A full-flow extreme power point rapid determination method and system for diesel fire pump set

Abstract

The present application relates to the field of fluid machinery, especially to a full-flow extreme power point rapid determination method and system for diesel engine fire pump set. According to the industry standard and pump set parameters, the method presets the reference parameters and solidifies the Q-N-H three-dimensional working condition mapping table to build a standardized test reference. Four test intervals are divided according to the flow, and exclusive control algorithm and safety protection logic are matched. After the equipment is preheated and stabilized, multi-source working condition data is collected through high-frequency sampling and time stamp calibration, and the real-time input power of the diesel engine is accurately calculated through sliding filter denoising, parameter normalization and multi-dimensional loss correction. Through the least square method five polynomial fitting P-Q characteristic curve, combined with the first and second derivative joint criterion, the only power maximum point in the effective flow interval is accurately calibrated. The method is accurate, fast and highly standardized, effectively improves the determination accuracy and efficiency of the extreme power point, and meets the combined rule detection requirements of the diesel engine fire pump set.

Description

Technical Field

[0001] This invention relates to the field of fluid machinery, and more particularly to a method and system for rapid determination of the extreme power point of the full flow rate of a diesel engine fire pump set. Background Technology

[0002] Fire pump sets are core lifeline equipment for ensuring urban public safety, and their operational reliability and response time are directly related to the safety of people's lives and property. Currently, the performance testing of diesel engine fire pump sets generally adopts the traditional steady-state point-by-point testing method, which collects parameters such as head and power at different flow rates by fixing the diesel engine speed and manually adjusting the outlet valve. Although this method is simple in principle, its inherent technical defects are becoming increasingly prominent in the context of increasingly stringent modern fire safety standards and the continuous improvement of the demand for efficient and accurate on-site testing. It is difficult to meet the actual application requirements of full-flow performance testing, extreme power calibration, and safety testing of pump sets.

[0003] Traditional testing techniques suffer from significant shortcomings in efficiency and adaptability. Full-flow point-by-point testing is cumbersome and time-consuming, failing to meet the demands of rapid deployment and immediate equipment performance verification in fire scenarios. This inefficient testing process can easily create potential safety risks. Furthermore, this technology presents a core conflict between extreme condition detection and equipment safety. When a fire pump exceeds its rated flow, its power output continues to rise until it reaches an extreme point. Traditional constant-speed testing, when approaching this extreme condition, can easily lead to input power exceeding the diesel engine's rated power, causing equipment overload, shutdown, or even permanent mechanical damage. This makes it impossible to simultaneously address performance boundary detection and equipment safety protection, resulting in difficulties in accurately obtaining the pump's true performance boundary parameters.

[0004] Furthermore, traditional test data acquisition and analysis capabilities are limited, only providing discrete, static flow and head data. They cannot continuously and accurately capture the dynamic power change trajectory across the entire flow range, making it difficult to precisely identify core parameters related to extreme power. Simultaneously, they lack standardized benchmark modeling, interval-based control, multi-source data calibration, and loss correction mechanisms. This results in large test data errors and a single dimension, failing to accurately reflect pump unit energy conversion efficiency, power matching characteristics, and potential fault hazards, thus hindering the support for refined equipment operation and maintenance and intelligent performance evaluation. Summary of the Invention

[0005] This invention aims to solve the problems of low efficiency, poor safety, and insufficient data accuracy in traditional diesel engine fire pump set testing technology. It overcomes the shortcomings of its inability to safely detect extreme power values ​​and its limited data dimensions, providing a rapid method and system for determining extreme power points across the entire flow rate. This enables efficient, safe, and accurate full-flow performance testing and extreme value calibration of pump sets. The specific technical solution is as follows:

[0006] A rapid method for determining the extreme power point of a diesel engine fire pump set at full flow rate includes the following steps:

[0007] S1: Based on the mandatory standards of the fire pump industry, combined with the inherent design parameters and factory test data of the diesel engine fire pump set under test, the core benchmark parameters of the pump set are pre-set and solidified, the compliance verification of the rated operating condition parameters is completed, the QNH three-dimensional operating condition mapping table covering the entire effective test range is constructed and solidified, and a unified standardized test benchmark is established.

[0008] S2: Based on the rated flow rate of the pump set, four full-flow test condition intervals are divided. According to the hydraulic and power characteristics of each interval, corresponding control algorithms, speed iterative adjustment functions, and safety constraint protection logic are configured, specifically as follows:

[0009] Rated flow range: 0 ≤ flow rate ≤ rated flow rate, configured with a self-tuning constant speed PID closed-loop control algorithm;

[0010] Exceeding rated flow range: Flow rate ≥ 1.1 times rated flow rate, based on the pre-cured QNH three-dimensional operating condition mapping table, a lookup table iterative decreasing speed regulation algorithm is configured;

[0011] Safety constraint verification range: 1.1 times rated flow rate ≤ flow rate ≤ 1.5 times rated flow rate. Iterative speed regulation is based on the QNH three-dimensional working condition mapping table, and a dual closed-loop adaptive speed regulation algorithm with speed reduction superimposed on head compensation is configured.

[0012] Exceeding the test range: Traffic flow > 1.5 times the rated traffic flow, configure a safety protection shutdown algorithm;

[0013] S3: After preheating and stabilizing the diesel engine fire pump set, conduct full flow gradient tests based on the control algorithms of each interval, and simultaneously collect hydraulic condition data of the pump set and power auxiliary data of the diesel engine. Complete the timing calibration of multi-source data through timing stamp alignment technology to eliminate sampling timing deviation.

[0014] S4: The original collected data is preprocessed for noise reduction using a sliding filter algorithm. The normalization conversion of parameters under different working conditions is completed based on the pump similarity law. A loss correction model is constructed by combining the multi-dimensional loss characteristics of pump volume, hydraulics, and mechanicals to calculate the real-time input power of the diesel engine under each working condition.

[0015] S5: The least squares method is used to fit the discrete flow-power data of the whole flow rate using a fifth-order polynomial to generate a continuous PQ characteristic curve. The extreme points of the curve are identified by the first and second derivatives combined with mathematical criteria. After eliminating invalid operating points, the unique true power maximum point in the effective range of 0 to 1.5 times the rated flow rate is calibrated, and the extreme power point of the whole flow rate is determined rapidly.

[0016] Preferably, in step S1, a three-dimensional QNH operating condition mapping table covering the entire effective test range is constructed and solidified. Specifically, this includes: based on the pump group similarity law, covering the entire effective test flow range of 0 to 1.5 times the rated flow and the entire speed adjustment range of 60% to 100% of the rated speed, the mapping table is constructed by using simulation fitting combined with factory test data calibration; the mapping table uses flow rate and speed as independent variables and head as dependent variable, stores each set of standard operating condition data, and retains 4 decimal places for data accuracy. The system is solidified before testing and used for iterative speed adjustment and operating condition deviation correction in the over-rated flow range.

[0017] Preferably, in step S2, when configuring the parameter self-tuning constant speed PID closed-loop control algorithm, a constant speed closed-loop control strategy is adopted to maintain the rated speed of the pump group; the algorithm includes three control dimensions: proportional, integral, and derivative, with the proportional coefficient adaptively tuned within the range of 0.8 to 1.5, the integral time constant within the range of 0.05 to 0.2 s, and the derivative time constant within the range of 0.01 to 0.05 s; the pump group speed fluctuation within the rated flow range is controlled within ±5 r / min.

