Magnetoelectric rotating speed sensing analysis method for hydroelectric generating set

Abstract

The invention provides a hydroelectric generating set magnetoelectric rotating speed sensing analysis method which comprises the following steps: acquiring water turbine operation data, analyzing theoretical rotating speed data based on the water turbine operation data, acquiring actual rotating speed data output by a magnetoelectric rotating speed sensor, and analyzing data deviation based on the theoretical rotating speed data and the actual rotating speed data. Comparing the data deviation with a preset deviation threshold value, collecting magnetoelectric rotating speed sensor data, analyzing the abnormality of the magnetoelectric rotating speed sensor based on the magnetoelectric rotating speed sensor data, collecting water wheel blade data, and analyzing the abnormality of the water wheel blade based on the water wheel blade data. According to the method, the deviation of the rotating speed data is analyzed to judge whether the rotating speed sensor has a problem or not, then the abnormal conditions of the magnetoelectric rotating speed sensor and the water wheel blade are analyzed respectively, the fault main body with the large fault probability is positioned, and the fault positioning accuracy is improved. The magnetoelectric rotating speed sensing analysis efficiency is improved, and accurate fault positioning is provided.

Description

Technical Field

[0001] The invention belongs to the technical field of hydro-generator monitoring, and in particular relates to a magnetoelectric speed sensing and analysis method for a hydro-generator set. Background Art

[0002] The magnetoelectric speed sensor uses the principle of magnetoelectric induction to measure speed. When the gear rotates, the magnetic lines of force passing through the sensor coil change, generating a periodic voltage in the sensor coil. The amplitude of the voltage is related to the speed. The higher the speed, the higher the output voltage (0 to a range), and the output frequency is proportional to the speed.

[0003] Existing magnetoelectric speed sensor analysis methods mostly collect real-time data from the magnetoelectric speed sensor for analysis and fault determination. They fail to first determine whether there is a speed sensor problem by analyzing speed data deviations, and then separately analyze the abnormal conditions of the magnetoelectric speed sensor and turbine blades. Consequently, they are unable to locate the main fault based on the fault probability, resulting in low magnetoelectric speed sensor analysis efficiency and a single fault determination method. In summary, how to improve the efficiency of magnetoelectric speed sensing analysis is an urgent problem to be solved by those skilled in the art. Summary of the Invention

[0004] The present invention provides a magnetoelectric speed sensing analysis method for a hydroelectric generator set. The present invention first analyzes the deviation of the speed data to determine whether there is a problem with the speed sensing, and then analyzes the abnormal conditions of the magnetoelectric speed sensor and the water turbine blades respectively to locate the fault subject with a higher probability of failure. This is conducive to improving the efficiency of magnetoelectric speed sensing analysis and providing accurate fault location.

[0005] In order to achieve the above technical features, the purpose of the present invention is achieved as follows: a method for analyzing the magnetoelectric speed sensing of a hydroelectric generator set, comprising the following steps: S1. Collect turbine operation data and analyze theoretical speed data based on the turbine operation data; S2. Collecting actual speed data output by the magnetoelectric speed sensor, and analyzing data deviation based on the theoretical speed data and the actual speed data; S3, comparing the data deviation with a preset deviation threshold. If the data deviation is greater than the deviation threshold, proceed to S4; S4. Collecting magnetoelectric speed sensor data, and analyzing magnetoelectric speed sensor abnormalities based on the magnetoelectric speed sensor data; S5. Collecting turbine blade data and analyzing turbine blade abnormalities based on the turbine blade data; S6. Determine the damage probability and locate the fault based on the abnormality of the magnetoelectric speed sensor and the abnormality of the turbine blade.

[0006] Preferably, the S1 includes the following specific steps: S101, collecting turbine operating data, wherein the turbine operating data includes water head, flow rate and ambient temperature; S102: Input the water head, flow rate, and ambient temperature into a turbine operation abnormality value calculation formula to calculate the turbine operation abnormality value. The turbine operation abnormality value calculation formula is: ; in, for t Abnormal value of turbine operation at time for t The water head of the moment, is the standard water head, for t The flow of time, is the standard flow rate, for t The ambient temperature at the moment, is the standard ambient temperature, is the head factor, is the flow factor, is the ambient temperature factor, ; S103, inputting the abnormal value of the turbine operation into the theoretical speed calculation formula to calculate the theoretical speed, the theoretical speed calculation formula is: ; in, for t The theoretical speed at the moment, The standard speed.

