Lifting chain state monitoring method and system

Abstract

The invention discloses a state monitoring method and system for a lifting chain, and relates to the technical field of chain state monitoring. According to the state monitoring method for the lifting chain, the monitoring data of the chain vertical section area in the conveying equipment is obtained in real time, data analysis is conducted on the monitoring data of the chain vertical section area in the conveying equipment, the real-time state monitoring index of the chain vertical section area is obtained, and judgment and analysis are conducted; by monitoring the strain, acoustic emission, temperature and electrical impedance of the chain in real time, possible problems such as excessive wear, cracks or structural weakening of the chain can be found in time, the chain can be prevented from being suddenly broken under high load through early diagnosis, and the safety and reliability of equipment are greatly enhanced. By preventing potential equipment faults, accidental shutdown and related production loss can be avoided, so that the stability of the continuous production process is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of chain status monitoring, and in particular to a method and system for monitoring the status of a lifting chain. Background Art

[0002] In various industrial applications, lifting chains are key mechanical components and are widely used in conveying systems, lifting machinery and various other heavy equipment. The integrity and performance of the chain are crucial to the stability and efficiency of the entire system. Once the chain fails, it will not only cause production stagnation, but may also cause serious safety accidents. Therefore, it is crucial to effectively monitor and maintain the health of these chains.

[0003] Traditional chain monitoring methods mainly rely on regular physical inspections and manual visual inspections. Although these methods are simple, they have limitations such as delayed response, high resource consumption and limited accuracy.

[0004] Based on the above solution, it is found that the limitations of the existing technology include at least the following problems. First, the traditional chain monitoring method is usually limited to regular inspection of the entire chain or simple visual inspection, lacking real-time and continuous data monitoring capabilities, making it difficult to timely detect the wear, corrosion or other forms of damage that gradually develops in the actual operation of the chain, which can easily lead to sudden chain breakage or failure, thereby bringing safety risks and high costs of downtime maintenance. Secondly, the existing technology often fails to use advanced data analysis technology to predict the development trend of chain failures. The lack of in-depth data analysis makes maintenance decisions more dependent on experience judgment rather than data-driven insights, which can easily lead to premature replacement of parts or late intervention in repairs, both of which are not conducive to cost control and equipment efficiency. Thirdly, when dealing with chain operation problems in specific environments, such as high temperature, high humidity or corrosive media environments, the existing monitoring methods are difficult to provide sufficient data support to ensure the reliable operation of the chain, especially in environments such as waste heat boiler cleaning, where the chain is greatly affected by the environment and traditional methods are difficult to achieve accurate monitoring. Summary of the invention

[0005] In view of the deficiencies of the prior art, the present invention provides a method and system for monitoring the state of a lifting chain, which solves the problem that traditional chain monitoring methods are usually limited to regular inspections of the entire chain or simple visual inspections, lack real-time and continuous data monitoring capabilities, and thus it is difficult to timely detect the wear, corrosion or other forms of damage that gradually develops during actual operation of the chain, which can easily lead to sudden chain breakage or failure, thereby bringing safety risks and high costs for downtime and maintenance. Secondly, the prior art often fails to use advanced data analysis technology to predict the development trend of chain failures. The lack of in-depth data analysis makes maintenance decisions more dependent on experience judgment rather than data-driven insights, which can easily lead to premature replacement of components or late intervention in repairs, both of which are not conducive to cost control and equipment efficiency. Thirdly, when dealing with chain operation problems in specific environments, such as high temperature, high humidity or corrosive media environments, existing monitoring methods are difficult to provide sufficient data support to ensure the reliable operation of the chain, especially in environments such as waste heat boiler cleaning, where the chain is greatly affected by the environment and traditional methods are difficult to achieve accurate monitoring.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a method for monitoring the state of a lifting chain, comprising the following steps: real-time acquisition of monitoring data of a vertical section area of ​​a chain in a conveying device for cleaning a waste heat boiler, the monitoring data including strain data, acoustic emission data, temperature data, and electrical signal data; data analysis is performed on the monitoring data of the vertical section area of ​​the chain in the conveying device for cleaning a waste heat boiler, respectively, to obtain a real-time strain index, real-time acoustic emission index, real-time temperature index, and real-time electrical signal index of the vertical section area of ​​the chain; comprehensive analysis is performed on the real-time strain index, real-time acoustic emission index, real-time temperature index, and real-time electrical signal index of the vertical section area of ​​the chain to obtain a real-time state monitoring index of the vertical section area of ​​the chain; it is determined whether the real-time state monitoring index of the vertical section area of ​​the chain is within a preset monitoring threshold range, and if the real-time state monitoring index of the vertical section area of ​​the chain is outside the preset monitoring threshold range, a chain vertical section abnormality alarm is sent, and chain protection measures are taken.

[0007] Furthermore, the strain data specifically includes an initial length value and a real-time length value of a vertical segment area of ​​the chain, the acoustic emission data specifically includes a real-time acoustic emission value of each measuring point in the vertical segment area of ​​the chain, the temperature data specifically includes a real-time surface temperature value of each measuring point in the vertical segment area of ​​the chain, and the electrical signal data specifically includes a real-time electrical impedance feedback signal value of each measuring point in the vertical segment area of ​​the chain.

