Metallurgy crane wheel multi-parameter monitoring system and method

Abstract

The invention discloses a metallurgical crane wheel multi-parameter monitoring system and method, and relates to the technical field of metallurgical crane wheel safety monitoring, and the system comprises an optical fiber sensing module and a signal acquisition and processing module, the optical fiber sensing module comprises a first vibration optical fiber sensor, a first strain optical fiber sensor, a temperature optical fiber sensor, a second vibration optical fiber sensor and a second strain optical fiber sensor; the signal acquisition and processing module is used for acquiring a vibration optical signal of a bearing, a strain optical signal of the bearing, a temperature optical signal of the bearing, a vibration optical signal of a tread and a strain optical signal of a rim respectively, and is further matched with the signal acquisition and processing module to monitor vibration, strain and temperature of the bearing, vibration of the tread and strain of the rim. According to the invention, multi-parameter monitoring can be realized, and the problems of poor reliability, short service life, susceptibility to electromagnetic interference and low monitoring precision are solved.

Description

Technical Field

[0001] The present application relates to the technical field of metallurgical crane wheel safety monitoring, and in particular to a metallurgical crane wheel multi-parameter monitoring system and method. Background Art

[0002] Cranes play a vital role in the metallurgical industry, lifting a variety of heavy loads. Due to the harsh operating environment (high temperatures, dust, vibration, and strong electromagnetic interference) and the heavy loads they carry, the wheels of metallurgical cranes are prone to wear, fatigue, overheating, and poor lubrication. These problems can seriously affect the operational safety and efficiency of metallurgical cranes and may even lead to safety accidents. Therefore, monitoring the wheels of metallurgical cranes is essential.

[0003] Traditional metallurgical crane wheel monitoring technology mostly uses monitoring technology based on electrical sensors (such as resistance strain gauges and piezoelectric sensors), which has many defects such as poor reliability, short lifespan and susceptibility to electromagnetic interference. At the same time, it mostly monitors a single parameter (such as vibration or temperature), which makes it difficult to fully reflect the health status of the wheel and has low monitoring accuracy. Summary of the Invention

[0004] The purpose of this application is to provide a multi-parameter monitoring system and method for metallurgical crane wheels, which can realize multi-parameter monitoring and solve the problems of poor reliability, short life, susceptibility to electromagnetic interference and low monitoring accuracy.

[0005] To achieve the above objectives, this application provides the following solutions:

[0006] In a first aspect, the present application provides a multi-parameter monitoring system for a metallurgical crane wheel, the multi-parameter monitoring system for a metallurgical crane wheel comprising: a fiber optic sensing module and a signal acquisition and processing module;

[0007] The optical fiber sensing module includes: a first vibration optical fiber sensor, a first strain optical fiber sensor, a temperature optical fiber sensor, a second vibration optical fiber sensor and a second strain optical fiber sensor;

[0008] The first vibration optical fiber sensor, the first strain optical fiber sensor, and the temperature optical fiber sensor are all installed on the bearing of the metallurgical crane wheel. The first vibration optical fiber sensor is used to collect the vibration optical signal of the bearing, the first strain optical fiber sensor is used to collect the strain optical signal of the bearing, and the temperature optical fiber sensor is used to collect the temperature optical signal of the bearing.

[0009] The second vibration optical fiber sensor is installed on the track on which the wheel of the metallurgical crane passes, and is used to collect the vibration optical signal of the tread of the wheel of the metallurgical crane; the second strain optical fiber sensor is installed on the rim of the wheel of the metallurgical crane, and is used to collect the strain optical signal of the rim;

[0010] The signal acquisition and processing module is communicatively connected to the optical fiber sensing module; the signal acquisition and processing module is used to convert the vibration optical signal of the bearing, the strain optical signal of the bearing, the temperature optical signal of the bearing, the vibration optical signal of the tread and the strain optical signal of the rim into the vibration electrical signal of the bearing, the strain electrical signal of the bearing, the temperature electrical signal of the bearing, the vibration electrical signal of the tread and the strain electrical signal of the rim, respectively, so as to monitor the vibration, strain and temperature of the bearing, the vibration of the tread and the strain of the rim.

[0011] Optionally, the first vibration optical fiber sensor and the second vibration optical fiber sensor are both distributed optical fiber sensors, the first vibration optical fiber sensor is spirally wound on the outer surface of the bearing seat of the bearing, and the second vibration optical fiber sensor is arranged along the track;

[0012] The first strain optical fiber sensor and the second strain optical fiber sensor both adopt fiber grating array sensors. The first strain optical fiber sensor is welded on the outer ring of the bearing, and the second strain optical fiber sensor is bonded to the wheel rim.

[0013] The temperature optical fiber sensor adopts a fiber grating sensor and is installed on the surface of the outer ring of the bearing.

[0014] Optionally, the surface of the first vibration optical fiber sensor is coated with a polyimide-silicon carbide composite layer, the first strain optical fiber sensor is packaged with a nickel alloy, the first strain optical fiber sensor is uniformly welded to the surface of the outer ring of the bearing along the circumference of the outer ring of the bearing, the surface of the second strain optical fiber sensor is coated with a ceramic coating, and the second strain optical fiber sensor is bonded to the surface of the rim by glue.

[0015] Optionally, the signal acquisition and processing module includes an optical fiber demodulation system and a processor, and the processor is an embedded system or an industrial computer;

[0016] The optical fiber demodulation system is communicatively connected to the optical fiber sensing module; the optical fiber demodulation system is used to convert the vibration optical signal of the bearing, the strain optical signal of the bearing, the temperature optical signal of the bearing, the vibration optical signal of the tread, and the strain optical signal of the rim into the vibration electrical signal of the bearing, the strain electrical signal of the bearing, the temperature electrical signal of the bearing, the vibration electrical signal of the tread, and the strain electrical signal of the rim;

[0017] The processor is communicatively connected to the optical fiber demodulation system; the processor is used to process the vibration electrical signal of the bearing, the strain electrical signal of the bearing, the temperature electrical signal of the bearing, the vibration electrical signal of the tread, and the strain electrical signal of the rim, to obtain the frequency and amplitude corresponding to the vibration component of the bearing, the strain value of the bearing, the temperature value of the bearing, the amplitude corresponding to the vibration component of the tread, and the strain value of the rim.

[0018] Optionally, the method for determining the frequency and amplitude corresponding to the vibration component of the bearing includes: performing CEEMD decomposition on the vibration electrical signal of the bearing to obtain multiple inherent modal function components of the bearing, calculating the variance contribution rate and correlation coefficient corresponding to each inherent modal function component of the bearing, screening the multiple inherent modal function components of the bearing based on the variance contribution rate and the correlation coefficient to obtain the vibration component of the bearing, and selecting the maximum frequency and the amplitude at the maximum frequency in the vibration component of the bearing as the frequency and amplitude corresponding to the vibration component of the bearing; wherein the variance contribution rate is the ratio of the variance of the inherent modal function component to the variance of the vibration electrical signal, and the correlation coefficient is the correlation coefficient between the inherent modal function component and the vibration electrical signal;

[0019] The method for determining the strain value of the bearing includes: determining the strain value of the bearing based on the strain electrical signal of the bearing;

[0020] The method for determining the temperature value of the bearing includes: determining the temperature value of the bearing based on the temperature electrical signal of the bearing;

[0021] The method for determining the amplitude corresponding to the vibration component of the tread includes: performing CEEMD decomposition on the vibration electrical signal of the tread to obtain multiple intrinsic modal function components of the tread, calculating the variance contribution rate and correlation coefficient corresponding to each intrinsic modal function component of the tread, screening the multiple intrinsic modal function components of the tread based on the variance contribution rate and the correlation coefficient to obtain the vibration component of the tread, and selecting the amplitude at the maximum frequency in the vibration component of the tread as the amplitude corresponding to the vibration component of the tread;

[0022] The method for determining the strain value of the wheel rim includes: determining the strain value of the wheel rim based on a strain electrical signal of the wheel rim.

