CN110626915B - Fourier transform-based elevator anti-falling independent safety monitoring method - Google Patents
Fourier transform-based elevator anti-falling independent safety monitoring method Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B5/00—Applications of checking, fault-correcting, or safety devices in elevators
- B66B5/02—Applications of checking, fault-correcting, or safety devices in elevators responsive to abnormal operating conditions
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B7/00—Other common features of elevators
- B66B7/12—Checking, lubricating, or cleaning means for ropes, cables or guides
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Abstract
The invention discloses an elevator anti-falling independent safety monitoring method based on Fourier transform, which comprises the following steps of: the steel wire rope vibration data monitoring device transmits the monitored vibration data to the computer through a collecting ring; step two, calculating the total monitoring signals of the multiple sensors: step three, extracting characteristic peaks of inherent signals; step four: extracting a single-strand fracture characteristic peak of the steel wire rope; step five: the safety monitoring of the steel wire rope in daily use comprises the following steps: the computer compares the daily signal characteristic peak with the inherent signal characteristic peak of the intact steel wire rope, compares the daily signal characteristic peak with the fracture characteristic peak of the broken steel wire rope, and sends out corresponding alarm. The method can sensitively monitor the vibration data of the elevator steel wire rope, and the computer judges whether the elevator steel wire rope is broken, so that the safety of the elevator is improved and the elevator is prevented from happening in the future.
Description
Technical Field
The invention relates to an elevator anti-falling independent safety monitoring method based on Fourier transform.
Background
Elevators have been in history for over 100 years, undergoing numerous improvements and enhancements from the earliest being crude, dangerous, to today's comfort, safety. Even so, elevator accidents of today occur occasionally, wherein the most harmful and deadly wire ropes of the elevator (including the elevator) of the current genus break. A 42-up elevator rope breakage accident occurred in 2006 only by the five major elevator companies in japan. Safety monitoring of wire ropes is currently a relatively weak and urgent issue to solve, compared to relatively sophisticated detection and monitoring means at other parts of the elevator.
The invention patent with the publication number of CN102101618B discloses a method and a system for detecting a steel wire rope for an elevator, which judges whether the steel wire rope of the elevator has a fracture risk by detecting whether the steel wire rope of the elevator is uniformly stressed in real time so as to prevent the steel wire rope of the elevator from being fractured and ensure the stable and reliable operation of the elevator. The defects of the technology are as follows: when the steel wire rope is broken in a single strand or a plurality of strands, the change of whether the stress of the elevator steel wire rope is uniform is very small, and the early-stage hidden danger is not easy to detect.
The invention patent of the publication number CN103253573B discloses an elevator dragging wire rope detection device, which mainly aims at the situation that when a wire rope has a broken strand or a loose strand, the wire rope has the situation that a steel wire at the broken strand part is exposed or the diameter of the loose strand part is increased, when the abnormal positions of the wire ropes are detected by an elevator dragging wire rope detection device arranged in an elevator shaft, an alarm signal is sent to inform maintenance personnel and stop the operation of an elevator, the wire rope breakage accident is prevented to a great extent in time, and the safety performance of the elevator is greatly improved. The defects of the technology are as follows: when the steel wire rope is broken but the broken single-stranded steel wire is arranged in the steel wire rope, the steel wire cannot be exposed, and the broken steel wire cannot be detected under the condition; when the steel wire rope is broken in a single strand, the diameter of the broken strand is not obviously increased, and the early-stage hidden danger is not easy to detect.
Disclosure of Invention
The invention aims to provide an elevator anti-falling independent safety monitoring method based on Fourier transform, which can sensitively monitor vibration data of an elevator steel wire rope, judge whether the elevator steel wire rope is broken by a computer, improve the safety of an elevator and prevent the elevator from being broken.
