Method and system for predicting service life of open-circuit water pump motor of RH furnace

Abstract

The invention provides a life prediction method and system for an RH furnace open-circuit water pump motor. The life prediction method comprises the steps that motor current instantaneous signals are collected; performing three-layer frequency band decomposition on the motor current instantaneous signal; preprocessing the motor current instantaneous signal; performing wavelet transformation on the instantaneous signal waveform of the motor current; extracting each scale wavelet coefficient obtained by wavelet transformation, calculating a wavelet energy value and constructing a feature vector; useful frequency bands are selected, and feature vectors are extracted and normalized; calculating the proportion of motor current instantaneous signal energy in a high-frequency part; when the proportion of the high-frequency part exceeds a set threshold value, a motor service life early warning signal is sent out. The method solves the problems that the service life of the RH furnace open-circuit water pump motor cannot be predicted and preventive maintenance has no basis, and stable operation of a hot well drainage system is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of iron and steel metallurgy, and in particular to a life prediction method for an open-circuit water pump motor of an RH furnace. Background Art

[0002] During the RH ladle refining furnace production process, the open-circuit water pump is responsible for sending cooling water back to the water plant. However, due to frequent motor starts and stops during operation, poor reliability of the check valves in the pipeline, impeller reversal, and frequent load starts by the pump motor, motor failures are common, and motor repairs are frequent. Although the design scheme is two pumps in operation and one as a backup, the motor failures are often unpredictable, causing significant maintenance challenges.

[0003] Traditional methods of measuring motor insulation for deterioration management are not suitable for open-circuit hydroelectric motors. Often, the motor burns out due to aging shaft seals, causing the insulation to drop to zero ground in an instant when water enters and causes a burst. It is difficult to detect the signs of motor burnout through routine inspections, and the failure to repair the motor in time often leads to the shutdown of the entire workstation.

[0004] Currently, motor lifespan management primarily involves immediate removal from production for repair upon failure. Preventative maintenance lacks a basis for judgment, and motor failures exhibit no predictable pattern. Therefore, developing a method for predicting the lifespan of open-circuit water pump motors in RH boilers is an urgent problem to be solved to ensure stable equipment operation. Summary of the Invention

[0005] The purpose of this invention is to provide a method and system for predicting the lifespan of an open-circuit water pump motor for an RH boiler, in order to solve the problems of unpredictable lifespan of the open-circuit water pump motor for an RH boiler and lack of basis for preventive maintenance, thereby achieving stable operation of the hot water well drainage system.

[0006] The present invention specifically adopts the following technical solutions:

[0007] According to a first aspect of the present invention, an embodiment of the present invention provides a life prediction method for an open-circuit water pump motor of an RH furnace, characterized by comprising:

[0008] Collect the instantaneous signal of motor current;

[0009] According to the Nyquist sampling theorem, the instantaneous signal of the motor current is decomposed into three frequency bands within the range of 0 to 120 Hz.

[0010] Preprocessing of the instantaneous motor current signal, including wavelet adaptive thresholding to eliminate noise and suppress baseline drift;

[0011] The instantaneous signal waveform of the motor current is transformed by wavelet transform, where the wavelet basis function is the Meyer type wavelet, and its characteristic function is as follows:

[0012]

[0013] The auxiliary function is: V(a)=2a 4 (25-14a+50a 2 -10a 3 ), a∈[0,1]

[0014] Where: ω is the angular frequency of the instantaneous signal of the motor current, α is the wavelet signal stretching coefficient;

[0015] Extract the wavelet coefficients of each scale obtained by wavelet transform, calculate the wavelet energy value and construct the eigenvector;

[0016] Select useful frequency bands, extract and normalize feature vectors;

[0017] Calculate the proportion of the motor current instantaneous signal energy that appears in the high-frequency part;

[0018] When the proportion of the high-frequency part exceeds the set threshold, a motor life warning signal is issued.

[0019] According to a second aspect of the present invention, an embodiment of the present invention provides a life prediction system for an open-circuit water pump motor of an RH furnace, characterized by comprising:

[0020] Signal acquisition module, used to collect instantaneous motor current signals;

[0021] The frequency band decomposition module is used to perform three-layer frequency band decomposition of the motor current instantaneous signal in the range of 0 to 120 Hz according to the Nyquist sampling theorem;

[0022] Signal preprocessing module, used to preprocess the instantaneous signal of the motor current, including wavelet adaptive threshold to eliminate noise and suppress baseline drift;

[0023] The wavelet transform module is used to perform wavelet transform on the instantaneous signal waveform of the motor current. The wavelet basis function selects the Meyer type wavelet, and its characteristic function is as follows:

[0024]

[0025] The auxiliary function is: V(a)=2a 4 (25-14a+50a 2 -10a 3 ), a∈[0,1]

[0026] Where: ω is the angular frequency of the instantaneous signal of the motor current, α is the wavelet signal stretching coefficient;

[0027] The eigenvector construction module is used to extract the wavelet coefficients of each scale obtained by wavelet transformation, calculate the wavelet energy value and construct the eigenvector;

[0028] The normalization module is used to select useful frequency bands and extract and normalize feature vectors;

[0029] The energy percentage calculation module is used to calculate the percentage of instantaneous motor current signal energy that appears in the high-frequency part;

[0030] The early warning module is used to issue a motor life warning signal when the proportion of high-frequency components exceeds a set threshold.

[0031] On the other hand, embodiments of the present invention also provide an electronic device, including a processor and a memory, wherein the memory stores a program that can run on the processor, characterized in that when the program is executed by the processor, it implements the steps of the above-described method for predicting the lifespan of an open-circuit water pump motor for an RH furnace.

[0032] In another aspect, embodiments of the present invention also provide a computer-readable storage medium storing at least one program, characterized in that the at least one program can be executed by at least one processor to implement the steps of the above-described method for predicting the lifespan of an open-circuit water pump motor for an RH furnace.

[0033] The present invention has the following beneficial effects:

[0034] (1) By performing wavelet analysis on the instantaneous current signal of the open-circuit hot water well pump motor of the RH boiler, the motor life can be predicted. When the motor life warning occurs, the motor can be sent for maintenance in advance by taking advantage of the scheduled maintenance time, which can shorten the maintenance cycle of the motor cycle.

[0035] (2) It significantly shortens the hot water well system's downtime due to failure and saves maintenance time.

[0036] (3) It has enabled true preventive maintenance and provided a powerful tool for life prediction.

[0037] (4) It realizes the automatic judgment of impeller detachment and can detect impeller malfunctions in a timely manner.

[0038] (5) It significantly reduces the occurrence of water leakage and equipment damage caused by accidental motor damage or untimely water outage in hot water wells. Attached Figure Description

[0039] Figure 1 This is a flowchart illustrating the life prediction method for the open-circuit water pump motor of the RH furnace according to Embodiment 1 of the present invention.

[0040] Figure 2 This is a schematic diagram of the impeller detachment and bearing wear early warning process in Embodiment 1 of the present invention;

[0041] Figure 3 A schematic diagram of the three-layer frequency band division for current signals;

[0042] Figure 4 This is a schematic diagram showing the distribution of abnormal characteristic values ​​of the motor.

[0043] Figure 5 This is a schematic diagram of the normal characteristic value distribution of the motor. Detailed Implementation

[0044] To make the technical solution of the present invention easier to understand, the technical solution of the present invention will be further described in detail below with reference to specific embodiments and accompanying drawings. Obviously, the following embodiments are only some embodiments of the present invention and do not constitute a limitation on the technical solution of the present invention. For those skilled in the art, other embodiments can be obtained based on the embodiments of this application without creative effort.

[0045] Example 1

[0046] This embodiment provides a life prediction method for an open-circuit water pump motor of an RH furnace. Figure 1 As shown, it includes the following steps:

[0047] Step 1: Collect the instantaneous current signal of the hot water well motor and send it to the embedded system for analysis.

[0048] In this embodiment, the sampling period is set to 20 milliseconds.

[0049] Step 2: According to the Nyquist sampling theorem, the motor current instantaneous signal is decomposed into three frequency bands within the range of 0 to 120 Hz. The division diagram is shown as follows: Figure 3 shown.

[0050] Step 3: Preprocess the instantaneous signal of the motor current, including using wavelet adaptive threshold to eliminate noise and suppress baseline drift to obtain a pure signal.

[0051] Step 4: Perform wavelet transform on the instantaneous signal waveform of the motor current. The wavelet basis function is Meyer type wavelet, and its characteristic function is as follows:

[0052]

[0053] The auxiliary function is: V(a)=2a 4 (25-14a+50a 2 -10a 3 ), a∈[0,1]

[0054] Where: ω is the angular frequency of the instantaneous signal of the motor current, α is the wavelet signal stretching coefficient;

[0055] Step 5: Extract the wavelet coefficients of each scale obtained by wavelet transform, calculate the wavelet energy value and construct the eigenvector. The standard wavelet energy is calculated as follows:

[0056] E jk =|D j (k)| 2

[0057] Where, E jk is the wavelet energy of f(t) at the jth scale and kth point. j (k) The kth data on the jth scale after the current signal is transformed by wavelet. Let be the sum of signal energy at sampling points k = 1, 2, ..., N at the j-th scale.

