CN113657328A - Self-powered bearing with torsional vibration fault diagnosis function and torsional vibration fault diagnosis method - Google Patents
Self-powered bearing with torsional vibration fault diagnosis function and torsional vibration fault diagnosis method Download PDFInfo
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- CN113657328A CN113657328A CN202110976783.7A CN202110976783A CN113657328A CN 113657328 A CN113657328 A CN 113657328A CN 202110976783 A CN202110976783 A CN 202110976783A CN 113657328 A CN113657328 A CN 113657328A
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Abstract
The application provides a self-powered bearing with torsional vibration fault diagnosis function, its characterized in that: the method comprises the following steps: the device comprises a bearing body, a novel variable reluctance structure fixedly connected with the inner annular surface of the outer ring of the bearing body, a wireless sensing unit fixedly connected with the inner annular surface of the outer ring of the bearing body, a voltage comparison unit connected with the output end of the novel variable reluctance structure and a torsional vibration fault diagnosis unit, wherein the fault diagnosis unit is in communication connection with the wireless sensing unit and the voltage comparison unit; according to the high-speed rail bearing with the self-powered torsional vibration fault diagnosis function and the torsional vibration fault diagnosis method, the wireless sensing unit and the novel variable reluctance structure are integrated in the bearing, and the intelligent bearing self-powered function, the rotation speed, the vibration and the temperature monitoring function with high power density, convenience in installation and high reliability are realized; meanwhile, the torsional vibration fault diagnosis is realized by utilizing the rotating speed information acquired by the wireless sensing unit based on a high-frequency sampling algorithm.
Description
Technical Field
The invention relates to the technical field of bearing and bearing fault diagnosis, in particular to a self-powered bearing with a torsional vibration fault diagnosis function and a torsional vibration fault diagnosis method.
Background
At present, the axle box bearing for the domestic high-speed train is mainly a double-row tapered roller bearing, the bearing not only needs to bear the weight of the whole train body, but also needs to bear certain axial load, and meanwhile, the bearing also needs to have high reliability at a high speed level, and failure caused by any factor is avoided. The reliability and the safety of the high-speed motor train unit are directly influenced by the reliability and the safety of the high-speed motor train unit, the running efficiency of the high-speed motor train unit is reduced slightly, the function and the performance of an axle bogie are influenced, accidents such as derailment and combustion of a high-speed train are caused seriously, casualties are caused, and hundreds of millions of property losses are caused. The high-speed rail axle box bearing is used as a joint for high-speed rail running, in the working process, on one hand, stress and deformation are generated near a contact area to form microcracks due to mutual extrusion of contact surfaces of a rolling body, an inner roller way, an outer roller way and a retainer pocket, on the other hand, the labyrinth seal interference magnitude is large, the higher the running speed of a train is, the larger the load borne by the axle box bearing is, the temperature rise of the axle box bearing is aggravated, and the unpredictable bearing faults seriously restrict the development of the high-speed rail bearing technology. The research shows that: the high-speed rail rolling bearing is a gradual change process from a healthy operation state to failure damage, early abnormal signals are timely found through real-time monitoring of physical signals such as high-speed rail axle box bearing rotating speed signals, vibration signals and temperature, early fault diagnosis is carried out on the bearing before the bearing is damaged, the service life of the bearing can be effectively prolonged, early prediction and prevention of accidents are achieved, and personal and property safety is prevented from being threatened due to unpredictable faults of the bearing.
