CN119533750B - A method and related equipment for detecting the peak-to-peak value of pressure pulsation of a hydropower station unit under transient conditions - Google Patents
A method and related equipment for detecting the peak-to-peak value of pressure pulsation of a hydropower station unit under transient conditionsInfo
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- CN119533750B CN119533750B CN202411422757.XA CN202411422757A CN119533750B CN 119533750 B CN119533750 B CN 119533750B CN 202411422757 A CN202411422757 A CN 202411422757A CN 119533750 B CN119533750 B CN 119533750B
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- G—PHYSICS
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- G01L—MEASURING FORCE, STRESS, TORQUE, WORK, MECHANICAL POWER, MECHANICAL EFFICIENCY, OR FLUID PRESSURE
- G01L9/00—Measuring steady of quasi-steady pressure of fluid or fluent solid material by electric or magnetic pressure-sensitive elements; Transmitting or indicating the displacement of mechanical pressure-sensitive elements, used to measure the steady or quasi-steady pressure of a fluid or fluent solid material, by electric or magnetic means
- G01L9/08—Measuring steady of quasi-steady pressure of fluid or fluent solid material by electric or magnetic pressure-sensitive elements; Transmitting or indicating the displacement of mechanical pressure-sensitive elements, used to measure the steady or quasi-steady pressure of a fluid or fluent solid material, by electric or magnetic means by making use of piezoelectric devices, i.e. electric circuits therefor
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01L—MEASURING FORCE, STRESS, TORQUE, WORK, MECHANICAL POWER, MECHANICAL EFFICIENCY, OR FLUID PRESSURE
- G01L9/00—Measuring steady of quasi-steady pressure of fluid or fluent solid material by electric or magnetic pressure-sensitive elements; Transmitting or indicating the displacement of mechanical pressure-sensitive elements, used to measure the steady or quasi-steady pressure of a fluid or fluent solid material, by electric or magnetic means
- G01L9/02—Measuring steady of quasi-steady pressure of fluid or fluent solid material by electric or magnetic pressure-sensitive elements; Transmitting or indicating the displacement of mechanical pressure-sensitive elements, used to measure the steady or quasi-steady pressure of a fluid or fluent solid material, by electric or magnetic means by making use of variations in ohmic resistance, e.g. of potentiometers, electric circuits therefor, e.g. bridges, amplifiers or signal conditioning
- G01L9/06—Measuring steady of quasi-steady pressure of fluid or fluent solid material by electric or magnetic pressure-sensitive elements; Transmitting or indicating the displacement of mechanical pressure-sensitive elements, used to measure the steady or quasi-steady pressure of a fluid or fluent solid material, by electric or magnetic means by making use of variations in ohmic resistance, e.g. of potentiometers, electric circuits therefor, e.g. bridges, amplifiers or signal conditioning of piezo-resistive devices
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
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- G06F17/10—Complex mathematical operations
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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
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Abstract
The disclosure provides a method for detecting pressure pulsation peak value of a hydropower station unit under transient working conditions and related equipment. The method comprises the steps of obtaining a pressure pulsation signal of a preset position in the hydropower station unit, decomposing the pressure pulsation signal to obtain a corresponding trend item signal and a pulsation item signal, carrying out signal mapping processing on the trend item signal and the pulsation item signal to obtain peak-to-peak values of the pulsation item under different cycle lengths, and calculating the average value of the peak-to-peak values of the pulsation item under different cycle lengths to obtain the pressure pulsation peak-to-peak value of the preset position.
Description
Technical Field
The disclosure relates to the field of pressure analysis, in particular to a method for detecting pressure pulsation peak value of a hydropower station unit under transient working conditions and related equipment.
Background
Under the transient state operating mode of the hydropower station unit, the volute pressure is increased and the draft tube pressure is reduced unstably, so that the safety problem is easy to occur. However, the pressure peak value detection accuracy under the existing transient working condition is low, the analysis time is long, and the actual requirements cannot be met.
Disclosure of Invention
The disclosure provides a method for detecting pressure pulsation peak value of a hydropower station unit under transient working conditions and related equipment, so as to solve the technical problems of low accuracy, long analysis time and the like of pressure peak value detection of the hydropower station unit under transient working conditions to a certain extent.
In a first aspect of the present disclosure, a method for detecting a peak-to-peak value of pressure pulsation of a hydropower station unit under a transient condition is provided, including:
acquiring a pressure pulsation signal of a preset position in the hydropower station unit;
Decomposing the pressure pulsation signal to obtain a corresponding trend term signal and pulsation term signal;
performing signal mapping processing on the trend item signal and the pulsation item signal to obtain peak-to-peak values of the pulsation items under different cycle lengths;
And calculating the average value of the peak value and the peak value of the pulsation item under different cycle lengths to obtain the pressure pulsation peak value and the peak value of the preset position.
