A method for optimizing a tolerance chain of a marine steam turbine rotor

Abstract

The application discloses a tolerance size chain optimization method for a marine steam turbine rotor, and belongs to the technical field of marine steam turbine manufacturing. In order to solve the problems of large tolerance size chain deviation and low dynamic balance precision in steam turbine rotor part machining, the application comprises the following steps: obtaining the probability distribution of the mass center of each stage cylindrical disc in the spatial position, generating a geometric offset deviation, obtaining a mass center offset deviation, arbitrarily selecting an end face, obtaining the position of the end face center point, and obtaining a normal offset angle according to the mass center offset deviation and the position of the end face center point; taking the geometric offset deviation of the cylindrical disc center, the position of the end face center point and the normal offset angle as geometric characteristics, constructing a size chain mass center offset prediction model, and outputting a concentric and mass center cooperative deviation prediction value; and performing feature sensitivity evaluation on the deviation prediction value, and if the feature sensitivity meets the geometric and mass center precision indexes, then taking the current concentric and mass center cooperative deviation prediction value as the rotor tolerance size chain. The application is used for dynamic balance of the steam turbine rotor.

Description

Technical Field

[0001] The invention relates to a method for optimizing the tolerance dimension chain of a marine steam turbine rotor, and belongs to the technical field of marine steam turbine manufacturing. Background Art

[0002] The working environment and operating conditions of marine steam turbines are different from those of power plant steam turbines. They are installed on a deformable hull base and are often affected by the hull's swing and impact. Their normal operation is directly related to the safety of the entire ship, so higher reliability requirements are required. The rotor structure is one of the most important components in the steam turbine.

[0003] During the manufacturing and assembly process, turbine rotors can become unbalanced due to varying tolerances. This imbalance can cause rotor vibration, accelerate wear on components like bearings and shaft seals, and reduce the lifespan and efficiency of the machine. Therefore, dynamic balancing of the rotor is necessary during manufacturing, maintenance, and operation. Dynamic balancing involves removing or adding counterweights to the rotor, changing its mass distribution. This reduces rotor vibration caused by centrifugal forces from the eccentric center of mass, as well as dynamic loads on the bearings, to within acceptable limits, thereby ensuring stable rotor operation.

[0004] The geometric concentricity and center of mass offset of each rotating component in a steam turbine rotor structure accumulate along the component's internal dimensional chain, causing the rotor's overall geometric center and center of mass to deviate from the ideal central axis, reducing vibration quality. The key factors influencing rotor geometric concentricity and center of mass offset are the geometric offset and center of mass offset of each cylindrical disc. Although the influencing factors of concentricity and center of mass offset are similar, their sensitivity and contribution vary significantly.

[0005] The existing steam turbine rotor processing has the following problems:

[0006] 1. Machining accuracy is mainly based on geometric indicators such as concentricity, and the changes in corresponding factors such as mass eccentricity are not considered;

[0007] 2. After the rotor parts are processed, their dynamic balance quality is mainly achieved by adjusting the position and weight of the balance block. The dynamic balance adjustment process relies on the operator's experience and lacks theoretical guidance, resulting in low efficiency and long cycle of the adjustment process.

[0008] Therefore, it is necessary to start with the tolerance chain of turbine rotor components and design the coordinated tolerances of rotor geometry and center of mass offset, thereby adjusting and optimizing dynamic balance and improving the dynamic balance accuracy of the turbine rotor. This fundamentally reduces the rotor's inherent imbalance and provides a design method for practical guidance on rotor adjustment and performance improvement. Summary of the Invention

[0009] The purpose of the present invention is to solve the problems of large tolerance dimension chain deviation and low dynamic balancing accuracy in the processing of steam turbine rotor parts, and to provide a method for optimizing the tolerance dimension chain of a marine steam turbine rotor.

[0010] The present invention provides a method for optimizing a tolerance dimension chain of a marine steam turbine rotor, comprising:

[0011] S1. Analyze and obtain the geometric tolerances of the rotor axis and the cylindrical disks at each level based on the rotor component dimensions, and then obtain the probability distribution of the center of mass of the cylindrical disks at each level in space.