[0008] Furthermore, the specific steps for obtaining the real-time status monitoring index of the vertical section area of ​​the chain are as follows: standardize the real-time strain index, real-time acoustic emission index, real-time temperature index, and real-time electrical signal index of the vertical section area of ​​the chain respectively; comprehensively analyze the real-time strain index, real-time acoustic emission index, real-time temperature index, and real-time electrical signal index of the vertical section area of ​​the chain after standardization to obtain the real-time status monitoring index of the vertical section area of ​​the chain.

[0009] Furthermore, the specific formula for calculating the real-time status monitoring index of the vertical section area of ​​the chain is as follows: Among them, ZtJ is the real-time status monitoring index of the vertical segment area of ​​the chain, SyB′ is the real-time strain index of the vertical segment area of ​​the chain after standardization, α1 is the strain coefficient stored in the database, SsF′ is the real-time acoustic emission index of the vertical segment area of ​​the chain after standardization, α2 is the acoustic emission coefficient stored in the database, SwD′ is the real-time temperature index of the vertical segment area of ​​the chain after standardization, α3 is the temperature coefficient stored in the database, SdQ′ is the real-time electrical signal index of the vertical segment area of ​​the chain after standardization, α4 ​​is the electrical signal coefficient stored in the database, e is a natural constant, α1+α2+α3+α4=1.

[0010] Furthermore, the specific steps for obtaining the real-time strain index of the vertical segment area of ​​the chain are as follows: perform difference analysis on the initial length value and the real-time length value of the vertical segment area of ​​the chain to obtain the real-time length change value of the vertical segment area of ​​the chain; perform ratio analysis on the real-time length change value of the vertical segment area of ​​the chain and the initial length value to obtain the real-time strain index of the vertical segment area of ​​the chain, and the calculation formula is as follows: Among them, SyB is the real-time strain index of the vertical segment area of ​​the chain, SbH is the real-time length change value of the vertical segment area of ​​the chain, SsD is the real-time length value of the vertical segment area of ​​the chain, and CsD is the initial length value of the vertical segment area of ​​the chain.

[0011] Furthermore, the specific steps for obtaining the real-time acoustic emission index and real-time temperature index of the vertical section area of ​​the chain are as follows: read the real-time acoustic emission value and real-time surface temperature value of each measuring point in the vertical section area of ​​the chain; perform mean analysis on the real-time acoustic emission value of each measuring point in the vertical section area of ​​the chain in combination with the mean method to obtain the real-time acoustic emission index of the vertical section area of ​​the chain; perform mean analysis on the real-time surface temperature value of each measuring point in the vertical section area of ​​the chain in combination with the weighted mean method to obtain the real-time temperature index of the vertical section area of ​​the chain.

[0012] Furthermore, the specific formulas for calculating the real-time acoustic emission index and real-time temperature index of the vertical section of the chain are as follows: Among them, SsF is the real-time acoustic emission index of the vertical section of the chain, SfS iis the real-time acoustic emission value of the i-th measuring point in the vertical section of the chain, SwD is the real-time temperature index of the vertical section of the chain, SbW i is the real-time surface temperature value of the i-th measuring point in the vertical section of the chain, W i is the weighting coefficient of the real-time surface temperature value of the i-th measuring point in the vertical section area of ​​the chain, i=1, 2, 3, ..., i0, i0 is the number of measuring points in the vertical section area of ​​the chain.

[0013] Furthermore, the specific steps for obtaining the real-time electrical signal index of the vertical section area of ​​the chain are as follows: read and preprocess the real-time electrical impedance feedback signal value of each measuring point in the vertical section area of ​​the chain; combine the moving exponential averaging method to conduct a comprehensive analysis of the real-time electrical impedance feedback signal value of each measuring point in the vertical section area of ​​the chain after preprocessing to obtain the real-time electrical signal index of the vertical section area of ​​the chain.

[0014] Furthermore, the specific formula for calculating the real-time electrical signal index of the vertical section area of ​​the chain is as follows: Among them, SdQ is the real-time electrical signal indicator of the vertical section of the chain, SdF i is the real-time electrical impedance feedback signal value of the ith measurement point in the vertical section of the chain, ξ i1 is the weight coefficient of the real-time electrical impedance feedback signal value of the i-th measurement point in the vertical section of the chain, SdF i+1 is the real-time electrical impedance feedback signal value of the i+1th measurement point in the vertical section of the chain, ξ i2 is the weight coefficient of the real-time electrical impedance feedback signal value of the i+1th measurement point in the vertical section of the chain, ξ i1 +ξ i2 =1, i=1, 2, 3, …, i0, i0 is the number of measuring points in the vertical section area of ​​the chain.

[0015] A state monitoring system for a lifting chain comprises: a data acquisition module, a calculation module, a comprehensive analysis module, and an abnormality monitoring module; the data acquisition module is used to acquire in real time the monitoring data of a vertical section area of ​​a chain in a conveying device for cleaning a waste heat boiler, the monitoring data comprising strain data, acoustic emission data, temperature data, and electrical signal data; the calculation module is used to respectively perform data analysis on the monitoring data of the vertical section area of ​​the chain in the conveying device for cleaning a waste heat boiler, and obtain the real-time strain index, real-time acoustic emission index, real-time temperature index, and real-time electrical signal index of the vertical section area of ​​the chain; the comprehensive analysis module is used to perform comprehensive analysis on the real-time strain index, real-time acoustic emission index, real-time temperature index, and real-time electrical signal index of the vertical section area of ​​the chain, and obtain the real-time state monitoring index of the vertical section area of ​​the chain; the abnormality monitoring module is used to determine whether the real-time state monitoring index of the vertical section area of ​​the chain is within a preset monitoring threshold range, and if the real-time state monitoring index of the vertical section area of ​​the chain is outside the preset monitoring threshold range, a vertical section abnormality alarm of the chain is sent, and chain protection measures are taken.

