A pipeline matching characteristic high-efficiency double-pump optimization design method and electronic device considering flow fluctuation

Abstract

The application provides a kind of pipeline matching characteristic high-efficiency double pump optimization design method and electronic device considering flow fluctuation, comprising the following steps: obtaining rated operating condition static hydraulic basic parameters, designing basic double suction pump based on rated operating condition static hydraulic basic parameters;Dynamic pipeline resistance model containing flow fluctuation is constructed;Double suction pump is optimized by matching-efficiency double iteration to obtain double suction pump meeting double constraint conditions, wherein the double constraint conditions refer to pipeline matching constraint and hydraulic efficiency constraint of double suction pump, and the problem that the actual operating point of pump deviates from design condition due to fluid fluctuation in existing pipeline, thereby causing dynamic mismatching of pump characteristic curve and pipeline characteristic is solved.

Description

Technical Field

[0001] This invention relates to the field of fluid machinery and industrial pipeline fluid transport systems, specifically to a high-efficiency dual-pump optimization design method and electronic device that considers pipeline matching characteristics for flow fluctuations. Background Technology

[0002] Double-suction centrifugal pumps have core advantages such as large flow rate, symmetrical inlet structure with axial force self-balancing, large inlet flow area, and excellent cavitation resistance. They are widely used in long-distance pipeline transportation scenarios such as urban large-scale water supply, inter-basin water transfer, industrial circulating cooling, and water lifting in water conservancy irrigation areas.

[0003] Currently, the mainstream hydraulic design system for dual-suction pumps in the industry is based on a single constant design condition for deriving static hydraulic parameters and determining the geometry of the impeller and volute. This design system only performs performance verification at a fixed operating point with rated flow and rated head, and the design boundary does not cover the dynamic operating characteristics of the pipeline network. However, actual pipeline systems in engineering generally have continuous flow disturbances: due to frequent valve adjustments, downstream load disturbances, parallel switching of pump sets, and the hydraulic instability of the fluid itself, the flow in the pipeline often exhibits periodic or random dynamic fluctuations. Traditional static design methods do not incorporate the dynamic flow disturbances of the pipeline into the derivation of pump geometric parameters, resulting in a sharp drop in the operating efficiency of dual-suction pumps under fluctuating conditions and an increase in impact losses caused by dynamic and static interference, failing to meet the current industrial requirements for high-efficiency and high-stability operation of conveying systems. Summary of the Invention

[0004] The purpose of this invention is to provide a high-efficiency dual-pump optimization design method and electronic device that takes into account the pipeline matching characteristics of flow fluctuations, and to specifically solve the problem that fluid fluctuations in existing pipelines cause the actual operating point of the pump to deviate from the design conditions, thereby causing a "dynamic mismatch" between the pump characteristic curve and the pipeline characteristics.

[0005] To achieve the above objectives, this technical solution provides a high-efficiency dual-pump optimization design method that considers pipeline matching characteristics and flow fluctuations, including the following steps: S1: Obtain the static hydraulic foundation parameters under rated operating conditions, and design the foundation double-suction pump based on the static hydraulic foundation parameters under rated operating conditions; S2: Construct a dynamic pipeline resistance model with flow fluctuations, in which the dynamic pipeline resistance model introduces a flow fluctuation correction term based on the Darcy-Weisbach equation; S3: Perform matching-efficiency dual-iteration optimization on the basic dual-suction pump to obtain a dual-suction pump that satisfies the dual constraints. Each iteration of the matching-efficiency dual-iteration process is as follows: Based on the pump characteristic curve of the current double-suction pump and the pipeline characteristic curve of the dynamic pipeline resistance model, a pump-pipeline dynamic coupling matching evaluation system is established. The pump-pipeline dynamic coupling matching evaluation system defines the instantaneous operating point stationary relationship between the double-suction pump and the pipeline under fluctuating conditions and the dynamic matching error function. Numerical simulation is used to calculate the head-flow performance curve of the current dual-suction pump. Combined with a dynamic pipeline resistance model, the matching and verification of extreme fluctuation conditions are carried out. If the dynamic matching error exceeds the allowable range, the impeller geometry parameters are adjusted to correct the pump performance curve until the dynamic matching error meets the allowable range to obtain the matched dual-suction pump. High-efficiency wide-condition forward optimization is carried out on the matched dual-suction pump. The high-efficiency wide-condition forward optimization includes impeller velocity coefficient optimization, blade profile optimization, volute throat optimization, and volumetric leakage optimization.

[0006] Compared with existing technologies, this technical solution has the following characteristics and beneficial effects: 1. Based on the Darcy-Weisbach equation, a flow fluctuation correction term is added to build a dynamic pipeline resistance model, which can accurately characterize the time-varying flow inertial head caused by valve regulation, load disturbance, and pump switching. A pump-pipeline dynamic coupling matching evaluation system is established to quantify the degree of hydraulic mismatch under fluctuating conditions through a dynamic matching error function, and the extreme fluctuation conditions are selected for verification. Compared with the traditional static pipeline calculation method that only targets the rated flow, this scheme can completely reproduce the real dynamic hydraulic boundary of the pipeline network, effectively suppress the impact loss, vibration and noise caused by the dynamic mismatch between pump and pipeline under flow fluctuation, and improve the operational stability of the dual-suction pump pipeline transportation system.

