CN117520887A - Method, device, equipment and storage medium for determining fault risk component of water turbine - Google Patents
Method, device, equipment and storage medium for determining fault risk component of water turbine Download PDFInfo
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Abstract
The application discloses a method, a device, equipment and a storage medium for determining a fault risk component of a water turbine, and relates to the technical field of water turbines. The method comprises the following steps: under the running state of the water turbine, acquiring a first pressure pulsation signal of a target monitoring component in the water turbine, wherein the target monitoring component comprises at least one of a volute, a top cover and a draft tube, and the first pressure pulsation signal is a pressure pulsation signal in a first period; processing the first pressure pulsation signal of the target monitoring component to obtain frequency domain information of the target monitoring component; and under the condition that the frequency domain information of the target monitoring component meets a preset rule, determining the target monitoring component as a fault risk component, wherein the fault risk component is a component with fault risk. According to the embodiment of the application, the fault risk component of the water turbine can be accurately diagnosed.
Description
Technical Field
The application belongs to the technical field of water turbines, and particularly relates to a method, a device, equipment and a storage medium for determining a fault risk component of a water turbine.
Background
In recent years, along with the increase of the proportion of intermittent renewable energy sources such as wind energy, photovoltaic power generation and other energy sources in a power grid, water and electricity serve as a regulator in a power system, and the regulation of power grid parameters can be realized by regulating the working condition of a water turbine of core equipment of a water power station. However, the change of the operation working condition of the water turbine can cause unstable flow phenomenon of water power, reduce the hydraulic performance of the unit, possibly cause strong vibration of the unit, and threaten the safe operation of the unit and even a power station when serious. The lack of monitoring and analysis of the operating conditions of the turbine in the prior art results in an inaccurate diagnosis of the components of the turbine that may malfunction.
Disclosure of Invention
The embodiment of the application provides a method, a device, equipment and a storage medium for determining a fault risk component of a water turbine, which can accurately diagnose the fault risk component of the water turbine.
In a first aspect, an embodiment of the present application provides a method for determining a fault risk component of a water turbine, where the method includes:
under the running state of the water turbine, acquiring a first pressure pulsation signal of a target monitoring component in the water turbine, wherein the target monitoring component comprises at least one of a volute, a top cover and a draft tube, and the first pressure pulsation signal is a pressure pulsation signal in a first period;
Processing the first pressure pulsation signal of the target monitoring component to obtain frequency domain information of the target monitoring component;
and under the condition that the frequency domain information of the target monitoring component meets a preset rule, determining the target monitoring component as a fault risk component, wherein the fault risk component is a component with fault risk.
In a second aspect, an embodiment of the present application provides a device for determining a failure risk component of a water turbine, where the device includes:
the system comprises a first acquisition module, a second acquisition module and a control module, wherein the first acquisition module is used for acquiring a first pressure pulsation signal of a target monitoring component in the water turbine when the water turbine is in an operating state, the target monitoring component comprises at least one of a volute, a top cover and a draft tube, and the first pressure pulsation signal is a pressure pulsation signal in a first period;
the first processing module is used for processing the first pressure pulsation signal of the target monitoring component to obtain frequency domain information of the target monitoring component;
the first determining module is configured to determine the target monitoring component as a fault risk component when the frequency domain information of the target monitoring component meets a preset rule, where the fault risk component is a component with a fault risk.
In a third aspect, an embodiment of the present application provides an electronic device, including: a processor and a memory storing computer program instructions; the method for determining the fault risk component of the water turbine according to any one of the above is realized when the processor executes the computer program instructions.
In a fourth aspect, embodiments of the present application provide a computer readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement a method of determining a turbine failure risk component as defined in any one of the above.
According to the method, the device, the equipment and the storage medium for determining the fault risk component of the water turbine, a first pressure pulsation signal of a target monitoring component in the water turbine can be obtained when the water turbine is in an operating state, the target monitoring component comprises at least one of a volute, a top cover and a draft tube, and the first pressure pulsation signal is a pressure pulsation signal in a first period; processing the first pressure pulsation signal of the target monitoring component to obtain frequency domain information of the target monitoring component; and under the condition that the frequency domain information of the target monitoring component meets the preset rule, determining the target monitoring component as a fault risk component, wherein the fault risk component is a component with fault risk. In this way, in the embodiment of the application, the pressure pulsation signal of the target monitoring component is monitored under the running state of the water turbine, the frequency domain information of the target monitoring component is obtained through processing, and whether the frequency domain information meets the preset rule or not is analyzed, so that the fault risk component of the water turbine is accurately diagnosed.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments of the present application will be briefly described, and it is possible for a person skilled in the art to obtain other drawings according to these drawings without inventive effort.