The main means for realizing real-time acquisition of the shaft carrying running state signals of the current intelligent bearing is to externally connect a temperature sensor, a vibration sensor and a rotating speed sensor at the position of an end cover on the side surface of the bearing, wherein a magnetic ring encoder and a Hall sensor are combined to extract the rotating speed signals, and the signals are transmitted to a computer end in a wired/wireless mode to be monitored. The method is simple and easy to install, can effectively extract the rotating speed, temperature and vibration signals of the bearing, but because the sensor is installed on the side surface of the bearing, the failure of the bearing mainly occurs in the bearing, and the installation mode of the sensor can not effectively monitor the vibration and temperature rise conditions in the bearing; because the high-speed rail bearing operates in a high-temperature environment and is heated rapidly, the rotating speed is measured by combining the magnetic encoder and the Hall sensor, and the problems that the magnet part of the magnetic encoder is oxidized and deteriorated, the extension and bending performance is reduced, cracks occur and the like exist. On the other hand, the problem that the sensors cannot work normally after the electric quantity is exhausted, the power supply needs to be replaced regularly or irregularly, the waste power supply pollutes the environment and the like exists when the chemical power supply is used for providing energy for various sensor nodes integrated in the intelligent bearing. In the prior art, a magnetoelectric self-powered technology is mainly adopted to supply power to an intelligent bearing wireless sensing node, magnetic steel N, S is alternately and uniformly arranged on a bearing rotating component, a coil is arranged on a static component/a bearing end cover, and the rotation of the bearing is utilized to cut a magnetic sensing wire, so that alternating current is generated on the coil. The magnetoelectric energy recovery structure for realizing the self-powered function of the intelligent bearing is easy to integrate on the bearing, but is inconvenient to install and low in reliability, and because the magnetic steel and the coil are mostly fixed inside the bearing in a bonding mode, the problems that the magnetic steel is low in installation precision, and the magnetic steel is easy to fall off in a high-temperature environment and the like exist. Torsional vibration is used as basic vibration generated by a rotating machine, in order to avoid serious potential safety hazard caused by the fact that a high-speed train works in torsional vibration resonance frequency of a bearing, a non-contact measuring instrument is mainly adopted in the prior art to extract torsional vibration signals through a special analog circuit processing unit and further analyze the signals, but a hardware circuit is unreliable in a high-speed high-temperature environment in the high-speed train bearing.
Therefore, a new bearing and a method for diagnosing torsional vibration failure are needed.
Disclosure of Invention
In view of this, the present invention provides a self-powered bearing with a torsional vibration fault diagnosis function, which is characterized in that: the method comprises the following steps: the device comprises a bearing body, a novel variable reluctance structure fixedly connected with the inner ring surface of the outer ring of the bearing body, a voltage comparison unit connected with the output end of the novel variable reluctance structure, and a torsional vibration fault diagnosis unit in communication connection with the output end of the voltage comparison unit;
the annular middle space ring of the bearing body is in a tooth shape;
novel become magnetic resistance mechanism includes coil, magnet steel, E type silicon steel and fixed casing, and the magnet steel is installed in E type silicon steel and is stretched out the end portion, and the coil winding stretches out the end at E type silicon steel, fixed casing encapsulates coil, magnet steel and E type silicon steel inside it, and fixed casing with bearing inner race inner ring face fixed connection.
Further, the torsional vibration fault diagnosis unit comprises a data preprocessing unit and a fault diagnosis unit, wherein the data preprocessing unit is used for receiving the data transmitted by the signal processing subunit and preprocessing the data, meanwhile, the preprocessed data are transmitted to the fault diagnosis unit, and the fault diagnosis unit diagnoses whether the bearing has a fault according to the preprocessed data.
Further, the data preprocessing unit comprises a data acquisition unit for receiving the data transmitted by the signal processing subunit, an envelope demodulation unit for receiving the data of the data acquisition unit and filtering noise in the data, a data zero interpolation unit for receiving the data output by the envelope demodulation unit and performing zero data interpolation on the data, a data threshold cleaning unit for receiving the data output by the data zero interpolation unit and performing threshold cleaning on the data, an average rotating speed determination unit for receiving the data of the data threshold cleaning unit and determining a periodic average rotating speed, and a torsion angle determination unit for determining a torsion angle rotated by the tapered roller.
Further, the fault diagnosis unit includes: the system comprises a data sequence conversion unit for performing sequence conversion on rotation speed data obtained by preprocessing, a data slice sorting unit for receiving the data of the data sequence conversion unit and performing slice sorting processing on the data, a data zero filling unit for receiving the data of the data slice sorting unit and filling zero into the data, a time-frequency analysis unit for receiving the data of the data zero filling unit and extracting torsional vibration time-domain signals according to the data, and a positioning unit for receiving the data of the time-frequency analysis unit and performing characteristic frequency positioning on the data.
Further, the non-bearing area of the inner ring surface of the outer ring of the bearing body is provided with a groove for accommodating the novel variable reluctance structure.
Further, the number of the coils is 1 or more.