[0016] The present invention has the following beneficial effects:

[0017] (1) The condition monitoring method of the lifting chain can immediately detect possible problems of the chain, such as excessive wear, cracks or structural weakening, by real-time monitoring of the chain's strain, acoustic emission, temperature and electrical impedance. This early diagnosis can prevent the chain from suddenly breaking under high load, greatly enhancing the safety and reliability of the equipment. By preventing potential equipment failures, unexpected downtime and related production losses can be avoided, thereby ensuring the stability of the continuous production process.

[0018] (2) The condition monitoring method of the lifting chain allows condition-based maintenance rather than periodic maintenance through real-time and continuous condition monitoring, which means that maintenance activities can be carried out only when they are really needed, avoiding unnecessary maintenance work and costs. In addition, accurate fault prediction can reduce the premature replacement of parts, extend the service life of the equipment, and reduce spare parts inventory costs. In the long run, this strategy can significantly reduce maintenance costs and improve the overall economic efficiency of the equipment.

[0019] (3) The condition monitoring method of the lifting chain can issue abnormal alarms in a timely manner through comprehensive monitoring indicators, so that the relevant maintenance team can respond quickly and conduct targeted fault diagnosis and repair. This rapid response can effectively reduce equipment downtime and increase production efficiency. At the same time, this monitoring method can also help maintenance personnel determine the most appropriate repair time and method, avoiding emergency and expensive maintenance during peak production periods, thereby optimizing overall operational management.

[0020] (4) The condition monitoring system of the lifting chain provides real-time and accurate monitoring results through the joint work of various modules in the system. This comprehensive data analysis capability enables management to make more accurate operation and maintenance decisions based on comprehensive and real-time data insights. For example, by continuously tracking the strain, temperature, acoustic emission and electrical signals of the chain, the management team can optimize maintenance plans, arrange production plans reasonably, and avoid production delays caused by equipment failures. In addition, this data-driven decision-making process helps to improve resource allocation, enhance equipment operating efficiency and production quality, thereby bringing greater competitive advantages and market response speed to the enterprise.

[0021] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 The present invention is a flow chart of a method for monitoring the state of a lifting chain.

[0023] Figure 2 This is a schematic diagram of the structure of the conveying equipment for waste heat boiler ash removal.

[0024] Figure 3 This is a schematic diagram of the side structure of the conveying equipment for cleaning the waste heat boiler.

[0025] Figure 4 The present invention is a flowchart of the specific steps for obtaining real-time status monitoring indicators of a vertical section of a chain in a status monitoring method for a lifting chain.

[0026] Figure 5 The present invention is a block diagram of a state monitoring system for a lifting chain.

[0027] In the figure: 1. Waste heat boiler mounting frame; 2. Waste heat boiler; 3. Vertical section chain break protection device. DETAILED DESCRIPTION

[0028] The embodiment of the present application solves the problem that traditional chain monitoring methods are usually limited to regular inspections of the entire chain or simple visual inspections, lacking real-time and continuous data monitoring capabilities, making it difficult to timely detect the wear, corrosion or other forms of damage that gradually develops during actual operation of the chain, which can easily lead to sudden chain breakage or failure, thereby bringing safety risks and high costs for downtime and maintenance. Secondly, the existing technology often fails to use advanced data analysis technology to predict the development trend of chain failures. The lack of in-depth data analysis makes maintenance decisions more dependent on experience judgment rather than data-driven insights, which can easily lead to premature replacement of parts or late intervention in repairs, both of which are not conducive to cost control and equipment efficiency. Thirdly, when dealing with chain operation problems in specific environments, such as high temperature, high humidity or corrosive media environments, existing monitoring methods are difficult to provide sufficient data support to ensure the reliable operation of the chain, especially in environments such as waste heat boiler cleaning, where the chain is greatly affected by the environment and traditional methods are difficult to achieve accurate monitoring.

[0029] The overall idea of ​​the problem in the embodiment of this application is as follows:

[0030] First, the vertical section of the chain of the conveying equipment for waste heat boiler cleaning is monitored in real time to obtain key data including strain data, acoustic emission data, temperature data and electrical signal data. These data are the basis for evaluating the chain status and provide necessary input for further analysis. Subsequently, each type of data is analyzed separately to extract real-time strain indicators, acoustic emission indicators, temperature indicators and electrical signal indicators. This step is to convert the original monitoring data into more specific status indicators, which provides a quantitative basis for the comprehensive evaluation of the chain status. The above-mentioned extracted indicators are comprehensively analyzed to form a comprehensive chain status monitoring indicator. This comprehensive indicator is compared with the preset monitoring threshold to determine whether the chain is abnormal. If the indicator exceeds the threshold, an abnormal alarm is triggered and chain protection measures are taken for processing.