[0007] Preferably, S2 includes the following specific steps: S201, collecting actual speed data output by the magnetoelectric speed sensor; S202: Input the theoretical speed and the actual speed into a data deviation value calculation formula to calculate the data deviation value. The data deviation value calculation formula is: ; Among them, T is the speed acquisition time, for t The actual speed at the moment, is the time integral.

[0008] Preferably, S3 includes the following specific steps: Compare the data deviation value with the preset deviation threshold; If the data deviation value is less than or equal to the deviation threshold, the speed sensor is judged to be normal; If the data deviation value is greater than the deviation threshold, it is determined that the speed sensor is abnormal and the S4 operation is performed.

[0009] Preferably, the S4 includes the following specific steps: S401, collecting magnetoelectric speed sensor data, wherein the magnetoelectric speed sensor data includes magnetic field strength and current magnitude; S402. If the collected magnetic field strength values are the same, the magnetic field strength is determined to be normal; if the collected magnetic field strength values are different, the magnetic field strength is determined to be abnormal and the magnetic field strength is input into a magnetic field strength abnormal value calculation formula to calculate the magnetic field strength abnormal value. The magnetic field strength abnormal value calculation formula is: ; Among them, T1 is the start time of the magnetoelectric speed sensor data collection, T2 is the end time of the magnetoelectric speed sensor data collection, T1-T2 is the magnetoelectric speed sensor data collection duration, for t The magnetic field strength at the moment, is the standard magnetic field strength; S403: Input the collected current into a current abnormal value calculation formula to calculate the current abnormal value. The current abnormal value calculation formula is: ; in, for t The current magnitude at the moment, for t The standard current size at the moment, when When t The current is normal at all times; S404: Input the abnormal value of the magnetic field intensity and the abnormal value of the current into a calculation formula for the abnormal value of the magnetoelectric speed sensor to calculate the abnormal value of the magnetoelectric speed sensor. The calculation formula for the abnormal value of the magnetoelectric speed sensor is: ; in, is the magnetic field intensity anomaly weight, is the current anomaly weight, .

[0010] Preferably, the S5 includes the following specific steps: S501, collecting turbine blade data, wherein the turbine blade data includes vibration frequency, amplitude, and noise; S502: Input the vibration frequency, amplitude, and noise into a water turbine blade abnormality calculation formula to calculate the water turbine blade abnormality. The water turbine blade abnormality calculation formula is: ; Among them, T3 is the start time of water turbine blade data collection, T4 is the end time of water turbine blade data collection, T4-T3 is the water turbine blade data collection time, for t The vibration frequency of the moment, is the standard vibration frequency, is the amplitude at time t, is the standard amplitude, for t The noise of the moment, is the standard noise, is the vibration frequency anomaly weight, is the amplitude anomaly weight, ,when hour, The value is 0, when hour, The value is 0, when hour, The value is 0.

[0011] Preferably, the S6 includes the following specific steps: S601: Divide the magnetoelectric speed sensor abnormal value by the magnetoelectric speed sensor abnormal threshold to obtain a magnetoelectric speed sensor damage probability. Also, divide the turbine blade abnormal value by the turbine blade abnormal threshold to obtain a turbine blade damage probability. The entity corresponding to the maximum value between the magnetoelectric speed sensor damage probability and the turbine blade damage probability is set as the fault entity. S602: locate the fault of the hydroelectric generating set based on the maximum value of the damage probability.

