Method and device for monitoring oscillation characteristics of water turbine generator ultra-high frequency partial discharge

Abstract

This application provides a method and apparatus for monitoring the ultra-high frequency partial discharge (UHF) oscillation characteristics of a hydro-generator, relating to the field of signal processing technology. The method includes: acquiring a partial discharge signal; preprocessing the partial discharge signal to obtain a preprocessed signal; extracting the first-order envelope of the preprocessed signal, and obtaining a second-order envelope based on the first-order envelope; and processing the pulses in the partial discharge signal based on the second-order envelope to obtain a processed partial discharge signal. The implementation provided in this application better captures subtle changes and attenuation behavior in the partial discharge signal, improves the accuracy of partial discharge signal processing, and meets the requirements for rapid and real-time monitoring of partial discharge and resistance to interference in complex electromagnetic environments.

Description

Technical Field

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

[0002] Partial discharge is accompanied by a rapid release of energy and excites local electromagnetic waves or mechanical vibrations. Due to the complex inductive and capacitive (LC) circuits within electrical equipment, and based on the inherent resonant characteristics of the electrical system, when a partial discharge generates a high-frequency pulse signal, these pulse signals excite the natural resonant frequency within the equipment, forming high-frequency oscillations. For generator windings, multiple possible LC resonant circuits are formed between the winding's inductance and the insulation layer's capacitance. The natural frequencies of these circuits are typically between tens and hundreds of kilohertz. The pulse excitation of partial discharge triggers resonance in these LC circuits, leading to the generation of oscillating signals. Simultaneously, the resistance and dielectric losses within the electrical equipment dissipate the resonant energy, ultimately causing the oscillations to gradually decay. This is manifested as the signal amplitude gradually decreasing over time until it disappears completely, resulting in the oscillation decay phenomenon of the partial discharge signal.

[0003] Furthermore, the electromagnetic waves generated by partial discharge propagate along different paths within electrical equipment. During propagation, these waves encounter the boundaries of different media, such as the interface between windings and insulation layers, and cable connections, causing reflection and refraction, resulting in complex multipath propagation phenomena. Due to differences in propagation speed and impedance in different media, signals are reflected at the medium interfaces. These reflected waves superimpose with the original direct wave, further generating oscillations. While the reflected waves gradually weaken, they still interfere with the overall signal for a period of time, forming oscillating waveforms. Because partial discharge is inherently a transient phenomenon, the electromagnetic waves it generates are characterized by high frequency and short duration. The transient nature of partial discharge determines that the oscillating signals it excites are also transient and decay rapidly over time.

[0004] Traditional energy spectrum analysis uses frequency domain analysis tools to convert signals from the time domain to the frequency domain and analyzes the frequency components and their corresponding energy distribution. Due to the oscillating decay characteristics of partial discharge (PD) signals, the signal's energy and frequency components gradually decrease over time. Energy spectrum analysis can only provide the average frequency distribution of the signal over the entire time period, failing to identify the details of frequency changes over time. This may lead to the oscillating frequency components being ignored, or the frequency components being too dispersed to obtain effective diagnostic information. Thresholding methods rely on the signal amplitude exceeding a certain fixed threshold to determine whether partial discharge has occurred. However, as the oscillating decay signal gradually weakens, the signal amplitude may initially exceed the threshold, but over time, the signal amplitude will rapidly drop below the threshold level. This makes it difficult for thresholding methods to effectively track and identify subsequent decaying signals, making it difficult to completely capture and identify PD signals. Furthermore, thresholding methods are highly sensitive to noise, especially when the PD signal amplitude is close to noise levels, where noise may falsely trigger the detection system. When there is oscillation attenuation in the signal, subsequent low-amplitude signals may be buried in noise, and a fixed threshold is difficult to effectively distinguish between signal and noise, which may frequently trigger threshold detection and generate a large number of false alarms.

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

[0006] The purpose of this application is to provide a method and apparatus for monitoring the oscillation characteristics of ultra-high frequency (UHF) partial discharge (PD) in a hydro-generator. First, a bandpass filter is used to remove noise and interference from non-target frequency bands in the UHF PD signal, retaining the core frequency components. For pulse detection and envelope extraction, a time-domain pulse detection algorithm is used to extract the transient pulse characteristics of the PD signal. Second-order envelope analysis is employed, using the Hilbert transform of the PD signal to obtain the signal envelope information and extract the amplitude variation characteristics of the oscillation attenuation signal, particularly effective when the signal amplitude is small, thus identifying the signal attenuation trend. Then, peak detection is performed on the extracted envelope signal. By using characteristic parameters such as the amplitude, duration, and pulse interval of the time-domain pulse, the type and intensity of the PD signal are identified, thereby at least addressing some of the problems in the background art.