[0031] See also Figure 1The embodiment of the present invention provides a technical solution: a method for monitoring the state of a lifting chain, comprising the following steps: acquiring monitoring data of a vertical section area of ​​a chain (i.e., a lifting chain area) in a conveying device for cleaning a waste heat boiler in real time, the monitoring data including strain data, acoustic emission data, temperature data, and electrical signal data; performing data analysis on the monitoring data of the vertical section area of ​​the chain in the conveying device for cleaning a waste heat boiler, respectively, to obtain a real-time strain index, a real-time acoustic emission index, a real-time temperature index, and a real-time electrical signal index of the vertical section area of ​​the chain; performing a comprehensive analysis on the real-time strain index, the real-time acoustic emission index, the real-time temperature index, and the real-time electrical signal index of the vertical section area of ​​the chain, to obtain a real-time state monitoring index of the vertical section area of ​​the chain; determining whether the real-time state monitoring index of the vertical section area of ​​the chain is within a preset monitoring threshold range, and if the real-time state monitoring index of the vertical section area of ​​the chain is outside the preset monitoring threshold range, sending a chain vertical section abnormality alarm, and taking chain protection measures.

[0032] The strain data specifically refers to the initial length value and real-time length value of the vertical section area of ​​the chain, the acoustic emission data specifically refers to the real-time acoustic emission value of each measuring point in the vertical section area of ​​the chain, the temperature data specifically refers to the real-time surface temperature value of each measuring point in the vertical section area of ​​the chain, and the electrical signal data specifically refers to the real-time electrical impedance feedback signal value of each measuring point in the vertical section area of ​​the chain (this value is a feedback signal measured by sending a low-voltage AC signal to the chain or its components, and the frequency and amplitude of this signal should be designed to be parameters that do not affect the normal operation of the chain).

[0033] It should be explained that the initial length is measured during chain installation or maintenance, usually recorded when not under load, and is completed using physical measuring tools such as calipers or rulers. The real-time length is obtained by continuous monitoring of the chain during operation through strain gauges. The resistance changes output by the strain gauges reflect the changes in the length of the chain. These changes are converted into length changes through dedicated reading equipment.

[0034] Real-time acoustic emission values ​​are obtained through acoustic emission sensors (acoustic emission monitoring usually captures high-frequency sound waves generated by micro-movement or fracture of materials, and acoustic emission signals are usually expressed as the frequency and sound pressure level of acoustic emission events. The acoustic emission signals captured by each sensor can be converted into electrical signals. After amplification and processing, these signals can obtain specific frequency and intensity values. In this scheme, the intensity value is selected as the acoustic emission value).

[0035] Real-time surface temperature values ​​are acquired in real time via thermocouples or infrared sensors.

[0036] The real-time electrical impedance feedback signal value is acquired in real time through the signal generator.

[0037] See also Figure 2-3The conveying equipment for cleaning the waste heat boiler includes: a waste heat boiler mounting frame 1, a waste heat boiler 2 is welded in the waste heat boiler mounting frame 1, a lifting chain is arranged on the waste heat boiler mounting frame 1, and the lifting chain is used to realize the circular transportation of steel balls, specifically, receiving the steel balls at the bottom of the waste heat boiler, and then conveying them to the top of the boiler (the steel balls hit the heating surface of the waste heat boiler through free fall, and the force of physical impact can break and remove the dust and other sediments attached to the pipeline), and collect the used steel balls for reuse, and a vertical section chain breaking protection device 3 for monitoring and protecting the lifting chain is arranged on the waste heat boiler mounting frame 1, and the vertical section chain breaking protection device 3 is installed on both sides of the waste heat boiler mounting frame, and at least three sets are installed on each side, which are installed near the top, middle and lower positions of the waste heat boiler mounting frame, including a chain breaking monitoring device and a chain breaking protection device, and the monitoring method adopted by the chain breaking monitoring device is the state monitoring method of the lifting chain, and the device composition includes a data acquisition module, a calculation module, a comprehensive analysis module, and an abnormality monitoring module.

[0038] If the real-time status monitoring index of the vertical section of the chain is outside the preset monitoring threshold range, an abnormal alarm of the vertical section of the chain is sent, and the specific process of taking chain protection measures is as follows: when the abnormal alarm of the vertical section of the chain is sent to notify the relevant staff, the DCS central control system controls the chain break protection device to work, so as to monitor in real time whether the lifting chain is broken. If the lifting chain is broken, the chain break protection device works to catch the rapidly falling chain part at the bottom of the broken part of the lifting chain, and hang the upper chain part at the broken part to prevent it from falling upside down due to gravity, thereby avoiding personnel safety problems and equipment losses caused by the rapid fall of the lifting chain components.

[0039] Specifically, Figure 4 As shown in the figure, the specific steps for obtaining the real-time status monitoring index of the vertical section area of ​​the chain are as follows: the real-time strain index, real-time acoustic emission index, real-time temperature index, and real-time electrical signal index of the vertical section area of ​​the chain are standardized respectively; the real-time strain index, real-time acoustic emission index, real-time temperature index, and real-time electrical signal index of the vertical section area of ​​the chain after the standardized processing are comprehensively analyzed to obtain the real-time status monitoring index of the vertical section area of ​​the chain.

[0040] The specific formula for calculating the real-time status monitoring index of the vertical section of the chain is as follows: Among them, ZtJ is the real-time status monitoring index of the vertical segment area of ​​the chain, SyB′ is the real-time strain index of the vertical segment area of ​​the chain after standardization, α1 is the strain coefficient stored in the database, SsF′ is the real-time acoustic emission index of the vertical segment area of ​​the chain after standardization, α2 is the acoustic emission coefficient stored in the database, SwD′ is the real-time temperature index of the vertical segment area of ​​the chain after standardization, α3 is the temperature coefficient stored in the database, SdQ′ is the real-time electrical signal index of the vertical segment area of ​​the chain after standardization, α4 ​​is the electrical signal coefficient stored in the database, e is a natural constant, α1+α2+α3+α4=1.

