Method for the automatic detection and identification of errors in a balancing machine

• US 8,561,463 B2
• Filed: 08/11/2010
• Issued: 10/22/2013
• Est. Priority Date: 08/20/2009
• Status: Active Grant

• Current Assignee: Schenck Rotec GmbH (Durr AG)
• Original Assignee: Schenck Rotec GmbH (Durr AG)
• Inventors: Baehr, Joachim, Isermann, Rolf, Thelen, Dieter, Scheithe, Wolfgang
• Primary Examiner(s): Macchiarolo, Peter
• Assistant Examiner(s): Shah, Samir M
• Application Number:
  US12/806,382
• Publication Number:
  US 20110067493A1
• Time in Patent Office: 1,168 Days
• Field of Search: 734/62, 737/60, 734/60, 73/66, 301/5.21, 700/279, 706/23
• US Class Current: 73/462
• CPC Class Codes: G01M 1/22 and converting vibrations due to imbalance into electric variables

Abstract

A method is disclosed for the automatic detection and identification of errors in a balancing machine during operation, in which a rotor provided with an unbalance is rotatably mounted in a vibratory bearing in the balancing machine and is set in rotation by a drive, the rotational frequency of the rotating rotor and the vibrations stimulated by the rotor are measured and measurement signals which comprise the measured values of the rotational frequency and the vibrations are generated and delivered to an evaluation computer. The evaluation calculation is based on mathematical models of the dynamic properties of the balancing machine which describe stimulations of the machine structure due to the unbalance, in particular in the balancing planes, and/or due to the rotor geometry and/or due to the bearing and/or possible damage to the bearing. Features such as vibration characteristics and/or process parameters are calculated by a signal-model-based method from the measurement signals, and discrepancies are established by comparing the calculated features with predetermined normal features of an error-free process.

Claims

1. A method for automatic detection and identification of errors in a balancing machine during operation, comprising the following steps:

rotating a rotor by a drive, the rotor being provided with an unbalance and being rotatably mounted in a vibratory bearing in the balancing machine;

measuring a rotational frequency of the rotating rotor and vibrations generated by the rotor;

delivering measurement signals which comprise measured values of the rotational frequency and the vibrations being generated to an evaluation computer; and

evaluating the measurement signals,

wherein said step of evaluating uses a calculation based on mathematical models of dynamic properties of the balancing machine, said models describing stimulations of a structure of the machine due to the unbalance and at least one of the following;

rotor geometry, the bearing, possible damage to the bearing, constraining forces, movement restriction of the vibratory bearing, and external interference vibrations,

wherein features including vibration characteristics or process parameters are calculated by a signal-model-based method from the measurement signals using various signal models, including at least one of constant-frequency vibrations, stochastic signals, and variable-frequency vibrations, and discrepancies are established by comparing calculated features with predetermined normal features of an error-free process, and

wherein the discrepancies, as error symptoms, are allocated to error types, and the error symptoms allocated to one or more error types are evaluated to determine causes of errors.

2. The method according to claim 1, wherein the features are additionally calculated using a process-model-based method and discrepancies are established by comparison with predetermined normal features of an error-free process.

3. The method according to claim 1, wherein a rule-based error diagnosis system based on fuzzy logic is used to determine the causes of errors, the probability of the occurrence of each error being determined by intermediate steps of converting the error symptoms into linguistic variables, i.e., (fuzzification) and evaluating an “

IF”

part, i.e., (aggregation) and a “

THEN”

part, i.e., (accumulation) of each rule of a rule base.

4. A method for automatic detection and identification of errors in a balancing machine during operation, comprising the following steps:

rotating a rotor by a drive, the rotor being provided with an unbalance and being rotatably mounted in a vibratory bearing in the balancing machine;

measuring a rotational frequency of the rotating rotor and vibrations generated by the rotor;

delivering measurement signals which comprise measured values of the rotational frequency and the vibrations being generated to an evaluation computer; and

evaluating the measurement signals,

wherein said step of evaluating uses a calculation based on mathematical models of dynamic properties of the balancing machine which describe stimulations of the machine structure due to at least one of the following;

the unbalance, rotor geometry, the bearing, and possible damage to the bearing,

wherein features including vibration characteristics or process parameters are calculated by a signal-model-based method from the measurement signals, and discrepancies are established by comparing calculated features with predetermined normal features of an error-free process, and

wherein the measurement signals having a frequency which varies over time are subjected to a wavelet transformation after filtering, and after calculating wavelet transforms, complex amplitude progressions of the vibrations are estimated, and wherein an amplitude progression of a reconstructed unbalance moment is estimated for an error-free case and features for error identification are formed by comparison thereof with complex amplitude progressions.

5. The method according to claim 4, wherein the measurement signals having a frequency which varies over time are detected during a run-up of the rotor to a measurement rotational speed.

6. The method according to claim 4, wherein a low-pass filter is used to filter the measurement signals.

7. The method according to claim 4, wherein the wavelet transformation uses a Morlet Wavelet.

8. The method according to claim 4, wherein estimation of the complex amplitude progressions of the vibrations uses a least squares method.