In order to achieve the purpose, the invention adopts the following technical scheme:
an elevator anti-falling independent safety monitoring method based on Fourier transform is disclosed, wherein the elevator comprises a car, a shaft, a traction device, an elevator control system and a computer arranged in the elevator control system, and the monitoring steps are as follows:
the method comprises the following steps: acquisition of vibration data
A steel wire rope vibration data monitoring device is arranged on the traction device, and when the elevator runs, the steel wire rope vibration data monitoring device transmits the monitored vibration data to the computer through a collecting ring;
step two: calculation of total monitoring signals of multiple sensors
Assuming that monitoring signals of a plurality of sensors sn1, sn2, … … and snn uniformly distributed in a steel wire groove of a traction sheave are respectively M1, M2, … … and Mn, a method for calculating a total multi-sensor monitoring signal SAS at a certain moment comprises the following steps:
the monitoring signals M1, M2, M3, … … and Mn of the sensors are sorted from large to small, and the sequence after sorting is as follows: MP1, MP2, MP3, … …, MPn, then the SAS algorithm is:
step three: extraction of characteristic peaks of intrinsic signal
Acquiring vibration data of the intact steel wire rope according to the method in the first step, acquiring total monitoring signal data of the multiple sensors by the computer through the SAS algorithm, acquiring a real-time monitoring signal spectrogram of the intact steel wire rope by the computer through Fourier transform (FFT) on the total monitoring signal data of the multiple sensors, wherein a characteristic peak appearing in the spectrogram is an inherent signal characteristic peak of the intact steel wire rope;
step four: extraction of steel wire rope single-strand fracture characteristic peak
Acquiring vibration data of the single-stranded broken steel wire rope according to the method in the first step, acquiring total monitoring signal data of a plurality of sensors by the computer through the SAS algorithm, acquiring a real-time monitoring signal frequency spectrum diagram of the single-stranded broken steel wire rope by the computer through Fourier transform (FFT) on the total monitoring signal data of the plurality of sensors, wherein a characteristic peak appearing in the diagram is an inherent signal characteristic peak of the single-stranded broken steel wire rope, removing the inherent signal characteristic peak in the third step, and a newly appearing characteristic peak in the diagram is a breaking characteristic peak of the broken steel wire rope;
step five: safety monitoring of steel wire rope in daily use
a) Acquiring vibration data of the steel wire rope in real time according to the method in the step one, acquiring total monitoring signal data of the multiple sensors by the computer through the SAS algorithm, acquiring a real-time monitoring signal spectrogram of the steel wire rope by the computer through Fourier transform (FFT) on the total monitoring signal data of the multiple sensors, wherein characteristic peaks appearing in the spectrogram are daily signal characteristic peaks of the steel wire rope;
b) comparing the daily signal characteristic peak of the real-time monitoring signal spectrogram in the step a) with the inherent signal characteristic peak of a perfect steel wire rope by the computer, if the daily signal characteristic peak and the inherent signal characteristic peak are the same, judging that the steel wire rope is perfect, repeating the step a), if the daily signal characteristic peak and the breakage characteristic peak of the broken steel wire rope are different, comparing the daily signal characteristic peak of the real-time monitoring signal spectrogram in the step a) with the breakage characteristic peak of the broken steel wire rope by the computer, if the daily signal characteristic peak and the breakage characteristic peak of the broken steel wire rope are the same, judging that the single steel wire rope is; if the peak is different from the fracture characteristic peak of the broken strand steel wire rope, the following steps are executed:
c) if the characteristic peak position Ps of the characteristic peak of the daily signal and the position P of the fracture characteristic peak are0Similarly, the number of broken strands can be determined according to the amplitudes of the two characteristic peaks: if 2P0>Ps≧1.5P0Judging that the two strands are broken, and sending out corresponding alarms; if 2.8P0>Ps≧2P0Judging that the three strands are broken, and sending out a corresponding alarm; if Ps ≧ 2.8P0Judging that the four strands or more are broken, and sending out corresponding alarm; if the characteristic peak position Ps of the characteristic peak of the daily signal and the position P of the fracture characteristic peak are0Different, judging that other mechanical parts are out of serviceAnd (4) sending a corresponding alarm when the problem occurs.
The steel wire rope vibration data monitoring device is a broken wire monitoring device, the traction device comprises a traction motor, a steel wire rope and a traction sheave, the steel wire groove of the traction sheave is semicircular, a plurality of broken wire monitoring devices are uniformly distributed at the bottom of the steel wire groove along the circumferential direction, each broken wire monitoring device comprises a vibration sensor, each vibration sensor is arranged in a corresponding mounting hole of the traction sheave, the top end of each vibration sensor is lower than the bottom surface of the steel wire groove, the vibration sensors are fixed in the respective mounting holes through pouring sealant, each vibration sensor is electrically connected with a corresponding conductive elastic needle of the collecting ring arranged on the side surface of the traction sheave through a lead, when the elevator runs, the steel wire rope is wound on the steel wire groove, each vibration sensor transmits the monitored vibration data to the computer through the collecting ring, and the computer judges whether the steel wire rope has a broken strand according to the vibration data.