In some embodiments, decomposing the pressure pulsation signal to obtain a corresponding trend term signal and pulsation term signal, including:
Decomposing the pressure pulsation signal into a plurality of eigenmode function components;
and carrying out convolution and local feature extraction on each eigenmode function component to obtain the trend term signal and the pulsation term signal.
In some embodiments, convolving and locally extracting features of each of the eigenmode function components to obtain the trend term signal and the pulsation term signal, including:
Extracting a low-frequency part in the eigenmode function component to obtain the trend term signal;
And extracting a high-frequency part in the eigenmode function component to obtain the pulsation item signal.
In some embodiments, performing signal mapping processing on the trend term signal and the pulsation term signal to obtain peak-to-peak values of the pulsation term under different cycle lengths, including:
determining a first time node corresponding to a maximum characteristic value and a second time node corresponding to a minimum characteristic value in the trend item;
determining at least one period length based on the first time node and/or the second time node;
And obtaining the peak-to-peak value of the pulsation item based on the difference value of the maximum value and the minimum value of the pulsation item in the period length for each period length.
In some embodiments, determining a first time node corresponding to a maximum eigenvalue and a second time node corresponding to a minimum eigenvalue in the trend item includes:
Obtaining a first time node based on the time node in the trend item time chain table pointed by the first pointer of the maximum characteristic value;
And obtaining the second time node based on the time node in the trend item time chain table pointed by the second pointer of the minimum characteristic value.
In some embodiments, calculating the average of the peak-to-peak values of the pulsation term at different cycle lengths includes:
Wherein A is the average value, n is the number of different period lengths, and k is the number of the period lengths.
In some embodiments, calculating the average of the peak-to-peak values of the pulsation term at different cycle lengths further comprises:
Calculating the confidence coefficient of the peak-to-peak value of the pulsation item corresponding to each period length;
and calculating the average value based on the peak-to-peak value of the pulsation item corresponding to the confidence coefficient greater than or equal to the confidence coefficient threshold.
In a second aspect of the present disclosure, a device for detecting a peak-to-peak value of pressure pulsation of a hydropower station unit under a transient condition is provided, including:
the acquisition module is used for acquiring a pressure pulsation signal of a preset position in the hydropower station unit;
the decomposition module is used for decomposing the pressure pulsation signal to obtain a corresponding trend term signal and a pulsation term signal;
The mapping module is used for carrying out signal mapping processing on the trend item signal and the pulsation item signal to obtain peak-to-peak values of the pulsation item under different cycle lengths;
and the average module is used for calculating the average value of the peak-to-peak value of the pulsation item under different cycle lengths to obtain the pressure pulsation peak-to-peak value of the preset position.
In some embodiments, decomposing the pressure pulsation signal to obtain a corresponding trend term signal and pulsation term signal, including:
Decomposing the pressure pulsation signal into a plurality of eigenmode function components;
and carrying out convolution and local feature extraction on each eigenmode function component to obtain the trend term signal and the pulsation term signal.
In some embodiments, convolving and locally extracting features of each of the eigenmode function components to obtain the trend term signal and the pulsation term signal, including:
Extracting a low-frequency part in the eigenmode function component to obtain the trend term signal;
And extracting a high-frequency part in the eigenmode function component to obtain the pulsation item signal.
In some embodiments, performing signal mapping processing on the trend term signal and the pulsation term signal to obtain peak-to-peak values of the pulsation term under different cycle lengths, including:
determining a first time node corresponding to a maximum characteristic value and a second time node corresponding to a minimum characteristic value in the trend item;
determining at least one period length based on the first time node and/or the second time node;
And obtaining the peak-to-peak value of the pulsation item based on the difference value of the maximum value and the minimum value of the pulsation item in the period length for each period length.
In some embodiments, determining a first time node corresponding to a maximum eigenvalue and a second time node corresponding to a minimum eigenvalue in the trend item includes:
Obtaining a first time node based on the time node in the trend item time chain table pointed by the first pointer of the maximum characteristic value;
And obtaining the second time node based on the time node in the trend item time chain table pointed by the second pointer of the minimum characteristic value.
In some embodiments, calculating the average of the peak-to-peak values of the pulsation term at different cycle lengths includes:
Wherein A is the average value, n is the number of different period lengths, and k is the number of the period lengths.
In some embodiments, calculating the average of the peak-to-peak values of the pulsation term at different cycle lengths further comprises:
Calculating the confidence coefficient of the peak-to-peak value of the pulsation item corresponding to each period length;
and calculating the average value based on the peak-to-peak value of the pulsation item corresponding to the confidence coefficient greater than or equal to the confidence coefficient threshold.
In a third aspect of the present disclosure, there is provided an electronic device comprising one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and executed by the one or more processors, the programs comprising instructions for performing the method according to the first aspect.
In a fourth aspect of the present disclosure, there is provided a non-transitory computer readable storage medium containing a computer program which, when executed by one or more processors, causes the processors to perform the method of the first aspect.
In a fifth aspect of the present disclosure, there is provided a computer program product comprising computer program instructions which, when executed on a computer, cause the computer to perform the method of the first aspect.