[0007] 2. A dual iterative optimization mechanism of matching and efficiency is adopted, simultaneously binding dynamic matching constraints of the pipeline and overall efficiency constraints. This solves the problem of pump HQ curve deviation and matching error exceeding the standard again, which is caused by the traditional serial design of matching first and then optimizing efficiency. After the matching error reaches the standard, positive optimization is carried out from four dimensions: impeller velocity coefficient, blade profile, volute throat, and volumetric seal. This uniformizes the flow velocity gradient in the flow channel, enlarges the volute throat area, reduces seal leakage, widens the pump's high-efficiency operating flow range, improves the actual operating efficiency under the condition of variable flow fluctuation in the pipeline network, and shortens the iterative design cycle of the hydraulic structure.

[0008] 3. Standardized quantitative calculation formulas are provided for everything from basic dual-suction pump parameter calculation, cavitation verification, dynamic matching iteration to multi-dimensional high-efficiency optimization. The entire process can be automatically executed by an electronic device composed of memory and processor. It is compatible with low, medium and high specific speed dual-suction pumps and is widely applicable to urban water supply, inter-basin water transfer, industrial circulating cooling and other scenarios. Cavitation safety verification is completed simultaneously during the design phase. Wide operating conditions and low loss operation can reduce long-term energy consumption. Dynamic hydraulic matching reduces impact wear of moving and static parts, extends the service life of the pump set, effectively reduces equipment operation and maintenance costs, and makes the project more feasible. Attached Figure Description

[0009] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 This is a flowchart of a high-efficiency dual-pump optimization design method considering pipeline matching characteristics and flow fluctuations according to an embodiment of this application; Figure 2 This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of this application. Detailed Implementation

[0010] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with one or more embodiments of this specification. Rather, they are merely examples of apparatuses and methods consistent with some aspects of one or more embodiments of this specification as detailed in the appended claims.

[0011] It should be noted that the steps of the corresponding methods are not necessarily performed in the order shown and described in this specification in other embodiments. In some other embodiments, the methods may include more or fewer steps than described in this specification. Furthermore, a single step described in this specification may be broken down into multiple steps in other embodiments; and multiple steps described in this specification may be combined into a single step in other embodiments.

[0012] Example 1 like Figure 1 As shown, this solution provides a high-efficiency dual-pump optimization design method that considers pipeline matching characteristics and flow fluctuations, including the following steps: S1: Obtain the static hydraulic foundation parameters under rated operating conditions, and design the foundation double-suction pump based on the static hydraulic foundation parameters under rated operating conditions; S2: Construct a dynamic pipeline resistance model with flow fluctuations, in which the dynamic pipeline resistance model introduces a flow fluctuation correction term based on the Darcy-Weisbach equation; S3: Perform matching-efficiency dual-iteration optimization on the basic dual-suction pump to obtain a dual-suction pump that satisfies the dual constraints. Each iteration of the matching-efficiency dual-iteration process is as follows: Based on the pump characteristic curve of the current double-suction pump and the pipeline characteristic curve of the dynamic pipeline resistance model, a pump-pipeline dynamic coupling matching evaluation system is established. The pump-pipeline dynamic coupling matching evaluation system defines the instantaneous operating point stationary relationship between the double-suction pump and the pipeline under fluctuating conditions and the dynamic matching error function. Numerical simulation is used to calculate the head-flow performance curve of the current dual-suction pump. Combined with a dynamic pipeline resistance model, the matching and verification of extreme fluctuation conditions are carried out. If the dynamic matching error exceeds the allowable range, the impeller geometry parameters are adjusted to correct the pump performance curve until the dynamic matching error meets the allowable range to obtain the matched dual-suction pump. High-efficiency wide-condition forward optimization is carried out on the matched dual-suction pump. The high-efficiency wide-condition forward optimization includes impeller velocity coefficient optimization, blade profile optimization, volute throat optimization, and volumetric leakage optimization.

[0013] Regarding step S1 of this plan: First, assuming a constant flow rate, the foundation double-suction pump is designed based on the static hydraulic foundation parameters under rated operating conditions.

[0014] Specifically, step S1 includes the following steps: Obtain the static hydraulic parameters under rated operating conditions, calculate the specific speed based on the static hydraulic parameters under rated operating conditions, and select the motor based on the specific speed. The static hydraulic parameters under rated operating conditions include rated flow rate, head, and speed. The impeller geometry parameters are designed based on the rotational speed, rated flow rate, and head. These parameters include the impeller outer diameter, impeller outlet width, blade outlet angle, and impeller inlet width. The basic double-suction pump is obtained by combining the geometric parameters of the motor and impeller.

[0015] In some embodiments, the impeller geometry parameters are designed based on the Euler equation, the continuity equation, and the velocity triangle, combined with the rotational speed, rated flow rate, and head. The impeller geometry parameters include the impeller outer diameter, impeller outlet width, blade outlet angle, and impeller inlet width.

[0016] In some embodiments, cavitation verification is performed on the basic double-suction pump design, and the overall operating efficiency of the basic double-suction pump is initially estimated by the efficiency decomposition method. If the basic double-suction pump meets the cavitation verification conditions and efficiency conditions, subsequent optimization design is carried out.