[0023] Optionally, the metallurgical crane wheel multi-parameter monitoring system further comprises: a monitoring and early warning module, the monitoring and early warning module being communicatively connected to the processor in the signal acquisition and processing module;

[0024] The monitoring and early warning module is used to determine whether the bearing and the rim are faulty based on the frequency and amplitude corresponding to the vibration component of the bearing, the strain value of the bearing, the temperature value of the bearing, the amplitude corresponding to the vibration component of the tread and the strain value of the rim, and to issue a bearing fault early warning signal when the bearing fails, and to issue a rim fault early warning signal when the rim fails.

[0025] Optionally, based on the frequency and amplitude corresponding to the vibration component of the bearing, the strain value of the bearing, the temperature value of the bearing, the amplitude corresponding to the vibration component of the tread and the strain value of the rim, it is determined whether the bearing and the rim are faulty, and a bearing fault warning signal is issued when the bearing fails, and a rim fault warning signal is issued when the rim fails, the monitoring and warning module is used to determine the vibration component of the bearing as a first vibration component when the absolute value of the error percentage between the frequency corresponding to the vibration component of the bearing and the outer ring fault characteristic frequency of the bearing is less than a preset error percentage, and determine the vibration component of the bearing as a second vibration component when the absolute value of the error percentage between the frequency corresponding to the vibration component of the bearing and the inner ring fault characteristic frequency of the bearing is less than a preset error percentage, and When the absolute value of the error percentage between the frequency corresponding to the vibration component of the bearing and the rolling element fault characteristic frequency of the bearing is less than the preset error percentage, the vibration component of the bearing is determined to be the third vibration component; when the amplitude corresponding to the first vibration component, the amplitude corresponding to the second vibration component or the amplitude corresponding to the third vibration component is greater than the first preset vibration threshold, the change in the strain value of the bearing is greater than the first preset strain change threshold, and the change in the temperature value of the bearing is greater than the preset temperature change threshold, it is determined that the bearing has failed and a bearing failure warning signal is issued; when the amplitude corresponding to the vibration component of the tread is greater than the second preset vibration threshold and the change in the strain value of the rim is greater than the second preset strain change threshold, it is determined that the rim has failed and a rim failure warning signal is issued.

[0026] Optionally, the metallurgical crane wheel multi-parameter monitoring system further includes: a data transmission module, the data transmission module being communicatively connected to the optical fiber sensing module, the signal acquisition and processing module, and the monitoring and early warning module respectively;

[0027] The data transmission module includes a first transmission unit and a second transmission unit. The first transmission unit is used to transmit the vibration light signal of the bearing, the strain light signal of the bearing, the temperature light signal of the bearing, the vibration light signal of the tread, and the strain light signal of the rim obtained by the optical fiber sensing module to the signal acquisition and processing module through wired transmission. The second transmission unit is used to transmit the frequency and amplitude corresponding to the vibration component of the bearing, the strain value of the bearing, the temperature value of the bearing, the amplitude corresponding to the vibration component of the tread, and the strain value of the rim obtained by the signal acquisition and processing module to the monitoring and early warning module through wired transmission or wireless transmission.

[0028] Optionally, the signal acquisition and processing module further includes an industrial cabinet, and the optical fiber demodulation system and the processor are both installed in the industrial cabinet;

[0029] The monitoring and early warning module is also used to calculate the stress value of the bearing based on the strain value of the bearing. When the stress value of the bearing is greater than a first preset stress threshold, the bearing is determined to be damaged and a bearing damage early warning signal is issued; the rim stress value is calculated based on the strain value of the rim. When the stress value of the rim is greater than a second preset stress threshold, the rim is determined to be damaged and a rim damage early warning signal is issued.

[0030] In a second aspect, the present application provides a multi-parameter monitoring method for a metallurgical crane wheel, which is applied to the above-mentioned multi-parameter monitoring system for a metallurgical crane wheel. The multi-parameter monitoring method for a metallurgical crane wheel comprises:

[0031] The optical fiber demodulation system converts the bearing vibration optical signal, the bearing strain optical signal, the bearing temperature optical signal, the tread vibration optical signal and the rim strain optical signal into the bearing vibration electrical signal, the bearing strain electrical signal, the bearing temperature electrical signal, the tread vibration electrical signal and the rim strain electrical signal respectively;

[0032] The processor processes the vibration electrical signal of the bearing, the strain electrical signal of the bearing, the temperature electrical signal of the bearing, the vibration electrical signal of the tread, and the strain electrical signal of the rim to obtain the frequency and amplitude corresponding to the vibration component of the bearing, the strain value of the bearing, the temperature value of the bearing, the amplitude corresponding to the vibration component of the tread, and the strain value of the rim;

[0033] The monitoring and early warning module determines whether the bearing and rim are faulty based on the frequency and amplitude corresponding to the vibration component of the bearing, the strain value of the bearing, the temperature value of the bearing, the amplitude corresponding to the vibration component of the tread and the strain value of the rim, and issues a bearing fault early warning signal when a bearing fails, and issues a rim fault early warning signal when a rim fails.

[0034] According to the specific embodiments provided in this application, this application has the following technical effects:

[0035] The present application provides a multi-parameter monitoring system and method for a metallurgical crane wheel, comprising: an optical fiber sensing module and a signal acquisition and processing module, wherein the optical fiber sensing module comprises a first vibration optical fiber sensor, a first strain optical fiber sensor, a temperature optical fiber sensor, a second vibration optical fiber sensor, and a second strain optical fiber sensor, wherein the first vibration optical fiber sensor is used to acquire a vibration optical signal of a bearing, the first strain optical fiber sensor is used to acquire a strain optical signal of a bearing, the temperature optical fiber sensor is used to acquire a temperature optical signal of a bearing, the second vibration optical fiber sensor is used to acquire a vibration optical signal of a tread, and the second strain optical fiber sensor is used to acquire a strain optical signal of a rim, and the signal acquisition and processing module is used to convert the vibration optical signal of the bearing, the strain optical signal of the bearing, the temperature optical signal of the bearing, the vibration optical signal of the tread, and the strain optical signal of the rim into a vibration electrical signal of the bearing, a strain electrical signal of the bearing, a temperature electrical signal of the bearing, a vibration electrical signal of the tread, and a strain electrical signal of the rim, respectively, to monitor the vibration, strain, and temperature of the bearing, the vibration of the tread, and the strain of the rim. All sensors designed in this application use fiber optic sensors. Since fiber optic sensors are inherently resistant to electromagnetic interference and high temperature, they can be used in high-load environments and are suitable for metallurgical environments. Therefore, they can solve the problems of poor reliability, short life and susceptibility to electromagnetic interference. They can also simultaneously monitor the vibration, strain and temperature of the bearing, the vibration of the tread and the strain of the wheel rim in real time, solving the problem of difficulty in fully reflecting the health status of the wheel and low monitoring accuracy when monitoring a single parameter. This can achieve multi-parameter monitoring and solve the problems of poor reliability, short life, susceptibility to electromagnetic interference and low monitoring accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0037] Figure 1 This is a schematic diagram of the overall architecture of a multi-parameter monitoring system for metallurgical crane wheels provided in Example 1 of the present application.

