Hydropower station debugging intelligent commanding and testing integrated system

Abstract

The invention discloses an intelligent commanding and testing integrated system for hydropower station debugging, and relates to the technical field of hydropower station equipment debugging and operation testing. Based on the physical connection relation and debugging parameters of the water turbine and the speed regulator, a three-dimensional function sub-region model is constructed, a multi-test-mode working condition database is established, through the effect recognition module, the system can construct and judge key indexes in each test mode, and the test efficiency is improved. Whether the problems of resonance effect, guide vane hysteresis, water attack abnormity and disturbance deviation exist or not is automatically recognized, a corresponding early warning instruction is sent out, and a closed-loop link from'phenomenon recognition 'to'reason tracing' is achieved. According to the method, whether a single test is qualified or not can be judged, the collaborative imbalance risk coefficient in the ith test mode can be further calculated, the risk level between collaborative effects is evaluated according to the collaborative imbalance risk coefficient, and intelligent adjustment of a test strategy is supported.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of commissioning and operation test of hydropower station equipment, and particularly relates to a commissioning intelligent command and test integrated system for hydropower station. BACKGROUND

[0002] The statements in this section merely provide background information related to the present disclosure and can not constitute the prior art.

[0003] The water turbine and the speed regulator are the core equipment in the hydropower station, and the operation performance thereof is directly related to the overall regulation capacity, safety and power generation efficiency of the power station. After the construction or overhaul of the hydropower station is completed, a series of commissioning and performance tests must be performed on the water turbine and the speed regulating system to verify whether the equipment state meets the design and operation requirements.

[0004] In the traditional technology, the commissioning work of the water turbine and the speed regulator usually relies on a large amount of manual experience, discrete instrument testing and multi-specialty collaborative operation. The traditional mode has the following main defects: 1. Dispersed test system and low integration degree: The traditional test process often relies on multiple independent devices such as vibration sensors, tachometers, guide vane angle measuring instruments, etc., lacks a unified coordinated platform, resulting in poor data synchronization and difficult information integration.

[0005] 2. Insufficient identification ability of resonance effect, guide vane hysteresis and response lag and disturbance effect: Due to the complex dynamic responses of the water turbine under different operating conditions, such as shaft system resonance, impeller oscillation, and offset after system disturbance when performing step response or sudden load test, the speed regulator has nonlinear characteristics such as guide vane action hysteresis or backlash during start-stop and transition process. In the traditional commissioning process, resonance, guide vane hysteresis, water hammer and disturbance response effects are often tested separately, and there is a lack of unified condition linkage observation means. For example, in the rapid load disturbance offset test, water hammer and shaft vibration may be induced at the same time, but the traditional test system cannot simultaneously capture and analyze the coordinated response of various physical quantities in the same time period and under the same test mode, resulting in one-sided judgment of the system comprehensive stability and risk identification blind area of coordinated disorder. Especially under complex regulation conditions, the nonlinear coupling relationship between various effects is more prominent, and if a unified test platform is not used for closed-loop identification and quantitative analysis, the system risk may be underestimated. SUMMARY

[0006] The present application aims at the problems in the prior art, and provides an intelligent command and test integrated system for commissioning of a hydropower station, which can construct a three-dimensional functional sub-region model and establish a multi-test mode working condition database based on a physical connection relationship and commissioning parameters of a hydraulic turbine and a governor, can construct and determine key indicators (such as a critical resonance coefficient, a guide vane lag response coefficient, a water hammer intensity coefficient and a hydraulic disturbance offset coefficient) in each test mode through an effect identification module, can automatically identify whether there is a resonance effect, guide vane lag, water hammer abnormality and disturbance offset problem, and can issue corresponding early warning instructions to realize a closed loop link from "phenomenon identification" to "cause tracing". Not only whether a single test is qualified can be judged, but also a coordinated disorder risk coefficient in the i th test mode can be further calculated , and a risk level among coordinated effects is evaluated to support intelligent adjustment of a test strategy.

[0007] The technical scheme of the present application is as follows: An intelligent command and test integrated system for commissioning of a hydropower station, comprising: a commissioning mapping modeling module, which is used for identifying and registering key equipment of a hydraulic turbine and a governor system, extracting structural parameters and commissioning constraint information, and establishing a three-dimensional commissioning functional sub-region model based on a physical connection relationship of the equipment; and extracting structural parameters, hydraulic connection parameters and control response parameters of the hydraulic turbine and the governor in a test mode, and establishing a test working condition database; the test mode includes an unloaded mode, a loaded mode, a speed-up mode and a load jump mode; an effect identification module, which is used for constructing a critical resonance coefficient , a guide vane lag response coefficient , a water hammer intensity coefficient and a hydraulic disturbance offset coefficient of the i th test mode based on the test working condition database, and respectively judging to identify a linkage effect type, including a resonance critical effect, a guide vane lag response, a water hammer impact abnormality and a hydraulic disturbance offset; if there is, corresponding early warning instructions are generated; a test command module, which is used for counting the unloaded mode, the loaded mode, the speed-up mode and the load jump mode, and when the values of the critical resonance coefficient , the guide vane lag response coefficient , the water hammer intensity coefficient and the hydraulic disturbance offset coefficient of the i th test mode are all zero, indicating that all test modes are qualified, a test qualified group is generated; otherwise, a first test command strategy and a second test command strategy are correspondingly screened and generated, the first test command strategy is used for regulating a single early warning instruction, and the second test command strategy is used for associatively generating a coordinated disorder risk coefficient The post-evaluation obtains a corresponding risk level of synergistic imbalance.

[0008] Further, the debugging mapping modeling module comprises: A device identification unit is configured to identify and label constituent devices of the hydro-turbine and governor system, collect information including device unique number, installation position, debugging number and interface control type through two-dimensional code / radio frequency tag scanning, control system device code analysis and historical operation data retrieval, and establish a device debugging identification table; A structure parameter extraction unit is configured to call structure data table and historical debugging template of the hydro-turbine and governor system according to the identified device number, extract corresponding structure parameters and action constraint information, including maximum opening of guide vane, opening adjustment rate range, main shaft rotational inertia, governor response delay range and oil pressure feedback sensitivity, generate a debugging constraint parameter set of each device, and establish a debugging function sub-region model according to the device debugging identification table and the corresponding structure parameters and action constraint information; A debugging region calibration unit is configured to identify device physical connection logic diagram according to device number, structure relationship and pipe connectivity of the hydro-turbine and governor system, divide a plurality of three-dimensional debugging function sub-region models of debugging function sub-regions, and establish, including a speed-up response debugging region, a steady-state load adjustment region, a guide vane linkage sensitivity debugging region and a jump impact test region, and perform region calibration and color coding in the three-dimensional debugging function sub-region model.

[0009] Further, the data stored in the test working condition database comprises: In different test modes, the acquired data includes hydro-turbine main shaft vibration data sequence, hydro-turbine main shaft speed sequence, response angle sequence of guide vane execution structure, target guide vane instruction sequence, pressure response data sequence in the hydro-turbine main flow passage, tail water level response sequence before disturbance and tail water level response sequence after disturbance.

[0010] Further, the effect identification module comprises a shaft vibration identification unit configured to: extract the hydro-turbine main shaft vibration data sequence in the i-th test mode from the test working condition database; identify the resonance peak frequency fr based on the FFT spectrum analysis method, and construct the critical resonance coefficient of the i-th test mode in combination with the main shaft speed change curve ; The specific acquisition method of the critical resonance coefficient is as follows: Vibration sensors or acceleration sensors are installed on the bearing housing or journal of the turbine main shaft to collect the turbine main shaft vibration data sequence in real time during the test process at a set sampling frequency. The turbine main shaft vibration data sequence is the instantaneous vibration response signal within a continuous time window, and the sampling duration covers each test mode stage. After performing DC drift removal, windowing, overlapping segmented averaging, and noise filtering on the vibration data sequence of the turbine main shaft, a fast Fourier transform is performed on the preprocessed vibration data sequence to obtain the spectral amplitude function, i.e., the relationship between vibration amplitude and frequency. Then, a spectrum is obtained, and the main peak frequency with the largest amplitude is identified in the spectrum, i.e., the main shaft vibration spectrum resonance peak frequency fr. At the same time, the maximum vibration amplitude Apeak corresponding to the main shaft vibration spectrum resonance peak frequency fr is recorded for resonance intensity assessment. In the process of shaft vibration identification, to avoid misjudgment, a clear criterion for determining the presence or absence of resonance is set. This criterion is used to determine whether the i-th test mode has entered the resonance region and whether it is necessary to calculate or mark the critical resonance coefficient of the i-th test mode. ; The critical resonance coefficient Obtain it using the following steps: Step S11: Extract the resonant peak frequency fr of the spindle vibration spectrum and the maximum vibration amplitude Apeak. Set a preset discrimination threshold Athresh and compare the maximum vibration amplitude Apeak with the discrimination threshold Athresh to determine whether structural resonance exists. If Apeak is greater than or equal to the discrimination threshold Athresh, structural resonance is considered to exist, and the first acquisition command is triggered. If Apeak is less than the discrimination threshold Athresh, structural resonance is considered not to exist. At this time, mark the critical resonance coefficient of the i-th test mode. It equals zero; Step S12: Receive the first acquisition command, extract the turbine main shaft speed sequence from the test condition database, and plot its time-varying curve. Further determine whether the main shaft speed curve has a resonance mode order at a certain moment. If it matches, the resonance frequency is considered to be consistent with the critical speed of the structure, thus establishing the resonance crossing condition. Calculate and obtain the critical speed under the i-th test mode. ; Step S13: Combine the maximum vibration amplitude Apeak obtained in steps S11 and S12 with the critical rotational speed under the i-th test mode. Calculate the critical resonance coefficient for the i-th test mode. ; Step S14: Preset the critical point resonance threshold Cthresh, and set the critical resonance coefficient of the i-th test mode. The comparison is performed with the critical resonance threshold Cthresh. If... ≥ Cthresh, indicating that the vibration growth of the resonance section of the hydraulic turbine exceeds the critical point, there is a risk of inducing periodic swing or jump of the main shaft of the hydraulic turbine, triggering the first early warning instruction; if < Cthresh, indicating that the vibration growth of the resonance section of the hydraulic turbine is within a safe range, and monitoring is continued.

[0011] Further, the effect recognition module further comprises a guide vane response recognition unit, configured to: extract the response angle sequence of the guide vane execution structure under the ith test mode and the target guide vane instruction sequence, recognize the time lag between the adjustment instruction and the guide vane response, and construct the guide vane lag response coefficient under the ith test mode ; The guide vane lag response coefficient is obtained by the following steps: Step S21: In the ith test mode, sensors are arranged on the guide vane execution structure of the hydraulic turbine to collect the response angle sequence of the guide vane execution structure, and the target guide vane instruction sequence is extracted from the speed regulation system control end at the same time, so as to obtain the time sequence data of the actual response curve and the target instruction curve; Step S22: Align and compare the actual response curve and the target instruction curve, and extract the response lag time Δt between the two by cross-correlation analysis or zero-crossing time delay analysis method; Step S23: A reference time window width Tref is preset, and the guide vane lag response coefficient under the ith test mode is calculated: ; Step S24: A lag judgment threshold Dthresh is set, if ≥ Dthresh, it is considered that there is a risk of adjustment response lag, triggering the second early warning instruction; if <Dthresh, it is considered that the guide vane response is normal, and at this time the guide vane lag response coefficient under the ith test mode is marked as zero; the guide vane lag response coefficient is used for transverse comparison of the response sensitivity and structural adaptability of the adjustment system under different test modes.