From the above, the method and the related equipment for detecting the peak value of the pressure pulsation of the hydropower station unit under the transient working condition provided by the disclosure can be used for decomposing the pressure signal of the target position of the hydropower station unit by adopting a variation modal decomposition technology to obtain a trend item and a pulsation item, and the peak value of the pulsation item under different period lengths can be obtained by signal mapping calculation, so that the peak value of the pressure pulsation is obtained. The accuracy of pressure pulsation peak value under transient working condition is improved, and reasonable and accurate technical support is provided for relevant pressure data analysis.
Drawings
In order to more clearly illustrate the technical solutions of the present disclosure or related art, the drawings required for the embodiments or related art description will be briefly described below, and it is apparent that the drawings in the following description are only embodiments of the present disclosure, and other drawings may be obtained according to these drawings without inventive effort to those of ordinary skill in the art.
Fig. 1 is a schematic diagram of a detection architecture of a peak-to-peak value of a pressure pulsation of a hydropower station unit under transient working conditions in an embodiment of the disclosure.
Fig. 2 is a schematic hardware architecture diagram of an exemplary electronic device according to an embodiment of the disclosure.
Fig. 3 is a flow chart of a method for detecting a peak-to-peak value of a pressure pulsation of a hydropower station unit under a transient working condition according to an embodiment of the disclosure.
Fig. 4 is a schematic diagram of a method for detecting a peak-to-peak value of a pressure pulsation of a hydropower station unit under a transient condition according to an embodiment of the disclosure.
Fig. 5 is a schematic diagram of a device for detecting peak-to-peak values of pressure pulsation of a hydropower station unit under transient working conditions in an embodiment of the disclosure.
Detailed Description
For the purposes of promoting an understanding of the principles and advantages of the disclosure, reference will now be made to the embodiments illustrated in the drawings and specific language will be used to describe the same.
It should be noted that unless otherwise defined, technical or scientific terms used in the embodiments of the present disclosure should be given the ordinary meaning as understood by one of ordinary skill in the art to which the present disclosure pertains. The terms "first," "second," and the like, as used in embodiments of the present disclosure, do not denote any order, quantity, or importance, but rather are used to distinguish one element from another. The word "comprising" or "comprises", and the like, means that elements or items preceding the word are included in the element or item listed after the word and equivalents thereof, but does not exclude other elements or items. The terms "connected" or "connected," and the like, are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "upper", "lower", "left", "right", etc. are used merely to indicate relative positional relationships, which may also be changed when the absolute position of the object to be described is changed.
It will be appreciated that prior to using the technical solutions disclosed in the embodiments of the present disclosure, the user should be informed and authorized of the type, usage range, usage scenario, etc. of the personal information related to the present disclosure in an appropriate manner according to the relevant legal regulations.
For example, in response to receiving an active request from a user, a prompt is sent to the user to explicitly prompt the user that the operation it is requesting to perform will require personal information to be obtained and used with the user. Thus, the user can autonomously select whether to provide personal information to software or hardware such as an electronic device, an application program, a server or a storage medium for executing the operation of the technical scheme of the present disclosure according to the prompt information.
It will be appreciated that the above-described notification and user authorization process is merely illustrative and not limiting of the implementations of the present disclosure, and that other ways of satisfying relevant legal regulations may be applied to the implementations of the present disclosure.
Fig. 1 shows a schematic diagram of a detection architecture of a peak-to-peak value of a pressure pulsation of a hydropower station unit under transient operating conditions according to an embodiment of the disclosure. Referring to fig. 1, a detection architecture 100 for peak-to-peak pressure pulsation of a hydroelectric generating set under transient conditions may include a server 110, a terminal 120, and a network 130 providing a communication link. The server 110 and the terminal 120 may be connected through a wired or wireless network 130. The server 110 may be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, security services, CDNs, and the like.
The terminal 120 may be a hardware or software implementation. For example, when the terminal 120 is a hardware implementation, it may be a variety of electronic devices having a display screen and supporting page display, including but not limited to smartphones, tablets, e-book readers, laptop and desktop computers, and the like. When the terminal 120 is implemented as software, it may be installed in the above-listed electronic device, and it may be implemented as a plurality of software or software modules (for example, software or software modules for providing distributed services), or may be implemented as a single software or software module, which is not specifically limited herein.
It should be noted that, the method for detecting the peak value of the pressure pulsation peak of the hydropower station unit under the transient working condition provided by the embodiment of the application may be executed by the terminal 120 or may be executed by the server 110. It should be understood that the number of terminals, networks, and servers in fig. 1 are illustrative only and are not intended to be limiting. There may be any number of terminals, networks, and servers, as desired for implementation.
Fig. 2 shows a schematic hardware structure of an exemplary electronic device 200 provided by an embodiment of the disclosure. As shown in FIG. 2, the electronic device 200 may include a processor 202, a memory 204, a network module 206, a peripheral interface 208, and a bus 210. Wherein the processor 202, the memory 204, the network module 206, and the peripheral interface 208 are communicatively coupled to each other within the electronic device 200 via a bus 210.
