Search Results (14)

Accurate prediction and optimization of assembly accuracy are critical to ensuring assembly quality and efficiency for multistage connected aero-engine rotors. To mitigate the effects of residual alignment errors induced by repeated component measurements and to avoid the formation of bowed rotors caused by conventional stacking strategies that only minimize parallel misalignment, a harmonic decomposition-based registration method is proposed to unify inconsistent measurement datums among multiple setups. Meanwhile, key assembly process parameters are considered simultaneously, including front-and-rear support concentricity, front-and-rear bearing mounting face end-face runout, rotor blade-tip runout, and rotor unbalance. Taking the discrete assembly phase angles of each rotor stage as independent variables, a multi-objective genetic algorithm is adopted to realize the assembly accuracy prediction and optimization of multistage flange-bolted rotors. The proposed method is validated using a four-stage simulated rotor assembly. Experimental results show that the harmonic decomposition-based registration method improves the average geometric prediction accuracy of rotor assembly by 1.2 percentage points, with the prediction error of geometric assembly parameters for each stage not exceeding 8.4% and the unbalance prediction error not exceeding 29.0%. Compared with random assembly, four-objective comprehensive optimization achieves significant reductions in all objectives: front-and-rear support concentricity is reduced by 66.2%, front-and-rear support shoulder end-face runout by 63.9%, blade-tip runout by 16.7%, and unbalance by 33.8%. The residual alignment error compensation method and stacking optimization strategy proposed in this study provide valuable engineering guidance for improving rotor assembly prediction accuracy and enhancing assembly reliability. Full article

Excessive vibration during critical speed traversal remains a primary challenge in assembling multi-stage rotors of aero-engines. Conventional assembly optimization methods, which target static geometric and mass eccentricity errors or vibration at a fixed operating speed, are inadequate to ensure smooth passage through multiple critical speeds. To address this gap, we propose a novel, vibration-suppression-oriented assembly optimization model. A normalized objective function is formulated to minimize the overall vibration response across multiple rotor nodes specifically at the first and second critical speeds. This function integrates an assembly error propagation model with a rotor dynamic model that considers flexible dynamic deflection. The optimal assembly angle sequence is solved using a genetic algorithm. Experimental validation on a four-stage rotor demonstrates that the proposed method reduces the maximum vibration displacement amplitude at the first and second critical speeds by 74.7% and 11.9%, respectively, significantly outperforming conventional objectives based on geometric error, unbalanced mass, or single-speed vibration. This work provides a practical and effective strategy to enhance rotor dynamic safety by ensuring low-vibration operation across the critical speeds encountered before reaching the operating speed through optimal assembly. Full article

The precise prediction of vibration response is crucial for optimizing the assembly quality of multi-stage rotors. Existing models possess two key limitations: they neglect the geometric displacement excitation from spigot eccentricity error and oversimplify rotor behavior by not accounting for the excitation redistribution caused by significant dynamic deflection at high speeds, particularly near critical speeds. To overcome these shortcomings, this study establishes a novel dynamic model based on the synchronous excitation of both mass and spigot eccentricity errors, which simultaneously incorporates the coupling mechanism of dynamic deflection. System dynamics equations are developed using a finite element approach combined with Timoshenko beam theory and solved via the Newmark-β method. Simulations and experiments on a four-stage rotor demonstrate that the proposed model provides significantly improved accuracy. At sub-critical, first, and second critical speeds, it reduces the maximum prediction error for nodal displacement amplitudes by 6.1%, 9.2%, and 36.4%, respectively, compared to a model neglecting dynamic deflection. Furthermore, analysis confirms that the targeted assembly error excitation exists solely at the fundamental frequency. The developed model, which uniquely integrates dual eccentricity sources with dynamic deflection coupling, is essential for reliable high-speed vibration prediction and assembly optimization, especially for flexible rotors operating near critical speeds. Full article