[0038] Figure 2 Schematic diagram of the layout of the optical fiber sensor provided in Example 1 of the present application.

[0039] Figure 3 Schematic diagram of the vibration electrical signal analysis process provided in Example 1 of the present application.

[0040] Figure 4 Schematic diagram of the strain electrical signal analysis process provided in Example 1 of the present application.

[0041] Figure 5 Schematic diagram of the temperature electrical signal analysis process provided in Example 1 of the present application.

[0042] Figure 6 A flow chart of a multi-parameter monitoring method for metallurgical crane wheels provided in Example 2 of the present application. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0044] Example 1

[0045] This embodiment provides a multi-parameter monitoring system for metallurgical crane wheels, such as Figure 1 As shown, the multi-parameter monitoring system for the wheels of a metallurgical crane includes: an optical fiber sensing module and a signal acquisition and processing module.

[0046] The optical fiber sensing module includes: a first vibration optical fiber sensor, a first strain optical fiber sensor, a temperature optical fiber sensor, a second vibration optical fiber sensor, and a second strain optical fiber sensor. The first vibration optical fiber sensor, the first strain optical fiber sensor, and the temperature optical fiber sensor are all installed on the bearing of the metallurgical crane wheel. The first vibration optical fiber sensor is used to collect the vibration optical signal of the bearing, the first strain optical fiber sensor is used to collect the strain optical signal of the bearing, and the temperature optical fiber sensor is used to collect the temperature optical signal of the bearing. The second vibration optical fiber sensor is installed on the track through which the metallurgical crane wheel passes, and the second vibration optical fiber sensor is used to collect the vibration optical signal of the tread of the metallurgical crane wheel. The second strain optical fiber sensor is installed on the rim of the metallurgical crane wheel, and the second strain optical fiber sensor is used to collect the strain optical signal of the rim.

[0047] The signal acquisition and processing module is communicatively connected to the optical fiber sensing module. The signal acquisition and processing module is used to convert the vibration optical signal of the bearing, the strain optical signal of the bearing, the temperature optical signal of the bearing, the vibration optical signal of the tread and the strain optical signal of the rim into the vibration electrical signal of the bearing, the strain electrical signal of the bearing, the temperature electrical signal of the bearing, the vibration electrical signal of the tread and the strain electrical signal of the rim, so as to monitor the vibration, strain and temperature of the bearing, the vibration of the tread and the strain of the rim.

[0048] The sensors designed to perform the monitoring function in this embodiment all employ optical fiber sensors, namely, a first vibration optical fiber sensor, a first strain optical fiber sensor, a temperature optical fiber sensor, a second vibration optical fiber sensor, and a second strain optical fiber sensor, thereby providing a multi-parameter monitoring system for metallurgical crane wheels based on optical fiber sensing technology. Since optical fiber sensors are inherently resistant to electromagnetic interference and resistant to high temperatures (special coatings allow for stable operation above 300°C), they can be used in high-load environments, including metallurgical environments. Therefore, they can address numerous drawbacks such as poor reliability, short lifespan, and susceptibility to electromagnetic interference. Furthermore, they can achieve distributed measurement of multiple parameters (vibration, strain, and temperature) with high sensitivity. Through multi-parameter collaborative monitoring, the problem of incomplete monitoring of a single wheel parameter is resolved. The system can simultaneously monitor the vibration, strain, and temperature of the bearing, the vibration of the tread, and the strain of the rim in real time, comprehensively reflecting the wheel's health status and improving monitoring accuracy. This makes it suitable for monitoring the health of crane wheels in high-temperature, high-load, and strong electromagnetic interference environments within the metallurgical industry.

[0049] The following, combined Figure 1 The multi-parameter monitoring system for the wheels of a metallurgical crane of this embodiment is introduced in detail. The multi-parameter monitoring system for the wheels of a metallurgical crane of this embodiment includes a fiber optic sensing module (also called a hidden danger perception module), a signal acquisition and processing module, a monitoring and early warning module (also called a data analysis and alarm module) and a data transmission module.

[0050] (1) Fiber optic sensing module

[0051] The optical fiber sensing module of this embodiment includes a variety of optical fiber sensors, such as Figure 2 As shown in the figure, distributed optical fiber sensors, optical fiber grating array sensors and optical fiber grating sensors are used for vibration, strain and temperature monitoring of bearings of metallurgical crane wheels, vibration monitoring of tread (arc surface where wheel contacts rail) and strain monitoring of wheel rim. Specifically, distributed optical fiber sensors, optical fiber grating array sensors, optical fiber grating sensors and other sensors are installed at positions such as bearings, treads and wheel rims to collect multi-physical field signals such as vibration, strain and temperature of the wheel. Subsequently, whether the bearing fails can be determined based on the vibration, strain and temperature monitoring of the bearing, and the bearing fault diagnosis can be completed. Whether the wheel rim fails can be determined based on the vibration monitoring of the tread and the strain monitoring of the wheel rim, and the wheel rim fault diagnosis can be completed, thereby realizing wheel defect monitoring.

[0052] (1) Bearing monitoring

[0053] 1) Vibration Monitoring: A distributed fiber optic sensor is spirally wound around the outer surface of the bearing housing, with a specific pitch of 10 mm, covering the axial vibration-sensitive area on the outer surface (which can be determined empirically). The distributed fiber optic sensor uses a phase-sensitive optical time domain reflectometer (Φ-OTDR) to capture broadband vibration optical signals. Bearing wear signals are subsequently captured by analyzing the frequency, amplitude, and other characteristics of the vibration optical signals. The distributed fiber optic sensor uses a single-mode optical fiber coated with a polyimide-silicon carbide composite layer to enhance its wear resistance and high-temperature oxidation resistance. This polyimide-silicon carbide composite layer overcomes the 300°C high-temperature limitation of polyimide while enhancing its mechanical strength. Through material synergy, the environmental adaptability of the single-mode optical fiber is improved.

[0054] A distributed fiber optic sensor is installed on the bearing seat so that it can sense the vibration of the bearing. The installation position and direction of the distributed fiber optic sensor should be optimized and adjusted according to the vibration characteristics of the bearing to obtain the most representative vibration light signal.

[0055] 2) Strain Monitoring: Fiber Bragg grating array sensors are uniformly welded around the bearing's outer ring in the non-load-bearing area (determined empirically) to monitor dynamic strain fluctuations as the rolling elements pass through. The sensors are encapsulated in a nickel alloy and welded directly to the bearing's outer ring. Since they are installed in the non-load-bearing area, welding is chosen to ensure a more secure installation without damaging the structure.

[0056] 3) Temperature monitoring: A fiber Bragg grating temperature sensor is installed on the surface of the outer ring of the bearing to monitor abnormal temperature rise caused by lubrication failure in real time.

[0057] (2) Wheel rim and tread monitoring

[0058] 1) Vibration monitoring: Distributed fiber optic sensors are deployed along the track, especially in the tread area. Distributed fiber optic sensors are laid along the crane trolley traveling beam to avoid mechanical damage. The phase-sensitive optical time domain reflectometer in the distributed fiber optic sensors monitors the wheel rolling sound waves in real time to identify defects such as tread cracks, spalling, and track deviation, and monitor fatigue crack propagation.