[0012] A magnetoelectric speed sensing and analysis system for a hydroelectric generator set, the system being used to implement a magnetoelectric speed sensing and analysis method for a hydroelectric generator set, the system comprising a data acquisition module for collecting turbine operating data, actual speed data output by a magnetoelectric speed sensor, magnetoelectric speed sensor data, and turbine blade data; The turbine operation analysis module is used to input the water head, flow rate and ambient temperature into the turbine operation abnormal value calculation formula to calculate the turbine operation abnormal value; Theoretical speed analysis module, used to input abnormal values of turbine operation into the theoretical speed calculation formula to calculate the theoretical speed; A data deviation analysis module is used to input the theoretical speed and the actual speed into a data deviation value calculation formula to calculate the data deviation value, and compare the data deviation value with a preset deviation threshold; A sensor abnormality analysis module is used to input the abnormal value of magnetic field intensity and the abnormal value of current into the abnormal value calculation formula of magnetoelectric speed sensor to calculate the abnormal value of magnetoelectric speed sensor; The water turbine blade abnormality analysis module is used to input the vibration frequency, amplitude and noise into the water turbine blade abnormality value calculation formula to calculate the water turbine blade abnormality value; A fault location module is used to input abnormal values of the magnetoelectric speed sensor and the turbine blade into a damage probability calculation formula to output a maximum damage probability, and to locate the fault of the hydroelectric generator set based on the maximum damage probability; The control module is used to control the operation of the data acquisition module, the turbine operation analysis module, the theoretical speed analysis module, the data deviation analysis module, the sensor anomaly analysis module, the turbine blade anomaly analysis module and the fault location module.

[0013] An electronic device comprising: a memory for storing a computer program; The processor is used to implement the steps of the above-mentioned method for magnetoelectric speed sensing and analysis of a hydroelectric generator set when executing the computer program.

[0014] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of a method for magnetoelectric speed sensing and analysis of a hydroelectric generator set.

[0015] The present invention has the following beneficial effects: The present invention collects turbine operation data, analyzes theoretical speed data based on the turbine operation data, collects actual speed data output by a magnetoelectric speed sensor, analyzes data deviation based on the theoretical speed data and the actual speed data, compares the data deviation with a preset deviation threshold, collects magnetoelectric speed sensor data, analyzes magnetoelectric speed sensor anomalies based on the magnetoelectric speed sensor data, collects water wheel blade data, analyzes water wheel blade anomalies based on the water wheel blade data, determines the damage probability based on the magnetoelectric speed sensor anomaly and the water wheel blade anomaly and performs fault location. The present invention first analyzes the deviation of the speed data to determine whether there is a problem with the speed sensing, and then analyzes the anomalies of the magnetoelectric speed sensor and the water wheel blades respectively, locates the fault subject with a higher probability of failure, which is beneficial to improving the efficiency of magnetoelectric speed sensing analysis and providing accurate fault location. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0017] Figure 1 The present invention is a flow chart of a method for magnetoelectric speed sensing and analysis of a hydroelectric generator set.

[0018] Figure 2 This is a schematic diagram of the S1 process in a magnetoelectric speed sensing analysis method for a hydroelectric generator set according to the present invention.

[0019] Figure 3 This is a schematic diagram of the S4 process in a magnetoelectric speed sensing analysis method for a hydroelectric generator set of the present invention.

[0020] Figure 4 This is a schematic diagram of the S6 process in a magnetoelectric speed sensing analysis method for a hydroelectric generator set according to the present invention.

[0021] Figure 5 The figure is a schematic diagram of the overall framework of a magnetoelectric speed sensing and analysis system for a hydroelectric generator set according to the present invention. DETAILED DESCRIPTION

[0022] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field are within the scope of protection of the present invention.

[0023] Example 1: See also Figure 1-Figure 4 , Figure 1 A schematic flow chart of a method for analyzing magnetoelectric speed sensing of a hydroelectric generator set provided by an embodiment of the present invention; The present invention provides a method for analyzing the magnetoelectric speed of a hydroelectric generator set, comprising the following specific steps: S1. Collect turbine operation data and analyze theoretical speed data based on the turbine operation data; Figure 2 A schematic diagram of the S1 process in a method for analyzing magnetoelectric speed sensing of a hydroelectric generator set provided by an embodiment of the present invention; In this embodiment, S1 includes the following specific steps: S101, collecting turbine operating data, wherein the turbine operating data includes water head, flow rate and ambient temperature; Specifically, the water head is the height difference of the water flow from the water inlet to the center of the impeller, which can provide potential energy to drive the turbine to rotate. The greater the water head, the greater the impact of the water flow on the turbine impeller, resulting in greater torque and power provided, thereby increasing the speed of the turbine. The smaller the water head, the smaller the impact of the water flow on the impeller, resulting in smaller torque and power provided, thereby reducing the speed of the turbine. The calculation formula for water head is: ; Among them, h is the head, that is, the potential energy of unit weight of water flow, pout is the pressure of water at the outlet, p in The pressure of water at the water inlet is measured by pressure sensors at the water inlet and outlet. is the density of the water flow, the density of water under standard conditions is 1000 kg / m³, is the acceleration due to gravity, usually taken as 9.8 meters per second squared (9.8m / s²); The flow rate is the volume of water passing through the turbine per unit time. Under certain head conditions, the flow rate of the turbine is proportional to the rotational speed. The flow rate is measured by installing an orifice flowmeter, vortex flowmeter, or other flowmeter in the water inlet pipe of the turbine. The higher the ambient temperature, the worse the heat dissipation conditions inside the hydroelectric generator set, resulting in reduced cooling system efficiency, increased temperatures of the generator and diesel engine, and reduced output power; the lower the ambient temperature, the higher the viscosity of the lubricating oil, resulting in unstable engine speed; the ambient temperature is measured by temperature sensors such as thermocouples and thermistors.