[0041] It needs to be explained that the specific calculation process of α1, α2, α3, and α4 in the database is: obtain the real-time strain standard index (under normal state), real-time acoustic emission standard index (under normal state), real-time temperature standard index (under normal state), and real-time electrical signal standard index (under normal state) of the vertical section area of ​​the chain after standardization, and then perform summation processing to obtain the state monitoring and value, and perform ratio analysis on the real-time strain standard index (under normal state), real-time acoustic emission standard index (under normal state), real-time temperature standard index (under normal state), and real-time electrical signal standard index (under normal state) of the vertical section area of ​​the chain after standardization with the state monitoring and value, and the ratio result is the corresponding coefficient, and the specific calculation logic of the real-time strain standard index, real-time acoustic emission standard index, real-time temperature standard index, and real-time electrical signal standard index is consistent with the logic of calculating the real-time strain index, real-time acoustic emission index, real-time temperature index, and real-time electrical signal index, and the calculation formula logic is also consistent.

[0042] In this implementation scheme, by standardizing the real-time monitoring data, the variation caused by different sensors and measurement conditions can be eliminated, so that data from different times and locations can be fairly compared. This is because the standardization process converts all data into a form relative to a predetermined standard (such as an indicator of normal status), thereby ensuring consistency between the data. This is especially important for data analysis across time periods and between different devices, and helps to identify real change trends and abnormal patterns, rather than illusions caused by measurement errors. By comparing real-time data with normal status indicators stored in the database and calculating the corresponding coefficients, the system can more accurately determine the deviation between the current state and the normal operating state. This method It can accurately locate which parameters have deviated from the normal range, allowing the system to detect potential problems earlier and intervene before the problem becomes a more serious failure. This early warning mechanism significantly improves the effectiveness of preventive maintenance and avoids costly emergency repairs. The system can dynamically adjust its monitoring thresholds and alarm conditions by continuously comparing real-time data with standard data and updating coefficients. This adaptive monitoring strategy enables the system to cope with changing operating conditions and environmental factors, ensuring that the monitoring strategy always matches the actual operating conditions of the current equipment. In addition, this dynamic adjustment also helps the system learn and adapt to new operating modes, especially after the equipment has been upgraded or repaired, or when operating conditions change.

[0043] Specifically, the specific steps for obtaining the real-time strain index of the vertical segment area of ​​the chain are as follows: perform difference analysis on the initial length value and the real-time length value of the vertical segment area of ​​the chain to obtain the real-time length change value of the vertical segment area of ​​the chain; perform ratio analysis on the real-time length change value of the vertical segment area of ​​the chain and the initial length value to obtain the real-time strain index of the vertical segment area of ​​the chain, and the calculation formula is as follows: Among them, SyB is the real-time strain index of the vertical segment area of ​​the chain, SbH is the real-time length change value of the vertical segment area of ​​the chain, SsD is the real-time length value of the vertical segment area of ​​the chain, and CsD is the initial length value of the vertical segment area of ​​the chain.

[0044] In this embodiment, by real-time monitoring of strain, the system can instantly capture the slight deformation of the chain caused by load, wear or other external factors. This deformation may be a precursor to potential future failures. For example, excessive elongation of the chain may indicate an impending break. By analyzing the real-time length changes and ratios, these problems can be identified early to achieve preventive maintenance and avoid chain intervention before undetected small problems accumulate into major failures. By comparing the real-time length with the initial length, the strain index obtained not only accurately reflects the current state of the chain, but also has a high degree of credibility because it is based on accurate data. This method eliminates the need to rely on subjective judgment, such as evaluating the health of the chain only through visual inspection. The calculated strain index provides a quantitative and objective chain health assessment, which is critical for making data-based maintenance decisions. Real-time monitoring and automated data analysis greatly improve the efficiency of monitoring and response. After capturing abnormal strain data, the system can quickly generate an alarm and guide maintenance personnel to conduct inspections and maintenance, thereby reducing interference with the production process and possible downtime. This improvement in efficiency not only reduces maintenance costs, but also increases the stability of the entire equipment operation and the continuity of production. This method provides an easy-to-implement and efficient monitoring strategy for various types of chains and similar conveying equipment through simple length measurement and strain calculation. This strategy is easily adapted to different industrial environments and can be adjusted and optimized according to specific monitoring needs and conditions, increasing the flexibility and scalability of the system. Through this monitoring and analysis method, industrial facilities can better manage and maintain key conveying equipment, ensuring that the equipment operates in the best condition while maximizing its operating life and production efficiency.

[0045] Specifically, the specific steps for obtaining the real-time acoustic emission index and real-time temperature index of the vertical section area of ​​the chain are as follows: read the real-time acoustic emission value and real-time surface temperature value of each measuring point in the vertical section area of ​​the chain; perform mean analysis on the real-time acoustic emission value of each measuring point in the vertical section area of ​​the chain in combination with the mean method to obtain the real-time acoustic emission index of the vertical section area of ​​the chain; perform mean analysis on the real-time surface temperature value of each measuring point in the vertical section area of ​​the chain in combination with the weighted mean method to obtain the real-time temperature index of the vertical section area of ​​the chain.