[0012] S2, based on the probability distribution of the center of mass in the space position obtained in S1, generate a geometric offset deviation of the center of the cylindrical disk that conforms to the probability distribution;

[0013] S3. Calculate the weight of the cylindrical disk based on the rotor size, and combine it with the probability distribution of the center of mass in the spatial position obtained in S1 to obtain the corresponding center of mass offset deviation;

[0014] S4. Select an end face at random, obtain the position of the end face center point, and obtain the normal offset angle based on the centroid offset deviation and the end face center point position;

[0015] S5. Using the geometric offset deviation of the cylindrical disk center, the end face center point position and the normal offset angle as geometric features, a dimensional chain centroid offset prediction model is constructed to output the predicted values ​​of concentricity and centroid coordination deviation;

[0016] S6. Evaluate the characteristic sensitivity of the predicted value of the coordinated deviation between concentricity and center of mass to determine whether the characteristic sensitivity meets the geometric and center of mass accuracy indicators. Otherwise, perform dynamic balancing optimization. If yes, use the current predicted value of the coordinated deviation between concentricity and center of mass as the rotor tolerance dimension chain.

[0017] Preferably, the dynamic balance optimization specifically includes:

[0018] S2-1. Based on the geometric and center-of-mass coordination deviations, statistical deviation simulation is used to obtain the probability distribution interval of the concentricity and center-of-mass coordination offsets;

[0019] S2-2, setting the mass and position of the balancing block within the probability distribution interval of the concentric and center-of-mass coordinated offsets obtained in S2-1;

[0020] S2-3, constructing a rotor mass center offset prediction model combined with a balancing mass, and outputting a predicted value of the rotor mass center offset including the balancing mass;

[0021] S2-4. Evaluate the dynamic balance performance of the predicted value of the center of mass offset of the rotor containing the balancing weight to determine whether the dynamic balance performance meets the dynamic balance performance index. If not, return to S2-1. If yes, use the mass and position of the current balancing weight as dynamic balance optimization parameters.

[0022] Preferably, the method for evaluating the dynamic balance performance of the predicted value of the center of mass offset of the rotor containing the balancing block described in S2-4 adopts the finite element analysis method.

[0023] Preferably, using the current predicted value of the coordinated deviation between concentricity and center of mass as the rotor tolerance dimension chain further includes:

[0024] The coordinated deviation between concentricity and centroid is set as the optimization target, and the optimization algorithm is used to optimize the tolerance zones of key geometric features at all levels to obtain the best optimized tolerance zone.

[0025] Preferably, the optimization algorithm includes: genetic algorithm, game theory, fuzzy algorithm and artificial intelligence algorithm.

[0026] Advantages of this invention: The method for optimizing the tolerance chain for marine steam turbine rotors, described herein, uses the optimized design tolerance chain to determine the probability distribution of mass eccentricity and optimal balancing block compensation for a given combination of random geometric deviations of the turbine's cylindrical disk. This method can control rotor imbalance within a narrow range using design tolerances, meeting rotor dynamic balancing requirements and improving turbine rotor dynamic balancing accuracy. This method fundamentally reduces rotor imbalance, providing a design approach for practical guidance in rotor adjustment and performance improvement. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a flowchart of the method for optimizing the tolerance dimension chain of a marine steam turbine rotor according to the present invention;

[0028] Figure 2 is a cross-sectional view of the rotor;

[0029] Figure 3 is the position where the rotor balancing weight is applied;

[0030] Figure 4 is the probability distribution of the turbine rotor axial offset;

[0031] Figure 5 is the probability distribution of the radial offset of the turbine rotor;

[0032] Figure 6 is the probability distribution of radial imbalance of the turbine rotor;

[0033] Figure 7 is the probability distribution of the radial imbalance compensation amount of the turbine rotor. DETAILED DESCRIPTION

[0034] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0035] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other.

[0036] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, but they are not intended to limit the present invention.

[0037] Example 1:

[0038] The following combination Figure 1 This embodiment describes a method for optimizing a tolerance dimension chain of a marine steam turbine rotor, which includes:

[0039] S1. Analyze and obtain the geometric tolerances of the rotor axis and the cylindrical disks at each level based on the rotor component dimensions, and then obtain the probability distribution of the center of mass of the cylindrical disks at each level in space.