[0059] 2) Strain Monitoring: Fiber Bragg grating array sensors are bonded to the wheel rim to monitor wheel force distribution. The Fiber Bragg grating array sensors are coated with a high-temperature resistant ceramic. Because welding is inconvenient at the wheel rim, they are bonded directly to the wheel surface using high-temperature adhesive.

[0060] At this time, in this embodiment, the optical fiber sensing module includes: a first vibration optical fiber sensor, a first strain optical fiber sensor, a temperature optical fiber sensor, a second vibration optical fiber sensor, and a second strain optical fiber sensor. The first vibration optical fiber sensor, the first strain optical fiber sensor, and the temperature optical fiber sensor are all installed on the bearing of the metallurgical crane wheel. The first vibration optical fiber sensor is used to collect the vibration optical signal of the bearing, the first strain optical fiber sensor is used to collect the strain optical signal of the bearing, and the temperature optical fiber sensor is used to collect the temperature optical signal of the bearing. The second vibration optical fiber sensor is installed on the track through which the metallurgical crane wheel passes, and the second vibration optical fiber sensor is used to collect the vibration optical signal of the tread of the metallurgical crane wheel. The second strain optical fiber sensor is installed on the rim of the metallurgical crane wheel, and the second strain optical fiber sensor is used to collect the strain optical signal of the rim.

[0061] The first and second vibration fiber sensors are both distributed fiber optic sensors. The first is spirally wound around the outer surface of the bearing seat, while the second is arranged along the track. The first and second strain sensors are both fiber grating array sensors. The first is welded to the outer ring of the bearing, while the second is bonded to the wheel rim. The temperature sensor is a fiber grating array sensor mounted on the outer ring of the bearing.

[0062] Among them, the surface of the first vibration optical fiber sensor is coated with a polyimide-silicon carbide composite layer, the first strain optical fiber sensor is packaged with nickel alloy, the first strain optical fiber sensor is uniformly welded on the surface of the outer ring of the bearing along the circumference of the outer ring of the bearing, the surface of the second strain optical fiber sensor is coated with a ceramic coating, and the second strain optical fiber sensor is bonded to the surface of the rim by glue.

[0063] This embodiment adopts a composite sensing network design. Distributed optical fiber sensors, optical fiber grating array sensors, and optical fiber grating sensors work together to achieve both local high-precision and global distributed monitoring. The first vibration optical fiber sensor is coated with a polyimide-silicon carbide composite layer to improve wear resistance and high-temperature oxidation resistance. The first strain optical fiber sensor is encapsulated in nickel alloy and directly welded to the non-load-bearing area of the bearing outer ring to avoid affecting the dynamic performance of the bearing. The second strain optical fiber sensor is coated with a high-temperature resistant ceramic coating to ensure long-term stability in metallurgical environments.

[0064] (2) Signal acquisition and processing module

[0065] The signal acquisition and processing module of this embodiment includes an optical fiber demodulation system, an embedded system or an industrial computer, acquisition software, and an industrial cabinet. The optical fiber demodulation system, the embedded system or the industrial computer, and the industrial cabinet are arranged near the metallurgical crane, wherein the optical fiber demodulation system and the embedded system or the industrial computer are installed in the industrial cabinet.

[0066] The optical fiber demodulation system is responsible for collecting the multi-source optical signals output by the optical fiber sensing module and converting the multi-source optical signals into multi-source electrical signals.

[0067] The acquisition software is installed on the embedded system or industrial computer, that is, the embedded system or industrial computer has built-in acquisition software, and the multi-source electrical signals are processed by the acquisition software to extract characteristic parameters such as vibration spectrum (the frequency and corresponding amplitude of the vibration electrical signal determined after converting the vibration electrical signal from the time domain to the frequency domain), strain value, temperature value, etc.

[0068] The signal acquisition module of this embodiment converts the multi-source optical signals collected by the optical fiber sensing module into multi-source electrical signals, and processes the multi-source electrical signals at the same time, extracts characteristic parameters such as vibration spectrum, strain value, temperature value, etc., and stores them in a database to provide data support for subsequent data analysis. Specifically, the CEEMD decomposition (Complementary Ensemble Empirical Mode Decomposition) method can be used to separate the vibration electrical signals, and further calculate the vibration spectrum. At the same time, the strain value and temperature value are calculated, which is conducive to subsequent data analysis to determine whether to issue an early warning.

[0069] The analysis process of the vibration electrical signal is as follows: for the vibration electrical signal, the CEEMD decomposition method is used to decompose the vibration electrical signal. The decomposition process can be completed using the MATLAB tool to obtain a series of intrinsic mode function (IMF) components, as shown in the following formula (1):

[0070]

[0071] In formula (1), X a (t) is the vibration electrical signal at time t; K is the total number of natural mode function components; I k (t) is X a (t) is the kth intrinsic mode function component of time t; R(t) is the remainder at time t.

[0072] After the decomposition is completed by formula (1), the first 10 intrinsic modal function components (other values can also be selected according to requirements) are selected, and the variance contribution rate and correlation coefficient corresponding to each of the first 10 intrinsic modal function components are calculated. The variance contribution rate is the ratio of the variance of the intrinsic modal function component to the variance of the vibration electrical signal, and the correlation coefficient is the correlation coefficient between the intrinsic modal function component and the vibration electrical signal, which characterizes the degree of correlation between the intrinsic modal function component and the vibration electrical signal. Among the first 10 intrinsic modal function components, the intrinsic modal function components with relatively large variance contribution rates and correlation coefficients are selected as effective vibration components. Specifically, the weighted sum of the variance contribution rate and correlation coefficient corresponding to each of the first 10 intrinsic modal function components can be calculated, and the first 10 intrinsic modal function components are sorted in descending order of the weighted sum. The intrinsic modal function components ranked in the first m positions (m is less than 10) are selected as vibration components, and the maximum frequency and amplitude at the maximum frequency of each vibration component are counted to obtain the frequency and amplitude corresponding to the vibration component.

[0073] At this time, in this embodiment, the signal acquisition and processing module includes a fiber optic demodulation system and a processor, and the processor is an embedded system or an industrial computer.

[0074] The optical fiber demodulation system is communicatively connected to the optical fiber sensing module. The optical fiber demodulation system is used to convert the vibration optical signal of the bearing, the strain optical signal of the bearing, the temperature optical signal of the bearing, the vibration optical signal of the tread and the strain optical signal of the rim into the vibration electrical signal of the bearing, the strain electrical signal of the bearing, the temperature electrical signal of the bearing, the vibration electrical signal of the tread and the strain electrical signal of the rim.

[0075] The processor is communicatively connected to the optical fiber demodulation system, and is used to process the vibration electrical signal of the bearing, the strain electrical signal of the bearing, the temperature electrical signal of the bearing, the vibration electrical signal of the tread, and the strain electrical signal of the rim, to obtain the frequency and amplitude corresponding to the vibration component of the bearing, the strain value of the bearing, the temperature value of the bearing, the amplitude corresponding to the vibration component of the tread, and the strain value of the rim.