[0024] S102: Input the water head, flow rate, and ambient temperature into a turbine operation abnormality value calculation formula to calculate the turbine operation abnormality value. The turbine operation abnormality value calculation formula is: ; in, for t Abnormal value of turbine operation at time for t The water head of the moment, is the standard water head, for t The flow of time, is the standard flow rate, for t The ambient temperature at the moment, is the standard ambient temperature, is the head factor, is the flow factor, is the ambient temperature factor, ; Specifically, the head and flow of the turbine are affected by the type and size of the turbine. The optimal working head in the turbine-related technical specifications or design scheme is used as the standard head of this embodiment, and the flow at the rated power of the turbine is used as the standard flow of this embodiment; the ambient temperature of the turbine is affected by the turbine material and working conditions. The optimal working temperature of the generator set cooling system is used as the standard ambient temperature of this embodiment.

[0025] S103, inputting the abnormal value of the turbine operation into the theoretical speed calculation formula to calculate the theoretical speed, the theoretical speed calculation formula is: ; in, for t The theoretical speed at the moment, The standard speed.

[0026] Specifically, the rotational speed of the turbine is affected by the size, model and design of the turbine, and the rotational speed at the rated power of the turbine is used as the standard rotational speed in this embodiment.

[0027] S2. Collecting actual speed data output by the magnetoelectric speed sensor, and analyzing data deviation based on the theoretical speed data and the actual speed data; In this embodiment, S2 includes the following specific steps: S201, collecting actual speed data output by the magnetoelectric speed sensor; S202: Input the theoretical speed and the actual speed into a data deviation value calculation formula to calculate the data deviation value. The data deviation value calculation formula is: ; Among them, T is the speed acquisition time, for t The actual speed at the moment, is the time integral.

[0028] S3, comparing the data deviation with a preset deviation threshold. If the data deviation is greater than the deviation threshold, proceed to S4; In this embodiment, S3 includes the following specific steps: Compare the data deviation value with the preset deviation threshold; If the data deviation value is less than or equal to the deviation threshold, the speed sensor is judged to be normal; If the data deviation value is greater than the deviation threshold, it is determined that the speed sensor is abnormal and the S4 operation is performed.

[0029] Specifically, several magnetoelectric speed sensors with normal measurements and several magnetoelectric speed sensors with abnormal measurements are selected to collect the speed of the turbine respectively. The corresponding speed data are collected and input into the data deviation value calculation formula to calculate the data deviation value, and the average value of the calculated data deviation value is taken as the deviation threshold of this embodiment.

[0030] S4. Collecting magnetoelectric speed sensor data, and analyzing magnetoelectric speed sensor abnormalities based on the magnetoelectric speed sensor data; Figure 3 A schematic diagram of the S4 process in a method for analyzing magnetoelectric speed sensing of a hydroelectric generator set provided by an embodiment of the present invention; In this embodiment, S4 includes the following specific steps: S401, collecting magnetoelectric speed sensor data, wherein the magnetoelectric speed sensor data includes magnetic field strength and current magnitude; Specifically, a magnetic field meter is installed within the set range of the magnetoelectric speed sensor to measure the magnetic field strength, and multiple measurements are performed at different positions and different rotation speeds; when the magnetic field source rotates, the inductive element inside the magnetoelectric speed sensor will generate a current signal, and an oscilloscope or other data acquisition equipment is installed to collect the current waveform on the oscilloscope, and analyze the current magnitude and waveform characteristics.