[0018] Preferably, in step S2, when configuring the lookup table iterative speed reduction algorithm, the pump group's adaptive speed iterative adjustment is performed based on the pre-cured QNH three-dimensional operating condition mapping table, using speed reduction adjustment logic; the speed adjustment step size is 5~10 r / min, and the corresponding step size is matched according to the pump group's power level; the system obtains the dimensionless flow correction coefficient by querying the three-dimensional operating condition mapping table based on the real-time flow; the larger the real-time flow, the larger the flow correction coefficient, and the larger the speed reduction amplitude; the single iteration cycle is ≤0.1s, the maximum number of iterations is 5, and the iteration is terminated when the comprehensive deviation of real-time flow, speed, and head operating conditions is ≤2%; the overall adjustment response time of a single operating condition is ≤0.5s.

[0019] Preferably, in step S2, when configuring the dual closed-loop adaptive speed regulation algorithm with speed reduction superimposed on head compensation, iterative speed regulation is completed based on the pre-fixed QNH three-dimensional working condition mapping table, and 0.65 times the rated head is set as the minimum effective head constraint threshold; the system monitors the pump unit's operating head in real time, and when the real-time head is lower than the threshold, it triggers adaptive speed increase compensation; the head closed-loop compensation coefficient ranges from 2.0 to 5.0, and the compensation coefficient is adaptively tuned according to the head deviation; the system continuously iteratively adjusts the speed until the real-time head meets the threshold requirement, forming a dual closed-loop speed regulation logic with speed reduction adjustment superimposed on head closed-loop compensation.

[0020] Preferably, in step S2, when configuring the safety protection shutdown algorithm, 1.5 times the rated flow rate is set as the maximum effective test flow rate threshold, and the system monitors the real-time flow rate of the pump group at a frequency of 100Hz. When the real-time flow rate is greater than 1.5 times the rated flow rate, the active speed regulation output is terminated, the diesel engine throttle opening is locked, the 3-second delay safety shutdown procedure is started, and the pump group is controlled to reduce speed and stop.

[0021] Preferably, in step S3, the pump set preheating condition is idle preheating for 3-5 minutes. After the diesel engine water temperature, oil pressure, and pump body pressure stabilize, the formal test is started. Throughout the test, a uniform high-frequency sampling frequency of 100Hz is set to simultaneously collect hydraulic condition data of the pump set and power auxiliary data of the diesel engine. The hydraulic condition data includes real-time flow rate, real-time head, real-time speed, and pump inlet and outlet pressure. The diesel engine power auxiliary data includes real-time fuel consumption, output torque, crankshaft speed, exhaust temperature, and load rate. Millisecond-level unified clock timing stamping technology is used to bind the collected data of each group, eliminate timing misalignment and abnormal sampling data, and achieve accurate timing calibration of multi-source data.

[0022] Preferably, step S4 includes the following sub-steps:

[0023] S41: Raw data noise reduction preprocessing: The raw sampled data is noise-reduced using a 10-point moving average filtering algorithm. The operating condition curve is smoothed by the filtering formula, and noise data caused by environmental interference, sensor pulse fluctuations and equipment vibration is filtered out, while retaining the true trend of operating condition changes.

[0024] S42: Normalization Conversion of Variable Operating Condition Parameters: Based on the pump similarity law, the data of non-rated operating conditions with variable speed and variable flow are uniformly converted to the standard reference operating conditions through the dedicated conversion formulas for flow rate and head, ensuring the comparability and accuracy of data calculation.

[0025] S43: Multi-dimensional loss correction modeling: Construct a three-dimensional correction loss model that includes volumetric efficiency, hydraulic efficiency, and mechanical efficiency, and obtain the total loss efficiency of the pump set by combining the three types of efficiency; the correction coefficients of the three types of efficiency are all obtained by adaptive fitting of the pump set's factory curve and real-time operating conditions, which can accurately compensate for various power losses caused by pump body medium leakage, water flow hydraulic friction impact, and mechanical transmission friction, and adapt to the loss characteristics of the full flow operating conditions.

[0026] S44: Real-time input power precision calculation: Combining hydraulic effective power and comprehensive loss efficiency across all dimensions, and matching water density, gravitational acceleration, real-time operating flow rate, and real-time operating head parameters, it accurately calculates the actual real-time input power of the diesel engine under various flow conditions, avoiding errors caused by ideal operating condition calculations, and adapting to various variable operating condition test scenarios.

[0027] Preferably, step S5 includes the following sub-steps:

[0028] S51: High-precision PQ characteristic curve fitting: The least squares method is used to fit the discrete flow-power data of the whole flow. By iteratively solving the polynomial fitting coefficient, a continuous and smooth PQ characteristic curve is generated. Abnormal operating points are automatically eliminated during the process to strictly ensure the accuracy of curve fitting. The fitting determination coefficient is not less than 0.995, which meets the requirements of high-precision extreme value identification.

[0029] S52: Joint Criterion Identification of Extreme Points: The first derivative of the fitted continuous PQ curve is calculated, and the condition that the first derivative equals 0 is used as the initial judgment condition for suspected extreme points; then the second derivative is used for precise verification. When the second derivative is less than 0, it is determined to be a power maximum point, and when the second derivative is greater than 0, it is determined to be a power minimum point.

[0030] S53: Precise calibration of extreme points across the entire flow range: Traverses the entire effective flow range from 0 to 1.5Qn, eliminates invalid operating conditions such as insufficient head, exceeding the range, and unstable operating conditions, performs secondary verification to select the unique true maximum power point within the range, records the corresponding operating parameters simultaneously, generates a standardized test report, and completes the rapid determination of extreme power points.

[0031] A rapid determination system for full-flow extreme power points of diesel engine fire pump sets includes a benchmark modeling and solidification module, a zone-level control module, a multi-source data synchronous acquisition and calibration module, a data correction and power calculation module, and an extreme value identification and calibration module.

[0032] The benchmark modeling and solidification module is used to combine industry standards and specifications, the inherent design parameters of the pump set under test, and factory test data to verify the compliance of rated operating condition parameters, pre-set and solidify the core benchmark parameters of the pump set, construct a three-dimensional operating condition mapping model covering the entire effective test range, and establish a standardized and unified test benchmark.

[0033] The segmented and graded control module divides the pump set into multiple full-flow test condition intervals based on the rated flow rate. It matches and adapts closed-loop control strategies, iterative speed regulation logic and safety constraint protection mechanisms for different flow condition intervals. It achieves graded, precise, and adaptive control and over-limit safety protection for rated flow intervals, over-rated flow intervals, safety constraint verification intervals and over-test range intervals, ensuring that the full-flow test process is stable, controllable and safe.

[0034] The multi-source data synchronous acquisition and calibration module is used to perform a full flow gradient test after the pump set has been preheated and stabilized, synchronously acquire the hydraulic operating parameters of the pump set and the power operating parameters of the diesel engine, and eliminate the sampling time sequence deviation of the multi-source data through the time sequence alignment calibration method to ensure the synchronization and consistency of the test data.