[0076] The method for determining the frequency and amplitude corresponding to the vibration component of the bearing includes: performing CEEMD decomposition on the vibration electrical signal of the bearing to obtain multiple intrinsic modal function components of the bearing (all intrinsic modal function components obtained by decomposition can be used, or the first few intrinsic modal function components among all intrinsic modal function components obtained by decomposition can be used), calculating the variance contribution rate and correlation coefficient corresponding to each intrinsic modal function component of the bearing, screening the multiple intrinsic modal function components of the bearing based on the variance contribution rate and correlation coefficient to obtain the vibration component of the bearing, and selecting the maximum frequency and amplitude at the maximum frequency in the vibration component of the bearing as the frequency and amplitude corresponding to the vibration component of the bearing. The variance contribution rate is the ratio of the variance of the intrinsic modal function component to the variance of the vibration electrical signal, and the correlation coefficient is the correlation coefficient between the intrinsic modal function component and the vibration electrical signal.

[0077] The method for determining the strain value of the bearing includes: determining the strain value of the bearing based on the strain electrical signal of the bearing.

[0078] The method for determining the temperature value of the bearing includes: determining the temperature value of the bearing based on a temperature electrical signal of the bearing.

[0079] Among them, the method for determining the amplitude corresponding to the vibration component of the tread includes: performing CEEMD decomposition on the vibration electrical signal of the tread to obtain multiple intrinsic modal function components of the tread (all the intrinsic modal function components obtained by decomposition can be used, or the first few intrinsic modal function components of all the intrinsic modal function components obtained by decomposition can be used), calculating the variance contribution rate and correlation coefficient corresponding to each intrinsic modal function component of the tread, screening the multiple intrinsic modal function components of the tread based on the variance contribution rate and correlation coefficient to obtain the vibration component of the tread, and selecting the amplitude at the maximum frequency in the vibration component of the tread as the amplitude corresponding to the vibration component of the tread.

[0080] The method for determining the strain value of the wheel rim includes: determining the strain value of the wheel rim based on the strain electrical signal of the wheel rim.

[0081] In this embodiment, the signal acquisition and processing module further includes an industrial cabinet, and the optical fiber demodulation system and the processor are both installed in the industrial cabinet.

[0082] (3) Monitoring and early warning module

[0083] The monitoring and early warning module of this embodiment receives monitoring data from the signal acquisition and processing module (i.e., the frequency and amplitude corresponding to the vibration component of the bearing, the strain value of the bearing, the temperature value of the bearing, the amplitude corresponding to the vibration component of the tread, and the strain value of the rim), and stores, analyzes and displays the monitoring data, provides early warning of possible hidden dangers and abnormal situations, and displays specific abnormal data (such as bearing failure, rim failure, bearing damage, or rim damage) and maintenance suggestions on a visual interface, so that maintenance personnel can take corresponding maintenance measures in a timely manner.

[0084] (1) Monitoring data analysis

[0085] This embodiment performs multi-physical quantity fusion diagnostic analysis based on monitoring data.

[0086] 1) Vibration

[0087] like Figure 3 As shown, for the frequencies and amplitudes corresponding to the vibration components of the bearing, this embodiment calculates the outer ring fault characteristic frequency, inner ring fault characteristic frequency, and rolling element fault characteristic frequency of the bearing based on the bearing theoretical fault characteristic frequency calculation formula, as shown in the following formulas (2) to (5):

[0088]

[0089] In the above formula, f r ,f0,f i 、f b They are respectively the rotation frequency of the rolling bearing, the characteristic frequency of the outer ring fault, the characteristic frequency of the inner ring fault, and the characteristic frequency of the rolling element fault; n is the fixed speed of the rolling bearing; N is the number of rolling elements in the rolling bearing; d is the diameter of the rolling element in the rolling bearing; D is the bearing pitch diameter of the rolling bearing (the diameter of the circle formed by the center points of the rolling elements under the ideal operating state of the bearing); α is the contact angle of the rolling bearing.

[0090] The frequency corresponding to the bearing vibration component is compared with the theoretical frequency (i.e., the outer race fault characteristic frequency, inner race fault characteristic frequency, and rolling element fault characteristic frequency of the bearing). Specifically, when the absolute value of the error percentage between the frequency corresponding to the bearing vibration component and the outer race fault characteristic frequency of the bearing is less than a preset error percentage (e.g., 5%), the bearing vibration component is determined to be a first vibration component. When the absolute value of the error percentage between the frequency corresponding to the bearing vibration component and the inner race fault characteristic frequency of the bearing is less than the preset error percentage, the bearing vibration component is determined to be a second vibration component. When the absolute value of the error percentage between the frequency corresponding to the bearing vibration component and the rolling element fault characteristic frequency of the bearing is less than the preset error percentage, the bearing vibration component is determined to be a third vibration component. The error percentage is the ratio of the difference between the frequency corresponding to the bearing vibration component and the theoretical frequency to the theoretical frequency, i.e., error percentage = (frequency corresponding to the bearing vibration component - theoretical frequency) / theoretical frequency * 100%.

[0091] 2) Strain

[0092] like Figure 4 As shown, this embodiment can process the strain value. Specifically, the quadratic exponential function in the CFTOOL toolbox of Matlab is used to perform online correction of the strain value to ensure the reliability of the strain value. Subsequently, fault diagnosis is performed based on the strain value after online correction. The quadratic exponential function is as follows (6):

[0093] y=a×e bx +c×e dx (6)

[0094] In formula (6), y is the strain data; a, b, c, and d are all parameters of the quadratic exponential function; and x is the number of acquisitions.

[0095] Based on the above formula (6), a relationship curve between strain data and acquisition times can be drawn. If the strain value is on the relationship curve, no correction is required. If the strain value is not on the relationship curve, the strain value is replaced by the strain data on the relationship curve to perform online correction on the strain value.

[0096] This embodiment can also record the initial strain value according to the no-load state of the metallurgical crane. The method for determining the initial strain value is as follows: when the metallurgical crane is no-loaded three times, the average value of the three strain values of the strain optical fiber sensor is recorded, and this average value is used as the initial strain value. Subsequently, the strain value is subtracted from the initial strain value to perform zero-point correction on the strain value, and then the strain value after zero-point correction is online corrected using the above formula (6).

[0097] Based on the strain value collected by the strain fiber optic sensor, the stress value can be further calculated. After removing the invalid stress value, the stress spectrum data is obtained. Combined with the material S-N curve, rain flow analysis and Miner's cumulative damage law, the remaining service life of the wheel can be dynamically corrected.

[0098] 3) Temperature

[0099] like Figure 5 As shown, the temperature change value (ie, the difference between the temperature value at the current moment and the temperature value at the previous moment) is calculated to perform temperature gradient analysis.

[0100] (2) Real-time fault warning

[0101] When an abnormality is detected, such as abnormal temperature, abnormal vibration, abnormal strain, or stress exceeding the allowable range, an early warning is triggered and an alarm message is automatically issued. Specific abnormal data and maintenance suggestions can be displayed on the visual interface, making it convenient for maintenance personnel to take appropriate maintenance measures in a timely manner.

[0102] The thresholds are set as follows:

[0103] 1) Vibration threshold: When the amplitude of the vibration component is greater than the preset vibration threshold (e.g. 20dB), an alarm is issued.

[0104] 2) Strain threshold: An early warning is issued when the strain gradient (i.e., the difference between the strain value at the current moment and the strain value at the previous moment) is greater than the preset strain change threshold.

[0105] 3) Temperature threshold: When the temperature is continuously higher than the preset threshold (such as 30°C) for 5 minutes or the temperature gradient (the difference between the current temperature and the previous temperature) is greater than the preset temperature change threshold (such as 5°C / min), an alarm is issued.