FIG. 1 is a flow chart of a method for determining a failure risk component of a hydraulic turbine according to an embodiment of the present application;
FIG. 2 is a schematic diagram of a system for determining a risk component of a turbine failure provided in one embodiment of the present application;
FIG. 3 is a volute monitoring point layout provided by one embodiment of the present application;
FIG. 4 is a top cover monitoring point layout provided in one embodiment of the present application;
FIG. 5 is a draft tube monitoring point placement diagram provided by one embodiment of the present application;
FIG. 6 is a schematic structural view of a device for determining a risk component of a water turbine failure according to an embodiment of the present application;
fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
Features and exemplary embodiments of various aspects of the present application are described in detail below to make the objects, technical solutions and advantages of the present application more apparent, and to further describe the present application in conjunction with the accompanying drawings and the detailed embodiments. It should be understood that the specific embodiments described herein are intended to be illustrative of the application and are not intended to be limiting. It will be apparent to one skilled in the art that the present application may be practiced without some of these specific details. The following description of the embodiments is merely intended to provide a better understanding of the present application by showing examples of the present application.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.
In recent years, along with the increase of the proportion of intermittent renewable energy sources such as wind energy, photovoltaic power generation and other energy sources in a power grid, water and electricity serve as a regulator in a power system, and the regulation of power grid parameters can be realized by regulating the working condition of a water turbine of core equipment of a water power station. However, the change of the operation working condition of the water turbine can cause unstable flow phenomenon of water power, reduce the hydraulic performance of the unit, possibly cause strong vibration of the unit, and threaten the safe operation of the unit and even a power station when serious. Whether the water turbine runs safely and stably is mainly determined by pressure pulsation, resonance and other influencing factors, and the energy conversion capability of the water turbine, the generation of blade path vortex, the cavitation, the state of a vortex belt of a draft tube, the phase vibration condition of a unit and the like can be reflected through the analysis of pressure pulsation signals of different monitoring positions of the water turbine. However, the lack of monitoring and analysis of the operating state of the turbine in the prior art results in an inaccurate diagnosis of the components of the turbine that may malfunction.
In order to solve the problems in the prior art, the embodiment of the application provides a method, a device, equipment and a storage medium for determining a hydraulic turbine fault risk component. The method for determining the fault risk component of the water turbine provided by the embodiment of the application is first described below.
Fig. 1 shows a flow chart of a method for determining a failure risk component of a water turbine according to an embodiment of the present application. As shown in fig. 1, a method for determining a failure risk component of a water turbine may include the following steps S101 to S103:
s101, under the running state of the water turbine, acquiring a first pressure pulsation signal of a target monitoring component in the water turbine, wherein the target monitoring component comprises at least one of a volute, a top cover and a draft tube, and the first pressure pulsation signal is a pressure pulsation signal in a first period.
S102, processing the first pressure pulsation signal of the target monitoring component to obtain frequency domain information of the target monitoring component.
And S103, determining the target monitoring component as a fault risk component, wherein the fault risk component is a component with fault risk under the condition that the frequency domain information of the target monitoring component meets a preset rule.
According to the method for determining the fault risk component of the water turbine, a first pressure pulsation signal of a target monitoring component in the water turbine can be obtained when the water turbine is in an operating state, the target monitoring component comprises at least one of a volute, a top cover and a draft tube, and the first pressure pulsation signal is a pressure pulsation signal in a first period; processing the first pressure pulsation signal of the target monitoring component to obtain frequency domain information of the target monitoring component; and under the condition that the frequency domain information of the target monitoring component meets the preset rule, determining the target monitoring component as a fault risk component, wherein the fault risk component is a component with fault risk. In this way, in the embodiment of the application, the pressure pulsation signal of the target monitoring component is monitored under the running state of the water turbine, the frequency domain information of the target monitoring component is obtained through processing, and whether the frequency domain information meets the preset rule or not is analyzed, so that the fault risk component of the water turbine is accurately diagnosed.
In S101, the hydraulic turbine may be a power machine capable of converting energy of water flow into rotational mechanical energy, and belongs to a turbine among fluid machines. The hydraulic turbine may be a mixed-flow hydraulic turbine or an axial-flow hydraulic turbine, but is not limited to this, and may be any other type of hydraulic turbine, and is not particularly limited herein.
The target monitoring component may include at least one of a volute, a top cover, and a draft tube, and is not limited thereto, but may also include at least one of a volute, a stationary vane, a moving vane, a top cover, and a draft tube, and is not particularly limited thereto.
The first pressure pulsation signal is a pressure pulsation signal in a first period.
The above-mentioned acquisition of the first pressure pulsation signal of the target monitoring component in the water turbine may be, for example, setting up monitoring points of a plurality of pressure pulsation sensors on components such as the volute, the top cover, and the draft tube, so as to acquire the first pressure pulsation signal of each component. The number of monitoring points of the volute is 4, and the monitoring points are respectively positioned at the inlet of the volute, the two sides of the nose end and the 180-degree section of the volute; the number of monitoring points of the top cover is 8, wherein 4 monitoring points are located at the periphery of the upper crown cavity (above the vaneless areas of the rotating wheel and the guide vane) and are evenly distributed in the 360-degree circumferential direction, and the inner periphery of the upper crown cavity (above the water leakage cone) at the 4 monitoring points is evenly distributed in the 360-degree circumferential direction; the number of the monitoring points of the draft tube is 6, wherein 2 monitoring points are symmetrically distributed at 180 degrees at the inlet position of the draft tube straight taper tube, 2 monitoring points are symmetrically distributed at 180 degrees at the middle height position of the draft tube straight taper tube, and 2 monitoring points are positioned at the middle position of the draft tube horizontal straight tube section. The position of the pressure pulsation monitoring point can be the position of the concrete structure of the mixed flow pump, and the number of the monitoring points can be increased to 2-3 times of the number of the monitoring positions; the acquisition frequency of the pressure pulsation sensor is as follows:
Wherein f is the acquisition frequency of the pressure pulsation sensor, fz is the lowest sampling frequency (known preset value), n is the rotating speed of the rotating wheel, zr is the number of rotating wheel blades, and Zg is the number of guide vane blades.
