A smart non-destructive monitoring device, system and method for monitoring the tension of mining hoisting wire ropes

Abstract

The present invention discloses an intelligent non-destructive monitoring device, system, and method for the tension of a hoisting wire rope used in mines. The monitoring device includes a housing formed by joining two half-shells. A passage for the hoisting wire rope is provided in the center of the housing. Permanent magnets are provided on the inner sides of the front and rear ends of the housing. A Hall sensor group is arranged in an annular manner in the middle. Magnetic field collectors are provided on both sides of the Hall sensor. The permanent magnets and magnetic field collectors are connected by an armature. The device also includes a guide wheel, a rotating encoder wheel with an encoder, a thermistor sensor, and an AC inductor coil. Each core component is composed of a half-shell assembly and is separately packaged in the two half-shells. The present invention adopts magnetic flux monitoring technology combined with a tension monitoring model to improve monitoring accuracy and anti-interference capability. It adapts to the complex environment of mining and can achieve non-destructive monitoring and dynamic alarm to ensure the safety of the hoisting system.

Description

Technical Field

[0001] This invention relates to the field of wire rope tension monitoring technology, specifically to an intelligent non-destructive monitoring device, system, and method for monitoring the tension of mining hoisting wire ropes. Background Technology

[0002] During mine hoisting, the stress on the wire rope is affected by the load weight, its own characteristics (length, diameter, wear, etc.), the operating status of the hoisting system (acceleration, drum and sheave parameters), and environmental factors (temperature, humidity, etc.). These factors intertwine, causing complex changes in tension. In severe cases, this can lead to fatigue deformation, breakage, or slippage of the wire rope. Once a wire rope breaks or slips, it can trigger a serious safety accident, resulting in damage to the mine hoisting mechanism and fatalities. To ensure production safety, wire rope tension monitoring technology has made significant progress in recent years. Among the published technologies, such as Chinese Patent CN118913520A, a pressure-side sensor force analysis system and its analysis method are disclosed. This system derives the force condition from the strain of an elastic body and calculates the force magnitude based on the resistance change of the strain gauge, thereby achieving wire rope tension monitoring. However, this system suffers from problems such as complex structure, difficult installation, and low monitoring accuracy, while also causing damage to the wire rope itself. Chinese patent CN119880228A discloses a wire rope tension monitoring method and device, which uses machine vision to collect real-time video of wire rope movement and combines it with a tension monitoring model to obtain the wire rope force. However, this device cannot adapt to the harsh operating conditions of actual wire ropes, such as insufficient lighting and the presence of oil and dust particles on the surface, resulting in low monitoring accuracy. Therefore, there is an urgent need for a monitoring technology that can be applied to the complex environment and harsh working conditions of mining hoisting systems and can accurately sense changes in wire rope tension in real time. Summary of the Invention

[0003] The purpose of this invention is to propose an intelligent non-destructive monitoring device, system, and method for monitoring the tension of steel wire ropes used in mining hoists, so as to overcome the problems of low monitoring efficiency, low monitoring accuracy, poor environmental applicability, and inability to accurately and non-destructively sense the tension of steel wire ropes in real time online in the existing technology.

[0004] The technical solution adopted by this invention is as follows: Firstly, this invention proposes an intelligent non-destructive monitoring device for the tension of a mining hoisting wire rope, comprising a housing with a central channel for the hoisting wire rope to pass through; permanent magnets, respectively disposed on the inner sides of the front and rear ends of the housing; a channel passing through the middle of the permanent magnets and a Hall sensor group located between the two permanent magnets, arranged circumferentially around the outer periphery of the channel; a magnetic focusing device disposed on both sides of the Hall sensor group, with an armature connecting the magnetic focusing device and the permanent magnets; the housing is composed of two half-housing units; the channel, Hall sensor group, permanent magnets, and magnetic focusing device are all composed of two half-housing units and are respectively installed in the two half-housing units; guide wheels, respectively installed at the front and rear ends of the housing, in rolling contact with the hoisting wire rope; and a rotating encoder wheel, which is a guide wheel equipped with an encoder, with the encoder located on one of the guide wheels.

[0005] As a further improvement of the present invention, the monitoring device also includes a thermistor sensor, which is respectively disposed on both sides of the Hall sensor group.

[0006] As a further improvement of the present invention, the monitoring device also includes an AC inductor coil wound around the channel between the permanent magnet and the housing.

[0007] As a further improvement of the invention, the channel is made of a nylon bushing.

[0008] Secondly, the present invention also proposes an intelligent non-destructive monitoring system for the tension of mining hoisting wire ropes, comprising: an intelligent non-destructive monitoring device for the tension of mining hoisting wire ropes as described above; and an information transmission module, which is wired or wirelessly connected to the Hall sensor group, the rotary encoder wheel, and the thermistor sensor respectively, for transmitting the signals measured by the Hall sensor group, the rotary encoder wheel, and the thermistor sensor to the host computer processing module in real time.