[0007] To achieve the above objectives, this application provides a method for monitoring the ultra-high frequency partial discharge oscillation characteristics of a hydro-generator. The method includes: acquiring a partial discharge signal; preprocessing the partial discharge signal to obtain a preprocessed signal; extracting the first-order envelope of the preprocessed signal and obtaining a second-order envelope based on the first-order envelope; and processing the pulses in the partial discharge signal based on the second-order envelope to obtain a processed partial discharge signal.

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

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

[0010] Optionally, extracting the first-order envelope of the preprocessed signal includes: obtaining an analytic signal from the preprocessed signal through a Hilbert transform; and extracting the magnitude of the analytic signal to obtain the envelope of the analytic signal as the first-order envelope of the preprocessed signal.

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

[0012] Optionally, processing the pulses 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 based on the maxima of the second-order envelope of the original data sequence and an interpolation algorithm; searching for pulses in the second-order envelope sequence whose amplitude is higher than the white noise level of the partial discharge signal, and determining the start and end points 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 with an interval time less than a preset time threshold to obtain an updated single-pulse start-end index matrix; and using the updated single-pulse start-end index matrix as the processed partial discharge signal.

[0013] Optionally, determining the start and end points 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 partial discharge signal; starting from the maximum amplitude of each pulse in the maximum value sequence, searching for the zero points of the second-order envelope to the left and right respectively, and indexing the searched left and right second-order envelope zero points as the start and end points of a single pulse.

[0014] This application also provides a device for monitoring the ultra-high frequency partial discharge oscillation characteristics of a hydro-generator. The device 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 the 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 the pulses in the partial discharge signal based on the second-order envelope to obtain a processed partial discharge signal.

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

[0016] This application also provides a machine-readable storage medium storing instructions that, when executed by a processor, configure the processor to perform the aforementioned method for monitoring the ultra-high frequency partial discharge oscillation characteristics of a hydro-generator.

[0017] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the aforementioned method for monitoring the ultra-high frequency partial discharge oscillation characteristics of a hydro-generator.

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

[0019] The embodiments of this application better capture subtle changes and attenuation behavior in partial discharge signals, improve the accuracy of partial discharge signal processing, meet the needs of rapid and real-time monitoring of partial discharge, and have the advantage of anti-interference in complex electromagnetic environments.

[0020] Other features and advantages of the embodiments of this application will be described in detail in the following detailed description section. Attached Figure Description

[0021] The accompanying drawings are provided to further illustrate the embodiments of this application and form part of the specification. They are used together with the following detailed description to explain the embodiments of this application, but do not constitute a limitation on the embodiments of this application. In the drawings:

[0022] Figure 1 This illustration schematically shows the steps of a method for monitoring the ultra-high frequency partial discharge oscillation characteristics of a hydro-generator according to an embodiment of this application.

[0023] Figure 2 The diagram illustrates the implementation process of the method for monitoring the ultra-high frequency partial discharge oscillation characteristics of a hydro-generator according to the embodiments of this application.

[0024] Figure 3 This schematic diagram illustrates the structure of a monitoring device for ultra-high frequency partial discharge oscillation characteristics of a hydro-generator according to an embodiment of this application.

[0025] Figure 4 The diagram schematically illustrates the internal structure of an electronic device according to an embodiment of this application. Detailed Implementation

[0026] The specific embodiments of this application will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the embodiments of this application.

[0027] Figure 1 The illustration shows a schematic diagram of the steps in the method for monitoring the ultra-high frequency partial discharge oscillation characteristics of a hydro-generator according to an embodiment of this application. For example... Figure 1 As shown, a method for monitoring the ultra-high frequency partial discharge oscillation characteristics of a hydro-generator includes:

[0028] S01. Acquire partial discharge signal;

[0029] S02. Preprocess the partial discharge signal to obtain a preprocessed signal;

[0030] S03. Extract the first-order envelope of the preprocessed signal, and obtain the second-order envelope based on the first-order envelope;

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

[0032] Through the above implementation methods, second-order envelope analysis is employed to obtain the envelope information of the partial discharge signal through the Hilbert transform, extracting the amplitude variation characteristics of the oscillating decay signal. This is particularly effective in identifying signal attenuation trends even when the signal amplitude is small. Then, peak detection is performed on the extracted envelope signal, and the type and intensity of the partial discharge signal are identified using characteristic parameters such as the amplitude, duration, and pulse interval of the time-domain pulse. Combined with a multi-threshold determination method, this ensures effective differentiation between the partial discharge signal and background noise.