In S102, the above-mentioned frequency domain information may describe information of a coordinate system used when the pressure pulsation signal is characteristic in terms of frequency, and may be, for example, frequency and amplitude.
The processing of the first pressure pulsation signal of the target monitoring component to obtain the frequency domain information of the target monitoring component may, for example, be that the fast fourier transform data processing system may perform the fast fourier transform on at least one obtained pressure pulsation signal to obtain a spectrogram of each pressure pulsation signal, and the main frequency and the corresponding amplitude of the first 10 th order pressure pulsation signal. Of course, in the present embodiment, the main frequency and the corresponding amplitude of the pressure pulsation signal of the first 10 steps are not limited, and the main frequency and the corresponding amplitude of the pressure pulsation signal of other steps may be used, and are not particularly limited.
In S103, the failure risk component may be a component having a failure risk.
The preset rule may include a preset first sub-rule, a preset second sub-rule, and a preset third sub-rule, because of the variability of rules of the different target detection components for identifying the fault risk components. The method comprises the steps that a first sub-rule is preset to indicate that the frequency of a draft tube is lower than a preset frequency threshold value, and the amplitude of the draft tube is larger than a preset first amplitude threshold value; the preset second sub-rule indicates that the amplitude of the volute is larger than a preset second amplitude threshold corresponding to the frequency of the volute; the deviation of the frequency of the preset third sub-rule indicating top cover from the fixed frequency of the top cover is smaller than a preset deviation value.
In some embodiments, when the target monitoring component is a draft tube, the frequency domain information may include frequency and amplitude;
the step S103 may specifically include:
determining the draft tube as a fault risk component under the condition that the frequency and the amplitude of the draft tube meet a preset first sub-rule, wherein the preset first sub-rule indicates that the frequency of the draft tube is lower than a preset frequency threshold value, and the amplitude of the draft tube is greater than a preset first amplitude threshold value;
the preset rule includes a preset first sub-rule.
The preset frequency threshold may be a value set by the user according to the actual running experience of the draft tube, and is not limited to a certain fixed value, but is not specifically limited herein. The same applies to the preset first amplitude threshold, and the description thereof is not repeated here.
In this embodiment, the condition that the frequency of the draft tube is lower than the preset frequency threshold value and the amplitude of the draft tube is greater than the preset first amplitude threshold value means that the draft tube has an unstable flow phenomenon, so that it can be determined that the draft tube has a fault risk, and therefore accurate diagnosis of fault risk components of the water turbine can be achieved.
As an implementation manner of the present application, in order to accurately diagnose the failure risk component of the water turbine, after S101, it may further include:
Processing a first pressure pulsation signal of the draft tube to obtain the energy characteristic of the draft tube;
and under the condition that the energy characteristic of the draft tube is a preset target energy characteristic, determining the draft tube as a fault risk component, wherein the target energy characteristic comprises any one of a She Daoguo energy characteristic in the rotating wheel, a cavitation energy characteristic in the rotating wheel, a low-head no-load energy characteristic, a guide vane opening swing energy characteristic and a draft tube vortex band energy characteristic.
The above-mentioned processing the first pressure pulsation signal of the draft tube to obtain the energy characteristic of the draft tube may be, for example, denoising and filtering the first pressure pulsation signal of the draft tube, then performing three-layer decomposition on the pressure pulsation signal by using a wavelet packet data transformation processing system to obtain the scale and frequency band of 8 sub-waveforms, calculating the obtained sub-waveforms by using sample entropy and permutation entropy to obtain the feature vector, obtaining the energy of each frequency band, and extracting the energy characteristic value of the first pressure pulsation signal. In this embodiment, the method is not limited to the wavelet packet data transformation processing system, and may be modified to a Hilbert-Huang transformation processing system, a Hilbert spectrum data processing system, and an energy spectrum analysis system.
The target energy characteristic may include any one of a She Daoguo energy characteristic in the runner, a cavitation energy characteristic in the runner, a low head no-load energy characteristic, a vane opening swing energy characteristic, and a draft tube vortex band energy characteristic. In this embodiment, the She Daoguo energy feature in the runner, the cavitation energy feature in the runner, the low-head no-load energy feature, the guide vane opening swing energy feature and the draft tube vortex band energy feature are preset energy features corresponding to various unstable states by a user when the water turbine is in an operating state.
In the embodiment, the energy characteristics are obtained by analyzing the pressure pulsation signals and compared with the preset target energy characteristics, and the occurrence of unstable states such as She Daoguo, cavitation and vortex strips of the draft tube can be accurately reflected, so that fault risk components of the water turbine are accurately diagnosed, and whether the water turbine is in a safe and stable running state is judged.