[0012] Further, the effect recognition module further comprises a water hammer analysis unit, configured to: for collecting the pressure fluctuation signal in the guide vane, spiral case or draft tube of the hydraulic turbine under the ith test mode, identifying the characteristics of the sharp change of pressure, and constructing the water hammer intensity coefficient of the ith test mode ; The water hammer intensity coefficient is obtained by the following steps: Step S31: Real-time acquisition of pressure response data sequence in the main flow passage of the hydraulic turbine by laying dynamic pressure sensors during the test process, and the sampling frequency satisfies >1 kHz; Step S32: High-pass filtering, normalization processing and differential transformation are performed on the pressure response data sequence in the main flow passage of the hydraulic turbine, and the pressure mean value Pref is calculated; Step S33: A detection time window is set before and after the quick closure event of the guide vane, and the pressure step value ΔP in the window is calculated; Step S34: The water hammer intensity coefficient of the i-th test mode is calculated by the following formula: ; Step S35: A water hammer judgment threshold Wthresh is set, if ≥Wthresh, it is judged that there is obvious water hammer risk, and a third early warning instruction is triggered; if <Wthresh, the water hammer intensity coefficient is marked as zero; the water hammer intensity coefficient is used to evaluate the fluid inertia response characteristics of the system in the quick regulation process; The effect recognition module further includes a disturbance offset analysis unit, which is configured to: acquire the response curve of the system flow, opening or power signal under the i-th test mode when being excited by a disturbance, recognize the steady-state offset degree, and construct the hydraulic disturbance offset coefficient under the i-th test mode; The hydraulic disturbance offset coefficient is acquired by the following steps: Step S41: A disturbance variable with a set amplitude is introduced during the test process, and the tail water level before and after the disturbance is synchronously acquired; Step S42: The sliding average and steady-state extraction analysis are performed on the tail water level disturbance response sequence, the sliding average algorithm is used to extract the steady-state tail water level H0 before the disturbance from the tail water level response sequence before the disturbance, and the sliding average algorithm is used to extract the new steady-state tail water level H1 after the disturbance from the tail water level response sequence after the end of the disturbance; wherein the length of the steady-state extraction window is set to 3-5 seconds before the disturbance and after the disturbance; Step S43: The hydraulic disturbance offset coefficient is defined as the tail water level offset rate caused by the disturbance: ; Step S44: A disturbance offset threshold Pthresh is set, if ≥Pthresh, it indicates that the system is sensitive to small disturbances, and there is a risk of structural regulation lag or dynamic coupling problem, and a fourth early warning instruction is triggered; if <Pthresh, it is considered that the response is controllable; the hydraulic disturbance offset coefficient Used to evaluate the offset compensation capability of structural control systems under disturbed environments.

[0013] Furthermore, the test command module includes a first screening unit, used for: Summarize the critical resonance coefficients of the i-th test mode Guide vane hysteresis response coefficient Water hammer intensity coefficient and hydraulic disturbance offset coefficient The value and the triggered first, second, third, and fourth warning commands; when the critical resonance coefficient of the i-th test mode... Guide vane hysteresis response coefficient Water hammer intensity coefficient and hydraulic disturbance offset coefficient When all values ​​are zero, it indicates that the turbine and governor have passed the test under the same test mode; And statistically analyze the critical resonance coefficient of the i-th test mode in the no-load mode, loaded mode, speed-up mode, and load jump mode. Guide vane hysteresis response coefficient Water hammer intensity coefficient and hydraulic disturbance offset coefficient When all values ​​are zero, it indicates that all test modes, the turbine and governor have passed the test, and a test pass group is generated.

[0014] Furthermore, the test command module also includes a second screening unit, used for: If any one of the first, second, third, or fourth warning instructions exists under any test mode, it indicates that there is a test risk under the i-th test mode. The first screening unit will generate the first test command strategy based on the corresponding test results. In response to the first warning instruction, a first strategy is generated, including: If Cthresh≤ When ≤Cthresh×120%, extend the frequency scanning range by 10% and encrypt the frequency scanning interval; If Cthresh × 120% < When ≤Cthresh×150%, increase the modal detection time window by 20%, and adjust the sweep frequency start frequency to avoid the resonance region; like When Cthresh reaches 150%, the test mode is stopped, "Structural resonance risk fault" is output, and manual verification is notified. In response to the second warning instruction, a second strategy is generated, including: If Dthresh≤ When ≤Dthresh×120%, reduce the target instruction slope by 10-20%, and observe the improvement of the hysteresis; When Dthresh×120% When ≤Dthresh×150%, reduce the target instruction slope by 21-30%, and observe the improvement of the hysteresis; When Dthresh×150% When ≥Dthresh×150%, stop the test mode, output the abnormal response risk of the execution structure, and notify the manual verification; For the third early warning instruction, a third strategy is generated, including: When Wthresh≤ When ≤Wthresh×120%, reduce the guide vane shutdown speed by 10%, and extend the adjustment instruction buffer; When Wthresh× When <Wji≤Wthresh×150%, enable the throttling buffer working condition, and compensate the pressurized tail water flow; When Wthresh×150% When ≥Wthresh×150%, stop the test mode, output the strong water hammer risk, and optimize the shutdown rhythm or add a buffer valve; For the fourth early warning instruction, a fourth strategy is generated, including: When Pthresh≤ When ≤Pthresh×120%, repeat the test disturbance three times, and take the median to eliminate the instantaneous offset error; When Pthresh×120% When ≤Pthresh×150%, switch to a weaker disturbance mode, reduce the disturbance input amplitude by 20%, and recalculate the offset curve; When Pthresh×150% When ≥Pthresh×150%, stop the test mode, output the disturbance adaptability risk, and suggest to adjust the speed feedback gain or the structure parameter again.

[0015] Further, the test command module further includes a third screening unit and an associated unit; The third screening unit is configured to, if any two or more of the first early warning instruction, the second early warning instruction, the third early warning instruction, or the fourth early warning instruction exist in any one test mode, indicate that the water turbine and the governor in the ith test mode have a multi-source coupling abnormality, a collaborative disorder risk exists between the structure dynamic characteristics and the control response, and a second test command strategy is generated; The associated unit is configured to extract the critical resonance coefficient of the ith test mode , the guide vane hysteresis response coefficient of the ith test mode The water hammer intensity coefficient of the i-th test mode and the hydraulic disturbance offset coefficient under the i-th test mode After dimensionless processing, the risk coefficient of coordination mismatch in the i-th test mode is calculated using a weighted method. .

[0016] Furthermore, the test command module also includes a disharmony risk level assessment unit, used for: The threshold value for the mismatch risk level is preset X, and the risk coefficient of the collaborative mismatch in the i-th test mode is set. The corresponding coordination disorder risk level is obtained by comparing and evaluating the disorder risk level with the disorder risk level threshold X, including: like When <X, the first coordination misalignment risk level is generated, indicating that there is a slight risk of coordination misalignment. The first coordination execution strategy is generated, including: all disturbance input amplitudes are uniformly reduced by 10%, guide vane response speed is uniformly reduced by 10%, frequency scan start frequency is offset by 5%, resonance point is avoided, and control feedback gain value is attenuated by 5% and readjusted adaptively. If X≤ When ≤X×120%, a second coordination misalignment risk level is generated, indicating a moderate risk of coordination misalignment. A second coordination execution strategy is generated, including: stopping the current test mode batch, delaying the control output feedback timing by 20ms to maintain closed-loop consistency, reducing the disturbance amplitude by 20%, increasing the control feedback delay by 15%, reducing the maximum opening of the guide vane adjustment by 10%, shifting the frequency starting point by 10%, and expanding the modal window by 20%, and then retesting. like When the value is greater than X×120%, a third coordination misalignment risk level is generated, indicating a high risk of coordinated operation. A third coordinated execution strategy is then generated, including: immediately terminating all current tests, blocking, control feedback, and structural parameter reconstruction; switching to a mode where the structure and regulator are separated; then separating the turbine's individual structure and governor; performing command output tests on the turbine's individual structure and governor under no physical structural load; if the structural response is abnormal, further locating the damaged component and replacing and repairing it accordingly; after repair, re-performing the turbine structure test and governor closed-loop commissioning; and updating the critical resonance coefficient of the i-th test mode. The guide vane hysteresis response coefficient under the i-th test mode The water hammer intensity coefficient of the i-th test mode and the hydraulic disturbance offset coefficient under the i-th test mode When the new round of testing reaches zero for all values, a structural repair qualification report is generated and summarized in the test qualification group.

[0017] Compared with existing technologies, the advantages of this invention are: Through the debugging mapping modeling module, the system can build a three-dimensional functional sub-region model and establish a multi-test mode working condition database based on the physical connection relationship between the water turbine and the governor and the debugging parameters, providing basic data support for systematic testing. Through the effect identification module, the system can construct and determine key indicators (such as critical resonance coefficient, guide vane lag response coefficient, water hammer intensity coefficient, hydraulic disturbance offset coefficient) under each test mode, automatically identify problems such as resonance effect, guide vane hysteresis, water hammer anomaly and disturbance offset, and issue corresponding warning instructions, realizing a closed-loop link from "phenomenon identification" to "cause tracing". Through the test command module, not only can it judge whether a single test is qualified, but it can further calculate the collaborative misalignment risk coefficient Z1i under the i-th test mode, and accordingly evaluate the risk level among collaborative effects, supporting the intelligent adjustment of test strategies and improving the safety and scientificity of debugging. The platform covers multiple typical test modes such as no-load, load-carrying, speed-up and load jump, and dynamically generates the first and second test command strategies in combination with the evaluation results of real-time effect indicators, realizing intelligent hierarchical response and intervention in the debugging process, and improving the debugging efficiency and reliability. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a principle block diagram of an intelligent command and test integrated system for hydropower station commissioning. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0019] It should be noted that relational terms such as "first" and "second" 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 "comprising", "including" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising one..." does not exclude the existence of additional identical elements in the process, method, article or device including the element.

[0020] The features and performance of the present invention will be further described in detail below in conjunction with the embodiments.

[0021] Embodiment 1 The water turbine and the governor are crucial core equipment in a hydropower station, and their operating performance directly relates to the overall regulating ability, safety and power generation efficiency of the power station. After the construction or major overhaul of a hydropower station, a series of commissioning and performance tests must be carried out on the water turbine and its governing system to verify whether the equipment status meets the design and operating requirements.

[0022] In the conventional technology, the commissioning of the hydraulic turbine and the governor usually relies on a large amount of manual experience, discrete instrument testing and multi-specialty collaborative operation. The conventional mode has the following main defects: 1. Dispersed testing system and low integration: The conventional testing process often relies on multiple independent devices, such as vibration sensors, tachometers, guide vane angle measuring instruments and the like, lacks a unified coordinated platform, and thus leads to poor data synchronization and difficult information integration.

[0023] 2. Insufficient identification capability for resonance effect, guide vane hysteresis and response lag and disturbance effect: Due to the complex dynamic responses of the hydraulic turbine under different operating conditions, such as shaft system resonance, impeller oscillation and offset after system disturbance when performing step response or sudden load testing, the governor has nonlinear characteristics such as guide vane action hysteresis or backlash during start-up and transition process. In the conventional commissioning process, the effects of resonance, guide vane hysteresis, water hammer and disturbance response are often tested separately, and there is a lack of linkage observation means under unified conditions. For example, in the rapid load disturbance offset testing, water hammer and shaft vibration may be induced at the same time, but the conventional testing system cannot simultaneously capture and analyze the coordinated response of various physical quantities in the same time period and under the same testing mode, which leads to one-sided judgment of the system stability and existence of coordinated imbalance risk identification blind area. Especially under complex regulation conditions, the nonlinear coupling relationship between various effects is more prominent, and if a unified testing platform is not used for closed-loop identification and quantitative analysis, the system risk may be underestimated.

