Rope wheel abrasion early warning method based on vibration signals

Abstract

The rope wheel abrasion early warning method based on the vibration signals comprises the steps that vibration data of a rope wheel are collected according to a preset period, and vibration energy of the rope wheel is calculated according to the vibration data collected in each period; when the total collection period n is not smaller than d + 1, the abrasion stage of the rope wheel in the (n-d) th period is judged according to the vibration energy, and d is larger than or equal to 3; the wear stage is divided into a running-in wear stage, a stable wear stage and a severe wear stage; under the condition that the abrasion early-warning threshold value is not set, when the abrasion stage of the rope wheel in the (n-d) th period is a stable abrasion stage or a severe abrasion stage, the abrasion early-warning threshold value is set; and judging whether the vibration energy of the current period exceeds the wear early warning threshold value or not, and if yes, sending out a wear early warning signal. By adopting the method, the sensor is convenient to install, and automatic monitoring is convenient to realize.

Description

Technical Field

[0001] The invention relates to the technical field of rotating part fault detection, and in particular to a rope wheel wear early warning method based on vibration signals. Background Art

[0002] The elevator traction sheave and wire rope play a vital role in the safe operation of the elevator. During the operation of the traction sheave (hereinafter referred to as the rope sheave), the rope sheave contacts each other and generates friction, which pulls the wire rope to operate. As the rope sheave runs for a long time, the friction will cause the rope sheave to wear, reduce the diameter of the wire rope, and reduce the friction coefficient, thus causing potential dangers such as insufficient traction and wire rope breakage, affecting the safety of the elevator.

[0003] At present, the main methods for detecting sheave wear include electromagnetic method, machine vision method, current method, etc. For example, Chinese patent document CN201911411098.9 discloses an elevator sheave status early warning method based on magnetic detection method and current method. This early warning method has the following two main shortcomings. On the one hand, the sensor is not convenient to install. For example, a strong magnetic sensor may cause the wire rope to contact the device, resulting in unnecessary wear of the wire rope. On the other hand, this method requires additional manual acquisition of parameters such as the number and surface area of ​​the elevator wire rope, which is not automated enough. Summary of the invention

[0004] The technical problem to be solved by the present invention is how to provide a technical solution for early warning of rope sheave wear which is convenient for hardware installation and can realize automatic monitoring.

[0005] In order to solve the above technical problems, the present invention provides a rope pulley wear early warning method based on vibration signals, which collects the vibration data of the rope pulley according to a preset period, and calculates its vibration energy according to the vibration data collected in each period; when the total collection period n is not less than d+1, the wear stage of the rope pulley in the ndth period is judged according to the vibration energy, where d≥3; the wear stage is divided into a running-in wear stage, a stable wear stage and a severe wear stage;

[0006] When the wear warning threshold is not set, when the wear stage of the rope wheel in the ndth cycle is the stable wear stage or the severe wear stage, the wear warning threshold is set; determine whether the vibration energy of the current cycle exceeds the wear warning threshold, and if so, issue a wear warning signal.

[0007] Preferably, the method for judging the wear stage of the rope pulley in the ndth cycle according to the vibration energy is as follows: plotting the vibration energy data from the ndth cycle to the current cycle on a two-dimensional coordinate system, with the ordinate being the vibration energy and the abscissa being the time period for collecting the rope pulley vibration data; fitting a univariate function curve to the d+1 group of vibration energy data using the least squares method to obtain the slope k of the function; if k<-k thr , then the wear stage is judged to be the running-in wear stage; if -k thr <k<k thr , then the wear stage is judged to be the stable wear stage; if k>k thr , then the wear stage is judged to be the severe wear stage; where k thr For a given threshold, k thr >0.

[0008] Preferably, the method for setting the wear warning threshold is: when the wear stage of the rope wheel in the ndth cycle is the stable wear stage, E thr =β 1 E b , where E thr is the wear warning threshold, β 1 is the first warning coefficient, E b is the baseline value; when the sheave is in the severe wear stage in the nd cycle, E thr =β 2 E b , where E thr is the wear warning threshold, β 2 is the second warning coefficient, E b is the baseline value.

[0009] Preferably, the first warning coefficient β 1 Greater than the second warning coefficient β 2 .

[0010] Preferably, when the wear stage of the rope wheel in the ndth cycle is a stable wear stage, the baseline value E b It is the average value of the vibration energy from the ndth cycle to the current cycle.

[0011] Preferably, when the wear stage of the rope wheel in the ndth cycle is a severe wear stage, the baseline value E b is the vibration energy of the nd cycle.

[0012] Preferably, the vibration data of the rope pulley is collected once every 30 days as a preset period.