[0031] S402. If the collected magnetic field strength values are the same, the magnetic field strength is determined to be normal; if the collected magnetic field strength values are different, the magnetic field strength is determined to be abnormal and the magnetic field strength is input into a magnetic field strength abnormal value calculation formula to calculate the magnetic field strength abnormal value. The magnetic field strength abnormal value calculation formula is: ; Among them, T1 is the start time of the magnetoelectric speed sensor data collection, T2 is the end time of the magnetoelectric speed sensor data collection, T1-T2 is the magnetoelectric speed sensor data collection duration, for t The magnetic field strength at the moment, is the standard magnetic field strength; Specifically, a new magnetoelectric speed sensor is selected to collect the turbine speed, and the magnetic field strength of the magnetoelectric speed sensor is measured as the standard magnetic field strength of this embodiment.

[0032] S403: Input the collected current into a current abnormal value calculation formula to calculate the current abnormal value. The current abnormal value calculation formula is: ; in, for t The current magnitude at the moment, for t The standard current size at the moment, when When t The current is normal at all times; Specifically, in order to facilitate calculation, the standard current in this embodiment is calculated using the standard current calculation formula: Get, where P is the turbine output power, N is the number of coil turns of the generator, C is the magnetic field intensity, A is the coil area, Sp is the turbine speed, This is the power factor of the generator, which is set according to the nature of the load.

[0033] S404: Input the abnormal value of the magnetic field intensity and the abnormal value of the current into a calculation formula for the abnormal value of the magnetoelectric speed sensor to calculate the abnormal value of the magnetoelectric speed sensor. The calculation formula for the abnormal value of the magnetoelectric speed sensor is: ; in, is the magnetic field intensity anomaly weight, is the current anomaly weight, .

[0034] S5. Collecting turbine blade data and analyzing turbine blade abnormalities based on the turbine blade data; In this embodiment, S5 includes the following specific steps: S501, collecting turbine blade data, wherein the turbine blade data includes vibration frequency, amplitude, and noise; Specifically, the vibration frequency is the number of times the turbine blade vibrates per unit time, and the amplitude is the maximum distance the turbine blade deviates from its equilibrium position during vibration. Analyzing vibration data can diagnose whether the turbine blade has cracks, material fatigue, or structural problems, and assess the operational stability of the turbine blade. By installing vibration sensors such as accelerometers on the turbine blades, bearings, or frames, parameters such as amplitude, frequency, and phase can be extracted from the collected vibration data. Noise is generated by the interaction between the turbine blades and the water flow or the vibration of the turbine blades themselves. By installing noise measuring instruments such as sound level meters, the noise data of the turbine blades at different positions and under different operating conditions can be measured.

[0035] S502: Input the vibration frequency, amplitude, and noise into a water turbine blade abnormality calculation formula to calculate the water turbine blade abnormality. The water turbine blade abnormality calculation formula is: ; Among them, T3 is the start time of water turbine blade data collection, T4 is the end time of water turbine blade data collection, T4-T3 is the water turbine blade data collection time, for t The vibration frequency of the moment, is the standard vibration frequency, is the amplitude at time t, is the standard amplitude, for t The noise of the moment, is the standard noise, is the vibration frequency anomaly weight, is the amplitude anomaly weight, ,when hour, The value is 0, when hour, The value is 0, when hour, The value is 0.

[0036] Specifically, a new turbine blade is selected to conduct an operation experiment under a set experimental environment, and the average values of several vibration frequencies, amplitudes and noises collected in the experiment are taken as the standard vibration frequency, standard amplitude and standard noise of this embodiment.

[0037] Specifically, several hydroelectric generating sets are selected, and the turbine operation data are collected to calculate the theoretical speed data; the actual speed data output by the magnetoelectric speed sensor is collected, and the data deviation between the theoretical speed data and the actual speed data is calculated; the magnetoelectric speed sensor data with a data deviation greater than the deviation threshold is collected, and the magnetoelectric speed sensor anomaly value is calculated; the water turbine blade data is collected, and the water turbine blade anomaly value is calculated. At the same time, several hydraulic experts are selected to analyze the speed data, data deviation, magnetoelectric speed sensor anomaly value and water turbine blade anomaly value of the hydroelectric generating sets respectively, and the calculated data and the expert analysis data are input into the fitting software to output the head factor, flow factor, ambient temperature factor, magnetic field strength anomaly weight, current anomaly weight, vibration frequency anomaly weight and amplitude anomaly weight corresponding to the data with the highest similarity as the head factor, flow factor, ambient temperature factor, magnetic field strength anomaly weight, current anomaly weight, vibration frequency anomaly weight and amplitude anomaly weight of this implementation.