[0024] Therefore, based on the above problems, the embodiment provides an intelligent command and testing integrated system for commissioning of a hydropower station. The system can construct a three-dimensional functional sub-region model and establish a multi-testing mode condition database based on the physical connection relationship and the commissioning parameters of the hydraulic turbine and the governor. Through an effect identification module, the system can construct and determine key indicators (such as critical resonance coefficient, guide vane lag response coefficient, water hammer intensity coefficient and water power disturbance offset coefficient) under each testing mode, automatically identify whether there is resonance effect, guide vane hysteresis, water hammer abnormality and disturbance offset problem, and issue corresponding warning instructions, so as to realize the closed-loop link from "phenomenon identification" to "reason tracing". Not only whether a single test is qualified can be judged, but also the coordinated imbalance risk coefficient under the i-th testing mode can be further calculated , and the risk level between the coordinated effects is evaluated according to the risk coefficient, so as to support intelligent adjustment of the testing strategy In the embodiment, specifically, refer to Figure 1 , an intelligent command and testing integrated system for commissioning of a hydropower station, comprising: The debugging mapping modeling module is used for identifying and registering key equipment of the hydraulic turbine and the governor system, extracting structural parameters and debugging constraint information, and establishing a three-dimensional debugging function sub-region model based on physical connection relationship of the equipment; and structural parameters, hydraulic connection parameters and control response parameters of the hydraulic turbine and the governor in a test mode are extracted, and a test working condition database is established; the test mode includes an idle load mode, a loaded mode, a speed-up mode and a load jump mode; The effect identification module is used for constructing critical resonance coefficients , guide vane lag response coefficients , water hammer strength coefficients and water force disturbance offset coefficients of the i-th test mode based on the test working condition database, and respectively judging to identify linkage effect types, including resonance critical effect, guide vane lag response, water hammer impact anomaly and water force disturbance offset; if existing, corresponding early warning instructions are generated; The test command module is used for counting the values of the critical resonance coefficients , the guide vane lag response coefficients , the water hammer strength coefficients and the water force disturbance offset coefficients of the i-th test mode in the idle load mode, the loaded mode, the speed-up mode and the load jump mode, and when all the values are zero, indicating that the test of the hydraulic turbine and the governor is qualified in all test modes, a test qualified group is generated; on the contrary, a first test command strategy and a second test command strategy are correspondingly screened and generated, the first test command strategy is used for regulating and controlling a single early warning instruction, and the second test command strategy is used for associating to generate a synergistic disorder risk coefficient of the i-th test mode, and a corresponding synergistic disorder risk level is obtained after evaluation.

[0025] In the embodiment, specifically, the debugging mapping modeling module comprises: The equipment identification unit is used for identifying and labeling constituent equipment of the hydraulic turbine and the governor system, collecting information including equipment unique number, installation position, debugging number, interface control type through two-dimensional code / radio frequency tag scanning, control system equipment code analysis and historical operation data retrieval, and establishing an equipment debugging identification table; in the embodiment, it needs to be noted that the identified constituent equipment includes a guide vane assembly, a runner blade, a main shaft system, a bearing assembly, a governor oil pressure unit, a governor control cabinet, a guide vane transmission mechanism and a feedback signal assembly; The structure parameter extraction unit is configured to call a structure data table and a historical debugging template of the hydraulic turbine-governor system according to the identified equipment number, extract corresponding structure parameters and action constraint information, including a maximum opening of a guide vane, an opening adjustment rate range, a main shaft rotational inertia, a governor response delay range and an oil pressure feedback sensitivity, generate a debugging constraint parameter set of each equipment, and establish a debugging function sub-region model according to an equipment debugging identification table and the corresponding structure parameters and action constraint information. The debugging area calibration unit is configured to identify an equipment physical connection logic diagram according to the equipment number, structure relationship and pipeline connectivity of the hydraulic turbine-governor system, divide a plurality of debugging function sub-region three-dimensional debugging function sub-region models, and establish, including a speed-up response debugging area, a steady-state load adjustment area, a guide vane linkage sensitivity debugging area and a jump impact test area, and perform area calibration and color coding in the three-dimensional debugging function sub-region model.

[0026] In this embodiment, specifically, the data stored in the test working condition database includes: In different test modes, the acquired hydraulic turbine main shaft vibration data sequence, the hydraulic turbine main shaft speed sequence, the response angle sequence of the guide vane execution structure, the target guide vane instruction sequence, the pressure response data sequence in the hydraulic turbine main flow passage, the tail water level response sequence before disturbance and the tail water level response sequence after disturbance are collected.

[0027] In this embodiment, specifically, the effect identification module includes a shaft vibration identification unit, configured to: extract the hydraulic turbine main shaft vibration data sequence in the i-th test mode from the test working condition database; identify a resonance peak frequency fr based on an FFT frequency spectrum analysis method, and construct a critical resonance coefficient of the i-th test mode in combination with a main shaft speed change curve ; The specific acquisition method of the critical resonance coefficient is as follows: When the actual speed of the main shaft equals a certain order of natural frequency of the structure, the corresponding critical speed of the main shaft system in the speed-up process will excite structure resonance; First, a vibration sensor or an acceleration sensor is arranged at a bearing seat or a shaft neck of the hydraulic turbine main shaft, and the main shaft vibration data sequence of the hydraulic turbine in the test process is collected in real time at a set sampling frequency, the main shaft vibration data sequence of the hydraulic turbine is an instantaneous vibration response signal in a continuous time window, and the sampling time length covers each test mode stage. After the water turbine main shaft vibration data sequence is subjected to DC drift removal, windowing processing, overlapping segment average processing and noise filtering, the pre-processed vibration data sequence is subjected to fast Fourier transform, a frequency spectrum amplitude function, i.e. a relationship between vibration amplitude and frequency, is obtained, a frequency spectrum diagram is obtained, a main peak frequency with the maximum amplitude in the frequency spectrum diagram, i.e. a main shaft vibration spectrum resonance peak frequency fr, is identified, and a maximum vibration amplitude Apeak corresponding to the main shaft vibration spectrum resonance peak frequency fr is recorded for resonance intensity evaluation; In the shaft vibration identification process, to avoid misjudgment, a clear criterion for determining whether resonance exists is set, which is used to determine whether the i th test mode enters the resonance region and whether the critical resonance coefficient of the i th test mode needs to be calculated or marked ; The critical resonance coefficient is obtained by the following steps: Step S11: Extract the main shaft vibration spectrum resonance peak frequency fr and the maximum vibration amplitude Apeak, preset a discrimination threshold Athresh, and compare the maximum vibration amplitude Apeak with the discrimination threshold Athresh to determine whether a structural resonance phenomenon exists. When Apeak is greater than or equal to the discrimination threshold Athresh, it is considered that a structural resonance phenomenon exists, and a first acquisition instruction is triggered. When Apeak is less than the discrimination threshold Athresh, it is considered that a structural resonance phenomenon does not exist, and at this time, the critical resonance coefficient of the i th test mode is marked as zero. Step S12: Receive the first acquisition instruction, extract the water turbine main shaft speed sequence in the test working condition database, and draw a curve of the main shaft speed sequence varying with time, and further determine whether the main shaft speed curve has a resonance mode order at a certain time. If it matches, it is considered that the resonance frequency is consistent with the structural critical speed, the through-resonance condition is established, and the critical speed under the i th test mode is calculated and obtained . Step S13: The maximum vibration amplitude Apeak obtained in steps S11 and S12 and the critical speed under the i th test mode are combined to calculate and obtain the critical resonance coefficient of the i th test mode . Step S14: A critical point resonance threshold Cthresh is preset, and the critical resonance coefficient of the i th test mode is compared with the critical point resonance threshold Cthresh. If ≥ Cthresh, it indicates that the vibration growth of the water turbine resonance section exceeds the critical point, there is a risk of inducing periodic swing or jumping of the water turbine main shaft to cause material fatigue, and a first warning instruction is triggered. If < Cthresh, it indicates that the vibration growth of the water turbine resonance section belongs to a safe range, and monitoring is continued.

[0028] In the embodiment, specifically, the effect recognition module further includes a guide vane response recognition unit, configured to: extract the response angle sequence of the guide vane execution structure in the ith test mode and the target guide vane instruction sequence, recognize the time lag between the adjustment instruction and the guide vane response, and construct the guide vane lag response coefficient in the ith test mode ; the guide vane lag response coefficient is obtained by the following steps: Step S21: In the ith test mode, sensors are arranged on the guide vane execution structure of the hydraulic turbine to collect the response angle sequence of the guide vane execution structure, and the target guide vane instruction sequence is extracted from the control end of the speed regulation system synchronously to obtain the time sequence data of the actual response curve and the target instruction curve; Step S22: The actual response curve and the target instruction curve are aligned and compared, and the response lag time Δt between the two is extracted by cross-correlation analysis or zero-crossing time delay analysis method; Step S23: A reference time window width Tref is preset, and the guide vane lag response coefficient in the ith test mode is calculated: ; Step S24: A lag judgment threshold Dthresh is set, if ≥Dthresh, it is considered that there is a risk of adjustment response lag, and a second early warning instruction is triggered; if <Dthresh, it is considered that the guide vane response is normal, and the guide vane lag response coefficient in the ith test mode is marked as zero; the guide vane lag response coefficient is used for transverse comparison of the response sensitivity and structural adaptability of the adjustment system in different test modes.