[0013] Preferably, the sheave is at least one of a traction sheave, a guide sheave, a return sheave or a compensating sheave in an elevator system.

[0014] Preferably, the vibration data of the collecting rope pulley is the vibration data of the rope pulley when the elevator runs at a rated speed uniformly from the end floor to the end floor.

[0015] Preferably, the method for calculating the vibration energy according to the vibration data is as follows: determining the frequency band for calculating the vibration energy, summing the time-domain signals after processing the vibration data in a single direction within the frequency band, and performing arithmetic square root calculation to obtain the vibration energy.

[0016] Preferably, the single direction is the radial direction relative to the rotation plane of the rope pulley.

[0017] Preferably, the method for determining the frequency band for calculating the vibration energy is as follows: obtaining the time-domain signals of each axis within each frequency band of the vibration data through harmonic wavelet packet transform, calculating the sum of the absolute values of the correlation coefficients between each axis according to the time-domain signals of each axis within each frequency band, and determining the frequency band with the largest sum of the absolute values of the correlation coefficients as the frequency band for calculating the vibration energy.

[0018] Compared with the prior art, the sensor of the present invention is convenient to install, does not affect the normal operation of the elevator, and at the same time, there is no need to obtain the elevator structure parameters, which is convenient for realizing automatic monitoring. Brief Description of the Drawings

[0019] The present invention will be further described in detail below in conjunction with the drawings and specific embodiments:

[0020] Figure 1 It is a schematic diagram of the decomposition of the harmonic wavelet packet transform of the vibration data in Embodiment 1;

[0021] Figure 2 It is a schematic diagram of the correlation coefficients between each axis within each frequency band after the harmonic wavelet packet transform of the vibration data in Embodiment 1;

[0022] Figure 3 It is a schematic diagram of the rope pulley wear stage and wear warning in Embodiment 1;

[0023] Figure 4 It is a schematic diagram of the rope pulley wear stage and wear warning in Embodiment 2;

[0024] Figure 5 It is a schematic diagram of the rope pulley wear stage and wear warning in Embodiment 3;

[0025] Figure 6 It is a schematic diagram of the correlation coefficients between each axis within each frequency band after the harmonic wavelet packet transform of the vibration data in Embodiment 4. Detailed Description of the Embodiments

[0026] The following describes the implementation methods of the present invention through specific specific embodiments, and those skilled in the art can fully understand other advantages and technical effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through different specific implementation methods, and the details in this specification can also be applied based on different viewpoints, and various modifications or changes can be made without deviating from the overall design concept of the invention. It should be noted that the following embodiments and the features in the embodiments can be combined with each other in the absence of conflict. The following exemplary embodiments of the present invention can be implemented in a variety of different forms and should not be interpreted as being limited to the specific embodiments described herein. It should be understood that these embodiments are provided to make the disclosure of the present invention thorough and complete, and to fully convey the technical solutions of these exemplary specific embodiments to those skilled in the art.

[0027] Example 1

[0028] In this embodiment, a sheave in an elevator system is taken as an example. The sheave in the elevator system is, for example, a traction sheave, a guide sheave, a counter sheave or a compensation sheave. A vibration sensor can be installed at the base of the sheave accessory to be monitored to collect vibration data of the sheave. The vibration sensor can be a three-axis vibration sensor, or a two-axis or single-axis vibration sensor, preferably a three-axis vibration sensor.

[0029] This embodiment provides a rope pulley wear early warning method based on vibration signals, which collects the vibration data of the rope pulley according to a preset period, and calculates its vibration energy according to the vibration data collected in each period; when the total collection period n is not less than d+1, the wear stage of the rope pulley in the ndth period is judged according to the vibration energy, where d≥3; the wear stage is divided into a running-in wear stage, a stable wear stage and a severe wear stage;

[0030] When the wear warning threshold is not set, when the wear stage of the rope wheel in the ndth cycle is the stable wear stage or the severe wear stage, the wear warning threshold is set; determine whether the vibration energy of the current cycle exceeds the wear warning threshold, and if so, issue a wear warning signal.

[0031] The preset period can be regular or irregular, and it is preferred to adopt regular collection, such as once a day, a week, a month or a quarter. This embodiment takes the collection of the vibration data of the rope wheel once every 30 days as the preset period for explanation, and a sampling frequency f is installed on the traction wheel base. s It is a triaxial vibration sensor with a frequency of 5120 Hz.

[0032] At each collection, the vibration data of the rope pulley collected is the rope pulley vibration data of the elevator running at a constant speed from end to end at the rated speed.