[0038] S6. Determine the damage probability and locate the fault based on the abnormality of the magnetoelectric speed sensor and the abnormality of the turbine blade.

[0039] Figure 4 A schematic diagram of the S6 process in a method for analyzing magnetoelectric speed sensing of a hydroelectric generator set provided by an embodiment of the present invention; In this embodiment, S6 includes the following specific steps: S601: Divide the magnetoelectric speed sensor abnormal value by the magnetoelectric speed sensor abnormal threshold to obtain a magnetoelectric speed sensor damage probability. Also, divide the turbine blade abnormal value by the turbine blade abnormal threshold to obtain a turbine blade damage probability. The entity corresponding to the maximum value between the magnetoelectric speed sensor damage probability and the turbine blade damage probability is set as the fault entity. S602: locate the fault of the hydroelectric generating set based on the maximum value of the damage probability.

[0040] Example 2: See also Figure 5 , Figure 5 A schematic diagram of the overall framework of a magnetoelectric speed sensing and analysis system for a hydroelectric generator set provided by an embodiment of the present invention; The present invention provides a magnetoelectric speed sensing and analysis system for a hydroelectric generator set, which is used to implement a magnetoelectric speed sensing and analysis method for a hydroelectric generator set. The system includes a data acquisition module for collecting turbine operation data, actual speed data output by the magnetoelectric speed sensor, magnetoelectric speed sensor data, and turbine blade data. The turbine operation analysis module is used to input the water head, flow rate and ambient temperature into the turbine operation abnormal value calculation formula to calculate the turbine operation abnormal value; Theoretical speed analysis module, used to input abnormal values of turbine operation into the theoretical speed calculation formula to calculate the theoretical speed; A data deviation analysis module is used to input the theoretical speed and the actual speed into a data deviation value calculation formula to calculate the data deviation value, and compare the data deviation value with a preset deviation threshold; A sensor abnormality analysis module is used to input the abnormal value of magnetic field intensity and the abnormal value of current into the abnormal value calculation formula of magnetoelectric speed sensor to calculate the abnormal value of magnetoelectric speed sensor; The water turbine blade abnormality analysis module is used to input the vibration frequency, amplitude and noise into the water turbine blade abnormality value calculation formula to calculate the water turbine blade abnormality value; A fault location module is used to input abnormal values of the magnetoelectric speed sensor and the turbine blade into a damage probability calculation formula to output a maximum damage probability, and to locate the fault of the hydroelectric generator set based on the maximum damage probability; The control module is used to control the operation of the data acquisition module, the turbine operation analysis module, the theoretical speed analysis module, the data deviation analysis module, the sensor anomaly analysis module, the turbine blade anomaly analysis module and the fault location module.

[0041] Example 3: The present invention provides an electronic device, comprising: a processor and a memory, wherein the memory stores a computer program that can be called by the processor, and the processor implements the above-mentioned magnetoelectric speed sensing analysis method of a hydroelectric generator set when executing the computer program stored in the memory by calling the computer program stored in the memory.

[0042] The electronic device may have relatively large differences due to different configurations or performances, and may include one or more processors (Central Processing Units, CPU) and one or more memories, wherein the memory stores at least one computer program, which is loaded and executed by the processor to implement a magnetoelectric speed sensing analysis method for a hydroelectric generator set provided in the above-mentioned method embodiment. The electronic device may also include other components for realizing the functions of the device. For example, the electronic device may also have components such as a wired or wireless network interface and an input and output interface to facilitate data input and output. This embodiment will not be described in detail here.