[0029] In the embodiment, specifically, the effect recognition module further includes a water hammer analysis unit, configured to: for collecting the pressure fluctuation signal in the guide vane, spiral case or draft tube of the hydraulic turbine in the ith test mode, recognizing the pressure sharp jump feature, and constructing the water hammer intensity coefficient of the ith test mode ; the water hammer intensity coefficient is obtained by the following steps: Step S31: In the test process, dynamic pressure sensors are arranged to collect the pressure response data sequence in the main flow passage of the hydraulic turbine in real time, and the sampling frequency satisfies >1kHz; Step S32: The pressure response data sequence in the main flow passage of the hydraulic turbine is subjected to high-pass filtering, normalization processing and differential transformation, and the pressure mean value Pref is calculated; Step S33: Set a detection time window before and after the test guide vane quick shutdown event, and calculate the pressure step value ΔP in the window; Step S34: The water hammer intensity coefficient of the i-th test mode is calculated by the following formula: ; Step S35: Set a water hammer judgment threshold Wthresh, if ≥ Wthresh, it is determined that there is a significant water hammer risk, and a third early warning instruction is triggered; if <Wthresh, the water hammer intensity coefficient is marked as zero; the water hammer intensity coefficient is used to evaluate the fluid inertia response characteristics of the system during the quick regulation process; The effect recognition module further includes a disturbance offset analysis unit, configured to: collect the response curve of the system flow, opening or power signal when subjected to a disturbance excitation in the i-th test mode, recognize the steady-state offset degree, and construct a hydraulic disturbance offset coefficient in the i-th test mode; The hydraulic disturbance offset coefficient is obtained by the following steps: Step S41: Introduce a disturbance variable of a set amplitude during the test, and synchronously collect the tail water level before and after the disturbance; specifically, prepare the equipment before the test, set the guide vane opening real-time collection device, active power signal collection equipment and ultrasonic water level meter, introduce a disturbance variable of a set amplitude during the test, and collect and obtain the tail water level response sequence before the disturbance and the tail water level response sequence after the end of the disturbance; the disturbance variable of a set amplitude is set as: guide vane opening change Δθ = ±1% or ±2%; the disturbance duration is set to be greater than 5 seconds, and a collection observation window is set, which is 5 seconds before the disturbance and 20 seconds after the disturbance, for a total of at least 25 seconds; Step S42: Perform sliding average and steady-state extraction analysis on the tail water level disturbance response sequence, extract the steady-state tail water level H0 before the disturbance by using a sliding average algorithm on the tail water level response sequence before the disturbance, and extract the new steady-state tail water level H1 after the disturbance by using a sliding average algorithm on the tail water level response sequence after the end of the disturbance; wherein the steady-state extraction window length is set to be 3-5 seconds before the disturbance and after the disturbance; Step S43: The hydraulic disturbance offset coefficient is defined as the tail water level offset rate caused by the disturbance: ; wherein H1 represents the 3-second average before the disturbance, and H0 represents the last 3-second average after the disturbance; Step S44: Set a disturbance offset threshold Pthresh, if ≥ Pthresh, it indicates that the system is sensitive to small disturbances, there is a risk of structural regulation lag or dynamic coupling problem, and a fourth early warning instruction is triggered; if <Pthresh, regarded as response controllable; hydraulic disturbance offset coefficient Used to evaluate the offset compensation ability of the structural control system in a disturbed environment.

[0030] In this embodiment, specifically, the test command module includes a first screening unit for: Summarize the critical resonance coefficient of the i-th test mode 、the guide vane lag response coefficient 、the water hammer intensity coefficient and the hydraulic disturbance offset coefficient <## values, as well as the triggered first warning instruction, second warning instruction, third warning instruction, and fourth warning instruction; when the critical resonance coefficient of the i-th test mode 、the guide vane lag response coefficient 、the water hammer intensity coefficient and the hydraulic disturbance offset coefficient values are all zero, it means that under the same test mode, the test of the water turbine and the governor is qualified; And count the critical resonance coefficient of the i-th test mode in the no-load mode, load mode, speed-up mode, and load jump mode <00##00310>、the guide vane lag response coefficient 、the water hammer intensity coefficient and the hydraulic disturbance offset coefficient values are all zero, indicating that for all test modes, the test of the water turbine and the governor is qualified, and generate a test qualified group.

[0031] In this embodiment, specifically, the test command module further includes a second screening unit for: Summarize that in any one test mode, if there is any one of the first warning instruction, second warning instruction, third warning instruction, or fourth warning instruction, it means that there is one test risk in the i-th test mode, and the first screening unit generates a first test command strategy for the corresponding test result; For the first warning instruction, generate a first strategy, including: If Cthresh ≤ ≤ Cthresh × 120%, extend the frequency scan range by 1##0%, and encrypt the scan frequency interval; <000032##0>If Cthresh × 120% < ≤ Cthresh × 150%, increase the modal detection time window by 20%, and at the same time adjust the starting frequency of the frequency scan to avoid the resonance area; If [[ID=5##2]] > Cthresh × 150%, stop this test mode, output "structural resonance risk failure", and notify the operator for verification; For the second early warning instruction, a second strategy is generated, including: If Dthresh≤ When Dthresh×120%≤ If Dthresh×120% When Dthresh×150%≤ If Dthresh×150% When Dthresh×150% For the third early warning instruction, a third strategy is generated, including: If Wthresh≤ When Wthresh×120%≤ If Wthresh× When Wthresh×150%≤ If Wthresh×150% When Wthresh×150% For the fourth early warning instruction, a fourth strategy is generated, including: If Pthresh≤ When Pthresh×120%≤ If Pthresh×120% When Pthresh×150%≤ If Pthresh×150% When Pthresh×150%

[0032] In this embodiment, specifically, the test command module further includes a third screening unit and an associated unit; The third screening unit is configured to, if any two or more of the first early warning instruction, the second early warning instruction, the third early warning instruction, or the fourth early warning instruction exist in any one test mode, indicate that the hydraulic turbine and the governor in the ith test mode have a multi-source coupling abnormality, and the structure dynamic characteristic and the control response have a collaborative disorder risk, and generate a second test command strategy. The associated unit is configured to extract a critical resonance coefficient of the ith test mode , a guide vane lag response coefficient in the ith test mode , a water hammer intensity coefficient of the ith test mode , and a hydraulic disturbance offset coefficient in the ith test mode After dimensionless processing, the cooperative disorder risk coefficient in the ith test mode is obtained by weighted calculation .

[0033] In this embodiment, specifically, the test command module further includes a disorder risk level evaluation unit, configured to: preset a disorder risk level threshold X, and compare the cooperative disorder risk coefficient in the ith test mode with the disorder risk level threshold X to obtain a corresponding cooperative disorder risk level, including: if X, a first cooperative disorder risk level is generated, indicating that there is a mild linkage coordination risk, and a first linkage execution strategy is generated, including: uniformly reducing all disturbance input amplitudes by 10%, uniformly reducing guide vane response speed by 10%, offsetting starting frequency of frequency scanning by 5% to avoid resonance points, and attenuating control feedback gain value by 5% to re-adaptively adjust; if X≤ X*120%, a second cooperative disorder risk level is generated, indicating that there is a moderate linkage coordination risk, and a second linkage execution strategy is generated, including: stopping the current test mode batch, delaying control output feedback timing by 20 ms to maintain closed-loop consistency, reducing disturbance amplitude by 20%, increasing control feedback delay by 15%, reducing maximum opening degree of guide vane adjustment by 10%, offsetting frequency starting point by 10%, and expanding modal window by 20%, and then retesting after the above operations; if X*120%, a third cooperative disorder risk level is generated, indicating that there is a high linkage coordination risk, and a third linkage execution strategy is generated, including: immediately terminating all current tests, blocking control feedback and structural parameter reconstruction, and switching to separate structures and governors, separately testing the structure and the governor of the hydraulic turbine without physical structure load, further positioning damaged components if the structural response is abnormal, and performing corresponding structural replacement and repair, and after the repair is completed, retesting the structure of the hydraulic turbine and the linkage of the governor, and updating the critical resonance coefficient of the ith test mode , the guide vane lag response coefficient in the ith test mode , the water hammer intensity coefficient of the ith test mode , and the hydraulic disturbance offset coefficient in the ith test mode When the new round of testing reaches all zeros, a structure repair qualified report is generated and summarized to the test qualified group.

[0034] In this embodiment, by debugging the mapping modeling module, the system can construct a three-dimensional functional sub-region model and establish a multi-test mode working condition database based on the physical connection relationship and debugging parameters of the hydraulic turbine and the governor, providing basic data support for systematic testing. Through the effect identification module, the system can construct and determine key indicators (such as critical resonance coefficient, guide vane lag response coefficient, water hammer intensity coefficient, and hydraulic disturbance offset coefficient) under each test mode, automatically identify whether there are resonance effects, guide vane lag, water hammer abnormalities, and disturbance offset problems, and issue corresponding warning instructions, realizing a closed-loop link from "phenomenon identification" to "cause tracing". Through the test command module, not only can it be determined whether a single test is qualified, but also the coordinated disorder risk coefficient under the i-th test mode can be further calculated , and the risk level between the coordinated effects is evaluated accordingly, supporting intelligent adjustment of the test strategy and improving the safety and scientificity of the debugging. The platform covers multiple typical test modes such as no-load, load, speed-up, and load jump, dynamically generates the first and second test command strategies in combination with real-time effect index evaluation results, realizes intelligent hierarchical response and intervention in the debugging process, and improves the debugging efficiency and reliability.

[0035] Embodiment Two This embodiment is an explanation and description of Embodiment One, please refer to Figure 1 , specifically, the debugging mapping modeling module includes a device identification unit, a structure parameter extraction unit, and a debugging area calibration unit; The device identification unit is used to identify and label the constituent devices of the hydraulic turbine and governor system, collect information including device unique number, installation location, debugging number, and interface control type through two-dimensional code / radio frequency tag scanning, control system device code analysis, and historical operation data retrieval, and establish a device debugging identification table; this dynamic parameter extraction mechanism based on device attributes makes subsequent test working condition modeling more targeted and engineering adaptable.

[0036] The identified constituent devices include guide vane assembly (number GL-i), runner blade (number FR-i), main shaft system (number MS-i), bearing assembly (number BR-i), governor oil pressure unit (number GP-i), governor control cabinet (number GC-i), guide vane transmission mechanism (number DM-i), and feedback signal assembly (number FS-i); The structure parameter extraction unit is configured to call a structure data table and a historical debugging template of the hydraulic turbine-governor system according to the identified equipment number, extract corresponding structure parameters and action constraint information, including a maximum opening of a guide vane, an opening adjustment rate range, a main shaft rotational inertia, a governor response delay range and an oil pressure feedback sensitivity, generate a debugging constraint parameter set of each equipment, and establish a debugging function sub-region model according to an equipment debugging identification table and the corresponding structure parameters and action constraint information. The debugging area calibration unit is configured to identify an equipment physical connection logic diagram according to the equipment number, structure relationship and pipeline connectivity of the hydraulic turbine-governor system, divide a plurality of three-dimensional debugging function sub-region models of debugging function sub-regions, and establish, including a speed-up response debugging area (number TA-i), a steady-state load adjustment area (number TR-i), a guide vane linkage sensitivity debugging area (number TG-i) and a jump impact test area (number TJ-i), and perform area calibration and color coding in the three-dimensional debugging function sub-region model.

[0037] In this embodiment, the equipment identification unit can quickly complete the automatic identification, unique number and information input of key equipment in the hydraulic turbine and governor system by means of two-dimensional code / radio frequency tag scanning, control system equipment code analysis and historical data retrieval, etc., reducing the problems of missing items, code errors and information redundancy in the traditional manual identification mode. The debugging area calibration unit constructs typical debugging function sub-region models of speed-up response, steady-state load adjustment, guide vane linkage sensitivity and jump impact based on the equipment number and structure connection logic, and performs area division and color coding in three-dimensional space. This mechanism not only visually displays the function boundaries of each debugging sub-region, but also provides a basis for subsequent debugging strategy formulation, command logic partitioning and fault location. The combination of the three-dimensional debugging function sub-region model and the equipment logical connection diagram enables the test personnel to intuitively identify the corresponding physical area and associated equipment of each debugging task under a unified platform, solving the problem of poor matching between the "virtual test model" and the "actual equipment structure" in the traditional debugging process, and improving the controllability and response efficiency of the debugging.

[0038] Embodiment Three This embodiment is an explanation and description of Embodiment One. Please refer to Figure 1 Specifically, the test working condition database includes hydraulic turbine main shaft vibration data sequences, hydraulic turbine main shaft speed sequences, response angle sequences of guide vane execution structures, target guide vane instruction sequences, pressure response data sequences in the hydraulic turbine main flow channel, pre-disturbance tail water level response sequences and post-disturbance tail water level response sequences collected and acquired in different test modes.