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

[0034] In some optional embodiments of this application, acquiring the partial discharge signal includes: determining a sampling frequency based on the frequency range of the partial discharge signal; the partial discharge signal is typically transmitted in the form of high-frequency pulses, with a frequency range of 300MHz to 3GHz, and exhibits short-time oscillating characteristics in the time domain. The partial discharge signal is acquired using a data acquisition card based on the sampling frequency; the partial discharge signal acquired by the high-speed data acquisition card is converted using 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, ensuring a sufficiently high acquisition frequency to capture the details of the high-frequency partial discharge signal, which is generally represented as:

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

[0036] Where 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 embodiments of this application, the preprocessing includes bandpass filtering and normalization; the bandpass filtering is implemented by constructing the impulse response of the filter; specifically, bandpass filtering can be implemented by constructing the impulse response of the filter. Assuming 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] Where h(t) is the time-domain impulse response of the bandpass filter, and * denotes the convolution operation. The frequency response of the filter can be designed to meet bandpass characteristics, filtering out frequency components below 300MHz and above 3GHz. This embodiment uses a bandpass filter to remove noise and interference in the non-target frequency band of the UHF partial discharge signal, retaining the core frequency components of the UHF partial discharge signal and improving the accuracy of subsequent partial discharge signal extraction.

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

[0041]

[0042] Where max(|x(t)|) is the maximum absolute value amplitude of the signal x(t). The normalized signal xb(t) ranges from -1 to 1. The normalization process in this embodiment can improve the standardization of the signal x(t).

[0043] In some optional embodiments of this application, extracting the first-order envelope of the preprocessed signal includes: obtaining an analytic signal from the preprocessed signal through a Hilbert transform; for the partial discharge signal x(t), obtaining an analytic signal Z(t) through a Hilbert transform:

[0044]

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

[0046]

[0047] “PV” stands for Cauchy principal value integral, used to handle singularities in the integral.

[0048] Then, the magnitude of the analytic signal is extracted to obtain the envelope of the analytic signal, which is used as the first-order envelope of the preprocessed signal. The envelope A(t) of the analytic signal is the magnitude of the analytic signal, representing the instantaneous amplitude of the partial discharge signal, i.e., the first-order envelope of the signal, and is calculated using the following formula:

[0049]

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

[0051]

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

[0053]

[0054] Since partial discharge signals have attenuation and oscillation characteristics, 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 this application, processing the pulses 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 based on the maxima of the second-order envelope of the original data sequence and an interpolation algorithm; searching for pulses in the second-order envelope sequence whose amplitude is higher than the white noise level of the partial discharge signal, and determining the start and end points 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 with an interval time less than a preset time threshold to obtain an updated single-pulse start-end index matrix; and using the updated single-pulse start-end index matrix as the processed partial discharge signal. Specifically, let the original data sequence be A. N×1 A i Where N is the signal amplitude, and N is the original data length, which is determined by the pulse interval.

[0056] Δt=t i+1 -t i (9)

[0057] First, the original data is mean-removed and its absolute value is taken. Then, the maximum value is searched twice to obtain the sequence P. peak Then for sequence P peak Linear interpolation yields 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 ) indicates that in the interval [t i , t i+1The peak value detected within the signal is used to determine the pulse amplitude by measuring the peak value and the pulse duration by measuring the full width at half maximum (FWHM). A sequence of maxima P′ with second-order envelope amplitudes higher than the white noise level of the original signal is searched. m×1 , m is the number of maxima in the second-order envelope that are above the white noise level, denoted by P′ i Starting from (i∈[1,2,…,m]), search for the zeros of the second-order envelope to the left and right respectively, and record their indices as the single-pulse starting point P. si With the termination point P ei The single pulse start and end index matrix is ​​obtained: P Index =[P s1 P e1 ;P s2 P e2 ;…;P sm P em Because a single pulse may have multiple second-order peak points, edge search may result in duplicate start and end points for single pulses, requiring the removal of duplicate rows. If a single pulse has a discontinuous second-order envelope, causing the pulse to appear in matrix P... Index It is presented in two lines, and P ei With P si+1 The difference is small, therefore the extracted pulse interval distance d pluse The magnitudes are compared when the interval between the two pulses is d. pluse A pulse duration >0.125μs (10 data points, manually adjustable) is considered two pulses; otherwise, it is considered the same pulse. Then, the single-pulse index matrix P is updated. Index =[P s1 P e1 ;P Max1 ;P s2 P e2 P Max2 ;…;P sm P em P Maxn ].