[0106] 4) Stress threshold: An early warning is issued when the stress value is greater than a preset stress threshold (e.g. 80% of the material yield strength).

[0107] At this time, when diagnosing bearing faults: when f0, f i or f b When the corresponding amplitude is greater than the first preset vibration threshold, the strain gradient is greater than the first preset strain change threshold, and the temperature gradient is greater than the preset temperature change threshold, it is determined that the bearing has a fault. At the same time, with the help of the theoretical frequency, it is preliminarily determined that it is an outer ring fault, an inner ring fault, or a rolling element fault. Specifically, when the amplitude corresponding to f0 is greater than the first preset vibration threshold, the outer ring is faulty. When f i The corresponding amplitude is greater than the first preset vibration threshold, then the inner ring is faulty. b The corresponding amplitude is greater than the first preset vibration threshold, then the rolling element fails. Specifically, when f iIf the corresponding amplitude is greater than 20 dB and the temperature gradient is greater than 8°C / min, the inner ring is judged to be peeling (confidence>90%).

[0108] When diagnosing a wheel rim fault, if the amplitude corresponding to a vibration component exceeds a second preset vibration threshold and the strain gradient exceeds a second preset strain change threshold, the wheel rim is determined to be faulty and to have a local defect. It should be noted that if there are multiple vibration components, and the amplitude corresponding to any one of them exceeds the second preset vibration threshold, the vibration component is considered to have an amplitude greater than the second preset vibration threshold.

[0109] The monitoring and early warning module of this embodiment features a visual interface that intuitively displays various wheel monitoring data and abnormality data, making it easy for operators to observe and manage the system. This visual display also enables remote monitoring, allowing managers to view wheel monitoring data, abnormality data, and other status information from anywhere with an internet connection. Once an abnormality is detected, an audible and visual alarm sounds an alarm, and the visual interface displays specific abnormality data and repair recommendations, allowing maintenance personnel to take timely and appropriate repair measures.

[0110] In this embodiment, the multi-parameter monitoring system for metallurgical crane wheels further includes a monitoring and early warning module, which is communicatively connected to the processor in the signal acquisition and processing module. The monitoring and early warning module is configured to determine whether a bearing or rim failure has occurred based on the frequency and amplitude corresponding to the bearing's vibration component, the bearing's strain value, the bearing's temperature value, the amplitude corresponding to the tread's vibration component, and the rim's strain value, and to issue a bearing failure early warning signal if a bearing failure occurs, and to issue a rim failure early warning signal if a rim failure occurs.

[0111] Wherein, based on the frequency and amplitude corresponding to the vibration component of the bearing, the strain value of the bearing, the temperature value of the bearing, the amplitude corresponding to the vibration component of the tread and the strain value of the rim, it is determined whether the bearing and the rim are faulty, and a bearing fault warning signal is issued when the bearing fails, and a rim fault warning signal is issued when the rim fails. The monitoring and warning module is used to determine the vibration component of the bearing as a first vibration component when the absolute value of the error percentage between the frequency corresponding to the vibration component of the bearing and the characteristic frequency of the outer ring fault of the bearing is less than a preset error percentage, determine the vibration component of the bearing as a second vibration component when the absolute value of the error percentage between the frequency corresponding to the vibration component of the bearing and the characteristic frequency of the inner ring fault of the bearing is less than a preset error percentage, and determine the vibration component of the bearing as a second vibration component when the absolute value of the error percentage between the frequency corresponding to the vibration component of the bearing and the characteristic frequency of the rolling element fault of the bearing is less than a preset error percentage. When the difference percentage is greater than the first preset vibration threshold, the vibration component of the bearing is determined to be the third vibration component. When the amplitude corresponding to the first vibration component, the amplitude corresponding to the second vibration component or the amplitude corresponding to the third vibration component is greater than the first preset vibration threshold, the change value of the strain value of the bearing (that is, the difference between the strain value of the bearing at the current moment and the strain value of the bearing at the previous moment) is greater than the first preset strain change threshold, and the change value of the temperature value of the bearing (that is, the difference between the temperature value of the bearing at the current moment and the temperature value of the bearing at the previous moment) is greater than the preset temperature change threshold, it is determined that the bearing has failed and a bearing failure warning signal is issued. When the amplitude corresponding to the vibration component of the tread is greater than the second preset vibration threshold and the change value of the strain value of the rim (that is, the difference between the strain value of the rim at the current moment and the strain value of the rim at the previous moment) is greater than the second preset strain change threshold, it is determined that the rim has failed and a rim failure warning signal is issued.

[0112] The monitoring and early warning module of this embodiment is also used to calculate the stress value of the bearing based on the strain value of the bearing. When the stress value of the bearing is greater than a first preset stress threshold, the bearing is determined to be damaged and a bearing damage early warning signal is issued. The stress value of the rim is calculated based on the strain value of the rim. When the stress value of the rim is greater than a second preset stress threshold, the rim is determined to be damaged and a rim damage early warning signal is issued.

[0113] This embodiment analyzes the vibration, strain, temperature, stress and other data of the bearing according to preset thresholds to determine whether the bearing is in a normal state. It also analyzes the vibration, strain, stress and other data of the rim according to preset thresholds to determine whether the rim is in a normal state, so as to evaluate the wheel status. When an abnormality is detected, an alarm message is issued to trigger a graded warning (if it is a bearing fault warning signal or a rim fault warning signal, a yellow warning is triggered to prompt maintenance; if it is a bearing damage warning signal or a rim damage warning signal, a red warning is triggered to force shutdown). It can also give corresponding maintenance suggestions based on different abnormal data, making it convenient for maintenance personnel to take targeted maintenance measures.

[0114] (4) Data transmission module

[0115] The data transmission module of this embodiment adopts both wired and wireless transmission methods. Wired transmission uses communication protocols such as Ethernet and RS485 to ensure data transmission stability and high bandwidth. Wired transmission is used between the fiber optic sensing module and the signal acquisition and processing module. The reason for using wired transmission is that the signal acquisition and processing module is located near the metallurgical crane and is subject to interference from the metallurgical crane's environment. Therefore, wired transmission can avoid interference from the metallurgical crane's environment on the transmitted data and improve transmission reliability. Wireless transmission uses communication technologies such as 5G, Wi-Fi, and ZigBee to facilitate flexible system deployment and remote monitoring, ensuring low latency and reliability during the transmission process. Wireless transmission is used between the signal acquisition and processing module and the monitoring and early warning module. Of course, wired transmission can also be used between the signal acquisition and processing module and the monitoring and early warning module. When wired transmission is used, data is transmitted to the monitoring and early warning module via an Ethernet or RS485 interface. When wireless transmission is used, data is transmitted to the monitoring and early warning module via 5G, Wi-Fi, or ZigBee, and the monitoring and early warning module receives the data through a corresponding wireless receiving module.

[0116] In this embodiment, the multi-parameter monitoring system for a metallurgical crane wheel further includes a data transmission module, which is communicatively connected to the fiber optic sensing module, the signal acquisition and processing module, and the monitoring and early warning module. The data transmission module includes a first transmission unit and a second transmission unit. The first transmission unit is configured to transmit the bearing vibration optical signal, the bearing strain optical signal, the bearing temperature optical signal, the tread vibration optical signal, and the rim strain optical signal obtained by the fiber optic sensing module to the signal acquisition and processing module via wired transmission. The second transmission unit is configured to transmit the frequency and amplitude corresponding to the bearing vibration component, the bearing strain value, the bearing temperature value, the amplitude corresponding to the tread vibration component, and the rim strain value obtained by the signal acquisition and processing module to the monitoring and early warning module via wired or wireless transmission.