[0043] Implementation 4: The present invention provides a computer-readable storage medium, wherein a computer program is stored in the computer-readable storage medium. When the computer program is executed by a processor, the following steps are implemented: Collect turbine operation data, and analyze theoretical speed data based on the turbine operation data; collect actual speed data output by the magnetoelectric speed sensor, and analyze data deviation based on the theoretical speed data and actual speed data; compare the data deviation with a preset deviation threshold, and if the data deviation is greater than the deviation threshold, perform S4 operation; collect magnetoelectric speed sensor data, and analyze magnetoelectric speed sensor anomalies based on the magnetoelectric speed sensor data; collect turbine blade data, and analyze turbine blade anomalies based on the turbine blade data; determine the damage probability and perform fault location based on the magnetoelectric speed sensor anomaly and turbine blade anomaly.

[0044] The computer-readable storage medium involved in the present invention includes random access memory (RAM), internal memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disks, removable disks, CD-ROMs, or any other form of storage medium known in the technical field.

[0045] It should also be noted that, in the present invention, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or apparatus that includes a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or apparatus.

[0046] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0047] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be obvious to those skilled in the art. The general principles defined in the present invention can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown in the present invention, but will conform to the widest scope consistent with the principles and novel features disclosed in the present invention.

Claims

1. A method for magnetoelectric speed sensing and analysis of a hydroelectric generator set, characterized in that: The following steps are involved: S1. Collect turbine operation data and analyze theoretical speed data based on the turbine operation data; S2. Collecting actual speed data output by the magnetoelectric speed sensor, and analyzing data deviation based on the theoretical speed data and the actual speed data; S3, comparing the data deviation with a preset deviation threshold. If the data deviation is greater than the deviation threshold, proceed to S4; S4. Collecting magnetoelectric speed sensor data, and analyzing magnetoelectric speed sensor abnormalities based on the magnetoelectric speed sensor data; S5. Collecting turbine blade data and analyzing turbine blade abnormalities based on the turbine blade data; S6. Determine the damage probability and locate the fault based on the abnormality of the magnetoelectric speed sensor and the abnormality of the turbine blade.

2. A method for analyzing the magnetoelectric speed of a hydroelectric generator set according to claim 1, characterized in that: The S1 includes the following specific steps: S101, collecting turbine operating data, wherein the turbine operating data includes water head, flow rate and ambient temperature; S102: Input the water head, flow rate, and ambient temperature into a turbine operation abnormality value calculation formula to calculate the turbine operation abnormality value. The turbine operation abnormality value calculation formula is: ； in, for t Abnormal value of turbine operation at time for t The water head of the moment, is the standard water head, for t The flow of time, is the standard flow rate, for t The ambient temperature at the moment, is the standard ambient temperature, is the head factor, is the flow factor, is the ambient temperature factor, ; S103, inputting the abnormal value of the turbine operation into the theoretical speed calculation formula to calculate the theoretical speed, the theoretical speed calculation formula is: ； in, for t The theoretical speed at the moment, The standard speed.

3. A method for magnetoelectric speed sensing and analysis of a hydroelectric generator set according to claim 1, characterized in that: The S2 includes the following specific steps: S201, collecting actual speed data output by the magnetoelectric speed sensor; S202: Input the theoretical speed and the actual speed into a data deviation value calculation formula to calculate the data deviation value. The data deviation value calculation formula is: ； Among them, T is the speed acquisition time, for t The actual speed at the moment, is the time integral.

4. A method for magnetoelectric speed sensing and analysis of a hydroelectric generator set according to claim 1, characterized in that: The S3 includes the following specific steps: Compare the data deviation value with the preset deviation threshold; If the data deviation value is less than or equal to the deviation threshold, the speed sensor is judged to be normal; If the data deviation value is greater than the deviation threshold, it is determined that the speed sensor is abnormal and the S4 operation is performed.

5. The method for magnetoelectric speed sensing and analysis of a hydroelectric generator set according to claim 1, characterized in that: The S4 includes the following specific steps: S401, collecting magnetoelectric speed sensor data, wherein the magnetoelectric speed sensor data includes magnetic field strength and current magnitude; S402: If the collected magnetic field strength values are the same, it is determined that the magnetic field strength is normal; If the collected magnetic field strength is different, the magnetic field strength is judged to be abnormal and the magnetic field strength is input into the magnetic field strength abnormal value calculation formula to calculate the magnetic field strength abnormal value. The magnetic field strength abnormal value calculation formula is: ； Among them, T1 is the start time of the magnetoelectric speed sensor data collection, T2 is the end time of the magnetoelectric speed sensor data collection, T1-T2 is the magnetoelectric speed sensor data collection duration, for t The magnetic field strength at the moment, is the standard magnetic field strength; S403: Input the collected current into a current abnormal value calculation formula to calculate the current abnormal value. The current abnormal value calculation formula is: ； in, for t The current magnitude at the moment, for t The standard current size at the moment, when When t The current is normal at all times; S404: Input the abnormal value of the magnetic field intensity and the abnormal value of the current into a calculation formula for the abnormal value of the magnetoelectric speed sensor to calculate the abnormal value of the magnetoelectric speed sensor. The calculation formula for the abnormal value of the magnetoelectric speed sensor is: ； in, is the magnetic field intensity anomaly weight, is the current anomaly weight, .