Accordingly, the present application also provides a torsional vibration fault diagnosis method, which is characterized in that the method is applied to a self-powered bearing with a torsional vibration fault diagnosis function, and the method comprises the following steps:
s1: inputting algorithm parameters and rotating speed data, wherein the algorithm parameters comprise sampling frequency f, tooth number z, rotating speed sequence length, rotating speed sequence X (i), tooth average M and period average M;
s2: determining a zero sequence of the rotating speed data by adopting a linear interpolation method;
s3: judging whether the false zero point introduced by the random noise is larger than a threshold value, if so, entering the next step, and if not, entering the next false zero point value and repeating the step S3;
s4: determining the instantaneous rotating speed sequence after periodic filtering by the zero sequence through periodic averaging;
s5: carrying out periodic sampling integral averaging on the instantaneous rotating speed series to obtain an average rotating speed sequence in each period;
s6: determining a torsion angle sequence through the instantaneous rotating speed sequence and the average rotating speed sequence;
s7: and (4) judging whether the torsion angle obtained in the step (S6) is obviously larger than the mean value of the torsion angles calculated when the shafting normally runs, if so, failing the bearing, otherwise, failing the bearing.
The invention has the beneficial technical effects that: according to the bearing with the torsional vibration fault diagnosis function and the torsional vibration fault diagnosis method, the wireless sensing unit and the novel variable reluctance structure are integrated in the bearing, and the intelligent bearing self-power supply and rotating speed monitoring functions with high power density, convenience in installation and high reliability are achieved; meanwhile, the torsional vibration fault diagnosis is realized by utilizing the rotating speed information acquired by the wireless sensing unit based on a high-frequency sampling algorithm.
Drawings
The invention is further described below with reference to the following figures and examples:
FIG. 1 is a system block diagram of the present invention.
Fig. 2 and 3 are schematic structural diagrams of a self-powered bearing integrating a novel variable reluctance structure and a flexible sensing unit according to the present invention.
Fig. 4 is a schematic structural diagram of an energy and rotation speed acquisition unit of the invention.
Fig. 5 is a waveform diagram of ac induced electromotive force generated by three coils during the operation of the bearing.
Fig. 6 is a flow chart of the torsional vibration fault diagnosis unit.
Fig. 7 is a block diagram of a torsional vibration fault diagnosis unit system.
Detailed Description
The invention is further described with reference to the accompanying drawings in which:
the invention provides a self-powered bearing with a torsional vibration fault diagnosis function, which is characterized in that: the method comprises the following steps: as shown in fig. 1, a bearing body, a voltage comparison unit connected to an output end of a novel variable reluctance structure fixedly connected to an inner annular surface of an outer ring of the bearing body, and a torsional vibration fault diagnosis unit communicatively connected to an output end of the voltage comparison unit; the bearing of the application also comprises a wireless sensing module 4, wherein the wireless sensing module 4 is used for collecting vibration, temperature and strain of the bearing and transmitting collected information to a fault diagnosis unit.
The annular middle space ring of the bearing body is in a tooth shape; wherein, the annular middle space ring of the bearing body is in a tooth shape; in the present example, the teeth of the toothed middle spacer 12 are evenly distributed, the number of teeth is 18, and the teeth are spaced 20 ° from the teeth.
As shown in fig. 2 and 3, the novel variable reluctance mechanism includes a coil 14, magnetic steel 15, E-type silicon steel 16 and a fixed housing 17, the magnetic steel 14 is installed at an end portion of an extending end of the E-type silicon steel 16, the coil 14 is wound at the extending end of the E-type silicon steel 16, the coil 14, the magnetic steel 15 and the E-type silicon steel 16 are packaged inside the fixed housing 17, and the fixed housing is fixedly connected with an inner ring surface 7-1 of the bearing outer ring. The magnetic steel 15 is designed to be embedded into a wedge-shaped groove at the end part of the extending end of the E-shaped silicon steel 16 in a wedge shape and is made of high-temperature resistant neodymium iron boron materials. The fixed shell 17 is made of a metal shielding material by using a 3D printing technology. Fig. 5 shows the alternating voltage generated by the coil 14 during the operation of the bearing by the variable reluctance acquisition module 13, wherein the induced electromotive forces of the coils 14-1 and 14-2 at the two sides of the E-type silicon steel 16 are in the same phase, and the induced electromotive forces generated by the coil 14-3 at the middle side are 180 degrees out of phase. Novel become magnetic resistance mechanism on the one hand and convert the rotary motion of bearing into the electric energy and provide the electric energy for wireless acquisition unit (modules such as vibration, temperature, strain transducer and wireless communication), on the other hand, the usable sinusoidal voltage signal who gathers converts PWM signal transmission into through voltage comparator and carries out the measurement and the failure diagnosis of rotational speed for torsional vibration failure diagnosis unit.