[0060] Optionally, in the preceding embodiment, determining the start and end points 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 partial discharge signal; starting from the maximum amplitude of each pulse in the maximum value sequence, searching for zero points of the second-order envelope to the left and right respectively, and indexing the searched left and right second-order envelope zero points as the start and end points of the single pulse. This embodiment provides a method for determining the start and end points of a single pulse based on the second-order envelope, which has the advantage of more accurate pulse duration extraction.

[0061] Through the above implementation methods, the method in this embodiment, combined with the multi-threshold determination method, ensures that partial discharge signals and background noise can be effectively distinguished, thereby improving the accuracy of partial discharge signals in the extraction process.

[0062] Figure 2 The diagram schematically illustrates the implementation process of the method for monitoring the ultra-high frequency partial discharge oscillation characteristics of a hydro-generator according to an embodiment of this application. Figure 2 As shown, the method includes: acquiring the original pulse signal, preprocessing the acquired signal including bandpass filtering and normalization, 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, this application also provides a device for monitoring the ultra-high frequency partial discharge oscillation characteristics of a hydro-generator. Figure 3 A schematic diagram of the structure of a monitoring device for ultra-high frequency partial discharge oscillation characteristics of a hydro-generator according to an embodiment of this application is shown. Figure 3 As shown, the device 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 the first-order envelope and the second-order envelope of the preprocessed signal; and a signal processing module for processing the pulses in the partial discharge signal based on the first-order envelope and the second-order envelope to obtain a processed partial discharge signal.

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

[0065] In some alternative embodiments of this application, the preprocessing includes bandpass filtering and normalization; the bandpass filtering is achieved by constructing the impulse response of the filter; and the normalization is achieved by a ratio to the maximum absolute value amplitude of the signal.

[0066] In some optional embodiments of this application, extracting the first-order envelope of the preprocessed signal includes: obtaining an analytic signal from the preprocessed signal through a Hilbert transform; and extracting the modulus of the analytic signal to obtain the envelope of the analytic signal as the first-order envelope of the preprocessed signal.

[0067] In some optional embodiments of this application, obtaining a second-order envelope based on the first-order envelope includes: obtaining a second-order analytic signal by performing a Hilbert transform on the first-order envelope of the preprocessed signal; and extracting the amplitude of the second-order analytic signal as the second-order envelope of the preprocessed signal.

[0068] In some optional embodiments of this application, processing the pulses 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 based on the maxima of the second-order envelope of the original data sequence and an interpolation algorithm; searching for pulses in the second-order envelope sequence whose amplitude is higher than the white noise level of the partial discharge signal, and determining the start and end points 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 with an interval time less than a preset time threshold to obtain an updated single-pulse start-end index matrix; and using the updated single-pulse start-end index matrix as the processed partial discharge signal.

[0069] In some optional embodiments of this application, determining the start and end points 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 partial discharge signal; starting from the maximum amplitude of each pulse in the maximum value sequence, searching for second-order envelope zeros to the left and right respectively, and indexing the searched left and right second-order envelope zeros as the start and end points of a single pulse.

[0070] The specific limitations of each functional module in the aforementioned monitoring device for ultra-high frequency partial discharge oscillation characteristics of hydro-generators can be found in the limitations of the monitoring method for ultra-high frequency partial discharge oscillation characteristics of hydro-generators described above, and will not be repeated here. Each module in the above system can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of the electronic device in hardware form or independently of it, or stored in the memory of the electronic device in software form, so that the processor can call and execute the corresponding operations of each module. This also allows for better capture of subtle changes and attenuation behavior in the partial discharge signal, improves the accuracy of partial discharge signal processing, meets the requirements for rapid and real-time monitoring of partial discharge, and has the advantage of anti-interference in complex electromagnetic environments.