Aiming to improve the accuracy of the aero-engine’s multi-stage rotor’s mating surface classification and initial unbalance prediction, a new intelligent approach for the unbalance prediction of the aero-engine’s multi-stage rotor is proposed in this paper. Numerical simulations of the proposed scheme were conducted on actual assembly datasets of actual aero-engine rotors, and assembly experiments implementing actual aero-engine’s multi-stage rotors were carried out to validate the effectiveness of the proposed method. Results of numerical simulation and experimental validation revealed that the proposed hybrid network method was not only capable of efficiently recognizing different types of rotors’ mating surfaces with a satisfactory accuracy of more than 98% in the training process and 93.3% in experiments, but also proved to accurately predict after-assembly initial unbalance with an acceptable error of less than 5% in both simulated and experimental scenarios. Therefore, the method proposed in this paper can not only be used for rotor surface classification, but also can be used to guide the assembly of aero-engine multi-stage rotors. Full article

In rotating machinery with a multi-stage assembled rotor, such as is found in aero engines, any unbalance present will undergo unknown changes at each stage when rotating the assembly phases of the rotor. Repeated disassembly and adjustments are often required to meet the rotor’s residual unbalance specifications. Therefore, developing a prediction model of this two-sided unbalance for a multi-stage assembled rotor is crucial for improving the first-time assembly pass rate and assembly efficiency. In this paper, we propose a prediction model of the two-sided unbalance seen in the multi-stage assembled rotor of an aero engine. Firstly, a method was proposed to unify the mass feature parameters of each stage’s rotor into a geometric measurement coordinate system, achieving the synchronous transmission of geometric and mass feature parameters during the assembly process of the multi-stage rotor. Building upon this, a linear parameter equation of the actual rotation axis of the multi-stage rotor was established. Based on this axis, the mass eccentricity errors of the rotor were calculated at each stage, further enabling the accurate prediction of two-sided unbalance and its action phase in a multi-stage rotor. The experimental results indicate that the maximum prediction errors of the two-sided unbalance and its action phase for a four-stage rotor are 9.6% and 2.5%, respectively, when using this model, which is a reduction of 53.0% and 38.1% compared to the existing model. Full article

Rotor unbalance is the most important factor affecting the dynamic performance of aircraft engines. The existing unbalance prediction and control methods are insufficient for multi-stage rotors. The post-assembly unbalance of rotors in aircraft engines is a critical factor affecting their dynamic performance. In order to predict and reduce the unbalance of multi-stage rotors after assembly, this paper establishes a measurement model for the center-of-mass offset of aircraft engine rotors through decoupled calculations of the unbalance. Furthermore, it constructs an unbalance prediction model using the spatial transfer mechanism of combined rotor offset centers under the influence of manufacturing errors. Additionally, a method for measuring rotor unbalance during the assembly phase is proposed. The experimental results of the unbalance in multi-stage combined rotor assembly indicate that the degree of agreement between the predicted results and the experimental results is 91.3%, resulting in a reduction in the mean error of 15.3% compared to before the correction. The study also investigates the impact of manufacturing errors on unbalance. This research provides robust support for controlling the unbalance in multi-stage combined rotor assembly. Full article

Multi-stage disc rotor assembly is an important part of the aero-engine rotor manufacturing process. To solve the problem that excessive unbalance of assembly affects the vibration of the whole machine, this paper presents an optimization method for aero-engine rotor assembly balance based on an improved Harris Hawk algorithm. Firstly, the assembly sequence model of the single-stage disc blade and the phase assembly model of a multi-stage disc of the engine rotor is established. Secondly, by using the initial population generation based on dynamic opposing learning and the escape energy function of the non-linear logarithmic convergence factor, the search mechanism of the whale optimization algorithm is introduced in the global exploration, and the adaptive weight strategy and mutation strategy of the genetic algorithm is introduced in the development to improve the algorithm. Then, the effectiveness of the algorithm is verified by experiments and compared with particle swarm optimization, genetic algorithm, and Harris Hawk algorithm, the unbalance of the optimal blade assembly sequence is reduced by 91.75%, 99.82%, and 83.39%, respectively. The algorithm comparison and analysis are carried out for all disc-blade assembly optimization of the rotor. The optimal unbalance of the improved Harris Hawk optimization algorithm is reduced by 79.71%, 99.48%, and 54.92% on average. The unbalance of the algorithm in this paper is the best. Finally, the improved Harris Hawk algorithm is used to find the best assembly phase, and the optimized unbalanced force and moment are reduced by 84.22% and 98.05%, respectively. The results of this study prove that the improved Harris Hawk algorithm for aero-engine rotor assembly balance optimization can effectively reduce the unbalance of rotor disc blade assembly and rotor unbalance and provide a powerful solution for solving engine vibration. Full article