[0035] The data correction and power calculation module is used to perform noise reduction and purification preprocessing on the original collected data, complete the normalization correction of the variable working condition parameters according to the pump similarity law, and construct a loss correction model in combination with the multi-dimensional loss characteristics of the pump group to accurately calculate the real-time input power of the diesel engine under each test condition.

[0036] The extreme value identification and calibration module is used to construct a continuous flow-power characteristic curve based on the full-flow discrete flow-power test data through high-order polynomial fitting, accurately identify the extreme value characteristics of the curve by relying on the joint criterion of high-order derivatives, eliminate abnormal and invalid operating condition data, and finally calibrate the unique true power maximum point within the effective test flow range, thus completing the rapid and accurate determination of the extreme power point of the pump group at full flow.

[0037] The beneficial effects of this invention are as follows:

[0038] 1. This invention simplifies the cumbersome process of traditional point-by-point testing by using a zoned and graded control testing mode, greatly reduces testing time, adapts to the practical needs of rapid verification at fire sites, and completely solves the various safety hazards caused by the inefficiency and lag of traditional testing.

[0039] 2. This invention is equipped with graded speed regulation logic and over-limit safety shutdown mechanism, which effectively avoids diesel engine overload, shutdown and mechanical damage under extreme conditions, and takes into account pump group performance boundary detection and equipment safety protection, greatly improving test safety.

[0040] 3. This invention employs multi-source data synchronous acquisition and timing calibration technology, combined with sliding filter noise reduction processing, breaking through the limitations of traditional discrete data acquisition, and can continuously and accurately capture the dynamic power change trajectory across the entire flow range.

[0041] 4. This invention constructs a multi-dimensional loss correction model and a normalized conversion system for operating conditions, which effectively corrects various operating condition losses and test deviations, solves the problems of large errors and low accuracy in traditional test data, and ensures the authenticity of test data.

[0042] 5. This invention relies on high-order polynomial fitting and dual derivative joint criteria to identify extreme points, accurately screen effective operating parameters, and stably calibrate the unique true power maximum point of the pump group, filling the shortcoming of traditional technology that cannot accurately detect performance boundaries.

[0043] 6. This invention establishes a standardized three-dimensional working condition test benchmark, which can comprehensively analyze the energy conversion and power matching characteristics of the pump set, accurately identify potential faults, and provide reliable data support for the refined operation and maintenance and intelligent performance evaluation of fire pump sets. Attached Figure Description

[0044] Figure 1 This is a schematic diagram illustrating the steps of a rapid method for determining the extreme power point of a diesel engine fire pump set at full flow rate, according to the present invention. Detailed Implementation

[0045] A rapid method for determining the extreme power point of a diesel engine fire pump set at full flow rate includes the following steps:

[0046] S1: Based on the mandatory standards of the fire pump industry, combined with the inherent design parameters and factory test data of the diesel engine fire pump set under test, the core benchmark parameters of the pump set are pre-set and solidified, the compliance verification of the rated operating condition parameters is completed, the QNH three-dimensional operating condition mapping table covering the entire effective test range is constructed and solidified, and a unified standardized test benchmark is established.

[0047] S2: Based on the rated flow rate of the pump set, four full-flow test condition intervals are divided. According to the hydraulic and power characteristics of each interval, corresponding control algorithms, speed iterative adjustment functions, and safety constraint protection logic are configured, specifically as follows:

[0048] Rated flow range: 0 ≤ flow rate ≤ rated flow rate, configured with a self-tuning constant speed PID closed-loop control algorithm;

[0049] Exceeding rated flow range: Flow rate ≥ 1.1 times rated flow rate, based on the pre-cured QNH three-dimensional operating condition mapping table, a lookup table iterative decreasing speed regulation algorithm is configured;

[0050] Safety constraint verification range: 1.1 times rated flow rate ≤ flow rate ≤ 1.5 times rated flow rate. Iterative speed regulation is based on the QNH three-dimensional working condition mapping table, and a dual closed-loop adaptive speed regulation algorithm with speed reduction superimposed on head compensation is configured.

[0051] Exceeding the test range: Traffic flow > 1.5 times the rated traffic flow, configure a safety protection shutdown algorithm;

[0052] S3: After preheating and stabilizing the diesel engine fire pump set, conduct full flow gradient tests based on the control algorithms of each interval, and simultaneously collect hydraulic condition data of the pump set and power auxiliary data of the diesel engine. Complete the timing calibration of multi-source data through timing stamp alignment technology to eliminate sampling timing deviation.

[0053] S4: The original collected data is preprocessed for noise reduction using a sliding filter algorithm. The normalization conversion of parameters under different working conditions is completed based on the pump similarity law. A loss correction model is constructed by combining the multi-dimensional loss characteristics of pump volume, hydraulics, and mechanicals to calculate the real-time input power of the diesel engine under each working condition.

[0054] S5: The least squares method is used to fit the discrete flow-power data of the whole flow rate using a fifth-order polynomial to generate a continuous PQ characteristic curve. The extreme points of the curve are identified by the first and second derivatives combined with mathematical criteria. After eliminating invalid operating points, the unique true power maximum point in the effective range of 0 to 1.5 times the rated flow rate is calibrated, and the extreme power point of the whole flow rate is determined rapidly.

[0055] In step S1, a three-dimensional QNH operating condition mapping table covering the entire effective test range is constructed and solidified. Specifically, it includes: based on the pump set similarity law, covering the entire effective test flow range of 0 to 1.5 times the rated flow and the entire speed adjustment range of 60% to 100% of the rated speed. The mapping table is constructed by combining simulation fitting with factory test data calibration. The mapping table uses flow rate and speed as independent variables and head as dependent variable, stores the standard operating condition data of each group, and retains 4 decimal places for data accuracy. The system is solidified before the test and used for iterative speed adjustment and operating condition deviation correction in the over-rated flow range.

[0056] In step S2, when configuring the parameter self-tuning constant speed PID closed-loop control algorithm, a constant speed closed-loop control strategy is adopted to maintain the rated speed of the pump group. The algorithm includes three control dimensions: proportional, integral, and derivative. The adaptive tuning range of the proportional coefficient is 0.8~1.5, the integral time constant range is 0.05~0.2s, and the derivative time constant range is 0.01~0.05s. The pump group speed fluctuation within the rated flow range is controlled within ±5r / min.

[0057] In step S2, when configuring the lookup table iterative speed reduction algorithm, the pump group's adaptive speed iterative adjustment is performed based on the pre-cured QNH three-dimensional operating condition mapping table, using speed reduction adjustment logic; the speed adjustment step size is 5~10 r / min, and the corresponding step size is matched according to the pump group's power level; the system obtains the dimensionless flow correction coefficient by querying the three-dimensional operating condition mapping table based on the real-time flow. The larger the real-time flow, the larger the flow correction coefficient, and the larger the speed reduction amplitude; the single iteration cycle is ≤0.1s, the maximum number of iterations is 5, and the iteration is terminated when the comprehensive deviation of real-time flow, speed, and head operating conditions is ≤2%, and the overall adjustment response time of a single operating condition is ≤0.5s.