[0058] Step 6: Select useful frequency bands, extract and normalize the feature vector: T′=[T CA3 , T CD3 , T CD2 ]

[0059] Step 7: Calculate the proportion of the motor current instantaneous signal energy that appears in the high-frequency part;

[0060] Step 8: When the high-frequency portion exceeds the set threshold, a motor life warning signal is issued.

[0061] Extensive experimental data shows that when a motor operates normally, the majority of the signal's energy is in the low-frequency portion, with the high-frequency portion approaching zero. However, when abnormal noise is present in the motor, its lifespan is impacted. During this condition, even when the motor is operating with no significant increase in the effective current value, a significant portion of the wavelet energy is present in the high-frequency portion. By setting a threshold based on this, a judgment can be made and a motor lifespan warning signal issued.

[0062] This embodiment outputs an alarm signal to the human-machine interface HMI, which can prompt the operator to perform motor maintenance in a timely manner.

[0063] Furthermore, the life prediction method of the RH furnace open circuit water pump motor of this embodiment also includes the impeller shedding and bearing wear warning steps, such as Figure 2 As shown:

[0064] Collect the hot water well liquid level value and the effective value of the motor current. When the hot water well liquid level reaches 2.85 meters and the effective value of the motor current does not increase significantly, it means that the motor's pumping capacity has decreased. It is most likely caused by the impeller detachment. It is necessary to repair it as soon as possible and issue an impeller detachment warning signal.

[0065] When the effective value of the motor current is greater than 105% of the rated current of the motor, it indicates that the motor bearing may be worn, causing a slight overload of the motor. A bearing wear warning signal is issued and an alarm is displayed on the human-machine interface, prompting the motor to need maintenance and bearing replacement.

[0066] The above life prediction method was tested in RH furnace and achieved good results. When the hot water well pump motor is working, the characteristic value distribution of the motor current after wavelet transformation is compared. Figure 4 , 5 .

[0067] The characteristic vectors corresponding to the abnormal and normal conditions of the hot water well pump motor are shown in Table 1:

[0068] Table 1: Eigenvectors corresponding to motor abnormality and normal conditions

[0069] Motor status CA3 CD3 CD2 Motor is normal 93.123 7.453 0.239 Motor is normal 91.288 4.603 0.327 Motor is normal 90.768 11.432 0.695 Motor abnormality 49.546 30.143 0.594 Motor malfunction 50.371 42.520 0.126 Motor malfunction 59.318 44.428 0.307

[0070] The data show that the sample characteristic values ​​are significantly different, and the CA3 and CD3 frequency bands have completely distinct characteristics, which can be used to predict motor life and perform preventive maintenance.

[0071] The lifespan prediction method for the open-circuit water pump motor of the RH boiler of the present invention can reduce the number of motor overhaul cycles and lower motor repair costs. Simultaneously, due to the reduced number of motor overhauls, the overall motor maintenance cycle is shortened, effectively alleviating the problems of insufficient motor capacity and untimely motor repair. The method of the present invention has low implementation cost and good potential for widespread application.

[0072] Example 2

[0073] This embodiment provides an automatic control system for dynamically adding slag material to a ladle refining furnace, comprising:

[0074] Signal acquisition module, used to collect instantaneous motor current signals;

[0075] The frequency band decomposition module is used to perform three-layer frequency band decomposition of the motor current instantaneous signal in the range of 0 to 120 Hz according to the Nyquist sampling theorem;

[0076] Signal preprocessing module, used to preprocess the instantaneous signal of the motor current, including wavelet adaptive threshold to eliminate noise and suppress baseline drift;

[0077] The wavelet transform module is used to perform wavelet transform on the instantaneous signal waveform of the motor current. The wavelet basis function selects the Meyer type wavelet, and its characteristic function is as follows:

[0078]

[0079] The auxiliary function is: V(a)=2a 4(25-14a+50a 2 -10a 3 ), a∈[0,1]

[0080] Where: ω is the angular frequency of the instantaneous signal of the motor current, α is the wavelet signal stretching coefficient;

[0081] The eigenvector construction module is used to extract the wavelet coefficients of each scale obtained by wavelet transformation, calculate the wavelet energy value and construct the eigenvector;

[0082] The normalization module is used to select useful frequency bands and extract and normalize feature vectors;

[0083] The energy percentage calculation module is used to calculate the percentage of instantaneous motor current signal energy that appears in the high-frequency part;

[0084] The early warning module is used to issue a motor life warning signal when the proportion of high-frequency components exceeds a set threshold.