[0033] In order to calculate the vibration energy based on the collected vibration data, the frequency band for calculating the vibration energy must first be determined. The method for determining the frequency band is as follows:

[0034] For the three-axis vibration sensor, the vibration data x(i), y(i), z(i) in the three directions of x, y, and z are transformed by harmonic wavelet packet. Taking the vibration data x(i) of the x-axis as an example, Figure 1 As shown, harmonic wavelet packet transform is performed. The highest analysis frequency of the signal is Decompose the signal into j (j = 0, 1, 2, 3, ...) frequency bands, and the frequency band bandwidth B can be expressed as B = 2 -j f h , s is the number of frequency bands, s = 2 j , the upper limit m and lower limit n of each analysis frequency band are

[0035]

[0036] Perform discrete-time Fourier transform on the signal to obtain the frequency domain signal, divide the frequency domain signal into s frequency bands, perform inverse Fourier transform on the frequency domain signal in each frequency band, and obtain the time domain signal x in each frequency band. 1 (i),x 2 (i)…x s (i).

[0037] The same harmonic wavelet packet transform process as above is used to transform y(i) and z(i) to obtain y 1 (i),y 2 (i)…y s (i) and z 1 (i),z 2 (i)…z s (i).

[0038] Calculate the correlation coefficient ρ of the x-axis and y-axis for the x, y, and z-axis time domain signals in each frequency band xy , the correlation coefficient between the x-axis and the z-axis ρ xz , the correlation coefficient between the y-axis and the z-axis ρ yz .

[0039] The correlation coefficient calculation formula is as follows to calculate the x- and y-axis correlation coefficient ρ xy For example.

[0040]

[0041] Calculate the sum of the absolute values ​​of the correlation coefficients in each frequency band.

[0042] ρ sum =|ρ xy |+|ρ xz |+|ρ yz|

[0043] Select the σth frequency band [m σ ,n σ ] as the frequency band for vibration energy calculation.

[0044] As a more specific example, for example, if the number of decomposition layers j of the vibration signal is 3, the ρ in each frequency band is calculated xy , xz , yz , sum like Figure 2 As shown, ρ in the frequency band [1920-2240Hz] sum Maximum, so the frequency band used to calculate the vibration energy is determined to be [1920-2240Hz].

[0045] After the frequency band is determined, the vibration data in the radial direction relative to the rotation plane of the rope wheel is preferred for calculating the vibration energy. The calculation process of the vibration energy is as follows:

[0046] If the x and z axes are radial and the y axis is normal, select the x-axis frequency band [m σ ,n σ ]’s vibration data to calculate the vibration energy.

[0047] One method of calculating vibration energy is to select vibration data processed by wavelet packet transform, for example, to select the time domain signal x in the σth frequency band. σ (i) Calculate the vibration energy E for the time domain signal x σ (i) Sum and perform arithmetic square root calculation. The calculation formula is as follows:

[0048]

[0049] Another method to calculate vibration energy is to perform FFT calculation on x(i) to obtain X(j), select the frequency band [m σ ,n σ ] σ (l), perform FFT energy calculation

[0050] It should be noted that the method of this embodiment does not determine the wear stage of the rope pulley and set the wear warning threshold when the vibration data of the rope pulley is collected for the first time, but requires multiple cycles of vibration data collection before determining the wear stage and setting the wear warning threshold.

[0051] Therefore, the total collection period n for judging the wear stage is not less than d+1, where d≥3. In this embodiment, d is set to 6, that is, the wear stage is judged after collecting vibration data of at least 7 periods.

[0052] An exemplary method for determining the wear stage is:

[0053] The vibration energy data from the ndth cycle to the current cycle are plotted on a two-dimensional coordinate system, with the ordinate being the vibration energy and the abscissa being the time period for collecting the rope pulley vibration data; the d+1 group of vibration energy data is fitted with a univariate function curve using the least squares method to obtain the slope k of the function; if k<-k thr , then the wear stage is judged to be the running-in wear stage; if -k thr <k<k thr , then the wear stage is judged to be the stable wear stage; if k>k thr , then the wear stage is judged to be the severe wear stage; where k thr For a given threshold, k thr >0.

[0054] Specific examples include Figure 3 As shown in the figure, point O is the vibration energy calculated based on the first vibration data collected at the beginning of monitoring, point A is the vibration energy data of the d+1th time, and the slope k obtained by fitting the 7 vibration energy data between OA is -0.25. The slope threshold k is set thr is 0.04. k<-k thr It is determined that the start of monitoring is the running-in wear stage. In the running-in wear stage, the wear warning threshold is not set, and the vibration data of the rope pulley continues to be collected according to the preset period (30 days).