The vibration sensor is a miniature high-sensitivity piezoelectric ceramic type vibration sensor.
Compared with the prior art, the invention has the beneficial effects that: according to the technical scheme, the difference is amplified through Fourier transform according to the difference of vibration data of the steel wire rope when the steel wire rope is intact and broken, the characteristic peak is extracted for comparison and judgment, and the judgment speed and the judgment accuracy are greatly improved.
The further beneficial effects are that: the elevator vibration monitoring device is characterized in that a plurality of broken wire monitoring devices are uniformly distributed on the bottom of the steel wire groove along the circumferential direction, each broken wire monitoring device comprises a vibration sensor, each vibration sensor is arranged in a corresponding mounting hole of the traction wheel, the top end of each vibration sensor is lower than the bottom surface of the steel wire groove, the vibration sensors are fixed in the respective mounting holes through pouring sealant, each vibration sensor is electrically connected with a corresponding conductive elastic pin of a collecting ring arranged on the side surface of the traction wheel through a lead, when an elevator runs, a steel wire rope is wound in the steel wire groove, and each vibration sensor transmits monitored vibration data to the computer through the collecting ring.
Drawings
FIG. 1 is a schematic structural view of the present invention;
fig. 2 is a longitudinal sectional view of the traction sheave of fig. 1;
FIG. 3 is an enlarged view of portion A of FIG. 2;
FIG. 4 is a cross-sectional view taken along line C-C of FIG. 2;
FIG. 5 is an enlarged view of portion B of FIG. 4;
FIG. 6 is a cross-sectional view taken along line D-D of FIG. 4;
FIG. 7 is a schematic diagram of the total monitored signal data of an intact steel wire rope monitored in real time by the vibration sensor in an embodiment as a function of time;
FIG. 8 is a schematic diagram of the total monitored signal data of a broken strand of steel wire rope monitored in real time by a vibration sensor over time in an embodiment;
FIG. 9 is an FFT spectrum of the intact steel cord in the example;
FIG. 10 is an FFT spectrum of a broken strand steel cable in the embodiment;
FIG. 11 is a non-linear resonance spectrum of a real-time monitor signal of a sound wire rope in an embodiment;
FIG. 12 is a non-linear resonance spectrum of a monitor signal of a broken wire rope cable in the embodiment;
fig. 13 is a schematic representation of the total monitored signal data collected over time while the elevator is in use;
FIG. 14 is a frequency spectrum diagram of a steel wire rope real-time monitoring signal obtained by Fourier transform of the vibration data of FIG. 13;
fig. 15 is a frequency spectrum diagram of a steel wire rope real-time monitoring signal obtained by the vibration data of fig. 13 through a nonlinear form resonance model.
Detailed Description
In order to make the technical solution of the present invention clearer, the present invention will be described in detail with reference to fig. 1 to 15. It should be understood that the detailed description and specific examples, while indicating the scope of the invention, are intended for purposes of illustration only and are not intended to limit the scope of the invention.