An aero engine fan rotor is composed of a multi-stage disk and multi-stage blades. Excessive unbalance of the aero engine fan rotor after assembly is the main cause of aero engine vibration. In the rotor assembly process, blade sequencing optimization and multi-stage blade set assembly phase optimization are important for reducing the overall rotor unbalance. To address this problem, this paper proposes a semi-physical simulation method based on reinforcement learning to optimize the balance in the fan rotor assembly process. Firstly, based on the mass moments of individual blades, the diagonal mass moment difference is introduced as a constraint to build a single-stage blade sorting optimization model, and reinforcement learning is used to find the optimal sorting path so that the balance of the single-stage blade after sorting is optimal. Then, on the basis of the initial unbalance of the disk and the unbalance of the single-stage blade set, a multi-stage blade assembly phase optimization model is established, and reinforcement learning is used to find the optimal assembly phase so that the overall balance of the rotor is optimal. Finally, based on the collection of data during the assembly of the rotor, the least-squares method is used to fit and calculate the real-time assembly unbalance to achieve a semi-physical simulation of the optimization of balance during the assembly process. The feasibility and effectiveness of the proposed method are verified by experiments. Full article

The rotation precision of rotors determines the efficiency and quality of the overall aero-engine, as well as its long-term and reliable operation ability. As the terminal link of aero-engine manufacturing, the assembly is the last guarantee of precision control. Rotor assembly relates to the accurate expression of the connection form and design optimization of the assembly scheme. The existing variation model cannot adequately handle the partial parallel chain problem, ignoring the bayonet circular connector between the rotor parts, and it is still deficient in multistage gyration error control. In this paper, the partial parallel connection and multistage revolving characteristics of rotors were discussed, and a novel modeling and optimizing method for a partial parallel dimension chain was proposed. On the one hand, the variation expression of the connection features for the revolving components considering the partial parallel structure was researched. Contact point-based torsors were represented, and a system for locating points was regarded as an assembly to describe the partial parallel chain. On the other hand, the variation propagation modeling and control for the stacking of the multistage revolving components was researched. A revolution joint was introduced in the unified Jacobian–Torsor model, and a novel assembly technique for concentricity control was proposed. Therefore, a unified variation analysis and control method for rotor assembly has been developed. Experimental results show that through this method, the final concentricity variation is 0.0539 mm, far less than the 0.1595 mm of the traditional model, and is closer to the true value range of 0.030–0.040 mm. Moreover, the optimum installed angles can be calculated as 3.153 rad, 6.025 rad, and 2.590 rad, to obtain the highest concentricity of 0.040 mm, which has strong practical guiding significance. Full article

The assembly quality of the multistage rotor is an essential factor affecting its vibration level. The existing optimization methods for the assembly angles of the rotors at each stage can ensure the concentricity and unbalance meet the requirements, but it cannot directly ensure its vibration responses meet the indexes. Therefore, in this study, we first derived the excitation formulas of the geometric and mass eccentricities on the multistage rotor and introduced it into the dynamics model of the multistage rotor system. Then, the coordinate transfer model of the geometric and mass eccentricities errors, including assembly angles of the rotors at all stages, was established. Moreover, the mathematical relationship between the assembly angles of the rotors at all stages and the nodal vibration responses was established by combining the error transfer model with the dynamics model of the multistage rotor system. Furthermore, an optimization function was developed, which takes the assembly angles as the optimization variables and the maximum vibration velocity at the bearings as the optimization objective. Finally, a simplified four-stage high-pressure rotor system was assembled according to the optimal assembly angles calculated in the simulations. The experimental results showed that the maximum vibration velocity at the bearings under the optimal assembly was reduced by 69.6% and 45.5% compared with that under the worst assembly and default assembly. The assembly optimization method proposed in this study has a significant effect on the vibration suppression of the multistage rotor of an aero-engine. Full article