[0046] The specific formula for calculating the real-time acoustic emission index and real-time temperature index of the vertical section of the chain is as follows: Among them, SsF is the real-time acoustic emission index of the vertical section of the chain, SfS i is the real-time acoustic emission value of the i-th measuring point in the vertical section of the chain, SwD is the real-time temperature index of the vertical section of the chain, SbW i is the real-time surface temperature value of the i-th measuring point in the vertical section of the chain, W iis the weighting coefficient of the real-time surface temperature value of the i-th measuring point in the vertical section area of ​​the chain, i=1, 2, 3, ..., i0, i0 is the number of measuring points in the vertical section area of ​​the chain.

[0047] In this embodiment, acoustic emission monitoring is particularly suitable for detecting early micro-cracks and other structural damages that may not be easily found in traditional visual or manual inspections. By analyzing the mean of acoustic emission data in real time, structural abnormalities can be identified early, so that preventive measures can be taken to prevent further damage. Temperature monitoring can detect hot spots caused by excessive friction, insufficient lubrication or other mechanical failures early. Using weighted mean analysis of temperature data, weights can be adjusted according to the importance of different locations to more accurately reflect temperature changes in key areas. By collecting data from multiple measurement points and calculating the mean or weighted mean of these data, a more comprehensive and representative real-time monitoring indicator for the entire vertical segment can be obtained. This method reduces the impact of outliers or deviations that may occur at any single measurement point on the overall diagnosis, provides more stable and reliable data to support decision-making, simplifies complex multi-point data into a single indicator (such as acoustic emission indicators and temperature indicators), and helps standardize data processing procedures and subsequent analysis work. This simplification can speed up data processing, improve response efficiency, and enable maintenance teams to quickly understand and respond to potential problems. Systematic real-time data analysis makes maintenance decisions more scientific and accurate. Based on real-time acoustic emission and temperature indicators, maintenance teams can more accurately determine when and how to perform maintenance or repairs, thereby optimizing maintenance plans and resource allocation, reducing unnecessary maintenance costs and avoiding premature equipment replacement.

[0048] Specifically, the specific steps for obtaining the real-time electrical signal index of the vertical section area of ​​the chain are as follows: read and preprocess the real-time electrical impedance feedback signal value of each measuring point in the vertical section area of ​​the chain; combine the moving exponential averaging method to conduct a comprehensive analysis of the real-time electrical impedance feedback signal value of each measuring point in the vertical section area of ​​the chain after preprocessing to obtain the real-time electrical signal index of the vertical section area of ​​the chain.

[0049] The specific formula for calculating the real-time electrical signal index of the vertical section area of ​​the chain is as follows: Among them, SdQ is the real-time electrical signal indicator of the vertical section of the chain, SdF i is the real-time electrical impedance feedback signal value of the ith measurement point in the vertical section of the chain, ξ i1 is the weight coefficient of the real-time electrical impedance feedback signal value of the i-th measurement point in the vertical section of the chain, SdF i+1 is the real-time electrical impedance feedback signal value of the i+1th measurement point in the vertical section of the chain, ξ i2 is the weight coefficient of the real-time electrical impedance feedback signal value of the +th measurement point in the vertical section of the chain, ξi1 +ξ i2 =1, i=1, 2, 3, …, i0, i0 is the number of measuring points in the vertical section area of ​​the chain.

[0050] It needs to be explained that i1 , i2 The specific calculation process is as follows: sum and analyze the real-time electrical impedance feedback signal values ​​of the i-th and i+1-th measuring points in the vertical section of the chain to obtain the electrical impedance feedback and value of the i-th measuring point in the vertical section of the chain; then calculate the ratio of the real-time electrical impedance feedback signal values ​​of the i-th and i+1-th measuring points in the vertical section of the chain to the electrical impedance feedback and value, and the ratio result is the corresponding weight coefficient.

[0051] In this embodiment, by combining the moving exponential averaging method, the real-time electrical signal indicator can more accurately capture the slight changes in the electrical impedance of the chain, which may be caused by internal corrosion, cracks or other changes in electrical properties. The moving exponential averaging method assigns different weights to the electrical impedance of each measurement point. This weighting method takes into account that the most recent measurement results have a more significant impact on the overall trend, thereby improving the response speed and sensitivity. This method ensures that when the environment or operating conditions change, the monitoring system can quickly adapt and detect problems in a timely manner. The use of the moving exponential averaging method for data analysis can update the electrical signal indicator in real time, which can not only provide continuous monitoring output, but also dynamically reflect the latest changes in the chain status. This dynamic update mechanism makes maintenance Maintenance decisions are more timely, reducing potential risks caused by delayed responses. Through real-time analysis of electrical impedance signals, preventive maintenance work can be planned more effectively, thereby optimizing maintenance plans and resource allocation. This analysis helps the maintenance team determine the most appropriate maintenance time, reduce unnecessary maintenance activities, reduce costs and improve the overall operating efficiency of the equipment. In addition, it can predict future maintenance needs of the equipment based on the changing trend of electrical impedance, thereby achieving more efficient asset management. Continuous and precise electrical impedance monitoring helps ensure the reliability and safety of conveying equipment. Accurate electrical property monitoring can detect problems before they become serious failures, so that corresponding measures can be taken to prevent equipment failures, protect the stable operation of the production line, and avoid safety accidents caused by equipment failures.