In some embodiments, where the target monitoring component is a volute, the frequency domain information may include frequency and amplitude;
the step S103 may specifically include:
determining the volute as a fault risk component under the condition that the frequency and the amplitude of the volute meet preset second sub-rules, wherein the preset second sub-rules indicate that the amplitude of the volute is larger than a preset second amplitude threshold corresponding to the frequency of the volute;
The preset rule includes a preset second sub-rule.
The preset second amplitude threshold may be a value set by the user according to the actual operation experience of the volute, and is not limited to a certain fixed value, but is not specifically limited herein.
In this embodiment, the condition that the amplitude of the volute is greater than the preset second amplitude threshold corresponding to the frequency of the volute means that the amplitude of the volute at the frequency of the monitoring point is overlapped, and at this time, the volute has a phase vibration phenomenon, so that the risk of faults of the volute can be determined, and therefore, accurate diagnosis of fault risk components of the water turbine can be achieved.
In some embodiments, where the target monitoring component is a cap, the frequency domain information may include frequency;
the step S103 may specifically include:
under the condition that the frequency of the top cover meets a preset third sub-rule, determining the top cover as a fault risk component, wherein the preset third sub-rule indicates that the deviation between the frequency of the top cover and the fixed frequency of the top cover is smaller than a preset deviation value;
the preset rule includes a preset third sub-rule.
The preset deviation value may be a value set by the user according to the practical operation experience of the top cover, and is not limited to a certain fixed value, but is not limited herein. The fixed frequency of the cap is a known value and can be measured by prior art techniques, such as, for example.
In this embodiment, the case where the deviation between the frequency of the top cover and the fixed frequency of the top cover is smaller than the preset deviation value means that the top cover has a resonance phenomenon, so that it can be determined that the top cover has a fault risk, and therefore accurate diagnosis of fault risk components of the water turbine can be achieved.
As another implementation manner of the present application, in order to accurately reflect the operation state of the target monitoring component, after S101, the method further includes:
and determining the operation state corresponding to the pressure pulsation interval where the first pressure pulsation signal of the target monitoring component is located as the operation state of the target monitoring component, wherein different operation states correspond to different pressure pulsation intervals.
The above-described operation states may include, for example, three operation states of A, B and C. Wherein the A state represents excellent, and the pressure pulsation interval where the first pressure pulsation signal indicating the target monitoring component is located is [0-3% ]; the operating state is not limited to A, B and C, but can be set according to the actual demands of users, and can be two or four or more operating states, and correspondingly, the pressure pulsation interval can also be set according to the actual demands of users, and is not limited to a fixed interval, but is not particularly limited.
In this embodiment, the operation state of the target monitoring component can be accurately reflected through the pressure pulsation interval where the first pressure pulsation signal of the target monitoring component is located, so that the operation state of the whole water turbine can be accurately reflected.
As still another implementation manner of the present application, in order to further identify whether the failure risk component has a failure, after S103 above, the method may further include:
acquiring a second pressure pulse signal of the fault risk component when the first pressure pulse signal of the fault risk component exceeds a preset pressure pulse threshold interval, wherein the second pressure pulse signal is a pressure pulse signal in a second period, and the second period is later than the first period;
in the event that the second pressure pulsation signal of the fault risk component exceeds the pressure pulsation threshold interval, the fault risk component is determined to be a fault component.
The pressure pulsation threshold value interval is a value interval set by a user according to actual needs, and is not limited to a certain fixed value interval, and is not particularly limited herein.
The second pressure pulsation signal is a pressure pulsation signal in a second period, which is later than the first period.
In this embodiment, under the condition that the first pressure pulsation signal of the fault risk component exceeds the preset pressure pulsation threshold value interval, the second pressure pulsation signal of the fault risk component is acquired again, and the pressure pulsation threshold value intervals are compared, so as to further identify whether the fault risk component has a fault, thereby ensuring stable operation of the water turbine.
In order to facilitate understanding of the method for determining the failure risk component of the water turbine in the embodiment of the present application, a practical application procedure of the method for determining the failure risk component of the water turbine is described as follows:
in order to monitor and diagnose the unstable flow phenomenon of the hydraulic power of the water turbine and the unstable running state of the unit, the application provides a system for determining the fault risk component of the water turbine. The principle of the application is that a plurality of pressure pulsation monitoring points are arranged on a volute, a top cover and a draft tube, and the running state of a water turbine unit and the unstable flow phenomenon inside the water turbine are determined by carrying out data analysis and judgment on collected pressure pulsation signals. The power station can adjust the operation condition of the water turbine according to the operation diagnosis state of the water turbine, and judge whether the water turbine has faults or not.