[0039] Example: The hydraulic turbine main shaft vibration data sequence (unit: mm / s) is as shown in Table 1: Table 1 Water turbine main shaft vibration data sequence

[0040] Water turbine main shaft speed sequence (unit: r / min), as shown in Table 2: Table 2 Water turbine main shaft speed sequence

[0041] Response angle sequence of guide vane execution structure (unit: °), as shown in Table 3: Table 3 Response angle sequence of guide vane execution structure

[0042] Target guide vane instruction sequence of guide vane execution structure (unit: °), as shown in Table 4: Table 4 Target guide vane instruction sequence of guide vane execution structure

[0043] Pressure response data sequence in water turbine main flow passage (unit: MPa), as shown in Table 5: Table 5 Pressure response data sequence in water turbine main flow passage

[0044] Tail water level response sequence before disturbance (unit: m), as shown in Table 6: Table 6 Tail water level response sequence before disturbance

[0045] Tail water level response sequence after disturbance (unit: m), as shown in Table 7: Table 7 Tail water level response sequence after disturbance

[0046] In this embodiment, specifically, the effect recognition module includes a shaft vibration recognition unit, the shaft vibration recognition unit is used for extracting water turbine main shaft vibration data sequence in the i th test mode in the test working condition database, recognizing resonance peak frequency fr based on FFT spectrum analysis method, and combining main shaft speed change curve to construct critical resonance coefficient of the i th test mode : Corresponding to Table 1 and Table 2, vibration peak corresponding time 1.0 seconds→main shaft speed just close to 500 rpm; In 0.4-1.2 second interval, the speed gradually approaches and passes through the critical zone, forming a “resonance window”; Subsequently, the main shaft speed decreases, and the vibration also rapidly weakens.

[0047] When the actual speed of the main shaft equals to the natural frequency of the structure, the corresponding critical speed will excite the structure resonance, which will cause the vibration amplitude of the main shaft to increase significantly. This process is called passing through the critical speed. The resonance critical effect refers to the phenomenon that when the speed of the main shaft of a rotating device (such as a hydraulic turbine unit) approaches the natural frequency of the structure (i.e. the critical speed), the vibration of the main shaft will be significantly enhanced due to resonance, resulting in a dramatic amplification of the structural response. Long-term repeated excitation of resonance will cause fatigue accumulation of the main shaft, rotor, coupling, guide vane mechanism and other key components, leading to crack initiation and propagation, bearing overload and wear, and equipment fastener loosening or falling off.

[0048] Different test modes (such as no load, with load, speed up, jump, etc.) have different sensitivities to resonance response. By quantitatively evaluating the resonance behavior under each test mode, the sensitivity to resonance is compared, and the risk priority of commissioning is sorted and early warning is realized.

[0049] The shaft vibration recognition unit further comprises a resonance recognition and discrimination mechanism, which is used to identify whether there is a structure resonance phenomenon based on the FFT spectrum analysis result and the main shaft speed data under the ith test mode. Only when the spectrum amplitude of the identified resonance peak frequency exceeds the set significance threshold and there is a corresponding relationship with the resonance condition of the main shaft speed curve, it is considered that the ith test mode enters the critical resonance zone, triggering the calculation process of the critical resonance coefficient. If it is not triggered, it is marked as "no resonance" or assigned a value of zero.

[0050] The "critical section" refers to a dangerous "resonance section" when the main shaft speed of the hydraulic turbine approaches the structural critical speed during the speed-up process. In this section, the structure resonance may cause the mechanical vibration amplitude to increase rapidly. The "vibration increment caused by resonance" refers to the growth rate (or amount) of the vibration amplitude of the main shaft when passing through the critical speed. For example, near the critical point, the vibration may increase rapidly from 0.02 mm to 0.09 mm. This sharp amplification of amplitude is a characteristic manifestation of resonance.

[0051] First, through the vibration sensor or acceleration sensor arranged at the bearing seat or journal of the main shaft of the hydraulic turbine, the main shaft vibration data sequence of the hydraulic turbine during the test process is collected in real time at a set sampling frequency. The main shaft vibration data sequence of the hydraulic turbine is the instantaneous vibration response signal within a continuous time window, and the sampling duration covers each test mode stage. The vibration data sequence of the water turbine main shaft is subjected to DC drift removal, windowing, overlapping segment averaging and noise filtering. After the preprocessed vibration data sequence is subjected to fast Fourier transform, the frequency spectrum amplitude function, i.e. the relationship between the vibration amplitude and the frequency, is obtained. The frequency spectrum diagram is obtained, and the main peak frequency, i.e. the main shaft vibration spectrum resonance peak frequency fr, with the unit of Hz is identified in the frequency spectrum diagram. The maximum vibration amplitude Apeak corresponding to the main shaft vibration spectrum resonance peak frequency fr is recorded, and the user resonance intensity is evaluated. In the shaft vibration identification process, clear discrimination criteria for whether resonance exists are set to determine whether the i-th test mode enters the resonance region and whether the critical resonance coefficient of the i-th test mode needs to be calculated or marked . S11, the main shaft vibration spectrum resonance peak frequency fr and the maximum vibration amplitude Apeak are extracted, a preset discrimination threshold Athresh is set, and the maximum vibration amplitude Apeak is compared with the discrimination threshold Athresh to determine whether the structural resonance phenomenon exists. When Apeak is greater than or equal to the discrimination threshold Athresh, it is considered that the structural resonance phenomenon exists, and the first acquisition instruction is triggered. When Apeak is less than the discrimination threshold Athresh, it is considered that the structural resonance phenomenon does not exist. At this time, the critical resonance coefficient of the i-th test mode is marked as zero. The source of the discrimination threshold Athresh is as follows: the distribution range of the main shaft vibration amplitude under the normal operation state and the abnormal (structural resonance) state is extracted through statistical analysis of a large amount of water turbine operation and test data. A reasonable critical value is determined in combination with expert experience. The vibration limit values provided by the relevant industry standards of the water turbine and the equipment manufacturers, and the safety operation specifications of the unit structure are referred to. These specifications usually give the safety threshold range of the vibration amplitude.

[0052] S12, the first acquisition instruction is received, the water turbine main shaft speed sequence in the test working condition database is extracted, and the curve thereof changing with time is drawn. It is further determined whether the main shaft speed curve exists the following relationship at a certain time. The critical speed under the i-th test mode is calculated by the following formula :

[0053] Wherein, n represents the resonance mode order, which is set to 1. If it is matched, it is considered that the resonance frequency is consistent with the structural critical speed, and the resonance passing condition is established. S13, the maximum vibration amplitude Apeak and the critical speed under the i-th test mode obtained in S11 and S12 are combined. The critical resonance coefficient of the i-th test mode is calculated by the following formula :

[0054] wherein, represents the average vibration baseline value of the main shaft in the normal operation state; the critical resonance coefficient of the ith test mode : reflects the vibration increment caused by resonance in the critical section, and is used for cross-mode comparison after relative standardization; S14, preset a critical point resonance threshold Cthresh, and compare the critical resonance coefficient of the ith test mode with the critical point resonance threshold Cthresh; If ≥ Cthresh, it indicates that the vibration growth of the water turbine resonance section exceeds the critical point, and there is a risk of inducing "periodic swing" or "jump" of the water turbine main shaft to cause material fatigue, triggering the first warning instruction; if <Cthresh, it indicates that the vibration growth of the water turbine resonance section belongs to a safe range, and continues to be monitored.

[0055] The source of the critical point resonance threshold Cthresh is that, through statistical analysis of a large amount of water turbine vibration spectrum test data, the resonance coefficient distribution range of the key frequency points in the non-resonance state and the critical resonance state is extracted, and a reasonable critical judgment value is determined combined with the experience judgment of professional technicians. Referring to the relevant technical specifications of the water turbine industry, the performance parameters and safety operation standards provided by the equipment manufacturer, these specifications usually give the threshold interval of the critical resonance judgment. The threshold is used to effectively distinguish between the normal working state of the equipment and the structural resonance risk state, and to ensure the safety and stability of the unit operation.

[0056] In this embodiment, the main shaft vibration response recognition based on actual test working condition data is realized, which has higher field adaptability; through the matching analysis of the spectrum main peak amplitude and the critical speed, resonance misjudgment is effectively avoided; the quantization method of the standardized critical resonance coefficient is proposed, which is convenient for resonance intensity comparison across test modes; the early warning instruction can be triggered when the vibration risk exceeds the limit, which improves the response ability of the system to "periodic swing" or "material fatigue" hidden dangers; it is helpful to identify the structural resonance point in the water turbine debugging process, and guide to avoid the resonance region in the actual operation.

[0057] Embodiment Four This embodiment is an explanation and description in Embodiment One, please refer to Figure 1 , specifically, the effect recognition module further includes a guide vane response recognition unit, a water hammer analysis unit and a disturbance offset analysis unit; The guide vane response recognition unit is used to extract the response angle sequence of the guide vane execution structure under the ith test mode, identify the time lag between the adjustment instruction and the guide vane response, and construct the guide vane lag response coefficient of the ith test mode , the acquisition method comprising: S21, in the i-th test mode, synchronously arranging sensors on the guide vane actuating structure to collect a sequence of response angles of the guide vane actuating structure, and synchronously extracting a target guide vane instruction sequence from the control end of the governing system to obtain time sequence data of the actual response curve and the target instruction curve; S22, aligning and comparing the actual response curve and the target instruction curve, extracting the response lag time Δt between the two through cross-correlation analysis or zero-crossing time delay analysis method; S23, presetting a reference time window width Tref, and calculating a guide vane lag response coefficient: ; S24, setting a lag judgment threshold Dthresh, if ≥Dthresh, it is considered that there is a risk of adjustment response lag, and a second warning instruction is triggered; if <Dthresh, it is considered that the guide vane response is normal, and the guide vane lag response coefficient in the i-th test mode is marked as zero; the guide vane lag response coefficient is used for transverse comparison of the response sensitivity and structural adaptability of the governing system in different test modes. The guide vane lag response coefficient in the i-th test mode has the beneficial effect that it can be used for transverse comparison of the response sensitivity of the guide vane actuating mechanism in different test modes or adjustment schemes; it can guide the optimization of the governing system, for example, replacing the actuator or modifying the control logic in the condition of larger lag; it has the function of adjustment structure adaptability evaluation, which is particularly important in the scene of frequent start-stop or large load variation.

[0058] The source of the lag judgment threshold Dthresh is that, based on statistical analysis of a large amount of response data of the water turbine governing system, the lag coefficient distribution range when the normal adjustment response and the obvious lag phenomenon exist is extracted, and combined with the industry expert experience and the control system design requirement, a reasonable lag judgment critical value is determined. Referring to the water turbine governor performance specification, the control system response time standard and the safe operation guide, these standards usually clearly define the maximum allowed lag time or lag amplitude of the adjustment response. The threshold is used to accurately identify the adjustment system response lag risk, and to ensure the stability and adjustment efficiency of the governing system.