[0085] Example 3

[0086] This embodiment provides an electronic device, including a processor and a memory. The memory stores a program that can run on the processor. When the program is executed by the processor, it implements the steps of the above-described method for predicting the lifespan of an open-circuit water pump motor for a RH furnace.

[0087] Example 4

[0088] This embodiment provides a computer-readable storage medium storing at least one program that can be executed by at least one processor to implement the steps of the above-described method for predicting the lifespan of an open-circuit water pump motor for an RH boiler.

[0089] The aforementioned storage media include: USB flash drives, portable hard drives, read-only memory, random access memory, magnetic disks, optical disks, and other media that can store program code.

[0090] Those skilled in the art will understand that the above embodiments are specific embodiments for implementing the present invention. In addition to the above embodiments, the present invention may have other implementation methods. All technical solutions formed by equivalent substitution or equivalent transformation fall within the protection scope claimed by the present invention.

Claims

1. A life prediction method for an open-circuit water pump motor of an RH furnace, characterized in that: include: Collect instantaneous signal of motor current; According to the Nyquist sampling theorem, the instantaneous signal of the motor current is decomposed into three frequency bands in the range of 0 to 120 Hz; Preprocessing of the instantaneous signal of the motor current includes wavelet adaptive threshold to eliminate noise and suppress baseline drift; The instantaneous signal waveform of the motor current is transformed by wavelet transform, where the wavelet basis function selects the Meyer type wavelet, and its characteristic function is as follows: The auxiliary function is: V(a) = 2a 4 (25-14a+50a 2 -10a 3 ), a∈[0,1] Where: ω is the angular frequency of the instantaneous signal of the motor current, α is the wavelet signal stretching coefficient; Extract the wavelet coefficients of each scale obtained by wavelet transform, calculate the wavelet energy value and construct the feature vector; Select useful frequency bands, extract and normalize feature vectors; Calculate the proportion of the instantaneous signal energy of the motor current that appears in the high-frequency part; When the proportion of the high-frequency part exceeds the set threshold, a motor life warning signal is issued.

2. The life prediction method of the RH furnace open circuit water pump motor according to claim 1, characterized in that: The wavelet energy value is calculated using the standard wavelet energy calculation formula.

3. The life prediction method of the RH furnace open circuit water pump motor according to claim 1, characterized in that: Also includes: The hot water well liquid level and the effective value of the motor current are collected. When the hot water well liquid level reaches 2.85 meters and the effective value of the motor current does not increase significantly, an impeller detachment warning signal is issued.

4. The life prediction method of the RH furnace open circuit water pump motor according to claim 1, characterized in that: Also includes: When the effective value of the motor current is greater than 105% of the rated current of the motor, a bearing wear warning signal is issued.

5. A life prediction system for an open-circuit water pump motor of an RH furnace, characterized in that: include: A signal acquisition module is used to collect instantaneous signals of motor current; The frequency band decomposition module is used to perform three-layer frequency band decomposition of the instantaneous signal of the motor current in the range of 0 to 120 Hz according to the Nyquist sampling theorem; A signal preprocessing module is used to preprocess the instantaneous signal of the motor current, including wavelet adaptive threshold to eliminate noise and suppress baseline drift; The wavelet transform module is used to perform wavelet transform on the instantaneous signal waveform of the motor current. The wavelet basis function selects the Meyer type wavelet, and its characteristic function is as follows: The auxiliary function is: v(a) = 2a 4 (25-14a+50a 2 -10a 3 ), a∈[0,1] Where: ω is the angular frequency of the instantaneous signal of the motor current, α is the wavelet signal stretching coefficient; The feature vector construction module is used to extract the wavelet coefficients of each scale obtained by wavelet transformation, calculate the wavelet energy value and construct the feature vector; Normalization module, used to select useful frequency bands, extract and normalize feature vectors; The energy proportion calculation module is used to calculate the proportion of the energy of the instantaneous signal of the motor current in the high-frequency part; The early warning module is used to issue a motor life warning signal when the proportion of the high-frequency part exceeds the set threshold.

6. An electronic device comprising a processor and a memory, wherein the memory stores a program that can be run on the processor, characterized in that When the program is executed by the processor, the steps of the life prediction method for the open-circuit water pump motor of the RH furnace described in any one of claims 1-4 are implemented.

7. A computer-readable storage medium storing at least one program, characterized in that: The at least one program can be executed by at least one processor to implement the steps of the life prediction method for the open-circuit water pump motor of the RH furnace as described in any one of claims 1-4.

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