[0058] In step S2, when configuring the dual closed-loop adaptive speed regulation algorithm with speed reduction superimposed on head compensation, iterative speed regulation is completed based on the pre-fixed QNH three-dimensional operating condition mapping table, and 0.65 times the rated head is set as the minimum effective head constraint threshold. The system monitors the pump unit's operating head in real time. When the real-time head is lower than the threshold, it triggers adaptive speed increase compensation. The head closed-loop compensation coefficient ranges from 2.0 to 5.0, and the compensation coefficient is adaptively tuned according to the head deviation. The system continuously iteratively adjusts the speed until the real-time head meets the threshold requirement, forming a dual closed-loop speed regulation logic with speed reduction adjustment superimposed on head closed-loop compensation.

[0059] In step S2, when configuring the safety protection shutdown algorithm, 1.5 times the rated flow rate is set as the maximum effective test flow rate threshold. The system monitors the real-time flow rate of the pump group at a frequency of 100Hz. When the real-time flow rate is greater than 1.5 times the rated flow rate, the active speed regulation output is terminated, the diesel engine throttle opening is locked, the 3-second delay safety shutdown procedure is started, and the pump group is controlled to reduce speed and stop.

[0060] In step S3, the pump set preheating condition is idling for 3-5 minutes. After the diesel engine water temperature, oil pressure, and pump body pressure stabilize, the formal test is started. Throughout the test, a uniform high-frequency sampling frequency of 100Hz is set to simultaneously collect hydraulic condition data of the pump set and power auxiliary data of the diesel engine. The hydraulic condition data includes real-time flow rate, real-time head, real-time speed, and pump inlet and outlet pressure. The diesel engine power auxiliary data includes real-time fuel consumption, output torque, crankshaft speed, exhaust temperature, and load rate. Millisecond-level unified clock timing stamping technology is used to bind the collected data of each group, eliminate timing misalignment and abnormal sampling data, and achieve accurate timing calibration of multi-source data.

[0061] Step S4 includes the following sub-steps:

[0062] S41: Raw data noise reduction preprocessing: The raw sampled data is noise-reduced using a 10-point moving average filtering algorithm. The operating condition curve is smoothed by the filtering formula, and noise data caused by environmental interference, sensor pulse fluctuations and equipment vibration is filtered out, while retaining the true trend of operating condition changes.

[0063] S42: Normalization Conversion of Variable Operating Condition Parameters: Based on the pump similarity law, the data of non-rated operating conditions with variable speed and variable flow are uniformly converted to the standard reference operating conditions through the dedicated conversion formulas for flow rate and head, ensuring the comparability and accuracy of data calculation.

[0064] S43: Multi-dimensional loss correction modeling: Construct a three-dimensional correction loss model that includes volumetric efficiency, hydraulic efficiency, and mechanical efficiency, and obtain the total loss efficiency of the pump set by combining the three types of efficiency; the correction coefficients of the three types of efficiency are all obtained by adaptive fitting of the pump set's factory curve and real-time operating conditions, which can accurately compensate for various power losses caused by pump body medium leakage, water flow hydraulic friction impact, and mechanical transmission friction, and adapt to the loss characteristics of the full flow operating conditions.

[0065] S44: Real-time input power precision calculation: Combining hydraulic effective power and comprehensive loss efficiency across all dimensions, and matching water density, gravitational acceleration, real-time operating flow rate, and real-time operating head parameters, it accurately calculates the actual real-time input power of the diesel engine under various flow conditions, avoiding errors caused by ideal operating condition calculations, and adapting to various variable operating condition test scenarios.

[0066] Step S5 includes the following sub-steps:

[0067] S51: High-precision PQ characteristic curve fitting: The least squares method is used to fit the discrete flow-power data of the whole flow. By iteratively solving the polynomial fitting coefficient, a continuous and smooth PQ characteristic curve is generated. Abnormal operating points are automatically eliminated during the process to strictly ensure the accuracy of curve fitting. The fitting determination coefficient is not less than 0.995, which meets the requirements of high-precision extreme value identification.

[0068] S52: Joint Criterion Identification of Extreme Points: The first derivative of the fitted continuous PQ curve is calculated, and the condition that the first derivative equals 0 is used as the initial judgment condition for suspected extreme points; then the second derivative is used for precise verification. When the second derivative is less than 0, it is determined to be a power maximum point, and when the second derivative is greater than 0, it is determined to be a power minimum point.

[0069] S53: Precise calibration of extreme points across the entire flow range: Traverses the entire effective flow range from 0 to 1.5Qn, eliminates invalid operating conditions such as insufficient head, exceeding the range, and unstable operating conditions, performs secondary verification to select the unique true maximum power point within the range, records the corresponding operating parameters simultaneously, generates a standardized test report, and completes the rapid determination of extreme power points.

[0070] A rapid determination system for full-flow extreme power points of diesel engine fire pump sets includes a benchmark modeling and solidification module, a zone-level control module, a multi-source data synchronous acquisition and calibration module, a data correction and power calculation module, and an extreme value identification and calibration module.

[0071] The benchmark modeling and solidification module is used to combine industry standards and specifications, the inherent design parameters of the pump set under test, and factory test data to verify the compliance of rated operating condition parameters, pre-set and solidify the core benchmark parameters of the pump set, construct a three-dimensional operating condition mapping model covering the entire effective test range, and establish a standardized and unified test benchmark.

[0072] The interval-level control module divides the pump set into multiple full-flow test condition intervals based on the rated flow rate. It matches and adapts closed-loop control strategies, iterative speed regulation logic and safety constraint protection mechanisms for different flow condition intervals. It achieves graded, precise, adaptive control and over-limit safety protection for rated flow intervals, over-rated flow intervals, safety constraint verification intervals and over-test range intervals, ensuring that the full-flow test process is stable, controllable and safe.

[0073] The multi-source data synchronous acquisition and calibration module is used to perform full flow gradient testing after the pump set has been preheated and stabilized. It synchronously acquires the hydraulic operating parameters of the pump set and the power operating parameters of the diesel engine. It eliminates the sampling timing deviation of multi-source data through timing alignment calibration to ensure the synchronization and consistency of test data.

[0074] The data correction and power calculation module is used to perform noise reduction and purification preprocessing on the raw collected data, complete the normalization correction of the variable operating condition parameters according to the pump similarity law, and build a loss correction model in combination with the multi-dimensional loss characteristics of the pump group to accurately calculate the real-time input power of the diesel engine under each test condition.

[0075] The extreme value identification and calibration module is used to construct a continuous flow-power characteristic curve based on the full-flow discrete flow-power test data through high-order polynomial fitting. Relying on the joint criterion of high-order derivatives, it accurately identifies the extreme value characteristics of the curve, eliminates abnormal and invalid operating condition data, and finally calibrates the unique true power maximum point within the effective test flow range, thus completing the rapid and accurate determination of the extreme power point of the pump group at full flow.

[0076] like Figure 1 As shown, this invention provides a method for rapid determination of the extreme power point of a diesel engine fire pump set at full flow rate. An embodiment is as follows:

[0077] S1. Presetting and standardizing pump set reference parameters

[0078] In the early stages of testing, the equipment's baseline parameters were preset, parameters were verified, and a working condition database was constructed. Based on the mandatory industry standards GB 6245 "Fire Pumps" and GB 50974 "Technical Specification for Fire Water Supply and Hydrant Systems", and combined with the inherent parameters of the diesel engine fire pump set under test from the factory test report and design drawings, the core baseline parameters of the pump set were preset and solidified. The parameters were standardized and calibrated to eliminate the impact of parameter deviations on subsequent working condition adjustments, power calculations, and extreme value calibrations, providing a unified and standardized baseline for the entire testing process.