[0052] See also Figure 5The embodiment of the present invention provides a technical solution: a state monitoring system for a lifting chain, comprising: a data acquisition module, a calculation module, a comprehensive analysis module, and an abnormality monitoring module; the data acquisition module is used to obtain real-time monitoring data of a vertical section area of ​​a chain in a conveying device for cleaning waste heat boilers, the monitoring data including strain data, acoustic emission data, temperature data, and electrical signal data; the calculation module is used to perform data analysis on the monitoring data of the vertical section area of ​​the chain in the conveying device for cleaning waste heat boilers, respectively, to obtain real-time strain indicators, real-time acoustic emission indicators, real-time temperature indicators, and real-time electrical signal indicators of the vertical section area of ​​the chain; the comprehensive analysis module is used to perform comprehensive analysis on the real-time strain indicators, real-time acoustic emission indicators, real-time temperature indicators, and real-time electrical signal indicators of the vertical section area of ​​the chain, to obtain real-time state monitoring indicators of the vertical section area of ​​the chain; the abnormality monitoring module is used to determine whether the real-time state monitoring indicators of the vertical section area of ​​the chain are within a preset monitoring threshold range, and if the real-time state monitoring indicators of the vertical section area of ​​the chain are outside the preset monitoring threshold range, a vertical section abnormality alarm of the chain is sent, and chain protection measures are taken.

[0053] In summary, this application has at least the following effects:

[0054] By monitoring the chain's strain, acoustic emission, temperature and electrical impedance in real time, it is possible to immediately detect possible problems with the chain, such as excessive wear, cracks or structural weakening. This early diagnosis can prevent the chain from breaking suddenly under high loads, greatly enhancing the safety and reliability of the equipment. By preventing potential equipment failures, unexpected downtime and related production losses can be avoided, thus ensuring the stability of the continuous production process.

[0055] Real-time and continuous condition monitoring allows condition-based maintenance rather than periodic maintenance, which means that maintenance activities can be carried out when they are really needed, avoiding unnecessary maintenance work and costs. In addition, accurate failure prediction can reduce premature replacement of parts, extend the service life of equipment, and reduce spare parts inventory costs. In the long run, this strategy can significantly reduce maintenance costs and improve the overall economic efficiency of equipment.

[0056] Through the abnormal alarms issued in a timely manner by comprehensive monitoring indicators, the relevant maintenance team can respond quickly and conduct targeted fault diagnosis and repairs. This quick response can effectively reduce equipment downtime and increase production efficiency. At the same time, this monitoring method can also help maintenance personnel determine the most appropriate repair time and method, avoiding emergency and expensive maintenance during peak production periods, thereby optimizing overall operational management.

[0057] Through the joint work of various modules in the system, real-time and accurate monitoring results are provided. This comprehensive data analysis capability enables management to make more accurate operation and maintenance decisions based on comprehensive and real-time data insights. For example, by continuously tracking the strain, temperature, acoustic emission and electrical signals of the chain, the management team can optimize maintenance plans, arrange production plans reasonably, and avoid production delays caused by equipment failure. In addition, this data-driven decision-making process helps to improve resource allocation, enhance equipment operating efficiency and production quality, thereby bringing greater competitive advantages and market response speed to enterprises.

[0058] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0059] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for monitoring the state of a lifting chain, characterized in that: The following steps are involved: Acquire real-time monitoring data of the vertical section of the chain in the conveying equipment, wherein the monitoring data includes strain data, acoustic emission data, temperature data, and electrical signal data; The monitoring data of the vertical section of the chain in the conveying equipment are analyzed separately to obtain the real-time strain index, real-time acoustic emission index, real-time temperature index, and real-time electrical signal index of the vertical section of the chain; Comprehensively analyze the real-time strain index, real-time acoustic emission index, real-time temperature index, and real-time electrical signal index of the vertical section of the chain to obtain the real-time status monitoring index of the vertical section of the chain; Determine whether the real-time status monitoring index of the vertical section area of ​​the chain is within the preset monitoring threshold range. If the real-time status monitoring index of the vertical section area of ​​the chain is outside the preset monitoring threshold range, send a chain vertical section abnormal alarm and take chain protection measures.

2. The method for monitoring the state of a lifting chain according to claim 1, characterized in that: The strain data specifically includes the initial length value and the real-time length value of the vertical section area of ​​the chain, the acoustic emission data specifically includes the real-time acoustic emission value of each measuring point in the vertical section area of ​​the chain, the temperature data specifically includes the real-time surface temperature value of each measuring point in the vertical section area of ​​the chain, and the electrical signal data specifically includes the real-time electrical impedance feedback signal value of each measuring point in the vertical section area of ​​the chain.

3. The method for monitoring the state of a lifting chain according to claim 1, characterized in that: The specific steps to obtain the real-time status monitoring indicators of the vertical section of the chain are as follows: The real-time strain index, real-time acoustic emission index, real-time temperature index and real-time electrical signal index of the vertical section of the chain are standardized respectively; The real-time strain index, real-time acoustic emission index, real-time temperature index and real-time electrical signal index of the vertical section of the chain after standardization are comprehensively analyzed to obtain the real-time status monitoring index of the vertical section of the chain.