[0059] The water hammer analysis unit is used for collecting pressure fluctuation signals in the guide vane, spiral case or draft tube of the water turbine in the i-th test mode, identifying the characteristics of sharp pressure jump, and constructing a water hammer intensity coefficient of the i-th test mode, the acquisition method comprising: S31, in the test process, real-time collection of pressure response data sequences in the main flow passage of the water turbine through the arrangement of dynamic pressure sensors, and the sampling frequency satisfies >1kHz; S32. Perform high-pass filtering, normalization processing, and differential transformation on the pressure response data sequence in the main flow channel of the water turbine, and calculate the average pressure Pref; S33. Before and after the test of the rapid closing event of the guide vane, set the detection time window and calculate the pressure step value ΔP within the window; S34. The water hammer intensity coefficient Wji is calculated by the following formula: ; S35. Set the water hammer judgment threshold Wthresh. If Wji ≥ Wthresh, it is determined that there is an obvious water hammer risk and the third warning instruction is triggered; if <Wthresh, then mark as zero; the water hammer intensity coefficient is used to evaluate the fluid inertia response characteristics of the system during the rapid regulation process; The source of the water hammer judgment threshold Wthresh is as follows: Through the statistical analysis of the data of water hammer events during the operation and testing of a large number of water turbines, the amplitude range of water hammer pressure fluctuations under normal conditions and when water hammer occurs is extracted. Combining the experience of industry experts and the safety specifications of hydraulic machinery, a reasonable critical value of water hammer intensity is determined. Referring to relevant national or industry standards for water hammer protection of water turbines, the maximum allowable pressure pulsation value provided by equipment manufacturers, and the design limit for the safe operation of the unit, this threshold is formulated to effectively identify and warn of water hammer risks and ensure the structural safety of the water turbine and the stable operation of the system.

[0060] In the present invention, the water hammer analysis unit can collect high-time-resolution pressure pulsation response data in real time by arranging high-frequency dynamic pressure sensors in the main flow channels such as the guide vane, volute, or draft tube of the water turbine. Combining high-pass filtering, normalization, and differential processing methods, it can effectively identify the pressure mutation behavior during the regulation process, especially under the condition of rapid closing of the guide vane. By calculating the ratio of the pressure step value to the reference average pressure, the water hammer intensity coefficient is constructed to achieve a quantitative evaluation of the strength of the water hammer effect caused by regulation. When the water hammer intensity coefficient exceeds the preset threshold Wthresh, the system can timely trigger the third warning instruction, thus indicating the existence of water hammer risk and having the ability to identify the accumulation of structural impact stress in advance and determine the risk level of the hydraulic transient process. This method is applicable to the analysis of fluid impact response under different test modes, has good generality and practicability, and helps to guide the optimization design of hydraulic structures and the formulation of regulation strategies, improving the safety and response stability of system operation.

[0061] The disturbance offset analysis unit is used to collect the response curve of the system flow rate, opening degree, or power signal under the i-th test mode when it is subjected to disturbance excitation, identify its steady-state offset degree, and construct the hydraulic disturbance offset coefficient under the i-th test mode. The acquisition method includes: S41, introducing a disturbance variable with a set amplitude during the test process, and synchronously collecting the tail water level before and after the disturbance; S41 specifically includes: S411, device preparation before the test, setting the guide vane opening degree real-time collection device, active power signal collection equipment and ultrasonic water level meter, introducing a disturbance variable with a set amplitude during the test process, and collecting and obtaining the tail water level response sequence before the disturbance and the tail water level response sequence after the disturbance; The disturbance variable with a set amplitude is set as: guide vane opening degree change Δθ = ± 1% or ± 2%; the set disturbance duration is > 5 seconds, and a collection observation window is set, 5 seconds before the disturbance, 20 seconds after the disturbance, and at least 25 seconds in total; S42, performing sliding average and steady-state extraction analysis on the tail water level disturbance response sequence, using a sliding average algorithm to extract the steady-state tail water level H0 before the disturbance from the tail water level response sequence before the disturbance, and using a sliding average algorithm to extract the new steady-state tail water level H1 after the disturbance from the tail water level response sequence after the disturbance; wherein the steady-state extraction window length is set as 3-5 seconds before the disturbance and after the disturbance; S43, hydraulic disturbance offset coefficient defined as the tail water level offset rate caused by the disturbance: ; wherein H1 represents the 3-second average before the disturbance, and H0 represents the last 3-second average after the disturbance; S44, setting a disturbance offset threshold Pthresh, if ≥ Pthresh, indicating that the system is sensitive to small disturbances, there is a risk of structural regulation lag or dynamic coupling problem, triggering the fourth early warning instruction; if <Pthresh, it is considered as a controllable response; the hydraulic disturbance offset coefficient is used to evaluate the offset compensation capability of the structural control system under the disturbance environment.

[0062] The source of the disturbance offset threshold Pthresh is: through statistical analysis of a large number of water turbines under different operating conditions and running data, the amplitude distribution range of the tail water level offset before and after the disturbance is extracted, combined with the system response characteristics and the structural control compensation capability, a reasonable disturbance offset critical value is determined. Referring to relevant hydraulic machinery dynamic response standards, feedback control performance indicators of equipment manufacturers, and expert experience, the threshold is formulated to accurately reflect the sensitivity of the system to the disturbance, identify the risk of structural regulation lag or dynamic coupling anomaly in time, and ensure the stable and safe operation of the water turbine and the governor system.

[0063] The tail water level response sequence of the system before and after the disturbance excitation is compared and analyzed by the disturbance offset analysis unit, so that the steady-state offset degree of the structure under the adjusting disturbance can be effectively identified. The unit introduces the guide vane opening change of a set amplitude as the disturbance source, cooperates with the high-precision water level collection equipment, extracts the steady-state values of the tail water level before and after the disturbance by the sliding average algorithm, constructs the hydraulic disturbance offset coefficient , and realizes the quantitative evaluation of the stability and control compensation ability of the disturbance response system. When the value is greater than or equal to the preset disturbance offset threshold Pthresh, the system will trigger the fourth early warning instruction, prompting that there is a risk of control system response lag or insufficient dynamic coupling, which helps to identify the performance defects and design bottlenecks of the regulating system in advance. The method has the advantages of non-invasiveness, strong real-time performance, high adaptability, and can be widely applied to dynamic performance evaluation of hydraulic regulating systems in different operating states and structural configurations.

[0064] Embodiment five This embodiment is an explanation and description in embodiment one, please refer to Figure 1 , specifically, the test command module comprises a first screening unit; The first screening unit is used for collecting the values of the critical resonance coefficient , the guide vane lag response coefficient , the water hammer intensity coefficient and the hydraulic disturbance offset coefficient of the ith test mode and the triggered first early warning instruction, the second early warning instruction, the third early warning instruction and the fourth early warning instruction; when the values of the critical resonance coefficient , the guide vane lag response coefficient , the water hammer intensity coefficient and the hydraulic disturbance offset coefficient of the ith test mode are all zero, it indicates that the test of the hydro-turbine and the governor is qualified under the same test mode; and the values of the critical resonance coefficient , the guide vane lag response coefficient , the water hammer intensity coefficient and the hydraulic disturbance offset coefficient of the ith test mode are all zero, it indicates that the test of the hydro-turbine and the governor is qualified under the same test mode;

[0065] In the embodiment, the first screening unit realizes comprehensive evaluation of the regulating performance of the hydraulic turbine and the governor by comprehensively analyzing the critical resonance coefficient, the guide vane lag response coefficient, the water hammer intensity coefficient and the hydraulic disturbance offset coefficient in the ith test mode and associating various early warning instructions. When the four key indicators are all zero, it indicates that there is no abnormal vibration, no lag response, no obvious water hammer risk and normal disturbance response in the system in the test mode, ensuring good cooperative operation of the hydraulic turbine and the governor, and determining that the test is qualified. Further, when the first screening unit is used to statistically analyze all test results of the no-load mode, the load mode, the speed-up mode and the load jump mode, if all the indicators corresponding to the modes are zero, it is determined that the entire test system meets the design and operation requirements, and a test qualified group is generated. The screening mechanism effectively improves the accuracy and reliability of the test results, facilitates quick determination of the overall performance of the system, reduces human judgment errors, ensures safe and stable operation of the equipment, and improves the maintenance efficiency and operation safety level of the hydraulic turbine unit.

[0066] Embodiment six This embodiment is an explanation and description in embodiment five, please refer to Figure 1 , in particular, the test command module further comprises a second screening unit; The second screening unit is configured to, in any one test mode, if there is any one of the first early warning instruction, the second early warning instruction, the third early warning instruction or the fourth early warning instruction, it indicates that there is a test risk in the ith test mode, and the first screening unit generates a first test command strategy corresponding to the test result; For the first early warning instruction, a first strategy is generated, including: If Cthresh≤ ≤Cthresh×120%, the frequency scanning range is extended by 10%, and the sweep interval is encrypted; If Cthresh×120%< ≤Cthresh×150%, the modal detection time window is increased by 20%, and the sweep start frequency is adjusted to avoid the resonance zone; If >Cthresh×150%, stop the test mode, output "structure resonance risk fault", and notify the artificial to check; For the second early warning instruction, a second strategy is generated, including: If Dthresh≤ ≤Dthresh×120%, the target instruction slope is reduced by 10-20%, and the lag improvement is observed; If Dthresh×120%< ≤Dthresh×150%, the target instruction slope is reduced by 21-30%, and the lag improvement is observed; If When ≥Dthreshx150%, stop the test mode, output "abnormal risk of structure response", and notify manual verification; For the third early warning instruction, a third strategy is generated, including: If Wthresh≤ When ≤Wthreshx120%, reduce the guide vane shutdown speed by 10% and extend the adjustment instruction buffer; If Wthreshx120% When ≤Wthreshx150%, enable throttling buffer working condition and pressurize tail water flow compensation; If When ≥Wthreshx150%, stop the test mode, output "strong water hammer risk", optimize the shutdown rhythm or add a buffer valve; For the fourth early warning instruction, a fourth strategy is generated, including: If Pthresh≤ When ≤Pthreshx120%, repeat the test disturbance three times to exclude transient deviation error; If Pthreshx120% When ≤Pthreshx150%, switch to a weaker disturbance mode, reduce the disturbance input amplitude by 20%, and recalculate the deviation curve; If When ≥Pthreshx150%, stop the test mode, output "risk of disturbance adaptability", and suggest to adjust the speed feedback gain or structure parameters.

[0067] In this embodiment, the second screening unit realizes fine management and targeted processing of various early warning instructions through systematic and hierarchical risk response strategies, effectively improving the safety and reliability of the water turbine and governor test. When any test mode triggers the first to fourth early warning instructions, the second screening unit timely identifies and generates corresponding test command strategies to ensure that risks are quickly responded and reasonably disposed. This module takes gradually stricter control measures for different risk levels, such as extending the frequency scanning range, adjusting the target instruction slope, slowing down the guide vane shutdown speed, repeating the disturbance test or switching to a weak disturbance mode, which not only ensures the continuity and effectiveness of the test process, but also prevents equipment from being damaged due to abnormal working conditions. For serious risks, the test is stopped in time and manual intervention is notified to verify, which maximizes the reduction of potential faults and safety hazards. This mechanism not only realizes the seamless connection of risk early warning and dynamic response, but also improves the system automation level, reduces human error, and improves test efficiency and accuracy.

[0068] Embodiment Seven This embodiment is an explanation and description in Embodiment Six, please refer toFigure 1 Specifically, the test command module further comprises a third screening unit, an association unit and a misadjustment risk grade evaluation unit. The third screening unit is configured to, in any one test mode, if there are any two or more of the first, second, third and fourth early warning instructions, indicate that the water turbine and the governor in the ith test mode have a multi-source coupling abnormality, and that there is a coordinated misadjustment risk between the structural dynamic characteristics and the control response of the water turbine and the governor in the ith test mode, generate a second test command strategy, which comprises: The association unit is configured to extract the critical resonance coefficient of the ith test mode , the guide vane lag response coefficient of the ith test mode , the water hammer intensity coefficient of the ith test mode and the water disturbance offset coefficient of the ith test mode , and calculate the coordinated misadjustment risk coefficient of the ith test mode by weighting after dimensionless processing.