[0079] 1. Preset core baseline parameters: Rated flow rate Qn (m³) 3 Rated head Hn (m) and rated speed Nn (r / min);

[0080] 2. Benchmark Parameter Verification Formula: The hydraulic matching verification mechanism under rated operating conditions of the pump set is adopted. The hydraulic efficiency of the pump set under rated operating conditions must meet the industry standard constraints. The verification formula is as follows: In the formula: The density of clean water at room temperature is fixed at 1000 kg / m³. 3 ; The acceleration due to gravity is fixed at 9.8 m / s². 2 ; Rated flow rate of the pump set (m³) 3 / h); Rated head of the pump unit (m); Rated shaft power of the pump unit (kW); Rated efficiency. Verification standard: Rated efficiency of the pump unit under test. The pump set must achieve a design efficiency of ≥98% of the rated efficiency. If this requirement is not met, the pump set is considered to have an initial fault, the test process is terminated, the equipment problem is investigated, and the pump set is recalibrated. Only after the calibration is passed can the formal test process begin.

[0081] 3. Construction and Consolidation of the QNH Three-Dimensional Operating Condition Mapping Table: Based on the pump set similarity law, covering the full effective test flow range of 0~1.5Qn and the full speed adjustment range of 60%Nn~100%Nn, a standardized QNH three-dimensional operating condition mapping table is constructed through simulation fitting and factory test data calibration. The table uses flow rate Q and speed N as independent variables and head H as the dependent variable, storing each set of precisely corresponding standard operating condition data. The data accuracy is retained to 4 decimal places. The system is consolidated before testing, providing a precise reference for subsequent iterative speed adjustment and operating condition deviation correction in the excess flow range.

[0082] S2, Full Flow Range Division and Inter-range Dynamic Control Algorithm Modeling

[0083] Based on the preset rated flow rate Qn as the interval division benchmark, and combined with the standard test condition boundary requirements of diesel engine fire pump sets, the full-flow test condition of the pump set is precisely divided into four independent and non-overlapping operating condition intervals. Considering the nonlinear variation characteristics and safety risk levels of flow rate, head, and power in each interval, a customized closed-loop control algorithm, speed adjustment iterative function, safety constraint criteria, and protection logic are designed to achieve millisecond-level dynamic adaptive adjustment under different operating conditions, balancing test accuracy, response speed, and equipment operational safety.

[0084] 2.1 Rated flow range (0≤Q≤Qn): Constant speed PID control algorithm

[0085] This range represents the standard operating range of the pump unit, covering flow rates from zero to the rated full flow. The pump unit exhibits good linearity in its hydraulic and power output characteristics, and operates stably. This range employs a parameter-self-tuning, constant-speed closed-loop PID control strategy. The core control objective is to eliminate diesel engine speed fluctuations, ensuring the speed remains constant at the rated speed Nn throughout the entire range. This completely avoids detection errors in hydraulic and power parameters caused by speed deviations, guaranteeing the stability and accuracy of test data within the rated operating range.

[0086] Speed ​​PID control algorithm formula:

[0087] In the formula: Let t be the real-time output speed (r / min) of the diesel engine at time t. This is the real-time deviation value of the rotational speed, which is the difference between the rated rotational speed and the actual collected rotational speed. The pump unit speed is collected in real time by the sensor; This is a proportionality coefficient, ranging from 0.8 to 1.5, and is adaptively tuned according to the pump unit model. The integral time constant, with a value ranging from 0.05 to 0.2 s, is used to eliminate steady-state speed deviation. The differential time constant, ranging from 0.01 to 0.05 s, is used to suppress speed overshoot and instantaneous fluctuations. Through the above-mentioned PID closed-loop continuous adjustment, the speed fluctuation in this range can be strictly controlled within ±5 r / min, ensuring stable operation and no data drift throughout the rated working condition.

[0088] 2.2 Flow Rate Exceeding Rated Limits (Q≥1.1Qn): Iterative Speed ​​Decrease Algorithm Based on Table Lookup

[0089] This range represents a non-standard operating condition exceeding the rated flow rate, with the flow rate exceeding 1.1 times the rated flow rate. This causes a surge in internal water velocity and a significant increase in hydraulic losses, resulting in a strong non-linear variation in head and power. Fixed-speed control would lead to operating instability and distorted power detection. Therefore, a high-speed decreasing iterative program was initiated, utilizing a pre-fixed QNH three-dimensional operating condition mapping table to achieve overshoot-free, high-response iterative speed regulation. The system's single-condition adjustment response time was strictly enforced to ≤0.5s, meeting rapid testing requirements.

[0090] 1. Core formula for iterative speed adjustment:

[0091] In the formula: The real-time running speed (r / min) for the kth iteration; Adjust the rotation speed (r / min) for the target of the (k+1)th iteration; To fix the speed adjustment step size, a preset step size of 5~10 r / min is used according to the power level of the pump group. Small step size is used for small power pump groups and large step size is used for large power pump groups to avoid sudden speed shock. The dimensionless flow correction coefficient is the real-time flow rate corresponding to the k-th iteration. It is accurately obtained by querying the QNH three-dimensional mapping table for real-time flow rate. The larger the flow rate, the larger the correction coefficient, and the speed reduction rate increases synchronously.

[0092] 2. Iteration Termination and Loop Logic: After each iteration, the system automatically compares the real-time operating parameters (Q, N, H) with the standard operating parameters in the 3D mapping table and calculates the relative deviation. When the combined operating condition deviation of the three parameters is ≤2%, the operating condition is considered stable, and the iteration is terminated; if the deviation exceeds the standard, the iteration continues. The single iteration cycle is set to ≤0.1s, and a maximum of 5 iterations are required to achieve operating condition convergence, ensuring that the overall response time is strictly ≤0.5s, achieving ultra-fast operating condition matching.

[0093] 3. Adaptive control logic: Within the range of flow exceeding the rated flow, the flow rate and speed exhibit a negatively correlated adaptive matching relationship. The larger the real-time flow rate, the more the system automatically amplifies the flow correction coefficient, increases the speed reduction, and accurately matches the nonlinear operating characteristics of the pump set with high flow rate, low head, and high loss. This effectively avoids abnormal problems such as diesel engine power overload and pump set surge under high flow conditions, ensuring the stability of extreme operating condition tests.

[0094] 2.3 Safety constraint verification interval (1.1Qn≤Q≤1.5Qn): Head threshold adaptive speed regulation algorithm

[0095] The range of 1.1Qn to 1.5Qn represents the permissible extreme safety operating condition range for testing, falling within the legally valid test boundary. Within this range, the pump head decays rapidly, making it highly susceptible to problems such as excessively low head, hydraulic efficiency failure, and distorted power data. There is also a risk of equipment overload damage. This range incorporates a closed-loop adaptive speed control algorithm based on iterative speed reduction, superimposed with a lower head limit safety constraint, forming a dual closed-loop control logic of "speed reduction + head compensation." This ensures the integrity of the extreme operating condition test while strictly adhering to the bottom lines of equipment safety and data validity.