The invention relates to an elevator anti-falling independent safety monitoring method based on Fourier transform, wherein an elevator comprises an elevator car 1, an elevator shaft 2, a traction device 4, an elevator control system 5 and a computer 6 arranged in the elevator control system 5, and the monitoring steps are as follows:
the method comprises the following steps: acquisition of vibration data
A steel wire rope vibration data monitoring device is arranged on the traction device 4, and when the elevator runs, the steel wire rope vibration data monitoring device transmits the monitored vibration data to the computer 6 through a collecting ring 46;
step two: calculation of total monitoring signals of multiple sensors
Assuming that the monitoring signals of the sensors sn1, sn2, … … and snn uniformly distributed in the steel wire groove of the traction sheave 43 are M1, M2, … … and Mn, respectively, the method for calculating the total multi-sensor monitoring signal SAS at a certain time is as follows:
the monitoring signals M1, M2, M3, … … and Mn of the sensors are sorted from large to small, and the sequence after sorting is as follows: MP1, MP2, MP3, … …, MPn, then the SAS algorithm is:
step three: extraction of characteristic peaks of intrinsic signal
Collecting vibration data of the intact steel wire rope 42 according to the method of the first step, obtaining total multi-sensor monitoring signal data by the computer 6 through the SAS algorithm, obtaining a real-time monitoring signal spectrogram of the intact steel wire rope 42 by the computer 6 through Fourier transform (FFT) on the total multi-sensor monitoring signal data, wherein characteristic peaks appearing in the spectrogram are inherent signal characteristic peaks of the intact steel wire rope;
step four: extraction of steel wire rope single-strand fracture characteristic peak
Acquiring vibration data of the steel wire rope 42 with the single-strand breakage according to the method in the first step, acquiring total monitoring signal data of a multi-sensor by the computer 6 through the SAS algorithm, acquiring a real-time monitoring signal frequency spectrum diagram of the steel wire rope 42 with the single-strand breakage by the computer 6 through Fourier transform (FFT) of the total monitoring signal data of the multi-sensor, wherein a characteristic peak appearing in the diagram is an inherent signal characteristic peak of the steel wire rope with the single-strand breakage, removing the inherent signal characteristic peak in the third step, and a newly appearing characteristic peak in the diagram is a breakage characteristic peak of the steel wire rope with the broken strand;
step five: safety monitoring of wire rope 42 during everyday use
a) Acquiring vibration data of the steel wire rope 42 in real time according to the method in the step one, acquiring total monitoring signal data of the multiple sensors by the computer 6 through the SAS algorithm, acquiring a real-time monitoring signal spectrogram of the steel wire rope 42 by the computer 6 through Fourier transform (FFT) on the total monitoring signal data of the multiple sensors, wherein characteristic peaks appearing in the spectrogram are daily signal characteristic peaks of the steel wire rope;
b) comparing the daily signal characteristic peak of the real-time monitoring signal spectrogram in the step a) with the inherent signal characteristic peak of a perfect steel wire rope by the computer 6, if the daily signal characteristic peak and the inherent signal characteristic peak are the same, judging that the steel wire rope 42 is perfect, repeating the step a), if the daily signal characteristic peak and the inherent signal characteristic peak are different, comparing the daily signal characteristic peak of the real-time monitoring signal spectrogram in the step a) with the breakage characteristic peak of a broken steel wire rope by the computer 6, and if the daily signal characteristic peak and the breakage characteristic peak of the broken steel wire rope are the same, judging that a single strand of the steel wire rope 42 is broken; if the peak is different from the fracture characteristic peak of the broken strand steel wire rope, the following steps are executed:
c) if the characteristic peak position Ps of the characteristic peak of the daily signal and the position P of the fracture characteristic peak are0Similarly, the number of broken strands can be determined according to the amplitudes of the two characteristic peaks: if 2P0>Ps≧1.5P0Judging that the two strands are broken, and sending out corresponding alarms; if 2.8P0>Ps≧2P0Judging that the three strands are broken, and sending out a corresponding alarm; if Ps ≧ 2.8P0Judging that the four strands or more are broken, and sending out corresponding alarm; if the characteristic peak position Ps of the characteristic peak of the daily signal and the position P of the fracture characteristic peak are0If not, judging that other mechanical parts have problems, and sending corresponding alarms.
Preferably, the steel wire rope vibration data monitoring device is a broken wire monitoring device, the traction device 4 includes a traction motor 41, a steel wire rope 42 and a traction sheave 43, a steel wire groove of the traction sheave 43 is semicircular, a plurality of broken wire monitoring devices are uniformly distributed on the bottom of the steel wire groove along the circumferential direction, each broken wire monitoring device includes a vibration sensor 44, each vibration sensor 44 is disposed in a corresponding mounting hole of the traction sheave 43, the top end of the vibration sensor 44 is lower than the bottom surface of the steel wire groove, the vibration sensor 44 is fixed in the respective mounting hole by a potting adhesive 47, each vibration sensor 44 is electrically connected with a corresponding conductive elastic pin of a slip ring 46 disposed on the side surface of the traction sheave 43 through a wire, when the elevator is in operation, the steel wire rope 42 is wound around the steel wire groove, each vibration sensor 44 transmits the monitored vibration data to the computer 6 through the slip ring 46, the computer 6 judges whether the steel wire rope 42 has a broken strand or not according to the vibration data. The vibration sensor 44 is a miniature high-sensitivity piezoelectric ceramic type vibration sensor.