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

[0072] Those skilled in the art will understand that Figure 4 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 electronic device to which 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 different component arrangements.

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

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

[0075] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0076] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0077] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0078] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function 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] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0081] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, 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 technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0082] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0083] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method for monitoring the oscillation characteristics of ultra-high frequency partial discharge of a hydroelectric generator, characterized in that, The method includes: Acquire partial discharge signals; The partial discharge signal is preprocessed to obtain a preprocessed signal; the preprocessing includes bandpass filtering and normalization; the bandpass filtering is achieved by constructing the impulse response of the filter; the normalization is achieved by the ratio of the signal's amplitude to the maximum absolute value of the signal. Extract the first-order envelope of the preprocessed signal, and obtain the second-order envelope based on the first-order envelope; obtaining the second-order envelope based on the first-order envelope includes: applying Hilbert transform to the first-order envelope of the preprocessed signal again to obtain a second-order analytic signal; and extracting the amplitude of the second-order analytic signal as the second-order envelope of the preprocessed signal. The pulses in the partial discharge signal are processed based on the second-order envelope to obtain the processed partial discharge signal.

2. The method of claim 1, wherein, Acquiring partial discharge signals includes: The sampling frequency is determined based on the frequency range of the partial discharge signal; The partial discharge signal is acquired by a data acquisition card based on the sampling frequency. The partial discharge signal acquired by the high-speed data acquisition card is converted using an analog-to-digital converter.

3. The method according to claim 1, characterized in that, Extracting the first-order envelope of the preprocessed signal includes: The preprocessed signal is then subjected to Hilbert transform to obtain an analytical signal. The magnitude of the analyzed signal is extracted to obtain the envelope of the analyzed signal, which is then used as the first-order envelope of the preprocessed signal.

4. The method according to claim 1, characterized in that, The pulses in the partial discharge signal are processed based on the second-order envelope to obtain a processed partial discharge signal, including: The pulses in the partial discharge signal are extracted to obtain the original data sequence; The second-order envelope sequence is obtained based on the maxima of the second-order envelope of the original data sequence and the interpolation algorithm; Search for pulses in the second-order envelope sequence whose amplitude is higher than the white noise level of the partial discharge signal, and determine the start and end points of each pulse to obtain a single pulse start and end index matrix. The interval time of adjacent pulses in the single pulse start-end index matrix is ​​judged, and adjacent pulses with an interval time less than a preset time threshold are merged to obtain an updated single pulse start-end index matrix. The updated single-pulse start-end index matrix is ​​used as the processed partial discharge signal.

5. The method according to claim 4, characterized in that, Determine the start and end points of each pulse, including: A maximum value sequence is obtained based on the pulses in the second-order envelope sequence whose amplitudes are higher than the white noise level of the partial discharge signal. Starting from the maximum amplitude of each pulse in the maximum value sequence, search for the zeros of the second-order envelope to the left and right respectively, and index the zeros of the second-order envelope on the left and right as the starting and ending points of the single pulse.

6. A device for monitoring the ultra-high frequency partial discharge oscillation characteristics of a hydro-generator, characterized in that, The device includes: The signal acquisition module is used to acquire partial discharge signals; A preprocessing module is used to preprocess the partial discharge signal to obtain a preprocessed signal; the preprocessing includes bandpass filtering and normalization; the bandpass filtering is achieved by constructing the impulse response of the filter; the normalization is achieved by the ratio of the signal's amplitude to the maximum absolute value of the signal. An envelope extraction module is used to extract the first-order envelope of the preprocessed signal, and to obtain a second-order envelope based on the first-order envelope. Obtaining the second-order envelope based on the first-order envelope includes: performing a Hilbert transform on the first-order envelope of the preprocessed signal to obtain a second-order analytic signal; extracting the amplitude of the second-order analytic signal as the second-order envelope of the preprocessed signal; and... The signal processing module is used to process the pulses in the partial discharge signal based on the second-order envelope to obtain the processed partial discharge signal.

7. An electronic device, characterized in that, include: At least one processor; A memory connected to the at least one processor; 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 the ultra-high frequency partial discharge oscillation characteristics of a hydro-generator as described in any one of claims 1 to 5 by executing the instructions stored in the memory.

8. A computer-readable storage medium having a computer program / instructions stored thereon, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method for monitoring the ultra-high frequency partial discharge oscillation characteristics of a hydro-generator as described in any one of claims 1 to 5.

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