A system for converting an input oscillation having an input frequency into an output oscillation having an output frequency is disclosed. The system comprises: a controller configured for receiving the input oscillation and responsively generating a multi-component drive signal. A frequency of at least one component of the drive signal is other than two times the input frequency. In some embodiments, a frequency of another component of the drive signal equals about two times the output frequency. The system also comprises an oscillator for generating pump oscillations responsively to the drive signal and applying parametric excitation to the input oscillation at the pump oscillations.

In a method for determining an equivalent modal unbalance for the first bending characteristic form of a shaft-elastic rotor, which unbalance is to be compensated for, a rotor model is created describing the geometric shape and material properties of the shaft-elastic rotor. The magnitude of compliance of the rotor model is calculated at a measurement point and at the center of gravity of the rotor at an assumed speed. The shaft-elastic rotor is received in a rotatable bearing and accelerated to the assumed speed which is below its first critical speed. Subsequently, the magnitude of outward deflection at the measurement point of the shaft-elastic rotor rotating at the assumed speed can be measured. The equivalent modal unbalance for the first bending characteristic form of the shaft-elastic rotor, which unbalance is to be compensated for, can be calculated from the magnitudes of the calculated compliance and the measured outward deflection.

In a method for determining an equivalent modal unbalance for the first bending characteristic form of a shaft-elastic rotor, which unbalance is to be compensated for, a rotor model is created describing the geometric shape and material properties of the shaft-elastic rotor. The magnitude of compliance of the rotor model is calculated at a measurement point and at the center of gravity of the rotor at an assumed speed. The shaft-elastic rotor is received in a rotatable bearing and accelerated to the assumed speed which is below its first critical speed. Subsequently, the magnitude of outward deflection at the measurement point of the shaft-elastic rotor rotating at the assumed speed can be measured. The equivalent modal unbalance for the first bending characteristic form of the shaft-elastic rotor, which unbalance is to be compensated for, can be calculated from the magnitudes of the calculated compliance and the measured outward deflection.

A dynamic balance testing device includes a vibrating unit configured to rotatably hold a predetermined rotating body being a specimen, a first spring configured to elastically support the vibrating unit and restrict displacement of the vibrating unit in a direction parallel to a rotation axis of the predetermined rotating body, and at least three second springs configured to elastically support the vibrating unit and restrict displacement of the vibrating unit in a predetermined direction orthogonal to the rotation axis. The at least three second springs are attached to the vibrating unit on a same predetermined plane, and the vibrating unit holds the predetermined rotating body such that a projection of a center of gravity of the predetermined rotating body onto the predetermined plane is substantially at the same position as a position where the first spring is attached to the vibrating unit.

A dynamic balance testing device includes a vibrating unit configured to rotatably hold a predetermined rotating body being a specimen, a first spring configured to elastically support the vibrating unit and restrict displacement of the vibrating unit in a direction parallel to a rotation axis of the predetermined rotating body, and at least three second springs configured to elastically support the vibrating unit and restrict displacement of the vibrating unit in a predetermined direction orthogonal to the rotation axis. The at least three second springs are attached to the vibrating unit on a same predetermined plane, and the vibrating unit holds the predetermined rotating body such that a projection of a center of gravity of the predetermined rotating body onto the predetermined plane is substantially at the same position as a position where the first spring is attached to the vibrating unit.

In a method for identifying an unbalance correction for flexible rotors (1), the rotor (1) is rotatably mounted in two bearing devices. An RPM sensor (4) records the speed of the rotor (1) and a radial movement of the rotor (1) is recorded, by means of position sensors (3) at measuring points (6), during an unbalance measurement run or a plurality of unbalance measurement runs for different rotor speeds. The measured values recorded are fed to an evaluation device (5), which determines the eccentricity measured values assigned to the measuring points (6) by means of expanding the influence coefficient method, and therefore unbalances are determined per plane and eccentricities are determined per measuring point for each measurement run.

In a method for identifying an unbalance correction for flexible rotors (1), the rotor (1) is rotatably mounted in two bearing devices. An RPM sensor (4) records the speed of the rotor (1) and a radial movement of the rotor (1) is recorded, by means of position sensors (3) at measuring points (6), during an unbalance measurement run or a plurality of unbalance measurement runs for different rotor speeds. The measured values recorded are fed to an evaluation device (5), which determines the eccentricity measured values assigned to the measuring points (6) by means of expanding the influence coefficient method, and therefore unbalances are determined per plane and eccentricities are determined per measuring point for each measurement run.

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.

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.

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.