[0055] When the B moment is monitored, the slope k of the 7 vibration energy data between A'B is fitted to be -0.03. At this time, the -k thr <k<k thr Condition, that is, the vibration energy calculated based on the collected vibration data at point A' can be used to determine that the rope pulley has entered the stable wear stage at time A'. Therefore, the wear warning threshold can be set at time B, and the average of the 7 vibration energies between A' and B, that is, the baseline value E b is 16.3, setting the first warning coefficient β 1 is 3, according to the wear warning threshold E thr =β 1 E b Calculate E thr The wear warning threshold E thr Once set, it is fixed and does not need to be set again later.

[0056] Then continue to collect the vibration data of the rope wheel according to the preset cycle. When the monitoring reaches time C, the slope k obtained by fitting the vibration energy data is 0.042. At this time, k>k is satisfied for the first time. thrConditions are met and the vehicle enters the severe wear stage. When the monitoring reaches time D, the vibration energy data is 50.1, which exceeds the threshold and a wear warning is issued.

[0057] The method of this embodiment can also be used to implement early warning of rope sheave wear on equipment such as cranes, hoists, and cable cars.

[0058] Example 2

[0059] The difference between this embodiment and embodiment 1 is that Figure 4 As shown in the figure, after collecting the vibration data of the rope wheel in the 7th cycle, the least square method is used to fit the 7 data from point E to point F to a univariate function, and the slope k of the function is -0.08. thr is 0.04, satisfying -k thr <k<k thr Therefore, it can be judged that the rope sheave is in the stable wear stage in the first cycle when the monitoring starts.

[0060] At this time, the wear warning threshold can be set to calculate the average value E of the seven vibration energies between EF. b is 16.1. Set the threshold coefficient according to the first warning coefficient β 1 is 3, according to formula E thr =β 1 E b Calculate the wear warning threshold E thr is 48.3,

[0061] Continue to collect the vibration data of the rope pulley according to the preset period. When the monitoring reaches time C, the slope k obtained by fitting the vibration energy data is 0.042. At this time, k>k is satisfied for the first time. thr Conditions, enter the severe wear stage; when the monitoring reaches time D, the vibration energy is 50.1, exceeding the wear warning threshold E thr , issuing a wear warning.

[0062] Example 3

[0063] The difference between this embodiment and embodiment 1 is that Figure 5 As shown in the figure, after collecting the vibration data of the rope pulley in the 7th cycle, the least square method is used to fit the 7 data from points G to H into a univariate function, and the slope k of the function is 0.16. thr is 0.04, satisfying k>k thr Therefore, it can be judged that the rope wheel is in the severe wear stage in the first cycle when the monitoring starts.

[0064] At this time, the wear warning threshold can be set, corresponding to the baseline value E set in the severe wear stage b Compared with the set baseline value E in the stable wear stageb Different, here the baseline value E b Directly the vibration energy value of the first cycle. The vibration energy of point G is 16.4, and the baseline value E is set. b It is 16.4.

[0065] Set the second warning coefficient β 2 is 2.5, according to formula E thr =β 2 E b Calculate the wear warning threshold E thr The vibration energy at point H is 55, which exceeds the wear warning threshold E thr , issuing a wear warning.

[0066] Example 4

[0067] The difference between this embodiment and Embodiment 1 is that an example of using a two-axis vibration sensor to determine a frequency band for calculating vibration energy is given, and the rest of the contents refer to Embodiment 1.

[0068] For the two-axis vibration sensor, the vibration data x(i) and y(i) in the x and y directions are transformed by harmonic wavelet packet transform.

[0069] Taking x(i) as an example, in the harmonic wavelet packet transform, the highest analysis frequency of the signal is The vibration data signal is decomposed into j (j = 0, 1, 2, 3, ...) frequency bands, and the frequency band bandwidth B can be expressed as B = 2 -j f h , s is the number of frequency bands, s = 2 j , the upper limit m and lower limit n of each analysis frequency band are

[0070] Perform discrete-time Fourier transform on the signal to obtain the frequency domain signal, divide the frequency domain signal into s frequency bands, perform inverse Fourier transform on the frequency domain signal in each frequency band, and obtain the time domain signal x in each frequency band. 1 (i),x 2 (i)…x s (i). Using the same harmonic wavelet packet transform process as above, y(i) is transformed to obtain y 1 (i),y 2 (i)…y s (i).

[0071] For the x-axis and y-axis time domain signals in each frequency band, calculate the absolute value of the correlation coefficient of the x-axis and y-axis respectively |ρ xy |. Select the σth frequency band with the largest absolute value of correlation coefficient [m σ ,n σ ] as the frequency band for vibration energy calculation.