Processor 202 may be a central processing unit (Central Processing Unit, CPU), a detector of peak to peak pressure pulsation of a hydropower station unit under transient conditions, a neural Network Processor (NPU), a Microcontroller (MCU), a programmable logic device, a Digital Signal Processor (DSP), an Application-specific integrated Circuit (ASIC), or one or more integrated circuits. The processor 202 may be used to perform functions related to the techniques described in this disclosure. In some embodiments, processor 202 may also include multiple processors integrated as a single logic component. For example, as shown in fig. 2, the processor 202 may include a plurality of processors 202a, 202b, and 202c.
The memory 204 may be configured to store data (e.g., instructions, computer code, etc.). As shown in fig. 2, the data stored by the memory 204 may include program instructions (e.g., program instructions for implementing a method of detecting peak-to-peak pressure pulsation of a hydropower station unit under transient conditions in accordance with an embodiment of the disclosure) as well as data to be processed (e.g., the memory may store configuration files of other modules, etc.). The processor 202 may also access program instructions and data stored in the memory 204 and execute the program instructions to perform operations on the data to be processed. The memory 204 may include volatile storage or nonvolatile storage. In some embodiments, memory 204 may include Random Access Memory (RAM), read Only Memory (ROM), optical disks, magnetic disks, hard disks, solid State Disks (SSD), flash memory, memory sticks, and the like.
The network module 206 may be configured to provide communications with other external devices to the electronic device 200 via a network. The network may be any wired or wireless network capable of transmitting and receiving data. For example, the network may be a wired network, a local wireless network (e.g., bluetooth, wiFi, near Field Communication (NFC), etc.), a cellular network, the internet, or a combination of the foregoing. It will be appreciated that the type of network is not limited to the specific examples described above. In some embodiments, network module 306 may include any combination of any number of Network Interface Controllers (NICs), radio frequency modules, receivers, modems, routers, gateways, adapters, cellular network chips, etc.
Peripheral interface 208 may be configured to connect electronic device 200 with one or more peripheral devices to enable information input and output. For example, the peripheral devices may include input devices such as keyboards, mice, touchpads, touch screens, microphones, various types of sensors, and output devices such as displays, speakers, vibrators, and indicators.
Bus 210 may be configured to transfer information between the various components of electronic device 200 (e.g., processor 202, memory 204, network module 206, and peripheral interface 208), such as an internal bus (e.g., processor-memory bus), an external bus (USB port, PCI-E bus), etc.
It should be noted that, although the architecture of the electronic device 200 described above only shows the processor 202, the memory 204, the network module 206, the peripheral interface 208, and the bus 210, in a specific implementation, the architecture of the electronic device 200 may also include other components necessary to achieve normal execution. Furthermore, those skilled in the art will appreciate that the architecture of the electronic device 200 may also include only the components necessary to implement the embodiments of the present disclosure, and not all of the components shown in the figures.
Under transient working conditions of the unit, the volute pressure rise and the draft tube pressure drop are unstable, so that the safety problem exists, and the pressure pulsation peak value is the most direct expression of whether the pressure of the measuring point is stable or not. In steady-state working condition, when the analysis duration satisfies a certain condition, the size of the peak to peak is approximate irrelevant to the duration, in transient working condition, the analysis duration is longer, the peak to peak value cannot accurately reflect the pressure change rule, and the analysis duration is shorter, and the peak to peak value is meaningless or unstable. Therefore, the peak-to-peak analysis of the pressure pulsation under the transient working condition needs to be processed, so that more accurate peak-to-peak value of the pressure pulsation is obtained. Therefore, how to reduce the detection error of the pressure pulsation peak value under the transient working condition, improve the detection efficiency and the like becomes a technical problem to be solved urgently.
In view of this, the embodiment of the disclosure provides a method for detecting peak-to-peak values of pressure pulsation of a hydropower station unit under transient working conditions and related equipment. Decomposing a pressure signal of a target position of a hydropower station unit by adopting a variation modal decomposition technology to obtain a trend term and a pulsation term, and obtaining peak-to-peak values of the pulsation term under different period lengths through signal mapping calculation to obtain pressure pulsation peak-to-peak values. The accuracy of pressure pulsation peak value under transient working condition is improved, and reasonable and accurate technical support is provided for relevant pressure data analysis.
Referring to fig. 3, fig. 3 shows a schematic flow chart of a method for detecting pressure pulsation peaks and peaks of a hydropower station unit under transient conditions according to an embodiment of the disclosure. The method for detecting the peak value of the pressure pulsation peak of the hydropower station unit under the transient working condition can be deployed at a server side or a client side. In fig. 3, the method 300 for detecting the peak-to-peak value of the pressure pulsation of the hydropower station unit under the transient condition may further include the following steps.
In step S310, a pressure pulsation signal of a preset position in the hydropower station unit is acquired.