[0117] This embodiment provides a multi-parameter monitoring system for metallurgical crane wheels based on fiber optic sensing technology. It can perform real-time and accurate monitoring of the vibration, strain, and temperature status of the wheels, addressing the reliability issues of traditional monitoring methods in harsh environments. It can achieve real-time, multi-parameter, high-precision monitoring of the wheel health status, as well as intelligent diagnosis and fault warning.

[0118] This embodiment has the following advantages:

[0119] (1) Real-time monitoring: It can obtain the status information of the wheel in real time, promptly discover potential safety hazards during the operation of the wheel, and avoid unexpected shutdowns and safety accidents caused by wheel failure.

[0120] (2) High precision: Through the high-precision and high-sensitivity real-time perception of the optical fiber sensor, various status parameters of the wheel are accurately monitored to ensure the accuracy of the monitoring data.

[0121] (3) Strong anti-interference ability: Fiber optic sensors are not affected by electromagnetic interference and can work stably in places with complex electromagnetic environments such as metallurgy, ensuring the reliability of the monitoring system.

[0122] (4) Remote monitoring: It is convenient for management personnel to conduct remote operation and management and timely understand the status of the wheels of the metallurgical crane.

[0123] This embodiment discloses a multi-parameter monitoring system for metallurgical crane wheels based on fiber optic sensing technology. Multiple fiber optic sensors are arranged at key locations on the wheels to convert multi-physical quantity information such as wheel vibration, strain, and temperature into optical signals. These signals are then converted into electrical signals by a signal acquisition and processing module, and characteristic parameters are extracted. These characteristic parameters are then transmitted to a monitoring and early warning module via a data transmission module. The monitoring and early warning module stores, analyzes, and displays the characteristic parameters, and issues alarms and maintenance recommendations when an anomaly occurs. This system implements real-time, high-precision, and interference-resistant status monitoring of the metallurgical crane wheels, ensuring the safe and efficient operation of the metallurgical crane.

[0124] Example 2

[0125] This embodiment provides a multi-parameter monitoring method for metallurgical crane wheels, which is applied to the multi-parameter monitoring system for metallurgical crane wheels described in Example 1. Figure 6 As shown, the multi-parameter monitoring method for metallurgical crane wheels includes:

[0126] S1: The optical fiber demodulation system converts the bearing vibration optical signal, bearing strain optical signal, bearing temperature optical signal, tread vibration optical signal and rim strain optical signal into bearing vibration electrical signal, bearing strain electrical signal, bearing temperature electrical signal, tread vibration electrical signal and rim strain electrical signal respectively.

[0127] S2: The processor processes the vibration electrical signal of the bearing, the strain electrical signal of the bearing, the temperature electrical signal of the bearing, the vibration electrical signal of the tread, and the strain electrical signal of the rim to obtain the frequency and amplitude corresponding to the vibration component of the bearing, the strain value of the bearing, the temperature value of the bearing, the amplitude corresponding to the vibration component of the tread, and the strain value of the rim.

[0128] S3: The monitoring and early warning module determines whether the bearing and the rim are faulty based on the frequency and amplitude corresponding to the vibration component of the bearing, the strain value of the bearing, the temperature value of the bearing, the amplitude corresponding to the vibration component of the tread and the strain value of the rim, and issues a bearing fault early warning signal when the bearing fails, and issues a rim fault early warning signal when the rim fails.

[0129] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0130] This document uses specific examples to illustrate the principles and implementation methods of this application. The description of the above examples is only intended to help understand the method and core concept of this application. At the same time, for those skilled in the art, based on the concept of this application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A multi-parameter monitoring system for metallurgical crane wheels, characterized in that: The multi-parameter monitoring system for wheels of metallurgical cranes includes: an optical fiber sensing module and a signal acquisition and processing module; The optical fiber sensing module includes: a first vibration optical fiber sensor, a first strain optical fiber sensor, a temperature optical fiber sensor, a second vibration optical fiber sensor and a second strain optical fiber sensor; The first vibration optical fiber sensor, the first strain optical fiber sensor, and the temperature optical fiber sensor are all installed on the bearing of the metallurgical crane wheel. The first vibration optical fiber sensor is used to collect the vibration optical signal of the bearing, the first strain optical fiber sensor is used to collect the strain optical signal of the bearing, and the temperature optical fiber sensor is used to collect the temperature optical signal of the bearing. The second vibration optical fiber sensor is installed on the track on which the wheel of the metallurgical crane passes, and is used to collect the vibration optical signal of the tread of the wheel of the metallurgical crane; the second strain optical fiber sensor is installed on the rim of the wheel of the metallurgical crane, and is used to collect the strain optical signal of the rim; The signal acquisition and processing module is communicatively connected to the optical fiber sensing module; the signal acquisition and processing module is used to convert the vibration optical signal of the bearing, the strain optical signal of the bearing, the temperature optical signal of the bearing, the vibration optical signal of the tread and the strain optical signal of the rim into the vibration electrical signal of the bearing, the strain electrical signal of the bearing, the temperature electrical signal of the bearing, the vibration electrical signal of the tread and the strain electrical signal of the rim, respectively, so as to monitor the vibration, strain and temperature of the bearing, the vibration of the tread and the strain of the rim.

2. The metallurgical crane wheel multi-parameter monitoring system according to claim 1 is characterized in that: The first vibration optical fiber sensor and the second vibration optical fiber sensor are both distributed optical fiber sensors, the first vibration optical fiber sensor is spirally wound on the outer surface of the bearing seat of the bearing, and the second vibration optical fiber sensor is arranged along the track; The first strain optical fiber sensor and the second strain optical fiber sensor both adopt fiber grating array sensors. The first strain optical fiber sensor is welded on the outer ring of the bearing, and the second strain optical fiber sensor is bonded to the wheel rim. The temperature optical fiber sensor adopts a fiber grating sensor and is installed on the surface of the outer ring of the bearing.

3. The multi-parameter monitoring system for metallurgical crane wheels according to claim 2 is characterized in that: The surface of the first vibration optical fiber sensor is coated with a polyimide-silicon carbide composite layer, the first strain optical fiber sensor is packaged with a nickel alloy, the first strain optical fiber sensor is uniformly welded to the surface of the outer ring of the bearing along the circumference of the outer ring of the bearing, the surface of the second strain optical fiber sensor is coated with a ceramic coating, and the second strain optical fiber sensor is bonded to the surface of the wheel rim by glue.

4. The metallurgical crane wheel multi-parameter monitoring system according to claim 1 is characterized in that: The signal acquisition and processing module includes an optical fiber demodulation system and a processor, and the processor is an embedded system or an industrial computer; The optical fiber demodulation system is communicatively connected to the optical fiber sensing module; the optical fiber demodulation system is used to convert the vibration optical signal of the bearing, the strain optical signal of the bearing, the temperature optical signal of the bearing, the vibration optical signal of the tread, and the strain optical signal of the rim into the vibration electrical signal of the bearing, the strain electrical signal of the bearing, the temperature electrical signal of the bearing, the vibration electrical signal of the tread, and the strain electrical signal of the rim; The processor is communicatively connected to the optical fiber demodulation system; the processor is used to process the vibration electrical signal of the bearing, the strain electrical signal of the bearing, the temperature electrical signal of the bearing, the vibration electrical signal of the tread, and the strain electrical signal of the rim, to obtain the frequency and amplitude corresponding to the vibration component of the bearing, the strain value of the bearing, the temperature value of the bearing, the amplitude corresponding to the vibration component of the tread, and the strain value of the rim.

