored in the memory of the electronic device in the form of software, so that the processor can call and execute the operations corresponding to the above modules. It also better captures the subtle changes and attenuation behaviors in the partial discharge signal, improves the accuracy of the partial discharge signal processing, meets the needs of fast and real-time monitoring of partial discharge, and has the advantage of anti-interference in complex electromagnetic environments.

[0071] In some embodiments of the present application, an electronic device is also provided, comprising: at least one processor; a memory connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the at least one processor executes the aforementioned method for monitoring the ultra-high frequency partial discharge oscillation characteristics of a hydro-turbine generator. The internal structure diagram can be as follows Figure 3 shown. Figure 4 The internal structure diagram of an electronic device according to an embodiment of the present application is schematically shown. The electronic device includes a processor A01, a network interface A02, a memory (not shown in the figure) and a database (not shown in the figure) connected via a system bus. Among them, the processor A01 of the electronic device is used to provide computing and control capabilities. The memory of the electronic device includes an internal memory A03 and a non-volatile storage medium A04. The non-volatile storage medium A04 stores an operating system B01, a computer program B02 and a database (not shown in the figure). The internal memory A03 provides an environment for the operation of the operating system B01 and the computer program B02 in the non-volatile storage medium A04. The network interface A02 of the electronic device is used to communicate with an external terminal through a network connection. When the computer program B02 is executed by the processor A01, a method for monitoring the ultra-high frequency partial discharge oscillation characteristics of a hydro-turbine generator is implemented.

[0072] Those skilled in the art will understand that Figure 4 The structure shown in the figure is merely a block diagram of a partial structure related to the scheme of the present application, and does not constitute a limitation on the electronic device to which the scheme of the present application is applied. The specific electronic device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0073] In one embodiment provided in the present application, a machine-readable storage medium is provided, on which instructions are stored, and when the instructions are executed by a processor, the processor is configured to execute the aforementioned method for monitoring ultra-high frequency partial discharge oscillation characteristics of a hydro-turbine generator.

[0074] In one embodiment provided in the present application, a computer program product is provided, including a computer program, which, when executed by a processor, implements the aforementioned method for monitoring ultra-high frequency partial discharge oscillation characteristics of a hydro-turbine generator.

[0075] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0076] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0077] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0078] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0079] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0080] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0081] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0082] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0083] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A method for monitoring ultra-high frequency partial discharge oscillation characteristics of a hydro-generator, characterized in that: The method includes: Acquire partial discharge signals; Preprocessing the partial discharge signal to obtain a preprocessed signal; Extracting a first-order envelope of the preprocessed signal, and obtaining a second-order envelope based on the first-order envelope; The pulses in the partial discharge signal are processed based on the second-order envelope to obtain a processed partial discharge signal.

2. The method according to claim 1, characterized in that Acquire partial discharge signals, including: Determining a sampling frequency according to a frequency range of the partial discharge signal; Based on the sampling frequency, a partial discharge signal is acquired by collecting data through a data acquisition card; The partial discharge signal collected by the high-speed data acquisition card is converted through an analog-to-digital converter.

3. The method according to claim 1, characterized in that: The preprocessing includes bandpass filtering and normalization; The bandpass filtering process is achieved by constructing an impulse response of the filter; The normalization is achieved by scaling with the maximum absolute amplitude of the signal.

4. The method according to claim 1, characterized in that: Extracting the first-order envelope of the preprocessed signal includes: Obtain an analytical signal by Hilbert transforming the preprocessed signal; The modulus of the analytical signal is extracted to obtain the envelope of the analytical signal as the first-order envelope of the preprocessed signal.

5. The method according to claim 1, characterized in that Obtaining a second-order envelope based on the first-order envelope includes: The first-order envelope of the preprocessed signal is transformed again by Hilbert transform to obtain a second-order analytical signal; The amplitude of the second-order analytical signal is extracted as the second-order envelope of the preprocessed signal.

6. The method according to claim 1, characterized in that Processing the pulse in the partial discharge signal based on the second-order envelope to obtain a processed partial discharge signal includes: Extracting pulses from the partial discharge signal to obtain an original data sequence; Obtaining a second-order envelope sequence according to the maximum value of the second-order envelope of the original data sequence and an interpolation algorithm; Searching for pulses with amplitudes higher than the white noise level of the partial discharge signal in the second-order envelope sequence, and determining the starting point and the ending point of each pulse to obtain a single pulse start-end index matrix; Determine the interval time of adjacent pulses in the single pulse start and end index matrix, merge adjacent pulses whose interval time is less than a preset time threshold, and obtain an updated single pulse start and end index matrix; The updated single pulse start-stop index matrix is ​​used as the processed partial discharge signal.

7. The method according to claim 6, characterized in that Determine the start and end points of each pulse, including: Obtaining a maximum value sequence based on pulses in the second-order envelope sequence whose amplitude is higher than the white noise level of the partial discharge signal; Taking the maximum amplitude of each pulse in the maximum value sequence as the starting point, the second-order envelope zero point is searched to the left and right respectively, and the searched left second-order envelope zero point and right second-order envelope zero point are indexed as the starting point and ending point of the single pulse.

8. A device for monitoring ultra-high frequency partial discharge oscillation characteristics of a hydro-generator, characterized in that: The device includes: A signal acquisition module, used for acquiring partial discharge signals; A preprocessing module, used for preprocessing the partial discharge signal to obtain a preprocessed signal; An envelope extraction module, used to extract a first-order envelope of the preprocessed signal, and obtain a second-order envelope based on the first-order envelope; and The signal processing module is used to process the pulses in the partial discharge signal based on the second-order envelope to obtain a processed partial discharge signal.

9. An electronic device, characterized in that: include: at least one processor; a memory connected to the at least one processor; Wherein, the memory stores instructions that can be executed by the at least one processor, and the at least one processor implements the steps of the method for monitoring ultra-high frequency partial discharge oscillation characteristics of a hydro-turbine generator as described in any one of claims 1 to 7 by executing the instructions stored in the memory.

10. A computer-readable storage medium having a computer program / instruction stored thereon, characterized in that: When the computer program / instruction is executed by a processor, the steps of the method for monitoring ultra-high frequency partial discharge oscillation characteristics of a hydro-turbine generator as described in any one of claims 1 to 7 are implemented.

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