The preset position can be a specific position preset according to design and monitoring requirements and provided with a sensor in the hydropower station unit. These locations are typically selected where critical information about the operating conditions of the unit can be reflected, such as volute inlet, draft tube outlet, vane perimeter, etc., as these areas are susceptible to hydrodynamic effects. The pressure pulsation signal can refer to pressure fluctuation generated in the pipeline or a specific structural part due to factors such as non-uniformity, vortex and cavitation of water flow when the water flow passes through the volute, the water guide mechanism, the rotating wheel and the like in the running process of the hydropower station. This rapid time-dependent pressure fluctuation is called a pressure pulsation signal, and contains rich information on the operating state of the unit. A sensor may be provided at a preset location, and means for sensing a physical quantity (e.g., pressure) and converting it into an electrical signal. Such as piezoresistive, piezoelectric, etc. pressure sensors to monitor pressure changes in real time and convert the pressure values into electrical signals that can be analyzed.
In step S320, the pressure pulsation signal is decomposed, so as to obtain a trend term signal and a pulsation term signal.
Wherein VMD techniques may be applied to the acquired pressure pulsation signals, respectively. The VMD decomposes the signal into a series of physically significant eigen-mode functions (IMFs) through an iterative optimization process, each IMF representing a specific frequency component of the signal, including a trend term (low frequency component) and a pulsation term (high frequency component). Specifically, the volute inlet pressure pulsation signal and the draft tube inlet pressure pulsation signal under transient conditions can be collected through the sensor. And decomposing the original pressure pulsation signal into a plurality of IMF components by using a variation modal decomposition technology on the volute inlet pressure pulsation signal and the draft tube inlet pressure pulsation signal under the transient working condition respectively, convoluting each IMF component, extracting local characteristics, and obtaining a trend term signal and a pulsation term signal of the pressure pulsation signal.
In some embodiments, decomposing the pressure pulsation signal to obtain a corresponding trend term signal and pulsation term signal, including:
Decomposing the pressure pulsation signal into a plurality of eigenmode function components;
and carrying out convolution and local feature extraction on each eigenmode function component to obtain the trend term signal and the pulsation term signal.
In some embodiments, convolving and locally extracting features of each of the eigenmode function components to obtain the trend term signal and the pulsation term signal, including:
Extracting a low-frequency part in the eigenmode function component to obtain the trend term signal;
And extracting a high-frequency part in the eigenmode function component to obtain the pulsation item signal.
And carrying out convolution operation on each IMF component so as to extract local characteristics of the signal, enhance the recognition capability of signal details and facilitate subsequent characteristic analysis. Based on the convolution result, a trend term signal and a pulsation term signal are separated. The trend term reflects the long-term trend of the signal, while the pulsation term reflects the transient fluctuation characteristic of the signal.
In step S330, signal mapping processing is performed on the trend term signal and the pulsation term signal, so as to obtain peak-to-peak values of the pulsation term under different cycle lengths.
And finding out the time nodes corresponding to the maximum and minimum characteristic values in the trend item according to the signal mapping process calculation formula. This helps to understand the overall trend change in the signal. The pulse term signal is periodically analyzed, the peak-to-peak value (i.e. the difference between the maximum value and the minimum value of the signal) under different periods is calculated, and the importance of the different periods is comprehensively considered by adopting a weighted average method (0.2k+0.8 in the formula), wherein k is a period sequence number and n is the total period number. This step aims at extracting the typical fluctuation amplitude of the pulsation term.
In some embodiments, performing signal mapping processing on the trend term signal and the pulsation term signal to obtain peak-to-peak values of the pulsation term under different cycle lengths, including:
determining a first time node corresponding to a maximum characteristic value and a second time node corresponding to a minimum characteristic value in the trend item;
And obtaining the peak-to-peak value of the pulsation item based on the difference value of the maximum value and the minimum value of the pulsation item in the period length for each period length.
In some embodiments, determining a first time node corresponding to a maximum eigenvalue and a second time node corresponding to a minimum eigenvalue in the trend item includes:
Obtaining a first time node based on the time node in the trend item time chain table pointed by the first pointer of the maximum characteristic value;
determining at least one period length based on the first time node and/or the second time node;
And obtaining the second time node based on the time node in the trend item time chain table pointed by the second pointer of the minimum characteristic value.
Wherein, since the time nodes of the signal transient instants cannot be acquired by the pulsation term, the corresponding time nodes can be determined by the trend term and then mapped to the pulsation term to determine the peak-to-peak value of the pulsation term at the corresponding time nodes. If the maximum characteristic value of the trend term corresponds to 3s, 2.8 s-3.2 s can be taken, the trend term is mapped to the pulsation term in the time interval, and the pulsation term data is taken to calculate the peak-to-peak value. Specifically, the maximum/small trend term feature value corresponding time node extraction formula may include maximum trend term feature value corresponding time node=trend term maximum feature value pointer→trend term time linked list, and minimum trend term feature value corresponding time node=trend term minimum feature value pointer→trend term time linked list.