On one hand, the novel variable reluctance mechanism can utilize the collected sinusoidal voltage signal to be converted into a PWM signal by a voltage comparator and then transmitted to a torsional vibration fault diagnosis unit for measuring the rotating speed and diagnosing the fault; on the other hand, the rotary motion of the bearing is converted into electric energy to provide working electricity for the acquisition equipment of the bearing, such as a sensor for acquiring vibration, temperature and strain signals.
In the embodiment, as shown in fig. 2 and 3, the bearing is a double-row tapered roller bearing, and the bearing comprises an outer ring 7, an inner ring 8, rollers 9, a retainer 10, a seal ring 11 and a spacer ring 12, supports a high-speed rail carriage, and bears radial and axial loads transmitted to the high-speed rail carriage by a bogie during high-speed operation. The wireless sensing unit 4 is made of a 0.4mm flexible circuit board and is fixedly connected with an inner ring surface 7-1 of the bearing outer ring, for example, the wireless sensing unit is fastened on the bearing outer ring 7 in a threaded connection mode. The novel variable reluctance structure comprises a coil 14, magnetic steel 15, E-type silicon steel 16, a fixed upper shell 17-1 and a fixed lower shell 17-2, and is shown in figure 4. The magnetic pole directions of the magnetic steel 15 are all along the radial direction of the bearing, the directions of the magnetic steels 15-1 and 15-2 at the end parts of the two extending ends at the outer side are the same, the directions of the magnetic poles of the magnetic steel 15-3 at the middle extending end are opposite to the directions of the magnetic poles of the magnetic steels 15-1 and 15-2 at the outer side extending ends, and magnetic lines of force are restrained in the whole variable reluctance structure 2. In order to prevent the coil 14 from short-circuiting during the operation of the bearing, the coil 14 is encapsulated by insulating glue and then sleeved on the extending end of the E-shaped silicon steel 16. Because the bearing steel is made of ferromagnetic materials, in order to prevent the variable reluctance structure 2 from generating a magnetic flux leakage phenomenon, the coil 14, the magnetic steel 15 and the E-shaped silicon steel 16 are packaged inside the fixed shell 17, an installation groove of the acquisition module 13 is processed in a non-bearing area of the inner ring surface 7-1 of the outer ring of the bearing, and the acquisition module 13 is fastened on the inner ring surface 7-1 of the outer ring of the bearing by screws penetrating through two outer lugs of the fixed shell.
In the working process of the bearing, the tooth-shaped middle spacer ring 12 of the variable reluctance structure 2 rotates along with the inner ring of the bearing, the acquisition module 13 arranged on the outer ring 7 of the bearing and the middle spacer ring 12 move relatively, the magnetic flux passing through the coil 14 can change along with the change of the relative position of the tooth-shaped middle spacer ring 12 and the extending end of the E-shaped silicon steel 16 in the whole movement process, so that induced electromotive force is generated in the coil 14 of the acquisition module 13, the rotary movement of the bearing is converted into electric energy to provide energy for the wireless sensing unit 4, and meanwhile, the voltage comparator 3 is utilized to convert the induced alternating current of the coil 14 in the acquisition module 13 into PWM (pulse width modulation) waves to measure the rotating speed information of the bearing. The torsional vibration fault diagnosis unit 6 comprises a data preprocessing module 18 and a fault diagnosis module 19, wherein the data preprocessing module 18 receives PWM wave information and reads and smoothly filters the rotating speed data; the fault diagnosis module 19 analyzes and processes the preprocessed rotating speed data, extracts characteristic information, and performs classification diagnosis on the frequency spectrum data to obtain a fault diagnosis result.
In this embodiment, the torsional vibration fault diagnosis unit includes a data preprocessing unit and a fault diagnosis unit, where the data preprocessing unit is configured to receive data transmitted by the signal processing subunit and preprocess the data, and transmit the preprocessed data to the fault diagnosis unit, and the fault diagnosis unit diagnoses whether the bearing has a fault according to the preprocessed data.