[0096] 1. Safety constraint determination formula:

[0097] In the formula: The pump head (m) is collected in real time at time t. The minimum effective head threshold for fire pump sets, as specified in GB 6245 standard, is a mandatory safety constraint value in the industry. If the head is lower than this threshold, the test condition is deemed invalid, and the equipment is at risk of failure.

[0098] 2. Head Adaptive Compensation Speed ​​Regulation Function: The system monitors the head parameters in real time, and when it detects... In the event of an invalid operating condition, the automatic speed increase compensation mechanism is immediately triggered. The compensation calculation formula is as follows: In the formula: For speed compensation increment (r / min); This is the head closed-loop compensation coefficient, ranging from 2.0 to 5.0. It is adaptively tuned based on the head deviation; the larger the deviation, the stronger the compensation. The system corrects the operating speed in real time and continuously iterates until the head meets the requirements. Constraints were applied to restore valid test conditions.

[0099] 3. Continuous control logic within the range: When the flow rate is stably maintained within the safety verification range of 1.1Qn~1.5Qn, the system continuously executes the dual closed-loop control of "flow rate adaptive speed reduction + real-time head closed-loop compensation", which not only ensures full coverage testing of extreme flow conditions, but also avoids test failure and equipment damage caused by excessive head attenuation, thus achieving a balance between safety, integrity and accuracy.

[0100] 2.4 Out of test range (Q > 1.5Qn): Safety protection shutdown algorithm

[0101] Based on industry standard test boundary requirements, a maximum effective test traffic threshold is set. The system monitors flow conditions in real time at a frequency of 100Hz and continuously determines flow boundary conditions. If a sudden surge in flow occurs, it meets the following criteria: When the pump exceeds its operating range, the hardware and software linkage safety protection mechanism is immediately triggered: all active speed regulation outputs are terminated instantly, the diesel engine throttle opening is locked, a 3-second delayed safety shutdown procedure is started simultaneously, and the pump is gradually decelerated and shut down to avoid equipment impact caused by sudden stop, completely eliminate safety risks such as pump overspeed, overload, and cavitation damage, and complete safety protection for the over-range operating condition.

[0102] S3. Pump unit start-up / stop operation and synchronous acquisition of all-dimensional data.

[0103] After completing the initial parameter calibration and algorithm initialization, the diesel engine fire pump set was started and allowed to idle for 3-5 minutes for preheating. Once the diesel engine water temperature, oil pressure, and pump body pressure stabilized without fluctuations, the full-flow gradient test was officially initiated. Throughout the test, the interval-based closed-loop control algorithm from step 2 was synchronously applied, and a 100Hz high-frequency unified sampling frequency was set to synchronously acquire pump set hydraulic data and diesel engine power auxiliary data at millisecond levels. High-precision time stamp alignment technology was used to ensure that all operating condition data corresponded one-to-one in time, eliminating time sequence deviations.

[0104] 1. Pump set hydraulic operating data: real-time flow rate Q, real-time head H, real-time speed N, pump inlet and outlet pressure;

[0105] 2. Diesel engine operating auxiliary data: real-time fuel consumption, output torque, crankshaft speed, exhaust temperature, and load rate of the diesel engine;

[0106] 3. Data Synchronization and Timing Calibration Algorithm: To solve the problem of asynchronous sampling by multiple sensors, the system adopts a unified clock timing stamping technology. Each set of flow rate, head, speed, torque, and temperature data is bound to the same millisecond-level timing code, which automatically eliminates timing misalignment and abnormal sampling data, ensuring accurate matching between operating condition data and power data. This eliminates data acquisition errors from the source and provides high-quality raw data support for subsequent accurate power calculation.

[0107] S4. Data Preprocessing and Fully Corrected Real-Time Power Calculation

[0108] To address the issues of transient pulse interference, small fluctuations, and random noise in the raw data collected by sensors, standardized data preprocessing was first performed to reduce noise, filter, and calibrate the data. Then, based on the hydraulic similarity law for pumps, variable operating condition parameters were converted. Combining the inherent loss characteristics of the pump set (volume, hydraulic, and mechanical), real-time loss correction coefficients were fitted to construct a multi-dimensional loss correction model. Finally, the real-time input power of the diesel engine under different flow conditions was accurately calculated, solving the problems of large errors and poor adaptability of traditional calculation methods.

[0109] 4.1 Raw Data Preprocessing Algorithm

[0110] A 10-point moving average filtering algorithm is used to preprocess the raw sampling data for noise reduction, effectively filtering out invalid noise data caused by environmental interference, sensor pulse fluctuations, and equipment vibration, thus smoothing the operating condition curve. Filtering calculation formula: In the formula: This is the raw sampled data for a single frame; The number of sliding sampling points is fixed at n=10; This is the filtered, effective operating condition data. The filtered data retains the true trend of operating condition changes, eliminates instantaneous outliers, and significantly improves data stability.

[0111] 4.2 Hydraulic similarity conversion formula for pump sets

[0112] The testing process involved numerous non-rated operating conditions with varying speeds and flow rates. Therefore, it was necessary to rely on pump similarity laws to normalize and convert the operating parameters, transforming all operating data to a standard reference condition to ensure data comparability and calculation accuracy. The core conversion formula is as follows:

[0113] Traffic conversion: Head conversion:

[0114] 4.3 Multidimensional Loss Correction Function

[0115] In actual operation, diesel engine fire pump sets experience multiple energy losses. Directly using ideal hydraulic power calculations will result in significant errors. Therefore, three core loss parameters of the pump set are introduced, and a three-dimensional corrected loss model adapted to all operating conditions is constructed based on real-time operating condition fitting and correction to accurately reproduce the real power loss.

[0116] Total loss efficiency:

[0117] In the formula: This is the volumetric efficiency correction factor, used to correct for flow loss caused by backflow of the medium inside the pump body and gap leakage. It increases slightly with the increase of flow rate. This is a hydraulic efficiency correction coefficient, used to correct hydraulic losses caused by water flow friction, eddies, and impacts within the pump. Losses increase significantly in the range exceeding the rated flow, while the coefficient decreases slightly. These are mechanical efficiency correction coefficients used to correct for mechanical friction losses in bearings, mechanical seals, and transmission structures, dynamically fitting changes in rotational speed. All three types of coefficients are obtained through adaptive fitting of the pump set's factory performance curves and real-time operating parameters, achieving accurate correction across all flow conditions.

[0118] 4.4 Core Formula for Calculating Diesel Engine Input Power

[0119] Calculate the real-time input power of the diesel engine by combining the effective hydraulic power and loss correction:

[0120]

[0121] In the formula: The real-time effective input power of the diesel engine (kW); The density of water (1000 kg / m³) 3 ); The acceleration due to gravity (9.8 m / s²) 2 Q represents the real-time operating flow rate after filtering (m³). 3 / h); H is the real-time operating head (m) after filtering. This formula represents the real-time, comprehensive loss efficiency under all operating conditions. It integrates the effective hydraulic power with all-dimensional equipment losses, enabling accurate calculation of the diesel engine's actual input power under any flow rate condition.