[0069] In the formula, , , and respectively represent the weight coefficients of the critical resonance coefficient of the ith test mode, the guide vane lag response coefficient of the ith test mode, the water hammer intensity coefficient of the ith test mode and the water disturbance offset coefficient of the ith test mode.

[0070] The misadjustment risk grade evaluation unit is configured to preset a misadjustment risk grade threshold X, and compare the coordinated misadjustment risk coefficient of the ith test mode with the misadjustment risk grade threshold X to obtain a corresponding coordinated misadjustment risk grade, which comprises: The misadjustment risk grade threshold X is derived from: through statistical analysis of a large amount of historical test data and actual operation cases, comprehensive evaluation of different coordinated misadjustment risk coefficients corresponding system operating states and their influence on the performance of the water turbine and the governor, combined with industry safety specifications and expert experience, a reasonable division threshold of multiple risk grades is determined. Referring to relevant hydraulic machinery structure safety standards, governor control response specifications and accident early warning models, the misadjustment risk grade threshold X is set to scientifically distinguish between mild, moderate and high linkage coordination risks, guide subsequent test command strategies and structural maintenance measures, and ensure the safety and stability of the unit operation.

[0071] If When X < 100%, a first synergic disorder risk level is generated, indicating a mild risk of linkage coordination, and a first linkage execution strategy is generated, including: all disturbance input amplitude is uniformly reduced by 10%, guide vane response speed is uniformly reduced by 10%, frequency scanning starting frequency is offset by 5% to avoid resonance points, and control feedback gain value is attenuated by 5% to adaptively adjust; When X ≤ 100%, When X ≤ X*120%, a second synergic disorder risk level is generated, indicating a moderate risk of linkage coordination, and a second linkage execution strategy is generated, including: stopping the current test mode batch, delaying the control output feedback timing by 20 ms to maintain closed-loop consistency, reducing the disturbance amplitude by 20%, increasing the control feedback delay by 15%, reducing the maximum opening of the guide vane adjustment by 10%, offsetting the frequency starting point by 10%, and expanding the modal window by 20%, and retesting; When X > 100%, When X > X*120%, a third synergic disorder risk level is generated, indicating a high risk of linkage coordination, and a third linkage execution strategy is generated, including: immediately terminating all current tests, blocking control feedback and structural parameter reconstruction, and switching to separate structures and governors, separately testing the structure and governor of the water turbine without physical structure load, if the structure response is abnormal, further positioning the damaged components, and performing corresponding structural replacement and repair, after repair, retesting the water turbine structure and governor closed-loop linkage, updating the critical resonance coefficient of the i-th test mode, the guide vane lag response coefficient under the i-th test mode, the water hammer intensity coefficient of the i-th test mode, and the water disturbance offset coefficient under the i-th test mode, when a new round of testing reaches all zeros, a "structure repair qualification report" is generated and is summarized into the test qualified group.

[0072] In the embodiment, the test command module realizes comprehensive identification and precise control of multi-source coupling abnormalities by introducing a third screening unit, an associated unit and a disorder risk level evaluation unit, significantly improving the intelligence and safety of the water turbine and governor joint test. When two or more warning instructions appear in any test mode, the third screening unit can timely determine the synergic disorder risk between the structure dynamic characteristics and the control response, and start the second test command strategy to avoid the risk blind area of single index that cannot fully reflect complex abnormalities. The associated unit scientifically integrates multiple key coefficients through dimensionless processing and weighted calculation, and quantitatively generates a synergic disorder risk coefficient The disordered risk grade evaluation unit combines with the preset threshold X to implement grading management, and the corresponding different levels of linkage execution strategies of three grades of risk including mild, moderate and high are implemented, which includes moderate adjustment of disturbance amplitude and control parameters, and also covers stopping test, delaying feedback timing, and even severe measures of separating detection and repair of structure and control system. The mechanism realizes layer-by-layer control and dynamic optimization of multi-dimensional complex abnormalities, reduces test misjudgment and equipment damage caused by multi-source coupling, and improves the overall stability and reliability of the system. At the same time, through the re-verification mechanism after structure repair, the equipment is guaranteed to return to the qualified state, and the long-term safe and efficient operation of the hydro-turbine unit is guaranteed. In summary, the design of the module greatly enhances the intelligent decision-making ability and fault response level of the test command module.

[0073] The size of the threshold is set for easy comparison. The size of the threshold depends on the amount of sample data and the base number set by the person skilled in the art for each group of sample data; as long as it does not affect the proportional relationship between the parameters and the quantized values.

[0074] The above-described embodiments only express the specific implementation of the present application, and the description is more specific and detailed, but it should not be understood as a limitation on the protection scope of the present application. It should be noted that for ordinary skilled persons in the art, without departing from the technical concept of the present application, some modifications and improvements can be made, which are all within the protection scope of the present application.

[0075] This background section is provided to generally present the context of the application, the work of the current named inventors, the work described in this background section to the extent described in this section, and neither expressly nor implicitly admitted to be prior art of the present application.

Claims

1. A hydropower station debugging intelligent command and test integrated system, characterized in that, Comprise: Debugging mapping modeling module, for identifying and registering the key equipment of the water turbine and the governor system, extracting the structural parameters and debugging constraint information, and establishing a three-dimensional debugging function sub-region model based on the physical connection relationship of the equipment; and extracting the structural parameters, hydraulic connection parameters and control response parameters of the water turbine and the governor in the test mode, and establishing a test working condition database; the test mode includes no-load mode, load mode, speed-up mode and load jump mode; An effect recognition module is configured to construct critical resonance coefficients of the ith test mode based on the test working condition database , guide vane lag response coefficients , water hammer strength coefficients , and hydraulic disturbance offset coefficients , and respectively judge to recognize the linkage effect types, including resonance critical effect, guide vane lag response, water hammer impact abnormality, and hydraulic disturbance offset; if existing, corresponding early warning instructions are generated. The test command module is used to calculate the critical resonance coefficient of the i-th test mode among the no-load mode, loaded mode, speed-up mode, and load jump mode. Guide vane hysteresis response coefficient Water hammer intensity coefficient and hydraulic disturbance offset coefficient When all values ​​are zero, it indicates that all test modes, the turbine and governor have passed the test, and a test pass group is generated; On the contrary, the first test command strategy and the second test command strategy are generated by corresponding screening, and the first test command strategy is used for regulating and controlling the single early warning instruction; The second test command strategy is used to associate the generation of the synergy risk coefficient under the ith test mode The post-evaluation obtains the corresponding synergy risk level.

2. The intelligent command and test integrated system for commissioning of a hydropower station according to claim 1, characterized in that, The debugging mapping modeling module comprises: A device identification unit for identifying and labeling the constituent devices of the water turbine and the governor system, collecting information including device unique number, installation location, debugging number, interface control type through two-dimensional code / radio frequency tag scanning, control system device code analysis and historical operation data retrieval, and establishing a device debugging identification table; A structural parameter extraction unit for calling the structural data table and historical debugging template of the water turbine-governor system according to the identified device number, extracting the corresponding structural parameters and action constraint information, including maximum opening of guide vane, opening adjustment rate range, main shaft rotational inertia, governor response delay range and oil pressure feedback sensitivity; and generating a debugging constraint parameter set for each device, and establishing a debugging function sub-region model according to the device debugging identification table and the corresponding structural parameters and action constraint information; A debugging area calibration unit for identifying the device physical connection logic diagram according to the device number, structural relationship and pipe connectivity of the water turbine governing system, dividing a number of debugging function sub-region three-dimensional debugging function sub-region models, and establishing, including the speed-up response debugging area, the steady-state load regulation area, the guide vane linkage sensitivity debugging area and the jump impact test area; and performing area calibration and color coding in the three-dimensional debugging function sub-region model.

3. The intelligent command and test integrated system for commissioning of a hydropower station according to claim 2, characterized in that, The data stored in the test working condition database includes: During the different test modes, the water turbine main shaft vibration data sequence, the water turbine main shaft speed sequence, the response angle sequence of the guide vane execution structure, the target guide vane instruction sequence, the pressure response data sequence in the water turbine main flow passage, the tail water level response sequence before disturbance and the tail water level response sequence after disturbance are collected and acquired.

4. The intelligent command and test integrated system for commissioning of a hydropower station according to claim 3, characterized in that, The effect recognition module comprises a shaft vibration recognition unit for: Extracting the water turbine main shaft vibration data sequence in the i-th test mode in the test working condition database; The resonance peak frequency fr is identified based on an FFT spectrum analysis method, and a critical resonance coefficient of the ith test mode is constructed in combination with a change curve of the main shaft speed ; The critical resonance coefficient The specific acquisition mode is as follows: Through the vibration sensor or acceleration sensor arranged at the water turbine main shaft bearing seat or shaft neck, the water turbine main shaft vibration data sequence in the test process is collected in real time at a set sampling frequency, and the water turbine main shaft vibration data sequence is the instantaneous vibration response signal in the continuous time window, and the sampling duration covers each test mode stage; After the water turbine main shaft vibration data sequence is subjected to DC drift removal, windowing processing, overlapping segment average processing and noise filtering, the pre-processed vibration data sequence is subjected to fast Fourier transform, a frequency spectrum amplitude function, i.e. a relationship between vibration amplitude and frequency is obtained, a frequency spectrum diagram is obtained, a main peak frequency with the maximum amplitude in the frequency spectrum diagram is identified, i.e. a main shaft vibration spectrum resonance peak frequency fr is obtained, and a maximum vibration amplitude Apeak corresponding to the main shaft vibration spectrum resonance peak frequency fr is recorded for resonance strength evaluation; In the shaft vibration identification process, to avoid misjudgment, a clear criterion for whether there is resonance is set to determine whether the ith test mode enters the resonance region and whether the critical resonance coefficient of the ith test mode needs to be calculated or marked ; the critical resonance coefficient is obtained using the following steps: Step S11: extract the spindle vibration frequency spectrum resonance peak frequency fr, and the maximum vibration amplitude Apeak, preset a discrimination threshold Athresh, and compare the maximum vibration amplitude Apeak with the discrimination threshold Athresh to determine whether there is a structure resonance phenomenon. When Apeak is greater than or equal to the discrimination threshold Athresh, it is considered that there is a structure resonance phenomenon, and the first collection instruction is triggered; when Apeak is less than the discrimination threshold Athresh, it is considered that there is no structure resonance phenomenon, at this time, the critical resonance coefficient of the ith test mode is marked as zero. Step S12: extract the spindle vibration frequency spectrum resonance peak frequency fr, and the maximum vibration amplitude Apeak, preset a discrimination threshold Athresh, and compare the maximum vibration amplitude Apeak with the discrimination threshold Athresh to determine whether there is a structure resonance phenomenon. When Apeak is greater than or equal to the discrimination threshold Athresh, it is considered that there is a structure resonance phenomenon, and the second collection instruction is triggered; when Apeak is less than the discrimination threshold Athresh, it is considered that there is no structure resonance phenomenon, at this time, the critical resonance coefficient of the ith test mode is marked as zero. Step S12: receiving the first acquisition instruction, extracting the water turbine main shaft rotation speed sequence in the test working condition database, and drawing a curve of the rotation speed sequence changing with time, further judging whether the main shaft rotation speed curve has a resonance mode order at a certain time, if matched, considering that the resonance frequency is consistent with the structural critical speed, the crossing resonance condition is established, and the critical speed in the i-th test mode is calculated ; Step S13: combining the maximum vibration amplitude Apeak obtained in step S11 and the critical speed in the i-th test mode obtained in step S12 , to obtain the critical resonance coefficient of the i-th test mode ; Step S14: preset a critical point resonance threshold Cthresh, and compare the critical resonance coefficient of the i-th test mode with the critical point resonance threshold Cthresh If the critical resonance coefficient of the i-th test mode is greater than or equal to the critical point resonance threshold Cthresh, it indicates that the vibration growth of the water turbine resonance section exceeds the critical point, and there is a risk of inducing water turbine main shaft periodic swing or jump to cause material fatigue, triggering the first warning instruction; if the critical resonance coefficient of the i-th test mode is less than the critical point resonance threshold Cthresh, it indicates that the vibration growth of the water turbine resonance section belongs to a safe range, and the monitoring is continued. If the critical resonance coefficient of the i-th test mode is greater than or equal to the critical point resonance threshold Cthresh, it indicates that the vibration growth of the water turbine resonance section exceeds the critical point, and there is a risk of inducing water turbine main shaft periodic swing or jump to cause material fatigue, triggering the first warning instruction; if the critical resonance coefficient of the i-th test mode is less than the critical point resonance threshold Cthresh, it indicates that the vibration growth of the water turbine resonance section belongs to a safe range, and the monitoring is continued. If the critical resonance coefficient of the i-th 5. The intelligent command and test integrated system for commissioning of a hydropower station according to claim 4, characterized in that, The effect recognition module further comprises a guide vane response recognition unit, configured to: extract the response angle sequence of the guide vane execution structure under the ith test mode and the target guide vane instruction sequence, identify the time lag between the adjustment instruction and the guide vane response, and construct the guide vane lag response coefficient under the ith test mode ; The guide vane lag response coefficient Is obtained using the following steps: Step S21: in the ith test mode, sensors are synchronously arranged on the water turbine guide vane execution structure to collect a guide vane execution structure response angle sequence, and a target guide vane instruction sequence is synchronously extracted from the speed regulation system control end to obtain time sequence data of the actual response curve and the target instruction curve; Step S22: the actual response curve and the target instruction curve are aligned and compared, and a response lag time Δt between the two is extracted through cross-correlation analysis or zero-crossing time delay analysis method; Step S23: preset a reference time window width Tref, and calculate the guide vane lag response coefficient under the ith test mode : ; Step S24: Set the hysteresis judgment threshold Dthresh, if ≥Dthresh, consider that there is a risk of adjusting response hysteresis, trigger the second early warning instruction; if <Dthresh, it is considered that the guide vane response is normal, at this time the is marked as zero under the i-th test mode; the guide vane hysteresis response coefficient is used for transverse comparison of the response sensitivity and structural adaptability of the adjusting system under different test modes.