In step S340, an average value of peak-to-peak values of the pulsation term under different cycle lengths is calculated, so as to obtain the pressure pulsation peak-to-peak value of the preset position.
In some embodiments, calculating the average of the peak-to-peak values of the pulsation term at different cycle lengths includes:
Wherein A is the average value, n is the number of different period lengths, and k is the number of the period lengths.
Specifically, the trend term and the pulsation term of the inlet pressure pulsation signal of the volute can be calculated through a signal mapping process to obtain peak and peak values of the pulsation term of the inlet pressure pulsation signal of the volute under different periods, the confidence coefficient is 97% (the fraction is 1.5% and 98.5%), and the trend term and the pulsation term of the inlet pressure pulsation signal of the draft tube obtained through the modal variation module can be calculated through a signal mapping process to obtain peak and peak values of the pulsation term of the inlet pressure pulsation signal of the draft tube under different periods, the confidence coefficient is 97% (the fraction is 1.5% and 98.5%). And respectively taking the average value as the peak value and the peak value of the volute inlet pressure pulsation and the draft tube inlet pressure pulsation under the transient working condition.
In some embodiments, calculating the average of the peak-to-peak values of the pulsation term at different cycle lengths further comprises:
Calculating the confidence coefficient of the peak-to-peak value of the pulsation item corresponding to each period length;
and calculating the average value based on the peak-to-peak value of the pulsation item corresponding to the confidence coefficient greater than or equal to the confidence coefficient threshold.
In order to improve the robustness of analysis, a confidence level of 97% (i.e. the most extreme 1.5% and 98.5% of data points are excluded) can be used to calculate confidence intervals of peak-to-peak values of pulsation items under different periods, which is helpful for removing abnormal values and ensuring the reliability of results. And determining representative peak-to-peak values under the transient working condition according to the calculated peak-to-peak average value (considering the confidence interval) of the pulsation items for the pressure pulsation signals of the volute inlet and the draft tube inlet respectively. This provides an important quantitative indicator for evaluating the system operating state and predicting potential faults.
Referring to fig. 4, fig. 4 is a schematic diagram illustrating a method for detecting a peak-to-peak value of a pressure pulsation of a hydropower station unit under a transient condition according to an embodiment of the disclosure. In FIG. 4, the working condition can be set to be that a single unit normally operates under 306MW load, and 100% rated load is suddenly removed, so as to simulate the system response when the emergency stop or the load suddenly changes under the transient working condition test scene of the hydropower station. The environmental conditions may include an upper reservoir water level 580.47m and a lower reservoir water level 229.76m, from which the head difference may be analyzed. Pressure sensors can be arranged at the volute inlet and the draft tube inlet, and when load mutation occurs, pressure pulsation signals are continuously recorded to provide raw data for subsequent analysis.
And (3) obtaining an IMF component from pressure pulsation data detected by the sensor by utilizing a Variation Modal Decomposition (VMD), and convolving the IMF component to obtain a pressure pulsation trend term and a pulsation term. For example, through signal mapping calculation, the maximum characteristic value time node of the volute inlet pressure measurement point trend item is 24.79s, the minimum characteristic value time node of the tail water inlet pressure measurement point trend item is 22.51s, 1T, 1.2T and 1.3T are taken respectively, the periods of 3.0T are taken, and the pressure pulsation peak-to-peak value of 97% confidence in each period is calculated. Therefore, under different time lengths, the pressure pulsation peak value changes smoothly between the volute inlet pressure measuring point and the draft tube inlet pressure measuring point, the average value is taken as the final pressure pulsation peak value, and according to the on-site actual measurement condition, compared with the pressure pulsation peak value calculated under a single time length, the result is more accurate.
Therefore, the method of the embodiment of the disclosure decomposes the pressure signal of the target position of the hydropower station unit by adopting a variation modal decomposition technology to obtain a trend term and a pulsation term, and calculates the peak value of the pulsation term under different period lengths through signal mapping so as to obtain the peak value of the pressure pulsation. The accuracy of pressure pulsation peak value detection under transient working conditions is improved, and reasonable and accurate technical support is provided for relevant pressure data analysis.
It should be noted that the method of the embodiments of the present disclosure may be performed by a single device, such as a computer or a server. The method of the embodiment can also be applied to a distributed scene, and is completed by mutually matching a plurality of devices. In the case of such a distributed scenario, one of the devices may perform only one or more steps of the methods of embodiments of the present disclosure, the devices interacting with each other to accomplish the methods.