[0122] S5, Power Curve Fitting and Intelligent Calibration of Extreme Power Points

[0123] Based on massive discrete operating condition data (flow-power corresponding data pairs) collected from full-flow gradient testing, a continuous, smooth, and high-precision power-flow (PQ) characteristic curve is constructed using the least squares fifth-order polynomial fitting technique, eliminating fluctuation errors in discrete data. Combining first- and second-order derivatives with joint mathematical criteria, the curve inflection points and extreme value locations are automatically identified, accurately screening critical operating points across the entire flow range. Ultimately, the unique true power extreme point within the effective operating range of the entire flow range is calibrated, achieving intelligent and precise determination of extreme power points.

[0124] 5.1 PQ Characteristic Curve Fitting Algorithm

[0125] Using a fifth-order high-order polynomial to fit discrete operating data can perfectly adapt to the nonlinear variation characteristics of the pump group's PQ curve, avoiding the problems of insufficient accuracy and severe distortion caused by low-order polynomial fitting. The continuous characteristic curve fitting formula is as follows: In the formula: The coefficients are polynomial fitting coefficients, obtained by iteratively solving massive discrete working condition data using the least squares method. The fitting process automatically removes outlier points, ultimately ensuring the accuracy of the curve fitting determination coefficient R0. 2 The value is ≥0.995, and the fitting accuracy is ≥99.5%, which fully meets the requirements for extreme value identification accuracy.

[0126] 5.2 Criteria for Identifying Curve Inflection Points and Extreme Points

[0127] 1. Initial Determination of First-Order Derivative Extrema: Take the first derivative of the fitted continuous PQ curve to obtain the slope variation pattern. The formula for the first derivative is: .when When the slope of the curve is zero, the corresponding flow point is a suspected extreme value operating point. The system automatically collects all suspected extreme value points and completes the preliminary screening of extreme value intervals.

[0128] 2. Precise Verification of the Second Derivative: Differentiate the first derivative result again to accurately determine the extremum type. Second derivative formula: Decision logic: If The curve is convex at this point, which is the point of maximum power and a key extreme point for fire pump set testing; if The curve dips at this point, which is the power minimum point. This is only used for data recording and is not used as the core extreme value calibration result.

[0129] 5.3 Calibration of Extreme Points in Full Flow

[0130] The system automatically traverses the full flow effective operating range from 0 to 1.5Qn, and, in conjunction with prior safety constraints, automatically eliminates invalid operating points such as insufficient head, exceeding the range, and unstable operating conditions. It performs secondary verification and comparison on all valid suspected extreme points, and selects the unique true maximum power point within the full flow range. Simultaneously, it records the flow rate, head, speed, and power parameters corresponding to this extreme point, generates a standardized extreme value test report, and finally completes the rapid and accurate determination and calibration of the extreme power point of the diesel engine fire pump set across the entire flow range.

Claims

1. A method for rapid determination of the extreme power point of a diesel engine fire pump set at full flow rate, characterized in that, Includes the following steps: S1: Based on the mandatory standards of the fire pump industry, combined with the inherent design parameters and factory test data of the diesel engine fire pump set under test, the core benchmark parameters of the pump set are pre-set and solidified, the compliance verification of the rated operating condition parameters is completed, the QNH three-dimensional operating condition mapping table covering the entire effective test range is constructed and solidified, and a unified standardized test benchmark is established. S2: Based on the rated flow rate of the pump set, four full-flow test condition intervals are divided. According to the hydraulic and power characteristics of each interval, corresponding control algorithms, speed iterative adjustment functions, and safety constraint protection logic are configured, specifically as follows: Rated flow range: 0 ≤ flow rate ≤ rated flow rate, configured with a self-tuning constant speed PID closed-loop control algorithm; Exceeding rated flow range: Flow rate ≥ 1.1 times rated flow rate, based on the pre-cured QNH three-dimensional operating condition mapping table, a lookup table iterative decreasing speed regulation algorithm is configured; Safety constraint verification range: 1.1 times rated flow rate ≤ flow rate ≤ 1.5 times rated flow rate. Iterative speed regulation is based on the QNH three-dimensional working condition mapping table, and a dual closed-loop adaptive speed regulation algorithm with speed reduction superimposed on head compensation is configured. Exceeding the test range: Traffic flow > 1.5 times the rated traffic flow, configure a safety protection shutdown algorithm; S3: After preheating and stabilizing the diesel engine fire pump set, conduct full flow gradient tests based on the control algorithms of each interval, and simultaneously collect hydraulic condition data of the pump set and power auxiliary data of the diesel engine. Complete the timing calibration of multi-source data through timing stamp alignment technology to eliminate sampling timing deviation. S4: The original collected data is preprocessed for noise reduction using a sliding filter algorithm. The normalization conversion of parameters under different working conditions is completed based on the pump similarity law. A loss correction model is constructed by combining the multi-dimensional loss characteristics of pump volume, hydraulics, and mechanicals to calculate the real-time input power of the diesel engine under each working condition. S5: The least squares method is used to fit the discrete flow-power data of the whole flow rate using a fifth-order polynomial to generate a continuous PQ characteristic curve. The extreme points of the curve are identified by the first and second derivatives combined with mathematical criteria. After eliminating invalid operating points, the unique true power maximum point in the effective range of 0 to 1.5 times the rated flow rate is calibrated, and the extreme power point of the whole flow rate is determined rapidly.

2. The method for rapid determination of the extreme power point of the full flow rate of a diesel engine fire pump set according to claim 1, characterized in that, In step S1, a three-dimensional QNH operating condition mapping table covering the entire effective test range is constructed and solidified. Specifically, this includes: based on the pump group similarity law, covering the entire effective test flow range of 0 to 1.5 times the rated flow and the entire speed adjustment range of 60% to 100% of the rated speed, the mapping table is constructed by using simulation fitting combined with factory test data calibration; the mapping table uses flow rate and speed as independent variables and head as dependent variable, stores the standard operating condition data of each group, and the data accuracy retains 4 decimal places. The system is solidified before testing and used for iterative speed adjustment and operating condition deviation correction in the over-rated flow range.

3. The method for rapid determination of the extreme power point of the full flow rate of a diesel engine fire pump set according to claim 1, characterized in that, In step S2, when configuring the parameter self-tuning constant speed PID closed-loop control algorithm, a constant speed closed-loop control strategy is adopted to maintain the rated speed of the pump group. The algorithm includes three control dimensions: proportional, integral, and derivative. The adaptive tuning range of the proportional coefficient is 0.8~1.5, the integral time constant range is 0.05~0.2s, and the derivative time constant range is 0.01~0.05s. Within the rated flow range, the pump speed fluctuation is controlled within ±5 r / min.

4. The method for rapid determination of the extreme power point of the full flow rate of a diesel engine fire pump set according to claim 1, characterized in that, In step S2, when configuring the lookup table iterative speed reduction algorithm, the pump group adaptive speed iterative adjustment is performed based on the pre-cured QNH three-dimensional working condition mapping table, and the speed reduction adjustment logic is adopted; the speed adjustment step size is 5~10 r / min, and the corresponding step size is matched according to the pump group power level. The system obtains the dimensionless flow correction coefficient by querying the three-dimensional operating condition mapping table based on the real-time flow. The larger the real-time flow, the larger the flow correction coefficient and the greater the speed reduction. The single iteration cycle is ≤0.1s, the maximum number of iterations is 5, the iteration is terminated when the comprehensive deviation of real-time flow rate, speed and head is ≤2%, and the overall adjustment response time of a single working condition is ≤0.5s.