[0017] Specifically, the formula for calculating specific speed is as follows:

[0018] Where Q1 is the flow rate on one side (i.e., half of the rated flow rate), in cubic meters per second (m³ / s); H is the head, in meters (m); and n is the rotational speed, in revolutions per minute (r / min). In the "Select Motor Based on Specific Speed" step, the type of double-suction pump is determined based on the specific speed, and a matching motor is selected. For example, when the specific speed is less than 80, it is a low specific speed double-suction pump; when the specific speed is between 80 and 300, it is a medium specific speed double-suction pump; and when the specific speed is between 300 and 500, it is a high specific speed double-suction pump.

[0019] In the step of "designing impeller geometric parameters based on rotational speed, rated flow rate, and head, where impeller geometric parameters include impeller outer diameter, impeller outlet width, blade outlet angle, and impeller inlet width", the impeller outer diameter design formula is derived based on Euler's equation, the geometric correspondence between head and impeller outer diameter is established, the impeller outlet width is calculated by combining the continuity equation, and the blade outlet angle is solved by velocity triangle to regulate the outlet flow matching state and energy conversion efficiency. The geometric parameter design of impeller inlet width is completed simultaneously.

[0020] Specifically, the design formula for the impeller outer diameter is as follows: ; ; ; Where D2 is the impeller outer diameter in millimeters (mm); n is the rotational speed in revolutions per minute (r / min); H is the head in meters (m); g is the acceleration due to gravity, usually taken as 9.81 m / s²; σ is the blade displacement coefficient, dimensionless. V is the flow coefficient, dimensionless; m2 u1 is the impeller outlet axial velocity, in meters per second (m / s); u2 is the impeller outlet circumferential velocity, in meters per second (m / s).

[0021] The impeller outlet width is determined by the continuity equation, and the design formula is as follows: ; Where b2 is the impeller outlet width in millimeters (mm); Q0 is the rated flow rate in cubic meters per hour (m³ / h); and D2 is the impeller outer diameter in millimeters (mm). is the flow coefficient, dimensionless; u2 is the impeller outlet circumferential velocity, in meters per second (m / s).

[0022] The blade exit angle is determined by the velocity triangle and is used to control the exit flow matching and energy conversion efficiency. The design formula is as follows:

[0023] Where β2 is the blade exit angle in degrees (°); σ is the blade displacement coefficient, dimensionless; u2 is the impeller exit circumferential velocity in meters per second (m / s); V m2The velocity at the impeller outlet shaft surface is expressed in meters per second (m / s). The design formula for the impeller inlet width is as follows:

[0024] Where b1 is the impeller inlet width in millimeters (mm); D1 is the impeller inlet diameter in millimeters (mm); Q0 is the rated flow rate in cubic meters per hour (m³ / h); V m1 The average inlet velocity is measured in meters per second (m / s), typically ranging from 0.8 to 1.2 m / s.

[0025] In the step of "performing cavitation verification on the design of the foundation double-suction pump", the required net positive suction head (NPSH) of the foundation double-suction pump is calculated, and the required NPSH is compared with the effective NPSH of the device. If the effective NPSH of the device is greater than the required NPSH, then the current foundation double-suction pump meets the cavitation verification conditions.

[0026] Specifically, the formula for calculating the required net positive suction head (NPSH) is as follows: ; Among them NPSH r The required net positive suction head (NPSH) is expressed in meters (m). p in This is the absolute pressure at the pump inlet, measured in Pascals (Pa). V 1 represents the fluid velocity at the pump inlet, in meters per second (m / s). p v This is the saturated vapor pressure of the fluid at the current temperature, expressed in Pascals (Pa). p The density is expressed in kilograms per cubic meter (kg / m³). g This is the acceleration due to gravity, usually taken as 9.81 m / s².

[0027] In some embodiments, the cavitation test bar is set as NPSH r NPSH is the required net positive suction head, expressed in meters (m). a This represents the effective net positive suction head (NPSH) of the device.

[0028] In the step of "preliminary estimation of the overall operating efficiency of the foundation double-suction pump by efficiency decomposition method", the hydraulic efficiency, volumetric efficiency and mechanical efficiency of the foundation double-suction pump are calculated. The overall operating efficiency is obtained by multiplying the hydraulic efficiency, volumetric efficiency and mechanical efficiency. If the overall operating efficiency is within the set value, the foundation double-suction pump meets the efficiency condition.

[0029] Specifically, the formula for the efficiency decomposition method is: ; Where η is the overall machine operating efficiency, which is dimensionless; η h η is the hydraulic efficiency, dimensionless. v For volumetric efficiency, dimensionless; η m For mechanical efficiency, dimensionless.