Example 1:
an independent safety monitoring device of an elevator comprises a lift car 1, a lift shaft 2, a traction device 4, an elevator control system 5 and a computer 6 arranged in the elevator control system 5, wherein the traction device 4 comprises a traction motor 41, a steel wire rope 42 and a traction sheave 43, the steel wire grooves of the traction sheave 43 are semicircular, the number of the steel wire grooves of the traction sheave 43 is six, 8 broken wire monitoring devices are uniformly distributed at the bottom of each steel wire groove along the circumferential direction, each broken wire monitoring device comprises a vibration sensor 44, each vibration sensor 44 is arranged in a corresponding mounting hole of the traction sheave 43, the top end of each vibration sensor 44 is 0.3-1 mm lower than the bottom surface of the steel wire groove, the vibration sensors 44 are fixed in the respective mounting holes through potting adhesive 47, the top end of the potting adhesive 47 is flush with the bottom surface of the steel wire groove, each vibration sensor 44 is electrically connected with a corresponding conductive elastic needle of a collecting ring 46 arranged on the side surface of the traction sheave 43 through a lead, when the elevator runs, the steel wire rope 42 is wound on a steel wire groove, each vibration sensor 44 transmits the monitored vibration data to the computer 6 through the collecting ring 46, and the computer 6 judges whether the steel wire rope 42 has a broken strand according to the vibration data. Preferably, the vibration sensor 44 is a micro high-sensitivity piezoelectric ceramic type vibration sensor.
Example 2:
the Fourier transform-based elevator anti-falling independent safety monitoring method using the independent safety monitoring device of the elevator comprises the following steps:
the method comprises the following steps: acquisition of vibration data
When the traction device 4 operates, the traction sheave 43 rotates and is in contact with the steel wire rope 42 wound in the steel wire groove of the traction sheave, and each vibration sensor 44 transmits the monitored vibration data to the computer 6 through the collecting ring 46; step two: calculation of total monitoring signals of multiple sensors
Assuming that the monitoring signals of the sensors sn1, sn2, … … and snn uniformly distributed in the steel wire groove of the traction sheave 43 are M1, M2, … … and Mn, respectively, the method for calculating the total multi-sensor monitoring signal SAS at a certain time is as follows:
the monitoring signals M1, M2, M3, … … and Mn of the sensors are sorted from large to small, and the sequence after sorting is as follows: MP1, MP2, MP3, … …, MPn, then the SAS algorithm is:
step three: extraction of characteristic peaks of intrinsic signal
Acquiring vibration data of the intact steel wire rope 42 according to the method in the first step, acquiring total monitoring signal data of each sensor by the computer 6 through the SAS algorithm, wherein a schematic diagram of the total monitoring signal data along with time change is shown in FIG. 7, acquiring a real-time monitoring signal spectrogram (see FIG. 9) of the intact steel wire rope 42 by the computer 6 through Fourier transform (FFT) on the total monitoring signal data, and a characteristic peak appearing in the spectrogram is an inherent signal characteristic peak of the intact steel wire rope;
step four: extraction of steel wire rope single-strand fracture characteristic peak
Acquiring vibration data of the single-strand broken steel wire rope 42 according to the method in the first step, acquiring total monitoring signal data (see fig. 8) of each sensor by the computer 6 through the SAS algorithm, acquiring a real-time monitoring signal frequency spectrum graph (see fig. 10) of the single-strand broken steel wire rope 42 by the computer 6 through Fourier transform FFT (fast Fourier transform) of the total monitoring signal data of the multiple sensors, wherein a characteristic peak appearing in the graph is an inherent signal characteristic peak of the single-strand broken steel wire rope, removing the inherent signal characteristic peak in the third step, and a characteristic peak newly appearing in the graph is a breaking characteristic peak of the broken steel wire rope;
step five: safety monitoring of wire rope 42 during everyday use
a) Acquiring vibration data of the steel wire rope 42 in real time according to the method in the first step, acquiring total monitoring signal data (see fig. 13) of each sensor by the computer 6 through the SAS algorithm, acquiring a real-time monitoring signal spectrogram (see fig. 14) of the steel wire rope 42 by the computer 6 through Fourier transform FFT (fast Fourier transform) on the total monitoring signal data, wherein characteristic peaks appearing in the spectrogram are daily signal characteristic peaks of the steel wire rope;
b) comparing the daily signal characteristic peak of the real-time monitoring signal spectrogram in the step a) with the inherent signal characteristic peak of the intact steel wire rope by the computer 6, namely comparing the signal characteristic peak in the step 14 with the inherent signal characteristic peak in the step 9, wherein the daily signal characteristic peak of the real-time monitoring signal spectrogram in the step a) with the breakage characteristic peak of the broken steel wire rope by the computer 6 because the daily signal characteristic peak is different from the inherent signal characteristic peak in the step 9, namely comparing the signal characteristic peak in the step 14 with the signal characteristic peak in the step 10, and because the characteristic peak position Ps of the daily signal characteristic peak and the position P of the breakage characteristic peak are different0Similarly, the computer will determine the number of strands broken from the amplitudes of the two characteristic peaks: due to P00.13dB and 0.15dB for Ps<1.5P0And therefore 1 strand is judged to be broken, the computer 6 issues a corresponding alarm.