As shown in fig. 2, the application is a system for determining a fault risk component of a water turbine, wherein the system comprises a pressure pulsation monitoring module, a data processing module, an operation state analysis module and a fault monitoring module. The pressure pulsation monitoring module is used for monitoring pressure pulsation signals in the volute, the vaneless area, the top cover and the draft tube; the data processing module is used for extracting, filtering and denoising the time domain and frequency domain information of the pressure pulsation signals at different monitoring positions to obtain frequency, corresponding amplitude and energy characteristic values; the running state analysis module is used for carrying out statistics, induction and reasoning on the energy characteristic values acquired by the data processing module and forming a visual data evaluation interface; the fault monitoring module is used for diagnosing and analyzing the acquired information of the running state analysis module and giving out running state signals or fault signals corresponding to the mixed-flow water turbine.
The pressure pulsation monitoring module comprises a pressure pulsation sensor and a high-performance data acquisition system. As shown in fig. 3 to 5, the monitoring positions of the pressure pulsation sensor are respectively located at the volute, the top cover and the draft tube; the monitoring points of the volute are 4 and are respectively positioned at the inlet of the volute, the two sides of the nose end and the 180-degree section of the volute; the number of monitoring points of the top cover is 8, wherein 4 monitoring points are located at the periphery of the upper crown cavity (above the vaneless areas of the rotating wheel and the guide vane) and are evenly distributed in the 360-degree circumferential direction, and the inner periphery of the upper crown cavity (above the water leakage cone) at the 4 monitoring points is evenly distributed in the 360-degree circumferential direction; the number of the monitoring points of the draft tube is 6, wherein 2 monitoring points are symmetrically distributed at 180 degrees at the inlet position of the draft tube straight taper tube, 2 monitoring points are symmetrically distributed at 180 degrees at the middle height position of the draft tube straight taper tube, and 2 monitoring points are positioned at the middle position of the draft tube horizontal straight tube section; the pressure pulsation monitoring position of the pressure pulsation monitoring module can be arranged at other positions of the volute, the static guide vane, the dynamic guide vane, the top cover and the draft tube by the concrete structure of the mixed flow pump, and the number of monitoring points can be increased to 2-3 times of the number of the monitoring positions; the acquisition frequency of the pressure pulsation sensor of the pressure pulsation monitoring module is as follows:
Wherein f is the acquisition frequency of the pressure pulsation sensor, fz is the lowest sampling frequency (known preset value), n is the rotating speed of the rotating wheel, zr is the number of rotating wheel blades, and Zg is the number of guide vane blades.
The data processing module comprises a fast Fourier transform data processing system and a wavelet packet data transformation processing system; the fast Fourier transform data processing system can perform fast Fourier transform on the pressure signals acquired by the pressure pulsation monitoring module, acquire a spectrogram of each pressure pulsation signal, and acquire the main frequency and the corresponding amplitude of the first 10-order pressure pulsation; the wavelet packet data transformation processing system firstly carries out denoising and filtering on an original pressure signal, then carries out three-layer decomposition on the pressure pulsation signal through wavelet transformation to obtain the scale and the frequency band of 8 sub waveforms, calculates the obtained sub waveforms by adopting sample entropy and permutation entropy to obtain feature vectors, obtains the energy of each frequency band, and extracts the energy feature value of the pressure pulsation. The wavelet packet data transformation processing system of the data processing module is changed into a Hilbert-Huang transformation processing system, a Hilbert spectrum data processing system and an energy spectrum analysis system. The data processing module can be used for realizing the induction and arrangement of time domain peak-to-peak value, first 10-order pulse frequency, corresponding amplitude and wavelet transformed energy characteristic values of each frequency band of pressure pulse signals of each monitoring point of the volute, the top cover and the draft tube.
The running state analysis module is used for analyzing and classifying the frequency, the amplitude and the characteristic value of the pressure pulsation signal obtained by the data processing module, analyzing the frequency and the amplitude of the pressure pulsation of each monitoring point in the volute, evaluating the time domain peak-to-peak value of the pressure pulsation and the first 3-order main frequency and the amplitude of the pressure pulsation, evaluating whether the amplitudes of the monitoring points of the volute are overlapped or not, and transmitting a warning signal to the fault monitoring module when the amplitudes are overlapped to generate a phase vibration phenomenon; analyzing the frequency and the amplitude of the pressure pulsation of the monitoring point in the top cover, evaluating the time domain peak-to-peak value of the pressure pulsation and the first 5-order main frequency and the amplitude of the pressure pulsation, comparing the frequency with the natural frequency of the first 10-order mode of the top cover structure, and transmitting a warning signal to the fault monitoring module when the frequency of the time domain peak-to-peak value of the pressure pulsation and the first 5-order main frequency and the amplitude of the pressure pulsation are close to each other; analyzing the frequency, amplitude and energy characteristic values of the pressure pulsation signal of the monitoring point in the draft tube, particularly monitoring the low-frequency pressure pulsation signal in the draft tube, and transmitting a warning signal to the fault monitoring module when the low-frequency pressure pulsation signal with large amplitude appears; and (3) evaluating the energy characteristic value of each frequency band of each monitoring point of the draft tube to judge the running state of the water turbine, and transmitting a warning signal to the fault monitoring module when any one of She Daoguo energy characteristic in the rotating wheel, cavitation energy characteristic in the rotating wheel, low-head idle energy characteristic, guide vane opening swing energy characteristic and draft tube vortex band energy characteristic value is monitored. The running state analysis module can evaluate the running state of the unit according to the pressure pulsation signal, and the running state of the unit can be divided into A, B and C running states, wherein the A state represents excellent, the B state represents good, and the C state represents qualified.