6. A method for magnetoelectric speed sensing and analysis of a hydroelectric generator set according to claim 1, characterized in that: The S5 includes the following specific steps: S501, collecting turbine blade data, wherein the turbine blade data includes vibration frequency, amplitude, and noise; S502: Input the vibration frequency, amplitude, and noise into a water turbine blade abnormality calculation formula to calculate the water turbine blade abnormality. The water turbine blade abnormality calculation formula is: ； Among them, T3 is the start time of water turbine blade data collection, T4 is the end time of water turbine blade data collection, T4-T3 is the water turbine blade data collection time, for t The vibration frequency of the moment, is the standard vibration frequency, is the amplitude at time t, is the standard amplitude, for t The noise of the moment, is the standard noise, is the vibration frequency anomaly weight, is the amplitude anomaly weight, ,when hour, The value is 0, when hour, The value is 0, when hour, The value is 0.

7. The method for magnetoelectric speed sensing and analysis of a hydroelectric generator set according to claim 1, characterized in that: The S6 comprises the following specific steps: S601: Divide the magnetoelectric speed sensor abnormal value by the magnetoelectric speed sensor abnormal threshold to obtain a magnetoelectric speed sensor damage probability. Also, divide the turbine blade abnormal value by the turbine blade abnormal threshold to obtain a turbine blade damage probability. The entity corresponding to the maximum value between the magnetoelectric speed sensor damage probability and the turbine blade damage probability is set as the fault entity. S602: locate the fault of the hydroelectric generating set based on the maximum value of the damage probability.

8. A magnetoelectric speed sensing and analysis system for a hydroelectric generator set, the system being configured to implement the magnetoelectric speed sensing and analysis method for a hydroelectric generator set as claimed in any one of claims 1 to 7, the system comprising a data acquisition module configured to acquire turbine operating data, actual speed data output by the magnetoelectric speed sensor, magnetoelectric speed sensor data, and turbine blade data; The turbine operation analysis module is used to input the water head, flow rate and ambient temperature into the turbine operation abnormal value calculation formula to calculate the turbine operation abnormal value; Theoretical speed analysis module, used to input abnormal values of turbine operation into the theoretical speed calculation formula to calculate the theoretical speed; A data deviation analysis module is used to input the theoretical speed and the actual speed into a data deviation value calculation formula to calculate the data deviation value, and compare the data deviation value with a preset deviation threshold; A sensor abnormality analysis module is used to input the abnormal value of magnetic field intensity and the abnormal value of current into the abnormal value calculation formula of magnetoelectric speed sensor to calculate the abnormal value of magnetoelectric speed sensor; The water turbine blade abnormality analysis module is used to input the vibration frequency, amplitude and noise into the water turbine blade abnormality value calculation formula to calculate the water turbine blade abnormality value; A fault location module is used to input abnormal values of the magnetoelectric speed sensor and the turbine blade into a damage probability calculation formula to output a maximum damage probability, and to locate the fault of the hydroelectric generator set based on the maximum damage probability; The control module is used to control the operation of the data acquisition module, the turbine operation analysis module, the theoretical speed analysis module, the data deviation analysis module, the sensor anomaly analysis module, the turbine blade anomaly analysis module and the fault location module.

9. An electronic device comprising: Memory for storing computer programs; A processor is used to implement the steps of the hydroelectric generator set magnetoelectric speed sensing analysis method described in any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium having a computer program stored therein, wherein the computer program, when executed by a processor, implements the steps of the method for magnetoelectric speed sensing and analysis of a hydroelectric generator set as claimed in any one of claims 1 to 7.

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