[0030] Regarding step S2 of this plan: This solution constructs a dynamic pipeline resistance model incorporating flow fluctuations to quantify the real-world flow fluctuation effects in engineering projects into calculable, benchmarkable, and iteratively optimized dynamic hydraulic boundary conditions. Traditional pipeline design relies solely on the Darcy-Weisbach equation to construct steady-state resistance characteristics, calculating only pipeline resistance under constant flow conditions, assuming the operating condition remains stable at the rated point. However, in actual pipeline networks, valve adjustments, load disturbances, and pump switching all induce periodic flow fluctuations. The water flow within the pipe exhibits inertia, generating additional inertial head during flow changes. The instantaneous head required by the pipeline is not the value calculated using the steady-state formula. Therefore, this solution introduces a flow fluctuation correction term into the dynamic pipeline resistance model, enabling the calculation of the instantaneous head requirement under arbitrary instantaneous flow and fluctuation amplitude, realistically reproducing the hydraulic characteristics of the pipeline under variable flow conditions. Furthermore, because this solution constructs a dynamic pipeline resistance model, a pump-pipeline dynamic coupling matching evaluation system capable of characterizing and establishing the instantaneous operating point equilibrium relationship under fluctuating conditions can be subsequently built.

[0031] Specifically, the dynamic pipeline resistance model is as follows: ; ; Where H sys (t) represents the instantaneous demand head of the pipeline, in meters (m); Hs represents the static head, in meters (m); K represents the pipeline resistance coefficient, in seconds² per meter (s² / m); Q(t) represents the instantaneous flow rate, in cubic meters per hour (m³ / h); Q0 represents the rated flow rate, in cubic meters per hour (m³ / h); δ(t) represents the flow fluctuation coefficient, dimensionless.

[0032] In some embodiments, the flow fluctuation correction term is used to characterize periodic flow fluctuations caused by valve regulation, load disturbances, and hydraulic instability during pipeline operation.

[0033] Regarding step S3 of this plan: This solution employs a dual-iterative optimization approach for the basic double-suction pump, involving matching verification, efficiency optimization, and reverse validation within each iteration. It's important to note that the core geometric parameters of the double-suction pump (impeller outer diameter, outlet width, blade outlet angle, volute throat area, etc.) have a bidirectional impact: they alter the pump's HQ (Head-Flow Rate) curve shape (determining pipeline matching accuracy) and directly affect internal friction, impact, and leakage losses (determining overall efficiency). A typical problem with traditional sequential designs is that parameters are adjusted first to meet matching error standards, followed by separate efficiency optimization. However, efficiency optimization modifies the impeller and volute geometry, causing the pump's HQ curve to shift, and the previously acceptable matching error exceeds limits. This solution's dual-iterative approach places both constraints within the same cycle. After efficiency optimization, the dynamic matching error is immediately verified, ensuring that parameter adjustments to improve efficiency do not compromise pipeline matching performance. This mechanism avoids the dilemma of achieving matching standards but failing efficiency, or improving efficiency but exceeding matching limits. This solution's matching-efficiency dual iteration deeply binds the dynamic matching constraints of the pipeline with the efficiency optimization of the pump itself. All parameter adjustments are always based on the actual dynamic operating conditions of the pipeline network, ultimately improving the pump's actual operating efficiency in the actual pipeline network, rather than just the theoretical efficiency under laboratory rated conditions, thus having greater engineering application value.

[0034] Specifically, the instantaneous stationary relationship between the dual-suction pump and pipeline under fluctuating conditions, defined in the pump-pipeline dynamic coupling matching evaluation system established in this scheme, is expressed as follows:

[0035] Where H p (Q(t),n) represents the instantaneous head of the pump, in meters (m), indicating the pump head at a speed of n and a flow rate of Q(t); H sys Q(t) represents the instantaneous head required by the pipeline, in meters (m), indicating the head required by the pipeline system when the flow rate is Q(t); Q(t) represents the instantaneous flow rate, in cubic meters per hour (m³ / h), indicating the flow rate at a certain moment; n represents the pump speed, in revolutions per minute (r / min).

[0036] The dynamic matching error function is expressed as: ; Where ε(t) is the dynamic matching error at time t, which is dimensionless; H p (Q(t),n) represents the instantaneous head provided by the pump, in meters (m); H s The static head is measured in meters (m); K is the pipeline resistance coefficient, measured in seconds per meter (s² / m); Q(t) is the instantaneous flow rate, measured in cubic meters per hour (m³ / h).

[0037] In some embodiments, the dynamic matching error function is defined as the instantaneous difference between the instantaneous pump supply head and the dynamic demand head of the pipeline, used to characterize the degree of hydraulic mismatch under flow fluctuation conditions.

[0038] Furthermore, after constructing the dynamic coupling matching evaluation system of pump-pipeline, this scheme optimizes the current dual-suction pump. In each iteration, dynamic matching error verification and matching geometric correction are performed first. After the dynamic matching error meets the allowable range, high-efficiency working condition forward optimization is performed.

[0039] Specifically, in the step of "combining the dynamic pipeline resistance model to carry out extreme fluctuation condition matching verification, and if the dynamic matching error exceeds the allowable range, adjusting the impeller geometric parameters to correct the pump performance curve until the dynamic matching error meets the allowable range to obtain the matched double-suction pump", the extreme condition with the most severe disturbance is selected to calculate the dynamic matching error function. If the dynamic matching error exceeds the allowable range, the impeller geometric parameters, including the impeller outer diameter, impeller outlet width, blade outlet angle, and impeller inlet width, are changed to obtain a new double-suction pump.