Example 3:
the elevator anti-falling independent safety monitoring method based on the nonlinear form resonance model by using the elevator independent safety monitoring device comprises the following steps:
the method comprises the following steps: acquisition of vibration data
When the traction device 4 operates, the traction sheave 43 rotates and is in contact with the steel wire rope 42 wound in the steel wire groove of the traction sheave, and each vibration sensor 44 transmits the monitored vibration data to the computer 6 through the collecting ring 46;
step two: calculation of total monitoring signals of multiple sensors
Assuming that the monitoring signals of the sensors sn1, sn2, … … and snn uniformly distributed in the steel wire groove of the traction sheave 43 are M1, M2, … … and Mn, respectively, the method for calculating the total multi-sensor monitoring signal SAS at a certain time is as follows:
the monitoring signals M1, M2, M3, … … and Mn of the sensors are sorted from large to small, and the sequence after sorting is as follows: MP1, MP2, MP3, … …, MPn, then the SAS algorithm is:
step three: extraction of characteristic parameters of monitoring signals
In order to monitor the state of the elevator steel wire rope 42, 5 characteristic parameters of the vibration data, such as integral, variance, steady-state average value, average differential value, wavelet energy and the like, are respectively extracted:
1) the integral INV is calculated as:
in the formula: IN (t) is an integral value, N is the number of data detected by the sensor on the sample, xiSetting the response value of ith second, setting t as the time interval between two adjacent sampling points, and selecting 0.1 s;
2) the variance VAR is calculated as:
in the formula:
in response to the mean value of the signal, N is the number of samples taken, xiIs the ith collection value in a sample test value;
3) the steady state average AVRS is calculated as:
in the formula: z is the relative steady state average value, t0For the time, x, at which the curve is to be stabilizediThe number of the ith acquisition value in a sample test value is N, and the total acquisition time point number of each sample is N;
4) the average differential value ADV is calculated as:
in the formula: ka is the average differential value of the response signal, N is the sample acquisition time, xiThe sampling value is the ith acquisition value of the sample test value, t is the interval between two adjacent sampling points, and t is 0.1 s;
5) wavelet energy WEV is calculated as:
in the formula: e is the wavelet energy value, a3iThe ith decomposition coefficient i in the approximation coefficient set after the signal 3 is subjected to scale decomposition is 1, …, m is the total number of coefficients in the approximation coefficient set;
step four: establishment of nonlinear morphological resonance model
The nonlinear form resonance is a phenomenon that an ideal particle generates a reciprocating transition in a nonlinear bistable system under the action of a variable periodic signal (periodic driving force) and random noise (random force), and a nonlinear form resonance model is described as follows:
in the formula:
to describe the potential function of a bistable system
For input signals as non-linear systems, A is the signal amplitude, f0For adjusting the frequency of the signal, m, n>0 is a system parameter; e (t) is external random noise, the statistical average value of e (t) is 0, and e (t) is white Gaussian distribution noise with noise intensity D; p is a correction constant;
equation (6) describes the barrier height of the system as U0＝m2A/4 n with its bottom at
The output state of the system is determined to stay in one of the two potential wells by the initial state, and under the adiabatic approximate condition that the amplitude, the frequency and the noise intensity of the input signal are less than 1, the nonlinear form resonance model expression can be obtained by the correlation function of the output signal of the nonlinear form resonance system:
step five: extraction of characteristic peaks of intrinsic signal
Acquiring vibration data of the intact steel wire rope 42 according to the method in the first step, acquiring total monitoring signal data (see fig. 7) of the multiple sensors by the computer 6 through the SAS algorithm, acquiring a nonlinear resonance frequency spectrum diagram (see fig. 11) of the intact steel wire rope in real time by the computer 6 through the total monitoring signal data through the nonlinear form resonance model, wherein a characteristic peak appearing in the diagram is an inherent signal characteristic peak of the intact steel wire rope;
step six: extraction of steel wire rope single-strand fracture characteristic peak