The fault monitoring module is used for setting a safety threshold range of the pressure pulsation signal of each monitoring point in the storage module of the fault monitoring module and carrying out abnormal characteristic marking on the warning information of the running state analysis module; checking whether the pressure pulsation signal characteristics of each monitoring point of the operation state analysis module are in a safety threshold range (namely the pressure pulsation threshold interval), and marking abnormal characteristics of the signal with the super threshold and the monitoring point; and judging and checking the abnormal feature marking information, displaying the abnormal feature on a monitoring platform in real time in a red warning mode, and simultaneously transmitting the received abnormal feature signal and the normal signal to a user side by the monitoring platform.
The system and the method are used for diagnosing the fluid dynamic characteristics such as pressure pulsation generated by dynamic and static interference of the water turbine, pressure pulsation generated by She Daoguo and cavitation vortex, propagation of pressure waves and the like, monitoring the running state of the whole machine in real time, feeding back unsteady flow in the machine set and the unsteady running state of the machine set to a control system of the machine set, and adjusting the running state of the machine set.
Based on the method for determining the hydraulic turbine fault risk component provided by the embodiment, correspondingly, the application also provides a specific implementation mode of the device for determining the hydraulic turbine fault risk component. Please refer to the following examples.
As shown in fig. 6, the device 600 for determining a fault risk component of a water turbine provided in an embodiment of the present application may include the following modules: a first acquisition module 601, a first processing module 602 and a first determination module 603.
The first obtaining module 601 is configured to obtain, when the water turbine is in an operating state, a first pressure pulsation signal of a target monitoring component in the water turbine, where the target monitoring component includes at least one of a volute, a top cover, and a draft tube, and the first pressure pulsation signal is a pressure pulsation signal in a first period;
the first processing module 602 is configured to process the first pressure pulsation signal of the target monitoring component to obtain frequency domain information of the target monitoring component;
the first determining module 603 is configured to determine the target monitoring component as a fault risk component, where the fault risk component is a component with a fault risk, if the frequency domain information of the target monitoring component meets a preset rule.
According to the determining device for the hydraulic turbine fault risk component, a first pressure pulsation signal of a target monitoring component in the hydraulic turbine can be obtained when the hydraulic turbine is in an operating state, the target monitoring component comprises at least one of a volute, a top cover and a draft tube, and the first pressure pulsation signal is a pressure pulsation signal in a first period; processing the first pressure pulsation signal of the target monitoring component to obtain frequency domain information of the target monitoring component; and under the condition that the frequency domain information of the target monitoring component meets the preset rule, determining the target monitoring component as a fault risk component, wherein the fault risk component is a component with fault risk. In this way, in the embodiment of the application, the pressure pulsation signal of the target monitoring component is monitored under the running state of the water turbine, the frequency domain information of the target monitoring component is obtained through processing, and whether the frequency domain information meets the preset rule or not is analyzed, so that the fault risk component of the water turbine is accurately diagnosed.
In some embodiments, when the target monitoring component is a draft tube, the frequency domain information may include frequency and amplitude;
the first determining module 603 may specifically include:
a first determining unit, configured to determine, as a fault risk component, the draft tube if the frequency and the amplitude of the draft tube satisfy a preset first sub-rule, the preset first sub-rule indicating that the frequency of the draft tube is lower than a preset frequency threshold, and the amplitude of the draft tube is greater than a preset first amplitude threshold;
the preset rule includes a preset first sub-rule.
As an implementation manner of the present application, in order to accurately diagnose the failure risk component of the water turbine, the apparatus 600 may further include:
the second processing module is used for processing the first pressure pulsation signal of the draft tube to obtain the energy characteristic of the draft tube;
and the second determining module is used for determining the draft tube as a fault risk component under the condition that the energy characteristic of the draft tube is a preset target energy characteristic, and the target energy characteristic comprises any one of a She Daoguo energy characteristic in the rotating wheel, a cavitation energy characteristic in the rotating wheel, a low-head idle energy characteristic, a guide vane opening swing energy characteristic and a draft tube vortex band energy characteristic.
In some embodiments, where the target monitoring component is a volute, the frequency domain information may include frequency and amplitude;
the first determining module 603 may specifically include:
the second determining unit is used for determining the volute as a fault risk component under the condition that the frequency and the amplitude of the volute meet a preset second sub-rule, and the preset second sub-rule indicates that the amplitude of the volute is larger than a preset second amplitude threshold corresponding to the frequency of the volute;
the preset rule includes a preset second sub-rule.
In some embodiments, where the target monitoring component is a cap, the frequency domain information may include frequency;
the first determining module 603 may specifically include:
a third determining unit, configured to determine the top cover as a fault risk component if the frequency of the top cover satisfies a preset third sub-rule, where the preset third sub-rule indicates that a deviation between the frequency of the top cover and a fixed frequency of the top cover is smaller than a preset deviation value;
the preset rule includes a preset third sub-rule.