6. The intelligent command and test integrated system for commissioning of a hydropower station according to claim 5, characterized in that, The effect recognition module further comprises a water hammer analysis unit, configured to: The water turbine guide vane, spiral case or draft tube in the i-th test mode is used to collect the pressure fluctuation signal, identify the pressure sharp jump characteristics, and construct the water hammer intensity coefficient of the i-th test mode ; said water hammer intensity coefficient is obtained using the following steps: Step S31: in the test process, dynamic pressure sensors are arranged to collect pressure response data sequences in the main flow passage of the water turbine in real time, and the sampling frequency satisfies >1kHz; Step S32: the pressure response data sequences in the main flow passage of the water turbine are subjected to high-pass filtering, normalization processing and differential transformation, and a pressure mean value Pref is calculated; Step S33: before and after the test guide vane quick shutdown event, a detection time window is set, and a pressure step value ΔP in the window is calculated; Step S34: Water hammer intensity coefficient of the i-th test mode is calculated by the following equation: ; Step S35: Set a water hammer judgment threshold Wthresh, if ≥ Wthresh, determine that there is a significant water hammer risk, trigger the third warning instruction; if <Wthresh, mark as zero; the water hammer intensity coefficient is used to evaluate the fluid inertia response characteristics of the system during the rapid regulation process; The effect recognition module further comprises a disturbance offset analysis unit, configured to: Collect the response curve of the system flow, opening or power signal under the i th test mode when it is disturbed by the excitation, identify the degree of steady-state deviation, and construct the hydraulic disturbance deviation coefficient under the i th test mode ; The hydraulic disturbance offset coefficient Is obtained using the following steps: Step S41: in the test process, a disturbance variable with a set amplitude is introduced, and tail water levels before and after the disturbance are synchronously collected; Step S42: the tail water level disturbance response sequence is subjected to sliding average and steady state extraction analysis, a steady state tail water level H0 before the disturbance is extracted from the tail water level response sequence before the disturbance by using a sliding average algorithm; a new steady state tail water level H1 after the disturbance is extracted from the tail water level response sequence after the disturbance by using a sliding average algorithm; and the steady state extraction window length is set to 3-5 seconds before and after the disturbance; Step S43: Hydraulic disturbance offset coefficient The disturbance-induced tailwater offset rate is defined as: ; Step S44: Set the perturbation offset threshold Pthresh, if ≥ Pthresh, it means that the system is sensitive to small perturbations, there is a risk of structural adjustment lag or dynamic coupling problem, triggering the fourth early warning instruction; if <Pthresh, it is considered that the response is controllable; the hydraulic perturbation offset coefficient is used to evaluate the offset compensation capability of the structure control system in the perturbation environment.

7. The intelligent command and test integrated system for commissioning of a hydropower station according to claim 6, characterized in that, The test command module comprises a first screening unit, configured to: the values of the critical resonance coefficient, the guide vane lag response coefficient, the water hammer intensity coefficient and the hydraulic disturbance offset coefficient of the i-th test mode and the triggered first, second, third and fourth early warning instructions of the i-th test mode are all zero, it indicates that the turbine and the governor pass the test under the same test mode.​​​​​​​ And statistics of no-load mode, with load mode, speed mode and load jump mode when the critical resonance coefficient of the i-th test mode , guide vane lag response coefficient , water hammer intensity coefficient And the water power disturbance offset coefficient The value is zero, indicating that all test modes, the test of the turbine and the governor is qualified, and the test qualified group is generated.

8. The intelligent command and test integrated system for commissioning of a hydropower station according to claim 7, characterized in that, The test command module further comprises a second screening unit, configured to: If any one of the first, second, third and fourth early warning instructions exists in any one of the test modes, it indicates that there is a test risk in the ith test mode, and the first screening unit generates a first test command strategy corresponding to the test result; For the first early warning instruction, a first strategy is generated, including: If Cthresh≤ If Cthresh≤ 120%, extend the frequency scanning range by 10%, and encrypt the scanning interval. If Cthresh × 120% < When ≤Cthresh×150%, increase the modal detection time window by 20%, and adjust the sweep frequency start frequency to avoid the resonance region; If When > Cthresh x 150%, stop the test mode, output "structure resonance risk fault", and notify the operator to check. For the second early warning instruction, a second strategy is generated, including: If Dthresh≤ If Dthresh≤ Dthresh x 120%, reduce the target instruction slope by 10-20% and observe the improvement of the hysteresis. If Dthresh x 120% < Dtarget < Dthresh x 150%, reduce target command slope 21-30% and observe improvement in lag. If Dthresh x 120% < Dtarget < Dthresh x 150%, reduce target command slope 21-30% and observe improvement in lag. If When Dthresh x 150% is reached, the test mode is stopped, an abnormal risk of execution structure response is output, and manual verification is notified. For the third early warning instruction, a third strategy is generated, including: If Wthresh≤ When Wthresh×120%, reduce the guide vane shut-off speed by 10% and extend the adjustment command buffer. If Wthresh x When < Wji≤ Wthresh x 150%, the throttling buffer working condition is enabled, and the tail water flow compensation is pressurized. If If Wthresh x 150% is exceeded, the test mode is stopped, a strong water hammer risk is output, the shut-off rhythm is optimized or a buffer valve is added. For the fourth early warning instruction, a fourth strategy is generated, including: If Pthresh < 0.5, then test for disturbance three times, take the median to exclude transient offset error. If Pthresh < 0.5, then test for disturbance three times, take the median to exclude transient offset error. If Pthresh × 120% < When the value is ≤Pthresh×150%, switch to a weaker disturbance mode, reduce the disturbance input amplitude by 20%, and recalculate the offset curve; If When Pthresh x 150% is reached, the test mode is stopped and a perturbation adaptability risk is output, suggesting re-adjustment of the speed regulation feedback gain or structural parameters.

9. The intelligent command and test integrated system for commissioning of a hydropower station according to claim 8, characterized in that, The test command module further comprises a third screening unit and an associated unit. The third screening unit is configured to, if any two or more of the first early warning instruction, the second early warning instruction, the third early warning instruction or the fourth early warning instruction exist in any one test mode, indicate that the water turbine and the governor in the i-th test mode have a multi-source coupling abnormality, and that there is a risk of a collaborative disorder between the structural dynamic characteristics and the control response in the i-th test mode, and generate a second test command strategy. The associated unit is configured to extract a critical resonance coefficient of the ith test mode , a guide vane lag response coefficient in the ith test mode , a water hammer intensity coefficient of the ith test mode , and a hydraulic disturbance offset coefficient in the ith test mode After dimensionless processing, the synergistic disorder risk coefficient in the ith test mode is obtained by weighted calculation .

10. The intelligent command and test integrated system for commissioning of a hydropower station according to claim 9, characterized in that, The test command module further includes a disorder risk level assessment unit configured to: a preset misalignment risk level threshold X, and comparing the synergy misalignment risk coefficient of the ith test mode with the misalignment risk level threshold X to obtain a corresponding synergy misalignment risk level, comprising: comparing evaluation with the misalignment risk level threshold X to obtain a corresponding synergy misalignment risk level, comprising: If When X, a first co-ordination risk level is generated, indicating a mild co-ordination risk, and a first co-ordination execution strategy is generated, including: all disturbance input amplitude uniformly down-regulated by 10%, guide vane response speed uniformly reduced by 10%, frequency scanning starting frequency offset by 5% to avoid resonance points, and control feedback gain value attenuated by 5% to re-adaptively adjust; if X≤ if X≤120%, a second synergy misalignment risk level is generated, indicating that there is a moderate linkage coordination risk, and a second linkage execution strategy is generated, including: stopping the current test mode batch, delaying the control output feedback timing by 20 ms to maintain closed-loop consistency, then reducing the disturbance amplitude by 20%, increasing the control feedback delay by 15%, reducing the maximum opening of the guide vane adjustment by 10%, shifting the frequency starting point by 10%, and expanding the modal window by 20%, and then retesting; If When X>120%, the third synergy disorder risk level is generated, indicating a high risk of linkage coordination, and the third linkage execution strategy is generated, including: immediately terminating all current tests, blocking, controlling feedback and structural parameter reconstruction, and switching to the separation of the structure and the governor, then performing command output tests on the separate structure of the water turbine and the governor under no physical structure load, if the structure response is abnormal, further positioning the damaged components, and performing corresponding structural replacement and repair, after the repair is completed, the water turbine structure test and the governor closed-loop linkage test are performed again, and the critical resonance coefficient of the ith test mode is updated The guide vane lag response coefficient under the ith test mode The water hammer intensity coefficient of the ith test mode And the hydraulic disturbance offset coefficient under the ith test mode When a new round of tests reaches all zeros, a structure repair qualified report is generated and is summarized into the test qualified group.

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