In this embodiment, as shown in fig. 7, the data preprocessing unit 18 includes a data acquiring unit 20 for receiving the data transmitted by the signal processing subunit, an envelope demodulating unit for receiving the data of the data acquiring unit and filtering noise in the data, a data zero-point interpolating unit 21 for receiving the data output by the envelope demodulating unit and performing zero-point data interpolation on the data, a data threshold cleaning unit 23 for receiving the data output by the data zero-point interpolating unit and performing threshold cleaning on the data, an average rotating speed determining unit for receiving the data of the data threshold cleaning unit and determining a periodic average rotating speed, and a torsion angle determining unit 25 for determining a torsion angle of the tapered roller.
The failure diagnosis unit 19 includes: the system comprises a data sequence conversion unit 26 for performing sequence conversion on the rotation speed data obtained by preprocessing, a data slice sorting unit 27 for receiving the data of the data sequence conversion unit and performing slice sorting processing on the data, a data zero filling unit 28 for receiving the data of the data slice sorting unit and filling zero in the data, a time-frequency analysis unit 30 for receiving the data of the data zero filling unit and extracting torsional vibration time-domain signals according to the data, and a positioning unit 31 for receiving the data of the time-frequency analysis unit and performing characteristic frequency positioning on the data.
And a non-bearing area of the inner ring surface of the outer ring of the bearing body is provided with a groove for accommodating the novel variable reluctance structure.
In the present embodiment, the number of the coils 14 is 1 or more. In this embodiment, the number of the coils 14 is 3, the coils 14 are respectively sleeved on three extending ends of the E-type silicon steel 16, and the energy of the coil output ends can be increased by simply connecting the output ends of the coils 14-1, 14-2 and 14-3 in series/parallel, and meanwhile, if one of the coils 14 fails, the other coils 14 can provide energy and bearing rotation speed information for the wireless sensing unit 4. The waveform of the ac induced electromotive force generated by the three coils during the operation of the bearing is shown in fig. 5.
Accordingly, the present application also provides a torsional vibration fault diagnosis method, which is characterized in that the method is applied to a self-powered bearing with a torsional vibration fault diagnosis function, and the method comprises the following steps:
s1: inputting algorithm parameters and rotating speed data, wherein the algorithm parameters comprise sampling frequency f, tooth number z, rotating speed sequence length, rotating speed sequence X (i), tooth average M and period average M;
s2: determining a zero sequence of the rotating speed data by adopting a linear interpolation method;
s3: judging whether the false zero point introduced by the random noise is larger than a threshold value, if so, entering the next step, and if not, entering the next false zero point value and repeating the step S3;
s4: determining the instantaneous rotating speed sequence after periodic filtering by the zero sequence through periodic averaging;
s5: carrying out periodic sampling integral averaging on the instantaneous rotating speed series to obtain an average rotating speed sequence in each period;
s6: determining a torsion angle sequence through the instantaneous rotating speed sequence and the average rotating speed sequence;
s7: and (4) judging whether the torsion angle obtained in the step (S6) is obviously larger than the mean value of the torsion angles calculated when the shafting normally runs, if so, failing the bearing, otherwise, failing the bearing. As shown in figure 5 of the drawings,
in addition, the application also provides a method for determining the torsional resonance frequency, and the method for determining the torsional resonance frequency comprises the following steps: as shown in figure 6 of the drawings,
s1: inputting algorithm parameters and rotating speed data, wherein the algorithm parameters comprise sampling frequency f, tooth number z, rotating speed sequence length, rotating speed sequence X (i), tooth average M and period average M;
s2: determining a zero sequence of the rotating speed data by adopting a linear interpolation method;
s3: judging whether the false zero point introduced by the random noise is larger than a threshold value, if so, entering the next step, and if not, entering the next false zero point value and repeating the step S3;
s4: determining the instantaneous rotating speed sequence after periodic filtering by the zero sequence through periodic averaging;
s5: carrying out periodic sampling integral averaging on the instantaneous rotating speed series to obtain an average rotating speed sequence in each period;
s6: determining a torsion angle sequence through the instantaneous rotating speed sequence and the average rotating speed sequence;
s7: rearranging the torsion angle signals according to the real time of the rotation of the upper teeth of each dentate middle spacer ring to obtain a torsion angle time domain sequence;
s8: and finding out the frequency at the maximum amplitude according to the torsional angle amplitude spectrum, namely the resonance frequency of the torsional vibration. The resonant frequency is used to guide the optimal design of the bearing, avoiding the resonant frequency during the design process.