9. A method for automatic detection and identification of errors in a balancing machine during operation, comprising the following steps:

rotating a rotor by a drive, the rotor being provided with an unbalance and being rotatably mounted in a vibratory bearing in the balancing machine;

measuring a rotational frequency of the rotating rotor and vibrations generated by the rotor;

delivering measurement signals which comprise measured values of the rotational frequency and the vibrations being generated to an evaluation computer; and

evaluating the measurement signals,

wherein said step of evaluating uses a calculation based on mathematical models of dynamic properties of the balancing machine which describe stimulations of the machine structure due to at least one of the following;

the unbalance, rotor geometry, the bearing, and possible damage to the bearing,

wherein features including vibration characteristics or process parameters are calculated by a signal-model-based method from the measurement signals, and discrepancies are established by comparing calculated features with predetermined normal features of an error-free process, and

wherein a respective power spectrum is calculated for harmonic amplitudes during run-up of the rotor to a measurement rotational speed and during the measuring process, and taking the difference between the power spectra from the measuring process and from the run-up results in differential amplitudes which are used to form features for error identification.

10. A method for automatic detection and identification of errors in a balancing machine during operation, comprising the following steps:

rotating a rotor by a drive, the rotor being provided with an unbalance and being rotatable mounted in a vibratory bearing in the balancing machine;

measuring a rotational frequency of the rotating rotor and vibrations generated by the rotor;

delivering measurement signals which comprise measured values of the rotational frequency and the vibrations being generated to an evaluation computer; and

evaluating the measurement signals,

wherein said step of evaluating uses a calculation based on mathematical models of dynamic properties of the balancing machine which describe stimulations of the machine structure due to at least one of the following;

the unbalance, rotor geometry, the bearing, and possible damage to the bearing,

wherein features including vibration characteristics or process parameters are calculated by a signal-model-based method from the measurement signals, and discrepancies are established by comparing calculated features with predetermined normal features of an error-free process, and

wherein by filtering the measurement signals, ranges around resonant frequencies are amplified and secondary frequencies are suppressed, an envelope is generated from a filtered signal and a frequency spectrum of an envelope is calculated, and features for error identification are generated by comparing the frequency spectrum with limit values which are based on empirical values, and the frequency spectrum of the envelope is calculated by the maximum entropy method.

11. The method according to claim 10, wherein a band-pass filter is used to filter the measurement signals.

12. A method for automatic detection and identification of errors in a balancing machine during operation, comprising the following steps:

rotating a rotor by a drive, the rotor being provided with an unbalance and being rotatably mounted in a vibratory bearing in the balancing machine;

measuring a rotational frequency of the rotating rotor and vibrations generated by the rotor;

delivering measurement signals which comprise measured values of the rotational frequency and the vibrations being generated to an evaluation computer; and

evaluating the measurement signals,

wherein said step of evaluating uses a calculation based on mathematical models of dynamic properties of the balancing machine which describe stimulations of the machine structure due to at least one of the following;

the unbalance, rotor geometry, the bearing, and possible damage to the bearing,

wherein features including vibration characteristics or process parameters are calculated by a signal-model-based method from the measurement signals, and discrepancies are established by comparing calculated features with predetermined normal features of an error-free process, and

wherein a noise intensity of a noise component, separate from the unbalance vibration, of the measurement signals is estimated and the estimated noise intensity exceeding a predetermined limit value is used as a feature for indicating errors caused by external interference effects, damage to the bearing rolling surface and lumping of the rotor.

13. The method according to claim 12, wherein the measurement signals are filtered by a low-pass filter to separate the noise component from the unbalance vibration, the measurement rotational speed forming an upper limit frequency of a low-pass filter.

14. A method for automatic detection and identification of errors in a balancing machine during operation, comprising the following steps:

rotating a rotor by a drive, the rotor being provided with an unbalance and being rotatably mounted in a vibratory bearing in the balancing machine;

measuring a rotational frequency of the rotating rotor and vibrations generated by the rotor;

delivering measurement signals which comprise measured values of the rotational frequency and the vibrations being generated to an evaluation computer; and

evaluating the measurement signals,

wherein said step of evaluating uses a calculation based on mathematical models of dynamic properties of the balancing machine which describe stimulations of the machine structure due to at least one of the following;

the unbalance, rotor geometry, the bearing, and possible damage to the bearing,

wherein features including vibration characteristics or process parameters are calculated by a signal-model-based method from the measurement signals, and discrepancies are established by comparing calculated features with predetermined normal features of an error-free process, and

wherein filtering the measurement signals suppresses the effects of the unbalance vibration and a frequency range is restricted to a range of the first two resonant frequencies, and wherein the measurement signal is composed of a response of a linear system of order four or higher to stochastic stimulation, a recursive parameter estimation is carried out to calculate parametric transfer functions of the first two resonant frequencies, and subsequently the resonant frequencies and a ratio of the resonant amplitudes is determined, a feature being formed by the ratio of the resonance amplitudes exceeding a limit value.

15. The method according to claim 14, wherein a band-pass filter is used to filter the measurement signals.

16. The method according to claim 14, wherein the recursive parameter estimation uses a least squares method.