Harbin Institute of Technology

Chuanzhi Sun

Jiubin Tan

Yongmeng Liu

Bo Zhao

Lei Wang

Huilin Wu

Provided is a large high-speed rotary equipment gap stacking assembly apparatus and assembly method based on digital twin, and relates to the technical field of engine assembly measurement. The disclosure solves the problem of unbalanced rotation of the rotary parts caused by large assembly error during multi-stage rotary parts are stacked in a gap way. The disclosure includes the assembly apparatus entity and the assembly method; the assembly apparatus entity is configured to establish data communication with the upper computer through data acquisition apparatus, and upper computer is configured to establish a virtual assembly model; the virtual assembly model and optimal coaxiality of the multi-stage rotary parts in gap stacking can be obtained according to the assembly method, and the assembly process can be controlled by using the virtual assembly model and the optimal coaxiality. The disclosure is suitable for controlling the assembly process of the rotary parts.

Large high-speed rotary device gap stacking assembly apparatus and assembly method based on digital twin

The present invention provides a large-scale high-speed rotary equipment measuring and intelligent learning assembly method and device based on vector minimization geometry center, mass center, the center of gravity and the center of inertia, belonging to the technical field of mechanical assembly. The method includes the steps of establishing a four-parameter circular profile measuring model for a single stage of rotor, simplifying the established four-parameter circular profile measuring model for the single stage of rotor, and establishing a four-target optimization model of the geometry center, mass center, the center of gravity and the center of inertia of multiple stages of rotors based on the angular orientation mounting position of each stage of rotor. The device include a base, an air flotation shaft system, an aligning and tilt regulating workbench, precise force sensors, a static balance measuring platform, an upright column, a lower transverse measuring rod, a lower telescopic inductive sensor, an upper transverse measuring rod and an upper lever type inductive sensor.

Large-scale high-speed rotary equipment measuring and intelligent learning assembly method and device based on vector minimization of geometry center, mass center, center of gravity and center of inertia

The disclosure provides a stage-by-stage measurement, regulation and distribution method for dynamic characteristics of multi-stage components of large-scale high-speed rotary equipment. Firstly, a single-stage rotor circular contour measurement model is established, and the circular contour measurement model is simplified by using a distance from an ith sampling point of an ellipse to a geometry center to obtain a simplified circular contour measurement model. Then, actually measured circular contour data is taken into the simplified circular contour measurement model to determine a relationship between dynamic response parameters after rotor assembly and eccentricity errors as well as the amount of unbalance of all stages of rotors. Finally, a rotor speed is set according to the relationship between the dynamic response parameters after rotor assembly and the eccentricity errors as well as the amount of unbalance of all stages of rotors to obtain a critical speed parameter objective function.

Stage-by-stage measurement, regulation and distribution method for dynamic characteristics of multi-stage components of large-scale high-speed rotary equipment based on multi-biased error synchronous compensation

The present invention provides a large-scale high-speed rotary equipment measuring and neural network learning regulation and control method and device based on rigidity vector space projection maximization, belonging to the technical field of mechanical assembly. The method utilizes an envelope filter principle, a two-dimensional point set S, a least square method and a learning neural network to realize large-scale high-speed rotary equipment measuring and regulation and control. The device comprises a base, an air flotation shaft system, an aligning and tilt regulating workbench, precise force sensors, a static balance measuring platform, a left upright column, a right upright column, a left lower transverse measuring rod, a left lower telescopic inductive sensor, a left upper transverse measuring rod, a left upper telescopic inductive sensor, a right lower transverse measuring rod, a right lower lever type inductive sensor, a right upper transverse measuring rod and a right upper lever type inductive sensor. The method and the device can perform effective measuring and accurate regulation and control on large-scale high-speed rotary equipment.

Large-scale high-speed rotary equipment measuring and neural network learning regulation and control method and device based on rigidity vector space projection maximization

The present invention provides a deep learning regulation and control and assembly method and device for large-scale high-speed rotary equipment based on dynamic vibration response properties. The present invention starts from geometrical deviation of multiple stages of rotor/stator of an aircraft engine, amount of unbalance of rotor/stator, rigidity of rotor/stator and vibration amplitude of rotor/stator, considers the influence of the area of the assembly contact surface between two stages of rotors/stators, and sets the rotation speed of rotor/stator to be the climbing rotation speed to obtain vibration amplitude parameters. According to the calculation method of the coaxiality, amount of unbalance, rigidity and vibration amplitude of multiple stages of rotor/stator, an objective function taking assembly phases as variables is established, a Monte Carlo method is used to solve the objective function, and a probability density function is solved according to a drawn distribution function to obtain the probability relationship between the contact surface runout of the rotor/stator of the aircraft engine and the final coaxiality, amount of unbalance, rigidity and vibration amplitude of multiple stages of rotor/stator, thereby realizing assembly optimization and distribution of tolerances of multiple stages of rotor/stator.

Deep learning regulation and control and assembly method and device for large-scale high-speed rotary equipment based on dynamic vibration response properties

An aero engine rotor air floatation assembling method and device based on a gantry structure belong to mechanical assembling technology. The present invention can effectively solve the problem of poor coaxality after the aero engine rotor is assembled and has the characteristics of high coaxality after the rotor is assembled, reduced vibration, mounting easiness, high flexibility and improved engine performance. The measuring method and device are: determining rotary reference based on a rotary air bearing; determining the angular positioning of a rotary table according to a grating ruler; extracting the radial error of the radial mounting plane and the inclination error of the axial mounting plane of the rotor based on the four-probe measuring device to obtain the influencing weight of this rotor to the assembled rotor on coaxality; measuring respectively all the rotors required for assembling to obtain the influencing weight of each rotor to the assembled rotor on coaxality; vector optimizing the weight of each rotor to obtain the assembling angle of each rotor.

Aero engine rotor air floatation assembling device based on gantry structure

Aircraft engine rotors traditionally have low coaxiality after assembly. This is solved by the methods and devices described herein, having advantages that the rotors have high coaxiality after assembly, reduced vibration, easy installation, high flexibility, and improved engine performance. A measurement method and device use an air flotation rotary shaft system determining a rotary reference. An induction synchronizer determines angular positioning of a turntable. Using a four probe measurement device, a radial error of a rotor radial assembly surface and an inclination error of an axial mounting surface are extracted and an influence weight value of the rotor on the coaxiality of assembled rotors is obtained. All rotors required for assembly are measured and an influence weight value of each on the coaxiality of the assembled rotors is obtained. Vector optimization is performed on the weight value of each rotor and an assembly angle of each rotor is obtained.

Aircraft engine rotor assembly method and device

An aero engine rotor assembling method and device based on concentricity and verticality measurement belongs to mechanical assembly technology. The present invention effectively solves the problem of poor coaxality after the aero engine rotor is assembled and has the characteristics of high coaxality after the rotor is assembled, reduced vibration, mounting easiness, high flexibility and improved engine performance. The measurement and device is: determining rotary reference; determining the angular positioning of a rotary table; extracting the radial error of the radial mounting plane and the inclination error of the axial mounting plane of the rotor based on the four-probe measuring device to obtain the influencing weight of this rotor to the assembled rotor on coaxality; measuring respectively all the rotors to obtain the influencing weight of each rotor to the assembled rotor on coaxality; vector optimizing the weight of each rotor to obtain the assembling angle of each rotor.

Growing community of inventors

Harbin, China

Chuanzhi Sun