[0072] As a preferred embodiment, the vibration data signal decomposition layer number j is 3 layers, and the calculated |ρ xy |As Figure 6 As shown, in [1600-1920Hz] |ρ xy | Maximum, so the frequency band for calculating vibration energy is selected [1600-1920Hz].

[0073] The present invention has been described in detail above through specific implementation modes and embodiments, but these do not constitute limitations of the present invention. Without departing from the principles of the present invention, those skilled in the art may also make many variations and improvements, which should also be regarded as the protection scope of the present invention.

Claims

1. A rope sheave wear early warning method based on vibration signals, characterized in that: The vibration data of the rope wheel is collected according to a preset period, and the vibration energy thereof is calculated respectively according to the vibration data collected in each period; when the total collection period n is not less than d+1, the wear stage of the rope wheel in the ndth period is judged according to the vibration energy, where d≥3; the wear stage is divided into a running-in wear stage, a stable wear stage and a severe wear stage; When the wear warning threshold is not set, when the wear stage of the rope wheel in the ndth cycle is the stable wear stage or the severe wear stage, the wear warning threshold is set; determine whether the vibration energy of the current cycle exceeds the wear warning threshold, and if so, issue a wear warning signal.

2. The rope sheave wear early warning method based on vibration signal according to claim 1 is characterized in that: The method for judging the wear stage of the rope wheel in the ndth cycle according to the vibration energy is: The vibration energy data from the ndth cycle to the current cycle are plotted on a two-dimensional coordinate system, with the ordinate being the vibration energy and the abscissa being the time period for collecting the rope pulley vibration data; the d+1 group of vibration energy data is fitted with a univariate function curve using the least squares method to obtain the slope k of the function; if k<-k thr , then the wear stage is judged to be the running-in wear stage; if -k thr <k<k thr , then the wear stage is judged to be the stable wear stage; if k>k thr , then the wear stage is judged to be the severe wear stage; where k thr For a given threshold, k thr >0.

3. The rope sheave wear early warning method based on vibration signal according to claim 1 is characterized in that: The method to set the wear warning threshold is: When the sheave is in the stable wear stage in the nd cycle, E thr =β1E b , where E thr is the wear warning threshold, β1 is the first warning coefficient, E b is the baseline value; When the sheave is in the severe wear stage in the nd cycle, E thr =β2E b , where E thr is the wear warning threshold, β2 is the second warning coefficient, E b is the baseline value.

4. The rope sheave wear early warning method based on vibration signal according to claim 3 is characterized in that: The first warning coefficient β1 is greater than the second warning coefficient β2.

5. The rope sheave wear early warning method based on vibration signal according to claim 3 is characterized in that: When the wear stage of the rope wheel in the ndth cycle is the stable wear stage, the baseline value E b It is the average value of the vibration energy from the ndth cycle to the current cycle.

6. The rope sheave wear early warning method based on vibration signal according to claim 3 is characterized in that: When the wear stage of the rope wheel in the ndth cycle is the severe wear stage, the baseline value E b is the vibration energy of the nd cycle.

7. The rope sheave wear early warning method based on vibration signal according to claim 1 is characterized in that: The vibration data of the rope pulley is collected once every 30 days as a preset period.

8. The rope sheave wear early warning method based on vibration signal according to claim 1, characterized in that: The sheave is at least one of a traction sheave, a guide sheave, a return sheave or a compensating sheave in an elevator system.

9. The rope sheave wear early warning method based on vibration signal according to claim 8, characterized in that: The vibration data of the rope sheave collected are the rope sheave vibration data of the elevator running at a constant speed from end to end at the rated speed.

10. The rope sheave wear early warning method based on vibration signal according to claim 1, characterized in that: The method for calculating vibration energy according to the vibration data is as follows: determining a frequency band for calculating vibration energy, summing time domain signals after processing vibration data in a single direction within the frequency band, and performing arithmetic square root calculation to obtain vibration energy.

11. The rope sheave wear early warning method based on vibration signal according to claim 10, characterized in that: The single direction is a radial direction relative to the plane of rotation of the sheave.

12. The rope sheave wear early warning method based on vibration signal according to claim 10, characterized in that: The method for determining the frequency band for calculating vibration energy is as follows: obtaining the time domain signal of each axis in each frequency band of vibration data through harmonic wavelet packet transform, calculating the sum of the absolute values ​​of the correlation coefficients between the axes according to the time domain signals of each axis in each frequency band, and determining the frequency band with the largest sum of the absolute values ​​of the correlation coefficients as the frequency band for calculating vibration energy.

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