Acquiring vibration data of the single-strand broken steel wire rope 42 according to the method in the first step, acquiring total monitoring signal data of a multi-sensor (see fig. 8) by the computer 6 through the SAS algorithm, acquiring a nonlinear resonance frequency spectrum graph (see fig. 12) of the single-strand broken steel wire rope 42 monitored in real time through the total monitoring signal data of the multi-sensor through the nonlinear form resonance model by the computer 6, wherein a characteristic peak appearing in the graph is an inherent signal characteristic peak of the single-strand broken steel wire rope, removing the inherent signal characteristic peak in the fifth step, and a newly appearing characteristic peak in the graph is a breaking characteristic peak of the broken steel wire rope;
step seven: safety monitoring of wire rope 42 during everyday use
a) Acquiring vibration data of the steel wire rope 42 in real time according to the method in the first step, acquiring total monitoring signal data (see fig. 13) of each sensor by the computer 6 through the SAS algorithm, and acquiring a real-time monitoring signal spectrogram (see fig. 15) of the steel wire rope 42 by the computer 6 through the total monitoring signal data through the nonlinear form resonance model, wherein characteristic peaks appearing in the spectrogram are daily signal characteristic peaks of the steel wire rope;
b) comparing the daily signal characteristic peak of the real-time monitoring signal spectrogram in the step a) with the inherent signal characteristic peak of the intact steel wire rope by the computer 6, namely comparing the signal characteristic peak in the step 15 with the inherent signal characteristic peak in the step 11, wherein the daily signal characteristic peak of the real-time monitoring signal spectrogram in the step a) with the breakage characteristic peak of the broken steel wire rope by the computer 6 because the daily signal characteristic peak is different from the inherent signal characteristic peak in the step 11, namely comparing the signal characteristic peak in the step 14 with the signal characteristic peak in the step 12, and because the characteristic peak position Ps of the daily signal characteristic peak and the position P of the breakage characteristic peak are different0Similarly, the computer will determine the number of strands broken from the amplitudes of the two characteristic peaks: due to P09.9dB and 12.1dB, satisfying Ps<1.5P0And therefore 1 strand is judged to be broken, the computer 6 issues a corresponding alarm.
Claims (3)
1. An elevator anti-falling independent safety monitoring method based on Fourier transform, wherein the elevator comprises a car (1), a shaft (2), a traction device (4), an elevator control system (5) and a computer (6) arranged in the elevator control system (5), and the monitoring steps are as follows:
the method comprises the following steps: acquisition of vibration data
A steel wire rope vibration data monitoring device is arranged on the traction device (4), and when the elevator runs, the steel wire rope vibration data monitoring device transmits the monitored vibration data to the computer (6) through a collecting ring (46);
step two: calculation of total monitoring signals of multiple sensors
The method for calculating the total monitoring signal SAS of the multiple sensors comprises the following steps of uniformly distributing the multiple sensors sn1, sn2, … … and snn in a steel wire groove of a traction wheel (43), wherein monitoring signals of the multiple sensors are M1, M2, … … and Mn respectively, and at a certain moment:
the monitoring signals M1, M2, M3, … … and Mn of the sensors are sorted from large to small, and the sequence after sorting is as follows: MP1, MP2, MP3, … …, MPn, then the SAS algorithm is:
step three: extraction of characteristic peaks of intrinsic signal
Collecting vibration data of the intact steel wire rope (42) according to the method in the first step, enabling the computer (6) to obtain total multi-sensor monitoring signal data through the SAS algorithm, enabling the computer (6) to obtain a real-time monitoring signal spectrogram of the intact steel wire rope (42) through Fourier transformation on the total multi-sensor monitoring signal data, and enabling characteristic peaks appearing in the spectrogram to be inherent signal characteristic peaks of the intact steel wire rope;
step four: extraction of steel wire rope single-strand fracture characteristic peak
Acquiring vibration data of the single-strand broken steel wire rope (42) according to the method in the first step, acquiring total monitoring signal data of a plurality of sensors by the computer (6) through the SAS algorithm, acquiring a real-time monitoring signal frequency spectrum diagram of the single-strand broken steel wire rope (42) through Fourier transform of the total monitoring signal data of the plurality of sensors by the computer (6), wherein a characteristic peak appearing in the diagram is an inherent signal characteristic peak of the single-strand broken steel wire rope, removing the inherent signal characteristic peak in the third step, and a characteristic peak newly appearing in the diagram is a breaking characteristic peak of the broken steel wire rope;