[0040] In some embodiments, the instantaneous demand head of the pipeline is calculated by substituting the instantaneous flow rate of the extreme operating condition with the most severe disturbance, and the instantaneous head provided by the pump is obtained according to the head-flow performance curve. The difference between the instantaneous head provided by the pump and the instantaneous demand head of the pipeline is taken as the dynamic matching error.

[0041] Furthermore, if the dynamic matching error exceeds the allowable range, the root cause of the problem is located by combining the laws of fluid mechanics. Based on the root cause, the impeller geometric parameters, including the impeller outer diameter, impeller outlet width, blade outlet angle, and impeller inlet width, are changed to obtain a new double-suction pump.

[0042] When the dynamic matching error meets the allowable range and a matched double-suction pump is obtained, high-efficiency wide-condition positive optimization is carried out on the matched double-suction pump.

[0043] This solution optimizes four dimensions: impeller velocity coefficient, blade profile, volute throat, and volumetric leakage. Specifically: Regarding impeller velocity coefficient optimization: While ensuring the design head is not reduced, a smaller circumferential velocity coefficient and a larger axial velocity coefficient are selected. This allows for recalculation and control of the impeller outer diameter and outlet width. The principle behind this optimization is that a smaller circumferential velocity coefficient controls the impeller outlet circumferential velocity, preventing an excessively large impeller outer diameter; a larger axial velocity coefficient corresponds to a wider outlet flow channel and a higher outlet axial velocity. The combination of these two factors reduces the absolute velocity of the liquid exiting the impeller while maintaining the theoretical head, thereby significantly reducing frictional dissipation after the liquid enters the volute and minimizing hydraulic losses.

[0044] Regarding blade profile optimization: The blade exit angle is constrained within a reasonable engineering range, a suitable number of blades is matched, and the slip effect of a finite number of blades is calculated and corrected using the Pfleur slip formula. The blade axial flow channel profile is iteratively adjusted until the diffusion gradient of relative velocity within the flow channel is uniform and without significant abrupt changes. The principle behind this optimization is that a uniform flow channel diffusion gradient can avoid sudden drops in local velocity, effectively delay boundary layer separation under off-design conditions, prevent rapid turbulence and efficiency drops after the flow rate deviates from the rated value, thereby widening the flow range for efficient operation and adapting to fluctuating flow conditions.

[0045] Regarding the optimization of the volute throat: First, calculate the effective flow area at the impeller outlet (including the blade displacement coefficient). Then, based on the pump's specific speed, find the Anderson optimal area ratio Y as the reference value for rated operating conditions. Manually reduce the reference area ratio appropriately, correspondingly enlarging the volute throat area. Use this as a benchmark to complete the hydraulic design of each section of the volute. The principle behind this optimization is that the traditional Anderson optimal area ratio only applies to rated operating conditions. Enlarging the throat area significantly reduces the throttling and impact effects of the impeller outlet fluid entering the volute under high flow conditions, greatly reducing the dynamic and static interference impact losses between the impeller and the volute. This shifts the high-efficiency zone towards higher flow rates, covering the upper limit of flow fluctuations.

[0046] Regarding volumetric leakage optimization: Based on the leakage calculation formula, within the engineering constraints of machining accuracy and thermal expansion tolerance, the gap area of ​​the sealing ring is minimized as much as possible; simultaneously, a labyrinth seal structure is preferentially adopted to reduce the leakage flow coefficient, thus reducing leakage from two dimensions. The principle behind this optimization is that the liquid on the high-pressure side of the dual-suction pump leaks back to the low-pressure inlet side through the gap in the sealing ring. This portion of liquid does not participate in effective work and constitutes volumetric loss. Reducing the gap area and using a labyrinth seal can significantly reduce leakage flow, improve volumetric efficiency, and thus increase the overall efficiency of the machine.

[0047] In some embodiments, the impeller velocity coefficient is optimized by selecting a smaller circumferential velocity coefficient K based on the previous parameters. u and a relatively large axial velocity coefficient K m2 Based on this, the impeller outer diameter D2 and impeller outlet width b2 are re-estimated and controlled to ensure the theoretical head while minimizing the absolute velocity at the impeller outlet, thereby suppressing frictional dissipation within the volute.

[0048] The blade profile optimization involves: constraining the blade exit angle within a certain range; simultaneously, setting a reasonable number of blades, and using the Pfleur slip formula to calculate and correct the slip effect of a finite number of blades, repeatedly adjusting the blade profile until the relative velocity diffusion gradient within the axial flow channel is uniform and without significant abrupt changes, so as to effectively delay boundary layer separation under non-design conditions.

[0049] The volute throat optimization involves calculating the effective flow area at the impeller outlet. ( (For the displacement coefficient), and based on the specific speed, the Anderson optimal area ratio is found, and the reference area ratio is artificially reduced appropriately, that is, the throat area of ​​the volute is relatively enlarged, and the hydraulic design of each section of the volute is completed accordingly, so as to reduce the impact loss induced by dynamic-static mismatch.

[0050] Volumetric leakage optimization is based on the leakage calculation formula, taking into account the machining accuracy and thermal expansion tolerance, minimizing the sealing ring gap area as much as possible, and preferentially using a labyrinth seal structure to reduce the flow coefficient.