A dynamic analysis model of the unbalanced vibration response of a single-rotor system is established to study the corresponding mechanism of the unbalanced excitation force and vibration response caused by the deviation of the rotor mass centroid in this paper, and finally to achieve the combined rotor vibration suppression. First, the installation of multi-stage rotors during vibration was studied, and the rotor mass centroid transfer model in the rotating coordinate system was established to obtain the unbalanced excitation force vectors of the rotors at all levels based on the traditional stacking assembly method and axiality measurement. Second, the rotor unbalance excitation force vectors were substituted at all levels to establish the finite element analysis model of the single-rotor system. Finally, a simulation analysis was carried out for the stacking assembly of the three-stage rotor, and the rotor test piece was used for the vibration experiment. The results show that the optimal assembly phase of the multi-stage rotor obtained by the dynamic analysis model of the unbalanced vibration response of the single-rotor system can effectively suppress the vibration of the combined rotor. Full article

The unbalanced exciting force of high-speed rotary asymmetric rotor equipment is the main factor causing rotor vibration. In order to effectively suppress the vibration of the asymmetric rotor equipment, the paper establishes a multistage asymmetric rotor coaxial measurement stacking method that minimizes the exciting force. By analyzing the propagation process of the centroid of the multistage asymmetric rotor assembly and analyzing the relationship between the geometric center and the centroid of a single asymmetric rotor, a multistage asymmetric unbalanced rotor propagation model based on geometric center stacking is established. The genetic algorithm is used to optimize the unbalance of the multistage asymmetric rotors. Combined with the vibration principle under the exciting force, the vibration amplitude of the left bearing at different rotation speeds under the minimization of the exciting force and the random assembly phase is analyzed. Finally, the experimental asymmetric rotors are dynamically measured, combined with the asymmetric rotors’ geometric error measurement experiment. The experimental results confirm that the vibration amplitude of the assembly phase with the minimum exciting force is smaller than the vibration amplitude under the random assembly phase at three-speed modes, and the optimization rate reached 73.2% at 9000 rpm, which proves the effectiveness of the assembly method in minimizing the exciting force. Full article

The assembly quality of an aero-engine directly determines its stability in high-speed operation. The coaxiality and unbalance out of tolerance caused by improper assembly may give rise to complicated vibration faults. To meet the requirements of the dual objective and reduce the test cost, it is necessary to predict the optimal assembly angles of the rotors at each stage during pre-assembly. In this study, we proposed an assembly optimization method for a multistage rotor of an aero-engine. Firstly, we developed a coordinate transmission model to calculate the coordinates of any point in the rotors at each stage during the assembly processes of a multistage rotor. Moreover, we proposed two different pieces of assembly optimization data for the coaxiality and unbalance, and established a dual objective evaluation function of that. Furthermore, we used the genetic algorithm to solve the optimal assembly angles of the rotors at each stage. Finally, the Monte Carlo simulation technique was used to investigate the effects of the geometric measured errors of each rotor on the proposed genetic algorithm. The simulation results show that the process of the dual objective optimization had good convergence, and the obtained optimal assembly angles of each rotor were not affected by the geometric measured errors. In addition, the dual objective optimization can ensure that both the coaxiality and unbalance can approach their respective optimal values to the most extent, and the experimental results also verified this conclusion. Therefore, the assembly optimization method proposed in this study can be used to guide the assembly processes of the multistage rotor of an aero-engine to achieve synchronous optimization for the coaxality and unbalance. Full article

For the assembly of a multi-stage rotor, such as an aero-engine or gas turbine, the parts need to be assembled optimally to avoid excessive unbalance. We propose a method to optimize the unbalance of a multi-stage rotor during assembly. First, we developed an assembly error propagation model for a multi-stage rotor. The alignment process and distribution of the screw holes of the adjacent rotors was considered for the first time. Secondly, we propose a new assembly datum for unbalance optimization to ensure consistency with the actual conditions of a dynamic balance test. Finally, the unbalance optimization of a multi-stage rotor was achieved using a genetic algorithm, and the corresponding optimal assembly orientations of rotors at different stages were also identified. The results of the simulations showed that the assembly error propagation model had high accuracy and that the genetic optimization process had good convergence. The effect of unbalance optimization was also proven with experiments. Full article