5. The method for rapid determination of the extreme power point of the full flow rate of a diesel engine fire pump set according to claim 1, characterized in that, In step S2, when configuring the dual closed-loop adaptive speed regulation algorithm with speed reduction superimposed on head compensation, iterative speed regulation based on the pre-fixed QNH three-dimensional working condition mapping table is completed, and 0.65 times the rated head is set as the minimum effective head constraint threshold; the system monitors the pump unit's operating head in real time, and when the real-time head is lower than the threshold, it triggers adaptive speed increase compensation; the head closed-loop compensation coefficient ranges from 2.0 to 5.0, and the compensation coefficient is adaptively tuned according to the head deviation; The system continuously iterates and adjusts the speed until the real-time head meets the threshold requirement, forming a dual closed-loop speed regulation logic that combines speed reduction regulation with head closed-loop compensation.

6. The method for rapid determination of the extreme power point of the full flow rate of a diesel engine fire pump set according to claim 1, characterized in that, In step S2, when configuring the safety protection shutdown algorithm, 1.5 times the rated flow rate is set as the maximum effective test flow rate threshold. The system monitors the real-time flow rate of the pump group at a frequency of 100Hz. When the real-time flow rate is greater than 1.5 times the rated flow rate, the active speed regulation output is terminated, the diesel engine throttle opening is locked, the 3-second delay safety shutdown procedure is started, and the pump group is controlled to reduce speed and stop.

7. The method for rapid determination of the extreme power point of the full flow rate of a diesel engine fire pump set according to claim 1, characterized in that, In step S3, the pump set preheating condition is idling for 3-5 minutes. After the diesel engine water temperature, oil pressure, and pump body pressure stabilize, the formal test is started. Throughout the test, a uniform high-frequency sampling frequency of 100Hz is set to simultaneously collect hydraulic condition data of the pump set and power auxiliary data of the diesel engine. The hydraulic condition data includes real-time flow rate, real-time head, real-time speed, and pump inlet and outlet pressure. The diesel engine power auxiliary data includes real-time fuel consumption, output torque, crankshaft speed, exhaust temperature, and load rate. Millisecond-level unified clock timing stamping technology is used to bind the collected data of each group, eliminate timing misalignment and abnormal sampling data, and achieve accurate timing calibration of multi-source data.

8. The method for rapid determination of the extreme power point of the full flow rate of a diesel engine fire pump set according to claim 1, characterized in that, Step S4 includes the following sub-steps: S41: Raw data noise reduction preprocessing: The raw sampled data is noise-reduced using a 10-point moving average filtering algorithm. The operating condition curve is smoothed by the filtering formula, and noise data caused by environmental interference, sensor pulse fluctuations and equipment vibration is filtered out, while retaining the true trend of operating condition changes. S42: Normalization Conversion of Variable Operating Condition Parameters: Based on the pump similarity law, the data of non-rated operating conditions with variable speed and variable flow are uniformly converted to the standard reference operating conditions through the dedicated conversion formulas for flow rate and head, ensuring the comparability and accuracy of data calculation. S43: Multi-dimensional loss correction modeling: Construct a three-dimensional correction loss model that includes volumetric efficiency, hydraulic efficiency and mechanical efficiency, and obtain the total loss efficiency of the pump set by combining the three types of efficiency; The correction coefficients of the three types of efficiency are all obtained by adaptive fitting of the pump set factory curve and real-time operating conditions, which can accurately compensate for various power losses caused by pump body medium leakage, water flow hydraulic friction impact and mechanical transmission friction, and adapt to the loss characteristics of full flow conditions. S44: Real-time input power precision calculation: Combining hydraulic effective power and comprehensive loss efficiency across all dimensions, and matching water density, gravitational acceleration, real-time operating flow rate, and real-time operating head parameters, it accurately calculates the actual real-time input power of the diesel engine under various flow conditions, avoiding errors caused by ideal operating condition calculations, and adapting to various variable operating condition test scenarios.

9. A method for rapid determination of the extreme power point of a diesel engine fire pump set at full flow rate, as described in claim 1, is characterized in that... Step S5 includes the following sub-steps: S51: High-precision PQ characteristic curve fitting: The least squares method is used to fit the discrete flow-power data of the whole flow. The polynomial fitting coefficients are solved iteratively to generate a continuous and smooth PQ characteristic curve. Abnormal operating points are automatically eliminated during the process to strictly ensure the accuracy of curve fitting. The fitting determination coefficient is not less than 0.995, which meets the requirements of high-precision extreme value identification. S52: Joint Criterion Identification of Extreme Points: The first derivative of the fitted continuous PQ curve is calculated, and the condition that the first derivative equals 0 is used as the initial judgment condition for suspected extreme points; then the second derivative is used for precise verification. When the second derivative is less than 0, it is determined to be a power maximum point, and when the second derivative is greater than 0, it is determined to be a power minimum point. S53: Precise calibration of extreme points across the entire flow range: Traverses the entire effective flow range from 0 to 1.5Qn, eliminates invalid operating conditions such as insufficient head, exceeding the range, and unstable operating conditions, performs secondary verification to select the unique true maximum power point within the range, records the corresponding operating parameters simultaneously, generates a standardized test report, and completes the rapid determination of extreme power points.

10. A rapid determination system for the extreme power point of the full flow rate of a diesel engine fire pump set, characterized in that, It includes a benchmark modeling and solidification module, a zone-level control module, a multi-source data synchronous acquisition and calibration module, a data correction and power calculation module, and an extreme value identification and calibration module; The benchmark modeling and solidification module is used to combine industry standards and specifications, the inherent design parameters of the pump set under test, and factory test data to verify the compliance of rated operating condition parameters, pre-set and solidify the core benchmark parameters of the pump set, construct a three-dimensional operating condition mapping model covering the entire effective test range, and establish a standardized and unified test benchmark. The segmented and graded control module divides the pump set into multiple full-flow test condition intervals based on the rated flow rate. It matches and adapts closed-loop control strategies, iterative speed regulation logic and safety constraint protection mechanisms for different flow condition intervals. It achieves graded, precise, and adaptive control and over-limit safety protection for rated flow intervals, over-rated flow intervals, safety constraint verification intervals and over-test range intervals, ensuring that the full-flow test process is stable, controllable and safe. The multi-source data synchronous acquisition and calibration module is used to perform a full flow gradient test after the pump set has been preheated and stabilized, synchronously acquire the hydraulic operating parameters of the pump set and the power operating parameters of the diesel engine, and eliminate the sampling time sequence deviation of the multi-source data through the time sequence alignment calibration method to ensure the synchronization and consistency of the test data. The data correction and power calculation module is used to perform noise reduction and purification preprocessing on the original collected data, complete the normalization correction of the variable working condition parameters according to the pump similarity law, and construct a loss correction model in combination with the multi-dimensional loss characteristics of the pump group to accurately calculate the real-time input power of the diesel engine under each test condition. The extreme value identification and calibration module is used to construct a continuous flow-power characteristic curve based on the full-flow discrete flow-power test data through high-order polynomial fitting, accurately identify the extreme value characteristics of the curve by relying on the joint criterion of high-order derivatives, eliminate abnormal and invalid operating condition data, and finally calibrate the unique true power maximum point within the effective test flow range, thus completing the rapid and accurate determination of the extreme power point of the pump group at full flow.

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