As another implementation manner of the present application, in order to accurately reflect the operation state of the target monitoring component, the apparatus 600 may further include:
and the third determining module is used for determining the operation state corresponding to the pressure pulsation interval where the first pressure pulsation signal of the target monitoring component is located as the operation state of the target monitoring component, and different operation states are corresponding to different pressure pulsation intervals.
As yet another implementation manner of the present application, to further identify whether the fault risk component has a fault, the apparatus 600 may further include:
the second acquisition module is used for acquiring a second pressure pulse signal of the fault risk component under the condition that the first pressure pulse signal of the fault risk component exceeds a preset pressure pulse threshold interval, wherein the second pressure pulse signal is a pressure pulse signal in a second period, and the second period is later than the first period;
and a fourth determining module for determining the fault risk component as the fault component if the second pressure pulsation signal of the fault risk component exceeds the pressure pulsation threshold interval.
Fig. 7 shows a schematic hardware structure of an electronic device according to an embodiment of the present application.
A processor 701 may be included in an electronic device, as well as a memory 702 in which computer program instructions are stored.
In particular, the processor 701 described above may include a Central Processing Unit (CPU), or an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), or may be configured to implement one or more integrated circuits of embodiments of the present application.
Memory 702 may include mass storage for data or instructions. By way of example, and not limitation, memory 702 may comprise a Hard Disk Drive (HDD), floppy Disk Drive, flash memory, optical Disk, magneto-optical Disk, magnetic tape, or universal serial bus (Universal Serial Bus, USB) Drive, or a combination of two or more of the foregoing. The memory 702 may include removable or non-removable (or fixed) media, where appropriate. Memory 702 may be internal or external to the integrated gateway disaster recovery device, where appropriate. In a particular embodiment, the memory 702 is a non-volatile solid state memory.
In particular embodiments, memory 702 may include Read Only Memory (ROM), random Access Memory (RAM), magnetic disk storage media devices, optical storage media devices, flash memory devices, electrical, optical, or other physical/tangible memory storage devices. Thus, in general, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software comprising computer-executable instructions and when the software is executed (e.g., by one or more processors) it is operable to perform the operations described with reference to methods in accordance with aspects of the present disclosure.
The processor 701 reads and executes the computer program instructions stored in the memory 702 to implement the method for determining the failure risk components of any one of the above embodiments.
In one example, the electronic device may also include a communication interface 703 and a bus 710. As shown in fig. 7, the processor 701, the memory 702, and the communication interface 703 are connected by a bus 710 and perform communication with each other.
The communication interface 703 is mainly used for implementing communication between each module, device, unit and/or apparatus in the embodiments of the present application.
Bus 710 includes hardware, software, or both that couple components of the electronic device to one another. By way of example, and not limitation, the buses may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an infiniband interconnect, a Low Pin Count (LPC) bus, a memory bus, a micro channel architecture (MCa) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a video electronics standards association local (VLB) bus, or other suitable bus, or a combination of two or more of the above. Bus 710 may include one or more buses, where appropriate. Although embodiments of the present application describe and illustrate a particular bus, the present application contemplates any suitable bus or interconnect.
The electronic device can execute the method for determining the fault risk component of the water turbine in the embodiment of the application, so that the method and the device for determining the fault risk component of the water turbine, which are described in connection with fig. 1 and 6, are realized.
In addition, in combination with the method for determining the failure risk component of the hydraulic turbine in the above embodiment, the embodiment of the application may be implemented by providing a computer readable storage medium. The computer readable storage medium has stored thereon computer program instructions; the computer program instructions, when executed by a processor, implement a method of determining a risk component of a hydraulic turbine failure in any of the above embodiments.
It should be clear that the present application is not limited to the particular arrangements and processes described above and illustrated in the drawings. For the sake of brevity, a detailed description of known methods is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method processes of the present application are not limited to the specific steps described and illustrated, and those skilled in the art can make various changes, modifications, and additions, or change the order between steps, after appreciating the spirit of the present application.
The functional blocks shown in the above-described structural block diagrams may be implemented in hardware, software, firmware, or a combination thereof. When implemented in hardware, it may be, for example, an electronic circuit, an Application Specific Integrated Circuit (ASIC), suitable firmware, a plug-in, a function card, or the like. When implemented in software, the elements of the present application are the programs or code segments used to perform the required tasks. The program or code segments may be stored in a machine readable medium or transmitted over transmission media or communication links by a data signal carried in a carrier wave. A "machine-readable medium" may include any medium that can store or transfer information. Examples of machine-readable media include electronic circuitry, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio Frequency (RF) links, and the like. The code segments may be downloaded via computer networks such as the internet, intranets, etc.
It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, the present application is not limited to the order of the above-described steps, that is, the steps may be performed in the order mentioned in the embodiments, may be different from the order in the embodiments, or several steps may be performed simultaneously.