The diagnostic method for faults and the method for determining the resonance frequency are now described in detail with respect to the individual steps of the two methods as follows:
determining the range of the zero point by using a linear interpolation algorithm, carrying out zero point data interpolation on the original rotating speed data, increasing the number of data sampling points, and carrying out interpolation at the zero point position by using cubic spline interpolation, wherein the formula of solving the zero point by using the linear interpolation is as follows:
in the formula, xk +1 and xk respectively represent two adjacent data points after interpolation, and the positive and negative units are different, k represents the kth data after interpolation, and S represents the position of the zero point.
And carrying out periodic average processing filtering operation on the data after the zero point interpolation. And according to the well-defined cycle average and tooth average, and taking the result after the smoothing processing as an instantaneous rotating speed signal under the equal angle.
Wherein, the formula of the tooth average instantaneous rotating speed is as follows:
in the formula, n represents an instantaneous rotation speed signal after roller averaging, and m represents the number of cycles of roller averaging.
The formula for periodically averaging and solving the instantaneous rotating speed is as follows:
in the formula, n represents the instantaneous rotating speed signal after cycle averaging, M represents the cycle number of cycle averaging, and Z represents the number of rollers.
And introducing a judgment branch to carry out threshold value cleaning on the data subjected to periodic average processing and filtering, wherein the threshold value cleaning is used for eliminating random noise of vibration of a rotating part of the bearing, and a margin value of 0.5 is set to eliminate a false zero point introduced by the random noise, so that the stability of a torsional vibration algorithm is ensured. The decision formula of the threshold is as follows:
and when the determination condition is true, determining that the instantaneous rotating speed signal is true.
Wherein p (j) represents the jth zero point, i.e. represents the position of the zero point, and the true instantaneous speed signal is determined when the determination condition is true.
Carrying out integral averaging according to the instantaneous rotating speed acquired and processed in one rotation period of the double-row tapered roller bearing 1, and using the rotating speed obtained by calculation as the average rotating speed of the current period, wherein the integral averaging formula is as follows:
the torsion angle generated when the high-speed rail bearing works is obtained, the instantaneous rotating speed obtained by periodic average filtering and the average rotating speed obtained by calculation of an average rotating speed calculation unit are subtracted, and then the subtraction is multiplied by the time required by each rotating speed to carry out integration to obtain the torsion angle of the current working state of the bearing, wherein the formula for calculating the torsion angle is as follows:
in the formula, theta represents a torsional angle of the bearing, and niRepresenting the instantaneous speed of rotation at the ith roller, nciRepresents the average speed of rotation at the i-th roller, TiRepresenting the time that the ith roller has been rotated.
And carrying out sequence conversion on the rotation speed data obtained by preprocessing to obtain sequence signal data of the torsion angle.
In order to facilitate subsequent Fourier transform, each data point of the torsional angle time domain sequence data obtained by the data sequence conversion unit is subjected to slice reordering processing to obtain torsional vibration time domain data.
And carrying out data zero padding on the torsional vibration time domain signal to obtain periodic torsional vibration data.
And windowing the torsional vibration time domain data after the periodic torsional vibration data is subjected to zero padding to obtain a smooth torsional vibration time domain signal. In order to prevent energy leakage caused by windowing before Fast Fourier Transformation (FFT) when performing time-frequency analysis on a signal, a 3-point convolution amplitude correction method is used to process the signal, wherein the 3-point convolution amplitude correction formula is as follows:
in the formula, the convolution corresponds to a three-point sequence h { Kt, Kt } ═ Kt {1,1,1} and the self spectrum YN. And the time-frequency analysis unit 30 is used for performing fast Fourier transform on the torsional vibration time-domain signal to obtain an amplitude spectrum of torsional vibration. And the positioning unit 31 is used for positioning the characteristic frequency of the amplitude spectrum of the torsional vibration data to obtain the frequency at the maximum amplitude, namely the maximum resonance frequency generated by torsional vibration of the high-speed rail bearing at the rotating speed.
Finally, the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all of them should be covered in the claims of the present invention.