It should be noted that the foregoing describes some embodiments of the present disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments described above and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
Based on the same technical concept, corresponding to the method in any embodiment, the disclosure further provides a device for detecting a peak value of pressure pulsation of a hydropower station unit under a transient working condition, referring to fig. 5, where the device for detecting the peak value of pressure pulsation of the hydropower station unit under the transient working condition includes:
the acquisition module is used for acquiring a pressure pulsation signal of a preset position in the hydropower station unit;
the decomposition module is used for decomposing the pressure pulsation signal to obtain a corresponding trend term signal and a pulsation term signal;
The mapping module is used for carrying out signal mapping processing on the trend item signal and the pulsation item signal to obtain peak-to-peak values of the pulsation item under different cycle lengths;
and the average module is used for calculating the average value of the peak-to-peak value of the pulsation item under different cycle lengths to obtain the pressure pulsation peak-to-peak value of the preset position.
For convenience of description, the above devices are described as being functionally divided into various modules, respectively. Of course, the functions of the various modules may be implemented in the same one or more pieces of software and/or hardware when implementing the present disclosure.
In some embodiments, decomposing the pressure pulsation signal to obtain a corresponding trend term signal and pulsation term signal, including:
Decomposing the pressure pulsation signal into a plurality of eigenmode function components;
and carrying out convolution and local feature extraction on each eigenmode function component to obtain the trend term signal and the pulsation term signal.
In some embodiments, convolving and locally extracting features of each of the eigenmode function components to obtain the trend term signal and the pulsation term signal, including:
Extracting a low-frequency part in the eigenmode function component to obtain the trend term signal;
And extracting a high-frequency part in the eigenmode function component to obtain the pulsation item signal.
In some embodiments, performing signal mapping processing on the trend term signal and the pulsation term signal to obtain peak-to-peak values of the pulsation term under different cycle lengths, including:
determining a first time node corresponding to a maximum characteristic value and a second time node corresponding to a minimum characteristic value in the trend item;
determining at least one period length based on the first time node and/or the second time node;
And obtaining the peak-to-peak value of the pulsation item based on the difference value of the maximum value and the minimum value of the pulsation item in the period length for each period length.
In some embodiments, determining a first time node corresponding to a maximum eigenvalue and a second time node corresponding to a minimum eigenvalue in the trend item includes:
Obtaining a first time node based on the time node in the trend item time chain table pointed by the first pointer of the maximum characteristic value;
And obtaining the second time node based on the time node in the trend item time chain table pointed by the second pointer of the minimum characteristic value.
In some embodiments, calculating the average of the peak-to-peak values of the pulsation term at different cycle lengths includes:
Wherein A is the average value, n is the number of different period lengths, and k is the number of the period lengths.
In some embodiments, calculating the average of the peak-to-peak values of the pulsation term at different cycle lengths further comprises:
Calculating the confidence coefficient of the peak-to-peak value of the pulsation item corresponding to each period length;
and calculating the average value based on the peak-to-peak value of the pulsation item corresponding to the confidence coefficient greater than or equal to the confidence coefficient threshold.
The device of the above embodiment is used for implementing the method for detecting the peak value of the pressure pulsation peak of the hydropower station unit under the corresponding transient working condition in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiment, which are not described herein.
Based on the same technical concept, corresponding to the method of any embodiment, the disclosure further provides a non-transitory computer readable storage medium, wherein the non-transitory computer readable storage medium stores computer instructions, and the computer instructions are used for enabling the computer to execute the method for detecting the peak-to-peak value of the pressure pulsation of the hydropower station unit under the transient working condition according to any embodiment.
The computer readable media of the present embodiments, including both permanent and non-permanent, removable and non-removable media, may be used to implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer 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 disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device.
The computer instructions stored in the storage medium of the foregoing embodiments are used to make the computer execute the method for detecting the peak value of the pressure pulsation peak of the hydropower station unit under the transient working condition described in any one of the foregoing embodiments, and have the beneficial effects of the corresponding method embodiments, which are not described herein.
It will be appreciated by persons skilled in the art that the foregoing discussion of any embodiment is merely exemplary and is not intended to imply that the scope of the disclosure, including the claims, is limited to these examples, that the steps may be implemented in any order and that many other variations of the different aspects of the disclosed embodiments described above are present, which are not provided in detail for the sake of brevity, and that the features of the above embodiments or of the different embodiments may also be combined within the spirit of the disclosure.
Additionally, well-known power/ground connections to Integrated Circuit (IC) chips and other components may or may not be shown within the provided figures, in order to simplify the illustration and discussion, and so as not to obscure the embodiments of the present disclosure. Furthermore, the devices may be shown in block diagram form in order to avoid obscuring the embodiments of the present disclosure, and this also accounts for the fact that specifics with respect to implementation of such block diagram devices are highly dependent upon the platform on which the embodiments of the present disclosure are to be implemented (i.e., such specifics should be well within purview of one skilled in the art). Where specific details (e.g., circuits) are set forth in order to describe example embodiments of the disclosure, it should be apparent to one skilled in the art that embodiments of the disclosure can be practiced without, or with variation of, these specific details. Accordingly, the description is to be regarded as illustrative in nature and not as restrictive.
While the present disclosure has been described in conjunction with specific embodiments thereof, many alternatives, modifications, and variations of those embodiments will be apparent to those skilled in the art in light of the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may use the embodiments discussed.