[0051] In some embodiments, the dual constraint conditions refer to the pipeline matching constraint and the hydraulic efficiency constraint of the dual-suction pump. That is, the dual-suction pump after the matching-efficiency dual iteration of this scheme can simultaneously satisfy the pipeline matching constraint and the hydraulic efficiency constraint of the dual-suction pump.

[0052] Example 2 This solution, based on the high-efficiency dual-pump optimization design method considering flow fluctuations in pipeline matching characteristics as described in Example 1, provides specific application examples as follows: S01: Based on the additional flow of the design That is, the suction flow rate on one side of the double-suction pump. Design head is The rotational speed is Therefore, the specific speed is calculated as It conforms to the structural characteristics of a double-suction pump, and the motor selection constraint meets the synchronous speed requirement of 1450 r / min; for The empirical circumferential velocity coefficient is taken as Then the impeller exit circumferential velocity is ,according to Calculate the impeller outer diameter as follows: ; Take the axial velocity coefficient as Then the exit axial velocity is The blade outlet displacement coefficient is set as follows: The total flow rate is Then the outlet width is ; The exit angle usually meets the range The initial selection of this plan ; Set inlet diameter Take the average import speed The width of the single-sided inlet is ; The required net positive suction head (NPSH) for this pump has been calculated. The system requires an effective net positive suction head (NPSH). Preliminary estimate of hydraulic efficiency The volumetric efficiency is mechanical efficiency Introducing a symmetric flow correction factor. The estimated efficiency is as follows ; S02: Set the static net head of the pipeline to be The average flow rate under design conditions is Then the pipeline resistance characteristic coefficient is set as Then the static characteristic curve is ; Considering the periodic fluctuations in the system, the flow function is defined as follows: The inertia of water flow in the pipeline is introduced as a dynamic correction term, and the pipe length is set. Pipe diameter and cross-sectional area The formula for calculating the instantaneous head requirement of the pipeline is: ; S03: The initial HQ performance curve equation of the dual-suction pump was obtained through numerical calculation and fitted as follows: The dynamic matching error function is defined as the instantaneous difference between the instantaneous pump supply head and the dynamic demand head of the pipeline. ; S04: Select the moment of most intense disturbance Perform a limit check; the instantaneous flow rate is at this point. The rate of change of flow rate ; Calculate the instantaneous head requirement of the pipeline. The pump provides an instantaneous head of 40m; The dynamic matching error is calculated as follows: Analysis revealed that the current dynamic matching error is greater than the set value of 2m. The reason is that the pipeline has a large dynamic inertial head, the pump's HQ curve is flat, and it cannot provide high pressure instantaneously.

[0053] Further modifications were made to the pump's geometry, including increasing the impeller's outer diameter. to and the blade exit angle Adjust to This caused the pump's performance curve to become steeper and shift upwards overall. After correction, numerical calculations yielded the following pump curve equation: After calculation, the dynamic matching error meets the requirements.

[0054] S05: When the dynamic matching error is within the allowable range after recalibration, numerical calculations show that its efficiency is not... The target range is within which further optimization is needed; Optimize based on the circumferential velocity coefficient, reducing the circumferential velocity coefficient to Increase the axial velocity coefficient to The impeller outer diameter was recalculated, and the correction in S04 was taken into account. The impeller outer diameter dimension was then determined to be... ; Setting the number of blades Z = 7, and using the Pfleur slip formula, the coefficient is calculated as follows: Adjust the flow channel profile of the blade axial surface to ensure a uniform relative velocity diffusion gradient; Calculate the effective flow area at the impeller outlet. The optimal area ratio baseline was reset, and the area ratio was artificially reduced to a lower value in order to expand the high-efficiency zone towards the high-flow-rate side. This enlarges the area of ​​the throat of the volute to ; The labyrinth seal structure is used to reduce the flow coefficient. The value was reduced from 0.6 to 0.35, and the gap area A was decreased. This was based on the leakage rate formula. The calculated leakage amount is from Down to This improves volumetric efficiency. Increased to 99%.

[0055] S06: After the above multiple iterations, the final pump characteristic curve was verified through numerical simulation. The dynamic matching error is The requirements are met, and the hydraulic efficiency is 92%. High-efficiency range. At this point, the dynamic matching requirements of the pipeline and the high-efficiency forward design of the dual-suction pump were simultaneously achieved.

[0056] Example 3 This embodiment also provides an electronic device, see reference. Figure 2 It includes a memory 402 and a processor 401, the memory 402 storing a computer program and the processor 401 being configured to run the computer program to perform the steps in any of the embodiments of the high-efficiency dual-pump optimization design method for considering flow fluctuations in pipeline matching characteristics.

[0057] Specifically, the processor 401 may include a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0058] The memory 402 may include a large-capacity memory 402 for data or instructions. The memory 402 can be used to store or cache various data files that need to be processed and / or communicated, as well as possible computer program instructions executed by the processor 401.

[0059] The processor 401 reads and executes computer program instructions stored in the memory 402 to implement any of the high-efficiency dual-pump optimization design methods for pipeline matching characteristics that take into account flow fluctuations in the above embodiments.