Claims (7)
1. A self-powered bearing with a torsional vibration fault diagnosis function is characterized in that: the method comprises the following steps: the device comprises a bearing body, a novel variable reluctance structure fixedly connected with the inner ring surface of the outer ring of the bearing body, a voltage comparison unit connected with the output end of the novel variable reluctance structure, and a torsional vibration fault diagnosis unit in communication connection with the output end of the voltage comparison unit;
the annular middle space ring of the bearing body is in a tooth shape;
novel become magnetic resistance mechanism includes coil, magnet steel, E type silicon steel and fixed casing, and the magnet steel is installed in E type silicon steel and is stretched out the end portion, and the coil winding stretches out the end at E type silicon steel, fixed casing encapsulates coil, magnet steel and E type silicon steel inside it, and fixed casing with bearing inner race inner ring face fixed connection.
2. Self-powered bearing with torsional vibration fault diagnosis according to claim 1, characterized in that: the torsional vibration fault diagnosis unit comprises a data preprocessing unit and a fault diagnosis unit, wherein the data preprocessing unit is used for receiving the data transmitted by the signal processing subunit and preprocessing the data, meanwhile, the preprocessed data are transmitted to the fault diagnosis unit, and the fault diagnosis unit diagnoses whether the bearing has a fault according to the preprocessed data.
3. A self-powered bearing with torsional vibration fault diagnosis in accordance with claim 2, wherein: the data preprocessing unit comprises a data acquisition unit for receiving the transmission data of the signal processing subunit, an envelope demodulation unit for receiving the data of the data acquisition unit and filtering noise in the data, a data zero interpolation unit for receiving the data output by the envelope demodulation unit and performing zero data interpolation on the data, a data threshold cleaning unit for receiving the data output by the data zero interpolation unit and performing threshold cleaning on the data, an average rotating speed determination unit for receiving the data of the data threshold cleaning unit and determining the periodic average rotating speed, and a torsion angle determination unit for determining the torsion angle rotated by the tapered roller.
4. A self-powered bearing with torsional vibration fault diagnosis as defined in claim 3, wherein: the failure diagnosis unit includes: the system comprises a data sequence conversion unit for performing sequence conversion on rotation speed data obtained by preprocessing, a data slice sorting unit for receiving the data of the data sequence conversion unit and performing slice sorting processing on the data, a data zero filling unit for receiving the data of the data slice sorting unit and filling zero into the data, a time-frequency analysis unit for receiving the data of the data zero filling unit and extracting torsional vibration time-domain signals according to the data, and a positioning unit for receiving the data of the time-frequency analysis unit and performing characteristic frequency positioning on the data.
5. Self-powered bearing with torsional vibration fault diagnosis according to claim 1, characterized in that: and a non-bearing area of the inner ring surface of the outer ring of the bearing body is provided with a groove for accommodating the novel variable reluctance structure.
6. Self-powered bearing with torsional vibration fault diagnosis according to claim 5, characterized in that: the number of the coils is more than or equal to 1.
7. A torsional vibration fault diagnosis method, wherein the method is applied to a self-powered bearing with a torsional vibration fault diagnosis function, and the method comprises the following steps:
s1: inputting algorithm parameters and rotating speed data, wherein the algorithm parameters comprise sampling frequency f, tooth number z, rotating speed sequence length, rotating speed sequence X (i), tooth average M and period average M;
s2: determining a zero sequence of the rotating speed data by adopting a linear interpolation method;
s3: judging whether the false zero point introduced by the random noise is larger than a threshold value, if so, entering the next step, and if not, entering the next false zero point value and repeating the step S3;
s4: determining the instantaneous rotating speed sequence after periodic filtering by the zero sequence through periodic averaging;
s5: carrying out periodic sampling integral averaging on the instantaneous rotating speed series to obtain an average rotating speed sequence in each period;
s6: determining a torsion angle sequence through the instantaneous rotating speed sequence and the average rotating speed sequence;
s7: and (4) judging whether the torsion angle obtained in the step (S6) is obviously larger than the mean value of the torsion angles calculated when the shafting normally runs, if so, failing the bearing, otherwise, failing the bearing.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1437709A (en) * | 2000-06-23 | 2003-08-20 | 迪姆肯公司 | Bearing with wireless self-powered sensor unit |
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2021
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| CN110006658A (en) * | 2019-04-10 | 2019-07-12 | 哈尔滨工程大学 | The monitoring method that shuttling device cylinder sleeve frictional force shaft torsional oscillation influences |
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