[0040] S2, based on the probability distribution of the center of mass in the space position obtained in S1, generate a geometric offset deviation of the center of the cylindrical disk that conforms to the probability distribution;

[0041] S3. Calculate the weight of the cylindrical disk based on the rotor size, and combine it with the probability distribution of the center of mass in the spatial position obtained in S1 to obtain the corresponding center of mass offset deviation;

[0042] S4. Select an end face at random, obtain the position of the end face center point, and obtain the normal offset angle based on the centroid offset deviation and the end face center point position;

[0043] S5. Using the geometric offset deviation of the cylindrical disk center, the end face center point position and the normal offset angle as geometric features, a dimensional chain centroid offset prediction model is constructed to output the predicted values ​​of concentricity and centroid coordination deviation;

[0044] S6. Evaluate the characteristic sensitivity of the predicted value of the coordinated deviation between concentricity and center of mass to determine whether the characteristic sensitivity meets the geometric and center of mass accuracy indicators. Otherwise, perform dynamic balancing optimization. If yes, use the current predicted value of the coordinated deviation between concentricity and center of mass as the rotor tolerance dimension chain.

[0045] Furthermore, the dynamic balance optimization specifically includes:

[0046] S2-1. Based on the geometric and center-of-mass coordination deviations, statistical deviation simulation is used to obtain the probability distribution interval of the concentricity and center-of-mass coordination offsets;

[0047] S2-2, setting the mass and position of the balancing block within the probability distribution interval of the concentric and center-of-mass coordinated offsets obtained in S2-1;

[0048] S2-3, constructing a rotor mass center offset prediction model combined with a balancing mass, and outputting a predicted value of the rotor mass center offset including the balancing mass;

[0049] S2-4. Evaluate the dynamic balance performance of the predicted value of the center of mass offset of the rotor containing the balancing weight to determine whether the dynamic balance performance meets the dynamic balance performance index. If not, return to S2-1. If yes, use the mass and position of the current balancing weight as dynamic balance optimization parameters.

[0050] Furthermore, the method described in S2-4 for evaluating the dynamic balancing performance of the predicted value of the center of mass offset of the rotor containing the balancing weight adopts the finite element analysis method.

[0051] Furthermore, the predicted value of the current concentricity and center of mass coordinated deviation is used as the rotor tolerance dimension chain, which also includes:

[0052] The coordinated deviation between concentricity and centroid is set as the optimization target, and the optimization algorithm is used to optimize the tolerance zones of key geometric features at all levels to obtain the best optimized tolerance zone.

[0053] Furthermore, the optimization algorithms include: genetic algorithm, game theory, fuzzy algorithm and artificial intelligence algorithm.

[0054] The present invention provides a method for optimizing the tolerance dimension chain of a marine steam turbine rotor to reduce the imbalance of the rotor itself and solve the problems of low efficiency and long cycle in the current dynamic balancing process of the rotor, which relies on experience and lacks theoretical guidance.

[0055] Specifically include:

[0056] Step 1: Analyze the tolerances of the rotor parts. Analyze the geometric tolerances of the rotor axis and the cylindrical disks at each level to obtain the probability distribution of their respective centers of mass in space.

[0057] Step 2: Calculate the random deviation of the parts. Based on the probability distribution of the center of mass of each cylindrical disk in space obtained in step 1, generate the geometric offset deviation of the center of mass of the cylindrical disk that conforms to the distribution; calculate the weight of the cylindrical disk based on the rotor size, and calculate the corresponding center of mass offset based on the spatial position relationship between the center of mass of each cylindrical disk;

[0058] Step 3: Modeling the dimensional chain and center of mass offset prediction. Based on the cylindrical disk center offset deviation, end face center position, and normal offset angle obtained in step 2, these are used as the deviation values ​​for geometric feature modeling.

[0059] Step 4: Comprehensive concentricity and mass eccentricity evaluation. Based on the model established in step 2, calculate the changes in the comprehensive concentricity and mass eccentricity of the entire rotor.

[0060] Step 5: Statistical deviation analysis. Repeat steps 2 to 4 above to obtain statistical deviation simulation results and identify the sensitivity and contribution of key geometric features.

[0061] Step 6: Rotor tolerance optimization. Set the overall comprehensive concentricity and mass eccentricity as the optimization targets. Utilize intelligent optimization algorithms (such as genetic algorithms, game theory, fuzzy algorithms, and artificial intelligence algorithms) to optimize the tolerance zones of key geometric features at all levels. Combined with the three-dimensional deviation model of the wheel disc, predict the new concentricity and center of mass offset to determine the optimal design tolerance zone. If the optimization targets are met, the final rotor tolerance design is obtained. If not, repeat steps 1 to 5.