[0060] Optionally, the electronic device may further include a transmission device 403 and an input / output device 404, wherein the transmission device 403 is connected to the processor 401 and the input / output device 404 is connected to the processor 401.

[0061] The transmission device 403 can be used to receive or send data via a network. Specific examples of the network described above may include wired or wireless networks provided by the communication provider of the electronic device. In one example, the transmission device includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 403 may be a Radio Frequency (RF) module used for wireless communication with the Internet.

[0062] Input / output device 404 is used to input or output information. In this embodiment, the input information may be static hydraulic foundation parameters under rated operating conditions, and the output information may be optimized double-suction pumps, etc.

[0063] Optionally, in this embodiment, the processor 401 can be configured to perform the following steps via a computer program: S1: Obtain the static hydraulic foundation parameters under rated operating conditions, and design the foundation double-suction pump based on the static hydraulic foundation parameters under rated operating conditions; S2: Construct a dynamic pipeline resistance model with flow fluctuations, in which the dynamic pipeline resistance model introduces a flow fluctuation correction term based on the Darcy-Weisbach equation; S3: Perform matching-efficiency dual-iteration optimization on the basic dual-suction pump to obtain a dual-suction pump that satisfies the dual constraints. Each iteration of the matching-efficiency dual-iteration process is as follows: Based on the pump characteristic curve of the current double-suction pump and the pipeline characteristic curve of the dynamic pipeline resistance model, a pump-pipeline dynamic coupling matching evaluation system is established. The pump-pipeline dynamic coupling matching evaluation system defines the instantaneous operating point stationary relationship between the double-suction pump and the pipeline under fluctuating conditions and the dynamic matching error function. Numerical simulation is used to calculate the head-flow performance curve of the current dual-suction pump. Combined with a dynamic pipeline resistance model, the matching and verification of extreme fluctuation conditions are carried out. If the dynamic matching error exceeds the allowable range, the impeller geometry parameters are adjusted to correct the pump performance curve until the dynamic matching error meets the allowable range to obtain the matched dual-suction pump. High-efficiency wide-condition forward optimization is carried out on the matched dual-suction pump. The high-efficiency wide-condition forward optimization includes impeller velocity coefficient optimization, blade profile optimization, volute throat optimization, and volumetric leakage optimization.

[0064] It should be noted that the specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementations, and will not be repeated here.

[0065] Generally, various embodiments can be implemented in hardware or dedicated circuitry, software, logic, or any combination thereof. Some aspects of the invention can be implemented in hardware, while others can be implemented by firmware or software executed by a controller, microprocessor, or other computing device, but the invention is not limited thereto. Although various aspects of the invention may be shown and described as block diagrams, flowcharts, or using some other graphical representation, it should be understood that, by way of non-limiting example, these blocks, apparatuses, systems, techniques, or methods described herein can be implemented in hardware, software, firmware, dedicated circuitry or logic, general-purpose hardware or controllers or other computing devices, or some combination thereof.

[0066] Embodiments of the present invention can be implemented by computer software, which may be executable by a data processor of a mobile device, such as a processor entity, or by hardware, or by a combination of software and hardware. Computer software or programs (also referred to as program products), including software routines, applets, and / or macros, can be stored in any device-readable data storage medium, and they include program instructions for performing specific tasks. A computer program product may include one or more computer-executable components configured to perform embodiments when the program is run. One or more computer-executable components may be at least one piece of software code or a portion thereof. Additionally, it should be noted that any block in the logical flow of the figures may represent a program step, or interconnected logical circuitry, blocks and functions, or a combination of program steps and logical circuitry, blocks and functions. The software may be stored on physical media such as memory chips or blocks of storage implemented within a processor, magnetic media such as hard disks or floppy disks, and optical media such as, for example, DVDs and their data variants, CDs, etc. The physical medium is a non-transient medium.

[0067] Those skilled in the art should understand that the technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments have been described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0068] The above embodiments are merely illustrative of several implementation methods of this application, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A high-efficiency dual-pump optimization design method considering pipeline matching characteristics with flow fluctuations, characterized in that, Includes the following steps: S1: Obtain the static hydraulic foundation parameters under rated operating conditions, and design the foundation double-suction pump based on the static hydraulic foundation parameters under rated operating conditions; S2: Construct a dynamic pipeline resistance model with flow fluctuations, in which the dynamic pipeline resistance model introduces a flow fluctuation correction term based on the Darcy-Weisbach equation; S3: Perform matching-efficiency dual-iteration optimization on the basic dual-suction pump to obtain a dual-suction pump that satisfies the dual constraints. Each iteration of the matching-efficiency dual-iteration process is as follows: Based on the pump characteristic curve of the current double-suction pump and the pipeline characteristic curve of the dynamic pipeline resistance model, a pump-pipeline dynamic coupling matching evaluation system is established. The pump-pipeline dynamic coupling matching evaluation system defines the instantaneous operating point stationary relationship between the double-suction pump and the pipeline under fluctuating conditions and the dynamic matching error function. Numerical simulation is used to calculate the head-flow performance curve of the current dual-suction pump. Combined with a dynamic pipeline resistance model, the matching and verification of extreme fluctuation conditions are carried out. If the dynamic matching error exceeds the allowable range, the impeller geometry parameters are adjusted to correct the pump performance curve until the dynamic matching error meets the allowable range to obtain the matched dual-suction pump. High-efficiency wide-condition forward optimization is carried out on the matched dual-suction pump. The high-efficiency wide-condition forward optimization includes impeller velocity coefficient optimization, blade profile optimization, volute throat optimization, and volumetric leakage optimization.