4. The method for monitoring the state of a lifting chain according to claim 3, characterized in that: The specific formula for calculating the real-time status monitoring index of the vertical section of the chain is as follows: Among them, ZtJ is the real-time status monitoring index of the vertical segment area of ​​the chain, SyB′ is the real-time strain index of the vertical segment area of ​​the chain after standardization, α1 is the strain coefficient stored in the database, SsF′ is the real-time acoustic emission index of the vertical segment area of ​​the chain after standardization, α2 is the acoustic emission coefficient stored in the database, SwD′ is the real-time temperature index of the vertical segment area of ​​the chain after standardization, α3 is the temperature coefficient stored in the database, SdQ′ is the real-time electrical signal index of the vertical segment area of ​​the chain after standardization, α4 ​​is the electrical signal coefficient stored in the database, e is a natural constant, α1+α2+α3+α4=1.

5. The method for monitoring the state of a lifting chain according to claim 2, characterized in that: The specific steps to obtain the real-time strain index of the vertical section of the chain are as follows: Perform difference analysis on the initial length value and the real-time length value of the vertical section of the chain to obtain the real-time length change value of the vertical section of the chain; The real-time length change value of the vertical section of the chain is analyzed by ratio analysis with the initial length value to obtain the real-time strain index of the vertical section of the chain. The calculation formula is as follows: Among them, SyB is the real-time strain index of the vertical segment area of ​​the chain, SbH is the real-time length change value of the vertical segment area of ​​the chain, SsD is the real-time length value of the vertical segment area of ​​the chain, and CsD is the initial length value of the vertical segment area of ​​the chain.

6. The method for monitoring the state of a lifting chain according to claim 2, characterized in that: The specific steps to obtain the real-time acoustic emission index and real-time temperature index of the vertical section of the chain are as follows: Read the real-time acoustic emission value and real-time surface temperature value of each measuring point in the vertical section of the chain; The real-time acoustic emission value of each measuring point in the vertical section of the chain is combined with the mean method to perform mean analysis to obtain the real-time acoustic emission index of the vertical section of the chain; The real-time surface temperature value of each measuring point in the vertical section of the chain is combined with the weighted mean method to perform mean analysis to obtain the real-time temperature index of the vertical section of the chain.

7. The method for monitoring the state of a lifting chain according to claim 6, characterized in that: The specific formula for calculating the real-time acoustic emission index and real-time temperature index of the vertical section of the chain is as follows: Among them, SsF is the real-time acoustic emission index of the vertical section of the chain, SfS i is the real-time acoustic emission value of the i-th measuring point in the vertical section of the chain, SwD is the real-time temperature index of the vertical section of the chain, SbW i is the real-time surface temperature value of the i-th measuring point in the vertical section of the chain, W i is the weighting coefficient of the real-time surface temperature value of the i-th measuring point in the vertical section area of ​​the chain, i=1.2.3,…,i0, i0 is the number of measuring points in the vertical section area of ​​the chain.

8. The method for monitoring the state of a lifting chain according to claim 2, characterized in that: The specific steps to obtain the real-time electrical signal indicators of the vertical section of the chain are as follows: Read and pre-process the real-time electrical impedance feedback signal value of each measuring point in the vertical section area of ​​the chain; Combined with the moving exponential average method, the real-time electrical impedance feedback signal value of each measuring point in the vertical section of the chain after preprocessing is comprehensively analyzed to obtain the real-time electrical signal index of the vertical section of the chain.

9. The method for monitoring the state of a lifting chain according to claim 8, characterized in that: The specific formula for calculating the real-time electrical signal index of the vertical section area of ​​the chain is as follows: Among them, SdQ is the real-time electrical signal indicator of the vertical section of the chain, SdF i is the real-time electrical impedance feedback signal value of the first measurement point in the vertical section of the chain, ξ i1 is the weight coefficient of the real-time electrical impedance feedback signal value of the i-th measurement point in the vertical section of the chain, SdF i+1 is the real-time electrical impedance feedback signal value of the i+1th measurement point in the vertical section of the chain, ξ i2 is the weight coefficient of the real-time electrical impedance feedback signal value of the i+1th measurement point in the vertical section of the chain, ξ i1 +ξ i2 =1, i=1, 2, 3, …, i0, i0 is the number of measuring points in the vertical section area of ​​the chain.

10. A lifting chain status monitoring system, using the lifting chain status monitoring method according to any one of claims 1 to 9, characterized in that: include: Data acquisition module, calculation module, comprehensive analysis module, and abnormality monitoring module; The data acquisition module is used to acquire the monitoring data of the vertical section area of ​​the chain in the conveying equipment in real time, and the monitoring data includes strain data, acoustic emission data, temperature data, and electrical signal data; The calculation module is used to analyze the monitoring data of the vertical section area of ​​the chain in the conveying equipment to obtain the real-time strain index, real-time acoustic emission index, real-time temperature index, and real-time electrical signal index of the vertical section area of ​​the chain; The comprehensive analysis module is used to comprehensively analyze the real-time strain index, real-time acoustic emission index, real-time temperature index, and real-time electrical signal index of the vertical section of the chain to obtain the real-time status monitoring index of the vertical section of the chain; The abnormal monitoring module is used to determine whether the real-time status monitoring index of the vertical segment area of ​​the chain is within the preset monitoring threshold range. If the real-time status monitoring index of the vertical segment area of ​​the chain is outside the preset monitoring threshold range, a chain vertical segment abnormality alarm is sent and chain protection measures are taken.

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