step five: safety monitoring of steel wire ropes (42) in daily use
a) Acquiring vibration data of the steel wire rope (42) in real time according to the method in the step one, enabling the computer (6) to obtain total monitoring signal data of the multiple sensors through the SAS algorithm, enabling the computer (6) to obtain a real-time monitoring signal spectrogram of the steel wire rope (42) through Fourier transform of the total monitoring signal data of the multiple sensors, wherein characteristic peaks appearing in the spectrogram are daily signal characteristic peaks of the steel wire rope;
b) comparing the daily signal characteristic peak of the real-time monitoring signal spectrogram obtained in the step a) with the inherent signal characteristic peak of a perfect steel wire rope by the computer (6), judging that the steel wire rope (42) is perfect if the daily signal characteristic peak of the real-time monitoring signal spectrogram obtained in the step a) is the same as the inherent signal characteristic peak of the perfect steel wire rope, repeating the step a), comparing the daily signal characteristic peak of the real-time monitoring signal spectrogram obtained in the step a) with the breakage characteristic peak of a broken steel wire rope by the computer (6) if the daily signal characteristic peak of the real-time monitoring signal spectrogram obtained in the step a) is different from the breakage characteristic peak of the broken steel wire rope; if the peak is different from the fracture characteristic peak of the broken strand steel wire rope, the following steps are executed:
c) if the characteristic peak position Ps of the characteristic peak of the daily signal and the position P of the fracture characteristic peak are0Similarly, the number of broken strands can be determined according to the amplitudes of the two characteristic peaks: if 2P0>Ps≧1.5P0Judging that the two strands are broken, and sending out corresponding alarms; if 2.8P0>Ps≧2P0Judging that the three strands are broken, and sending out a corresponding alarm; if Ps ≧ 2.8P0Judging that the four strands or more are broken, and sending out corresponding alarm; if the characteristic peak position Ps of the characteristic peak of the daily signal and the position P of the fracture characteristic peak are0If not, judging that other mechanical parts have problems, and sending corresponding alarms.
2. The Fourier transform-based elevator anti-falling independent safety monitoring method according to claim 1, characterized in that: the steel wire rope vibration data monitoring device is a broken wire monitoring device, the traction device (4) comprises a traction motor (41), a steel wire rope (42) and a traction sheave (43), a steel wire groove of the traction sheave (43) is semicircular, a plurality of broken wire monitoring devices are uniformly distributed at the bottom of the steel wire groove along the circumferential direction, each broken wire monitoring device comprises a vibration sensor (44), each vibration sensor (44) is arranged in a corresponding mounting hole of the traction sheave (43), the top end of each vibration sensor (44) is lower than the groove bottom surface of the steel wire groove, the vibration sensors (44) are fixed in the respective mounting holes through pouring sealant (47), each vibration sensor (44) is electrically connected with a corresponding conductive elastic needle of the collecting ring (46) arranged on the side surface of the traction sheave (43) through a lead, when the elevator runs, the steel wire rope (42) is arranged in the steel wire groove, each vibration sensor (44) transmits the monitored vibration data to the computer (6) through a collecting ring (46), and the computer (6) judges whether the steel wire rope (42) has a broken strand according to the vibration data.
3. The Fourier transform-based elevator anti-falling independent safety monitoring method according to claim 2, characterized in that: the vibration sensor (44) is a miniature high-sensitivity piezoelectric ceramic type vibration sensor.
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| JPWO2011158871A1 (en) * | 2010-06-16 | 2013-08-19 | Natac株式会社 | Elevator wire rope damage monitoring method and elevator wire rope damage monitoring apparatus |
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| JP6026251B2 (en) * | 2012-11-30 | 2016-11-16 | 三菱電機ビルテクノサービス株式会社 | Elevator rope strand break detection device and rope strand break detection method |
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