2. The high-efficiency dual-pump optimization design method considering flow fluctuations in pipeline matching characteristics according to claim 1, characterized in that, Obtain the static hydraulic parameters under rated operating conditions, calculate the specific speed based on the static hydraulic parameters under rated operating conditions, and select the motor based on the specific speed. The static hydraulic parameters under rated operating conditions include rated flow rate, head, and speed. The impeller geometry parameters are designed based on the rotational speed, rated flow rate, and head. These parameters include the impeller outer diameter, impeller outlet width, blade outlet angle, and impeller inlet width. The basic double-suction pump is obtained by combining the motor and impeller geometry parameters.

3. The high-efficiency dual-pump optimization design method considering flow fluctuations in pipeline matching characteristics according to claim 2, characterized in that, Based on the Euler equation, the impeller outer diameter design formula is derived, the geometric correspondence between head and impeller outer diameter is established, the impeller outlet width is calculated by combining the continuity equation, the blade outlet angle is solved by the velocity triangle, and the geometric parameter design of the impeller inlet width is completed simultaneously.

4. The high-efficiency dual-pump optimization design method considering flow fluctuations in pipeline matching characteristics according to claim 1, characterized in that, The dynamic pipeline resistance model is as follows: ； ； Where H sys (t) represents the instantaneous demand head of the pipeline; Hs represents the static head; K represents the pipeline resistance coefficient; Q(t) represents the instantaneous flow rate; Q0 represents the rated flow rate; δ(t) represents the flow fluctuation coefficient.

5. The high-efficiency dual-pump optimization design method considering flow fluctuations in pipeline matching characteristics according to claim 1, characterized in that, The instantaneous stationary relationship between a double-suction pump and its pipeline under fluctuating conditions, as defined in the pump-pipeline dynamic coupling matching evaluation system, is expressed as follows: Where H p (Q(t),n) represents the instantaneous head provided by the pump; H sys (t) represents the instantaneous head demand of the pipeline; Q(t) represents the instantaneous flow rate; n represents the pump speed; The dynamic matching error function is expressed as: ； Where ε(t) is the dynamic matching error at time t; H p (Q(t),n) represents the instantaneous head provided by the pump; H s t is the static head; K is the pipeline resistance coefficient; Q(t) is the instantaneous flow rate.

6. The high-efficiency dual-pump optimization design method considering flow fluctuations in pipeline matching characteristics according to claim 1, characterized in that, The dynamic matching error of the dynamic matching error function is calculated under the extreme operating condition with the most severe disturbance. If the dynamic matching error exceeds the allowable range, the impeller geometric parameters, including the impeller outer diameter, impeller outlet width, blade outlet angle, and impeller inlet width, are changed to obtain a new double-suction pump.

7. The high-efficiency dual-pump optimization design method considering flow fluctuations in pipeline matching characteristics according to claim 6, characterized in that, Substitute the instantaneous flow rate of the extreme operating condition with the most severe disturbance into the calculation of the instantaneous demand head of the pipeline, obtain the instantaneous head provided by the pump according to the head-flow performance curve, and take the difference between the instantaneous head provided by the pump and the instantaneous demand head of the pipeline as the dynamic matching error.

8. The high-efficiency dual-pump optimization design method considering flow fluctuations in pipeline matching characteristics according to claim 1, characterized in that, The impeller speed coefficient is optimized as follows: Based on the previous parameters, a smaller circumferential speed coefficient and a larger axial speed coefficient are selected, and the impeller outer diameter and impeller outlet width are re-estimated and controlled accordingly. The blade profile optimization involves: constraining the blade exit angle within a certain range; simultaneously, setting a reasonable number of blades, and using the Prafrederer slip formula to calculate and correct the slip effect of a finite number of blades, repeatedly adjusting the blade profile until the relative velocity diffusion gradient within the axial flow channel is uniform and without significant abrupt changes. The optimization of the volute throat is as follows: calculate the effective flow area at the impeller outlet, and find the Anderson optimal area ratio based on the specific speed, and artificially reduce the reference area ratio appropriately; The volumetric leakage optimization is as follows: based on the leakage calculation formula, and taking into account the machining accuracy and thermal expansion tolerance, the sealing ring gap area is reduced, and a labyrinth seal structure is adopted to reduce the flow coefficient.

9. The high-efficiency dual-pump optimization design method considering flow fluctuations in pipeline matching characteristics according to claim 1, characterized in that, The dual constraints refer to the pipeline matching constraints and the hydraulic efficiency constraints of the dual-suction pump.

10. An electronic device comprising a memory and a processor, characterized in that, The memory stores a computer program, and the processor is configured to run the computer program to execute the high-efficiency dual-pump optimization design method for pipeline matching characteristics considering flow fluctuations as described in any one of claims 1 to 9.

Images