5. The metallurgical crane wheel multi-parameter monitoring system according to claim 4 is characterized in that: The method for determining the frequency and amplitude corresponding to the vibration component of the bearing includes: performing CEEMD decomposition on the vibration electrical signal of the bearing to obtain multiple inherent modal function components of the bearing, calculating the variance contribution rate and correlation coefficient corresponding to each inherent modal function component of the bearing, screening the multiple inherent modal function components of the bearing based on the variance contribution rate and the correlation coefficient to obtain the vibration component of the bearing, and selecting the maximum frequency and the amplitude at the maximum frequency in the vibration component of the bearing as the frequency and amplitude corresponding to the vibration component of the bearing; wherein the variance contribution rate is the ratio of the variance of the inherent modal function component to the variance of the vibration electrical signal, and the correlation coefficient is the correlation coefficient between the inherent modal function component and the vibration electrical signal; The method for determining the strain value of the bearing includes: determining the strain value of the bearing based on the strain electrical signal of the bearing; The method for determining the temperature value of the bearing includes: determining the temperature value of the bearing based on the temperature electrical signal of the bearing; The method for determining the amplitude corresponding to the vibration component of the tread includes: performing CEEMD decomposition on the vibration electrical signal of the tread to obtain multiple intrinsic modal function components of the tread, calculating the variance contribution rate and correlation coefficient corresponding to each intrinsic modal function component of the tread, screening the multiple intrinsic modal function components of the tread based on the variance contribution rate and the correlation coefficient to obtain the vibration component of the tread, and selecting the amplitude at the maximum frequency in the vibration component of the tread as the amplitude corresponding to the vibration component of the tread; The method for determining the strain value of the wheel rim includes: determining the strain value of the wheel rim based on a strain electrical signal of the wheel rim.

6. The metallurgical crane wheel multi-parameter monitoring system according to claim 4 is characterized in that: The multi-parameter monitoring system for wheels of metallurgical cranes further includes: a monitoring and early warning module, the monitoring and early warning module being communicatively connected to the processor in the signal acquisition and processing module; The monitoring and early warning module is used to determine whether the bearing and the rim are faulty based on the frequency and amplitude corresponding to the vibration component of the bearing, the strain value of the bearing, the temperature value of the bearing, the amplitude corresponding to the vibration component of the tread and the strain value of the rim, and to issue a bearing fault early warning signal when the bearing fails, and to issue a rim fault early warning signal when the rim fails.

7. The metallurgical crane wheel multi-parameter monitoring system according to claim 6, characterized in that: Based on the frequency and amplitude corresponding to the vibration component of the bearing, the strain value of the bearing, the temperature value of the bearing, the amplitude corresponding to the vibration component of the tread and the strain value of the rim, it is determined whether the bearing and the rim are faulty, and a bearing fault warning signal is issued when the bearing fails, and a rim fault warning signal is issued when the rim fails. The monitoring and warning module is used to determine the vibration component of the bearing as a first vibration component when the absolute value of the error percentage between the frequency corresponding to the vibration component of the bearing and the characteristic frequency of the outer ring fault of the bearing is less than a preset error percentage, and to determine the vibration component of the bearing as a second vibration component when the absolute value of the error percentage between the frequency corresponding to the vibration component of the bearing and the characteristic frequency of the inner ring fault of the bearing is less than a preset error percentage, and to determine the vibration component of the bearing as a second vibration component when the absolute value of the error percentage between the frequency corresponding to the vibration component of the bearing and the characteristic frequency of the inner ring fault of the bearing is less than a preset error percentage. When the absolute value of the error percentage between the frequency corresponding to the vibration component and the rolling element fault characteristic frequency of the bearing is less than the preset error percentage, the vibration component of the bearing is determined to be the third vibration component; when the amplitude corresponding to the first vibration component, the amplitude corresponding to the second vibration component or the amplitude corresponding to the third vibration component is greater than the first preset vibration threshold, the change value of the strain value of the bearing is greater than the first preset strain change threshold, and the change value of the temperature value of the bearing is greater than the preset temperature change threshold, it is determined that the bearing has failed and a bearing failure warning signal is issued; when the amplitude corresponding to the vibration component of the tread is greater than the second preset vibration threshold and the change value of the strain value of the rim is greater than the second preset strain change threshold, it is determined that the rim has failed and a rim failure warning signal is issued.

8. The metallurgical crane wheel multi-parameter monitoring system according to claim 6, characterized in that: The metallurgical crane wheel multi-parameter monitoring system further includes: a data transmission module, the data transmission module being communicatively connected to the optical fiber sensing module, the signal acquisition and processing module, and the monitoring and early warning module respectively; The data transmission module includes a first transmission unit and a second transmission unit. The first transmission unit is used to transmit the vibration light signal of the bearing, the strain light signal of the bearing, the temperature light signal of the bearing, the vibration light signal of the tread, and the strain light signal of the rim obtained by the optical fiber sensing module to the signal acquisition and processing module through wired transmission. The second transmission unit is used to transmit the frequency and amplitude corresponding to the vibration component of the bearing, the strain value of the bearing, the temperature value of the bearing, the amplitude corresponding to the vibration component of the tread, and the strain value of the rim obtained by the signal acquisition and processing module to the monitoring and early warning module through wired transmission or wireless transmission.

9. The metallurgical crane wheel multi-parameter monitoring system according to claim 6, characterized in that: The signal acquisition and processing module further comprises an industrial cabinet, in which the optical fiber demodulation system and the processor are both installed; The monitoring and early warning module is further configured to calculate a stress value of the bearing based on the strain value of the bearing. When the stress value of the bearing is greater than a first preset stress threshold, the bearing is determined to be damaged and a bearing damage early warning signal is issued. The stress value of the rim is calculated based on the strain value of the rim. When the stress value of the rim is greater than a second preset stress threshold, it is determined that the rim is damaged and a rim damage warning signal is issued.

10. A multi-parameter monitoring method for a metallurgical crane wheel, applied to the multi-parameter monitoring system for a metallurgical crane wheel according to any one of claims 1 to 9, characterized in that: The multi-parameter monitoring method for metallurgical crane wheels comprises: The optical fiber demodulation system converts the bearing vibration optical signal, the bearing strain optical signal, the bearing temperature optical signal, the tread vibration optical signal and the rim strain optical signal into the bearing vibration electrical signal, the bearing strain electrical signal, the bearing temperature electrical signal, the tread vibration electrical signal and the rim strain electrical signal respectively; The processor processes the vibration electrical signal of the bearing, the strain electrical signal of the bearing, the temperature electrical signal of the bearing, the vibration electrical signal of the tread, and the strain electrical signal of the rim to obtain the frequency and amplitude corresponding to the vibration component of the bearing, the strain value of the bearing, the temperature value of the bearing, the amplitude corresponding to the vibration component of the tread, and the strain value of the rim; The monitoring and early warning module determines whether the bearing and rim are faulty based on the frequency and amplitude corresponding to the vibration component of the bearing, the strain value of the bearing, the temperature value of the bearing, the amplitude corresponding to the vibration component of the tread and the strain value of the rim, and issues a bearing fault early warning signal when a bearing fails, and issues a rim fault early warning signal when a rim fails.

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