Aspects of the present disclosure are described above with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. 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 may be provided to a processor of a general purpose computer, special purpose computer, 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, enable the implementation of the functions/acts specified in the flowchart and/or block diagram block or blocks. Such a processor may be, but is not limited to being, a general purpose processor, a special purpose processor, an application specific processor, or a field programmable logic circuit. It will also be understood that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware which performs the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In the foregoing, only the specific embodiments of the present application are described, and it will be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the systems, modules and units described above may refer to the corresponding processes in the foregoing method embodiments, which are not repeated herein. It should be understood that the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive various equivalent modifications or substitutions within the technical scope of the present application, which are intended to be included in the scope of the present application.
Claims (10)
1. A method for determining a failure risk component of a water turbine, comprising:
under the running state of the water turbine, acquiring a first pressure pulsation signal of a target monitoring component in the water turbine, wherein the target monitoring component comprises at least one of a volute, a top cover and a draft tube, and the first pressure pulsation signal is a pressure pulsation signal in a first period;
processing the first pressure pulsation signal of the target monitoring component to obtain frequency domain information of the target monitoring component;
and under the condition that the frequency domain information of the target monitoring component meets a preset rule, determining the target monitoring component as a fault risk component, wherein the fault risk component is a component with fault risk.
2. The method of claim 1, wherein the frequency domain information includes frequency and amplitude at the target monitoring component is the draft tube;
and determining the target monitoring component as a fault risk component under the condition that the frequency domain information of the target monitoring component meets a preset rule, wherein the method comprises the following steps:
determining the draft tube as a fault risk component if the frequency and amplitude of the draft tube meet a preset first sub-rule, the preset first sub-rule indicating that the frequency of the draft tube is below a preset frequency threshold and the amplitude of the draft tube is greater than a preset first amplitude threshold;
the preset rule includes the preset first sub-rule.
3. The method of claim 2, further comprising, after said acquiring the first pressure pulsation signal of the target monitoring component in the water turbine:
processing a first pressure pulsation signal of the draft tube to obtain an energy characteristic of the draft tube;
and determining the draft tube as a fault risk component under the condition that the energy characteristic of the draft tube is a preset target energy characteristic, wherein the target energy characteristic comprises any one of a She Daoguo in-runner energy characteristic, a cavitation in-runner energy characteristic, a low-head idle energy characteristic, a guide vane opening swing energy characteristic and a draft tube vortex band energy characteristic.
4. The method of claim 1, wherein, in the case where the target monitoring component is the volute, the frequency domain information includes frequency and amplitude;
and determining the target monitoring component as a fault risk component under the condition that the frequency domain information of the target monitoring component meets a preset rule, wherein the method comprises the following steps:
determining the volute as a fault risk component under the condition that the frequency and the amplitude of the volute meet a preset second sub-rule, wherein the preset second sub-rule indicates that the amplitude of the volute is larger than a preset second amplitude threshold corresponding to the frequency of the volute;
the preset rule includes the preset second sub-rule.
5. The method of claim 1, wherein the frequency domain information comprises frequency if the target monitoring component is the cap;
and determining the target monitoring component as a fault risk component under the condition that the frequency domain information of the target monitoring component meets a preset rule, wherein the method comprises the following steps:
determining the top cover as a fault risk component under the condition that the frequency of the top cover meets a preset third sub-rule, wherein the preset third sub-rule indicates that the deviation between the frequency of the top cover and the fixed frequency of the top cover is smaller than a preset deviation value;
The preset rule includes the preset third sub-rule.
6. The method of claim 1, further comprising, after said acquiring the first pressure pulsation signal of the target monitoring component in the water turbine:
and determining an operation state corresponding to a pressure pulsation interval where a first pressure pulsation signal of the target monitoring component is located as the operation state of the target monitoring component, wherein different operation states correspond to different pressure pulsation intervals.
7. The method of claim 1, further comprising, after said determining said target monitoring component as a failure risk component:
acquiring a second pressure pulse signal of the fault risk component when the first pressure pulse signal of the fault risk component does not accord with a preset pressure pulse threshold interval, wherein the second pressure pulse signal is a pressure pulse signal in a second period, and the second period is later than the first period;
and determining the fault risk component as a fault component if the second pressure pulsation signal of the fault risk component does not meet the pressure pulsation threshold interval.
8. A device for determining the risk of failure of a hydraulic turbine, said device comprising:
The system comprises a first acquisition module, a second acquisition module and a control module, wherein the first acquisition module is used for acquiring a first pressure pulsation signal of a target monitoring component in the water turbine when the water turbine is in an operating state, the target monitoring component comprises at least one of a volute, a top cover and a draft tube, and the first pressure pulsation signal is a pressure pulsation signal in a first period;
the first processing module is used for processing the first pressure pulsation signal of the target monitoring component to obtain frequency domain information of the target monitoring component;
the first determining module is configured to determine the target monitoring component as a fault risk component when the frequency domain information of the target monitoring component meets a preset rule, where the fault risk component is a component with a fault risk.
9. An electronic device, the device comprising: a processor and a memory storing computer program instructions; the processor, when executing the computer program instructions, implements a method for determining a risk component for a water turbine failure according to any one of claims 1-7.
10. A computer readable storage medium, characterized in that it has stored thereon computer program instructions which, when executed by a processor, implement a method for determining a risk component of a hydraulic turbine according to any one of claims 1-7.
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