[0062] Step 7: Optimized rotor tolerance design. Based on the optimized tolerance design of the rotor rotating components obtained in step 6, the probability distribution intervals of the overall concentricity and center of mass offset are obtained based on statistical deviation simulation;

[0063] Step 8: Add the weight and position of the balancing mass. Set the mass and position of the initial balancing mass within the feasible region of the center of mass offset obtained in step 7.

[0064] Step 9: Center of mass shift prediction modeling. Construct a prediction model for the center of mass shift of the rotor structure taking into account the balancing mass.

[0065] Step 10: Rotor structure mass eccentricity evaluation. Predict the center of mass offset of the rotor structure with balancing weights established in step 9.

[0066] Step 11: Dynamic balance performance evaluation of the rotor structure. Based on the mass eccentricity prediction value in step 10, the dynamic balance performance of the rotor structure is evaluated (based on finite element or experimental methods);

[0067] Step 12: Dynamic balancing parameter optimization. Based on the dynamic balancing performance results, an optimization algorithm is used to optimize the mass and position of the balancing weights. The new center of mass offset is predicted using the rotor structure's overall center of mass offset model. If the optimization target is achieved, the final balancing weight mass and installation position are obtained. If not, repeat steps 8 through 11.

[0068] In the above process, the evaluation of concentricity and center of mass deviation is a comprehensive measure of the geometric eccentricity and mass eccentricity of the cylindrical disks at all levels. The overall concentricity and mass eccentricity control function of the multi-stage cylindrical disk projected on the axial vertical plane is as follows:

[0069]

[0070] Among them, γ i is the geometric eccentricity weight coefficient of the i-th level, ε geo and ε mass are the control functions of comprehensive geometric concentricity and mass eccentricity, ε min is a comprehensive evaluation index, and α and β are the corresponding weight coefficients.

[0071] In the present invention, a feasible domain of dimensional tolerance is set, and the runout tolerance of the rotor disc is optimized with the rotor eccentric mass as the optimization target. The probability distribution of mass eccentricity and optimal balancing block compensation under a given combination of random geometric deviations of the turbine cylindrical disc is obtained, and the balancing block parameters are regulated and optimized for compensation during the dynamic balancing process. This enables the turbine rotor structure to fundamentally reduce the imbalance of the rotor itself, providing theoretical support for the actual turbine rotor dynamic balancing adjustment process.

[0072] The present invention optimizes the dynamic balancing process by designing the coordinated tolerances of turbine rotor component geometry and center of mass offset, improving turbine rotor dynamic balancing accuracy. This approach overcomes the traditional reliance on experience and lacks theoretical guidance in the dynamic balancing process, shortening the rotor dynamic balancing cycle and improving efficiency.

[0073] In the present invention, Figure 2 The figure shows the cross section of the rotor. Figure 3 To determine the position between the applied balancing weight and the center of mass on the rotor, the aforementioned dimension chain-based dynamic balancing optimization method for rotating rotor components was used to obtain the probability distribution of mass eccentricity and optimal balancing weight compensation for a given combination of random geometric deviations of the turbine cylindrical discs. The runout tolerance of each cylindrical disc is a key tolerance affecting the mass eccentricity of the component. Therefore, the following optimization focuses on this runout tolerance. Based on the actual process level, the optimization feasible region was set according to Table 1 to optimize the runout tolerance of each rotor disc. The runout tolerance of the rotor discs was optimized with the rotor eccentric mass as the optimization target, and the probability distribution of the corresponding compensation amount was calculated.

[0074] Table 1

[0075]

[0076] Figure 4 The figure shows the probability distribution of the axial offset of the rotor center of mass, with a distribution range of [-0.1186, 0.1197] mm.

[0077] like Figure 5 As shown, it is expressed as the probability distribution diagram of the radial offset of the rotor mass center. Figure 5 It can be seen that the distribution range is [0,1.985]×10 -3 mm.

[0078] like Figure 6As shown in the figure, it is represented as the probability distribution diagram of the radial imbalance of the rotor mass center, and the distribution range is [0,3.397]×10 3 g·mm.

[0079] When the radial distance between the two compensation blocks is 300 mm, the probability distribution of the radial imbalance compensation amount of the rotor center of mass is as follows: Figure 7 As shown, the imbalance distribution range is [0,10.324]g.