The disclosed embodiments are intended to embrace all such alternatives, modifications and variances which fall within the broad scope of the appended claims. Accordingly, any omissions, modifications, equivalents, improvements, and the like, which are within the spirit and principles of the embodiments of the disclosure, are intended to be included within the scope of the disclosure.
Claims (10)
1. The method for detecting the peak value of the pressure pulsation peak of the hydropower station unit under the transient working condition is characterized by comprising the following steps of:
acquiring a pressure pulsation signal of a preset position in the hydropower station unit;
Decomposing the pressure pulsation signal to obtain a corresponding trend term signal and pulsation term signal, wherein the trend term signal and pulsation term signal are obtained by decomposing the pressure pulsation signal into a plurality of eigenmode function components by adopting a variation modal decomposition technology;
the method comprises the steps of carrying out signal mapping processing on a trend item signal and a pulsation item signal to obtain peak-to-peak values of the pulsation item under different period lengths, wherein the signal mapping processing comprises the steps of determining a first time node corresponding to a maximum characteristic value and a second time node corresponding to a minimum characteristic value in the trend item;
wherein calculating the average value of the peak-to-peak value of the pulsation term under different cycle lengths comprises:
wherein A is the average value, n is the number of different cycle lengths, and k is the serial number of the cycle length;
And calculating the average value of the peak value and the peak value of the pulsation item under different cycle lengths to obtain the pressure pulsation peak value and the peak value of the preset position.
2. The method of claim 1, wherein convolving and locally extracting features from each of the eigenmode function components to obtain the trend term signal and the pulsation term signal comprises:
Extracting a low-frequency part in the eigenmode function component to obtain the trend term signal;
And extracting a high-frequency part in the eigenmode function component to obtain the pulsation item signal.
3. The method of claim 1, wherein determining a first time node corresponding to a maximum eigenvalue and a second time node corresponding to a minimum eigenvalue in the trend term comprises:
Obtaining a first time node based on the time node in the trend item time chain table pointed by the first pointer of the maximum characteristic value;
And obtaining the second time node based on the time node in the trend item time chain table pointed by the second pointer of the minimum characteristic value.
4. The method of claim 1, wherein calculating an average of peak-to-peak values of the pulsation term at different cycle lengths further comprises:
Calculating the confidence coefficient of the peak-to-peak value of the pulsation item corresponding to each period length;
and calculating the average value based on the peak-to-peak value of the pulsation item corresponding to the confidence coefficient greater than or equal to the confidence coefficient threshold.
5. The utility model provides a detection device of pressure pulsation peak value of hydroelectric power generating set under transient state operating mode, its characterized in that includes:
the acquisition module is used for acquiring a pressure pulsation signal of a preset position in the hydropower station unit;
the decomposition module is used for decomposing the pressure pulsation signal to obtain a corresponding trend item signal and pulsation item signal, and comprises decomposing the pressure pulsation signal into a plurality of eigenmode function components by adopting a variation modal decomposition technology;
the mapping module is used for carrying out signal mapping processing on the trend item signal and the pulsation item signal to obtain peak-to-peak values of the pulsation item under different period lengths, and comprises a first time node corresponding to a maximum characteristic value and a second time node corresponding to a minimum characteristic value in the trend item, a period length determining module and a pulse item processing module, wherein the period length determining module is used for determining at least one period length based on the first time node and/or the second time node;
wherein calculating the average value of the peak-to-peak value of the pulsation term under different cycle lengths comprises:
wherein A is the average value, n is the number of different cycle lengths, and k is the serial number of the cycle length;
and the average module is used for calculating the average value of the peak-to-peak value of the pulsation item under different cycle lengths to obtain the pressure pulsation peak-to-peak value of the preset position.
6. The apparatus of claim 5, wherein convolving and locally extracting features from each of said eigenmode function components to obtain said trend term signal and said pulsation term signal comprises:
Extracting a low-frequency part in the eigenmode function component to obtain the trend term signal;
And extracting a high-frequency part in the eigenmode function component to obtain the pulsation item signal.
7. The apparatus of claim 5, wherein determining a first time node corresponding to a maximum eigenvalue and a second time node corresponding to a minimum eigenvalue in the trend term comprises:
Obtaining a first time node based on the time node in the trend item time chain table pointed by the first pointer of the maximum characteristic value;
And obtaining the second time node based on the time node in the trend item time chain table pointed by the second pointer of the minimum characteristic value.
8. The apparatus of claim 5, wherein calculating an average of peak-to-peak values of the pulsation term at different cycle lengths further comprises:
Calculating the confidence coefficient of the peak-to-peak value of the pulsation item corresponding to each period length;
and calculating the average value based on the peak-to-peak value of the pulsation item corresponding to the confidence coefficient greater than or equal to the confidence coefficient threshold.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the method of any one of claims 1 to 4 when the program is executed.
10. A non-transitory computer readable storage medium storing computer instructions for causing a computer to perform the method of any one of claims 1 to 4.
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