[0080] Using a dimensional chain-based method for optimizing the dynamic balancing of marine steam turbine rotors, a comparison of the radial imbalance at the rotor's center of mass before and after optimizing the runout tolerance of the rotor disc reveals a significant reduction in the mass of the balancing block from 31.025g before optimization to 10.324g afterward. These results demonstrate the effectiveness of the rotor imbalance optimization method targeting runout.

[0081] The present invention can efficiently and quickly optimize the probability distribution of mass eccentricity and optimal balancing block compensation amount, select the balancing block compensation amount within a given range, and obtain a rotor with higher dynamic balancing accuracy.

[0082] This optimization method minimizes rotor imbalance from the perspective of dimensional chain design and improves the dynamic balancing accuracy of steam turbine rotors. It overcomes the traditional reliance on experience and lacks theoretical guidance during steam turbine rotor dynamic balancing, shortens the rotor dynamic balancing process, and improves efficiency.

[0083] Although the present invention is described herein with reference to specific embodiments, it should be understood that these embodiments are merely illustrative of the principles and applications of the invention. It should be understood that many modifications may be made to the illustrative embodiments, and that other arrangements may be devised, without departing from the spirit and scope of the invention as defined by the appended claims. It should be understood that the various dependent claims and features described herein may be combined in ways other than those described in the original claims. It should also be understood that features described in conjunction with individual embodiments may be employed in conjunction with other described embodiments.

Claims

1. A method for optimizing the tolerance dimension chain of a marine steam turbine rotor, characterized in that: It includes: S1. Analyze and obtain the geometric tolerances of the rotor axis and the cylindrical disks at each level based on the rotor component dimensions, and then obtain the probability distribution of the center of mass of the cylindrical disks at each level in space. S2, based on the probability distribution of the center of mass in the space position obtained in S1, generate a geometric offset deviation of the center of the cylindrical disk that conforms to the probability distribution; S3. Calculate the weight of the cylindrical disk based on the rotor size, and combine it with the probability distribution of the center of mass in the spatial position obtained in S1 to obtain the corresponding center of mass offset deviation; S4. Select an end face at random, obtain the position of the end face center point, and obtain the normal offset angle based on the centroid offset deviation and the end face center point position; S5. Using the geometric offset deviation of the cylindrical disk center, the end face center point position and the normal offset angle as geometric features, a dimensional chain centroid offset prediction model is constructed to output the predicted values ​​of concentricity and centroid coordination deviation; S6. Evaluate the characteristic sensitivity of the predicted value of the coordinated deviation between concentricity and center of mass to determine whether the characteristic sensitivity meets the geometric and center of mass accuracy indicators. Otherwise, perform dynamic balancing optimization. If yes, use the current predicted value of the coordinated deviation between concentricity and center of mass as the rotor tolerance dimension chain.

2. The method for optimizing the tolerance dimension chain of a marine steam turbine rotor according to claim 1, characterized in that: The dynamic balance optimization specifically includes: S2-1. Based on the geometric and center-of-mass coordination deviations, statistical deviation simulation is used to obtain the probability distribution interval of the concentricity and center-of-mass coordination offsets; S2-2, setting the mass and position of the balancing block within the probability distribution interval of the concentric and center-of-mass coordinated offsets obtained in S2-1; S2-3, constructing a rotor mass center offset prediction model combined with a balancing mass, and outputting a predicted value of the rotor mass center offset including the balancing mass; S2-4. Evaluate the dynamic balance performance of the predicted value of the center of mass offset of the rotor containing the balancing weight to determine whether the dynamic balance performance meets the dynamic balance performance index. If not, return to S2-1. If yes, use the mass and position of the current balancing weight as dynamic balance optimization parameters.

3. The method for optimizing the tolerance dimension chain of a marine steam turbine rotor according to claim 2, characterized in that: The method described in S2-4 for evaluating the dynamic balancing performance of the predicted value of the center of mass offset of the rotor containing the balancing block adopts the finite element analysis method.

4. The method for optimizing the tolerance dimension chain of a marine steam turbine rotor according to claim 1, characterized in that: The current predicted value of the deviation between concentricity and center of mass as the rotor tolerance dimension chain also includes: The coordinated deviation between concentricity and centroid is set as the optimization target, and the optimization algorithm is used to optimize the tolerance zones of key geometric features at all levels to obtain the best optimized tolerance zone.

5. The method for optimizing the tolerance dimension chain of a marine steam turbine rotor according to claim 4, characterized in that: The optimization algorithms include: genetic algorithm, game theory, fuzzy algorithm and artificial intelligence algorithm.

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