[0009] Thirdly, this invention proposes an intelligent non-destructive monitoring method for the tension of mining hoisting wire ropes. Based on the aforementioned intelligent non-destructive monitoring system for the tension of mining hoisting wire ropes, the method includes the following steps:

[0010] Step S1: Install two intelligent non-destructive monitoring devices for the tension of the mining hoisting wire rope on the left and right vertical rope sections on both sides of the friction wheel, and fix them to the headframe. Step S2: After the hoisting wire rope has been in operation, use two AC inductors to demagnetize the hoisting wire rope, removing its own magnetic flux. Step S3: Use a Hall sensor array to acquire the magnetic flux signal after demagnetization. Step S4: Use a thermistor sensor to acquire the operating temperature of the Hall sensor array and correct the magnetic flux signal. Step S5: Transmit the magnetic flux signal of the hoisting wire rope from the information transmission module to the host computer processing module for preprocessing and feature extraction. Step S6: Establish a wire rope tension monitoring model and convert the acquired magnetic flux signal of the hoisting wire rope into tension data in real time using the model. Step S7: Evaluate and classify the tension of the hoisting wire rope for alarm purposes.

[0011] As a further improvement of the present invention, in step S4, the magnetic flux signal is corrected using the following formula: ,in, This is the temperature-corrected magnetic flux. The magnetic flux at the reference temperature T0 Here, T represents the temperature coefficient, and T is the real-time measured temperature.

[0012] As a further improvement of the present invention, in step S6, the method for establishing the wire rope tension monitoring model is as follows: Step S61, the hoisting wire rope to be tested is placed on a universal tensile testing machine, and the intelligent non-destructive monitoring device for the tension of the mining hoisting wire rope is installed on the hoisting wire rope to be tested; Step S62, different tensions are applied to the hoisting wire rope to be tested step by step using the universal tensile testing machine until the wire rope breaks and is scrapped; Step S63, the magnetic flux signal of the wire rope under different tensions is obtained through the intelligent non-destructive monitoring device for the tension of the mining hoisting wire rope, and the operating temperature of the Hall sensor is obtained by the thermistor sensor; Step S64, the magnetic flux signal of the wire rope is preprocessed and feature values ​​are extracted; Step S65, a deep learning database of the feature values ​​of the magnetic flux signal of the wire rope, the corresponding tension data and temperature data is established; Step S66, based on the deep learning database, a CNN-LSTM fusion wire rope tension monitoring model is established.

[0013] As a further improvement of the present invention, in step S7, the tension of the lifting wire rope is evaluated and graded for alarm, including load-bearing safety evaluation and graded alarm. The specific steps are as follows: S711, set tension threshold I and tension threshold II for the wire rope tension, where tension threshold I is 50% of the minimum breaking tensile force of the wire rope and tension threshold II is the minimum breaking tensile force of the wire rope; S712, if the wire rope tension is less than tension threshold I, output that the wire rope load-bearing condition is good; S713, if the wire rope tension is greater than tension threshold I but less than tension threshold II, output a first-level alarm and record the lifting height of the wire rope; S714, if the wire rope tension is greater than tension threshold II, output a second-level alarm and replace the wire rope.

[0014] As a further improvement of the present invention, in step S7, the tension of the lifting wire rope is evaluated and graded for alarm, which also includes anti-slip safety evaluation and graded alarm. The specific steps are as follows: S721, the tension of the left and right vertical rope segments of the lifting wire rope is differentially processed, and tension difference threshold I and tension difference threshold II are set respectively, wherein tension difference threshold I is 50% of the maximum tension difference of the wire rope without slippage, and tension difference threshold II is the maximum tension difference without slippage; S722, if the tension difference of the wire rope is less than tension difference threshold I, the anti-slip condition of the wire rope is output as good; S723, if the tension difference of the wire rope is greater than tension difference threshold I, but less than tension difference threshold II, a first-level alarm is output and the lifting height of the wire rope is recorded; S724, if the tension difference of the wire rope is greater than tension difference threshold II, a second-level alarm is output and the wire rope is inspected.

[0015] Compared with the prior art, the present invention has the following technical advantages:

[0016] (1) High monitoring accuracy and strong anti-interference ability: This invention adopts wire rope magnetic flux monitoring technology, combined with magnetic focusing device to enhance magnetic field strength, Hall sensor group circumferential arrangement to collect signals in all directions, and thermistor sensor to realize temperature correction, effectively reducing the interference of environmental factors such as temperature and vibration on monitoring results; the wire rope is demagnetized by AC inductor coil to eliminate its own magnetic flux influence, ensuring that the magnetic signal mainly comes from tension change; at the same time, based on CNN-LSTM fusion deep learning model, after training with a large amount of tension-magnetic flux data, the tension of wire rope can be accurately identified, avoiding the problems of insufficient light, oil and dust, and low accuracy of elastic strain monitoring in traditional visual monitoring.

[0017] (2) Comprehensive dynamic alarm and safety assessment capabilities: Combining the lifting height data obtained by the rotating encoder wheel, the host computer processing module can monitor the tension of the wire rope at different positions in real time and display it intuitively through the visualization module; set multi-level tension thresholds (bearing safety assessment) and tension difference thresholds (anti-slip safety assessment) to form a graded alarm mechanism of "good condition - first-level alarm - second-level alarm", which can accurately locate dangerous lifting heights, provide decision support for wire rope replacement or maintenance, effectively prevent safety accidents such as breakage and slippage, and ensure the safety of the lifting system.

[0018] (3) Real-time and dynamic response efficiency: The information transmission module supports wired or wireless real-time transmission, and the host computer processing module can perform real-time preprocessing and feature extraction of magnetic flux signals. Combined with the lifting height data, it can realize dynamic synchronous monitoring of tension, capture tension changes in real time, provide data support for emergency decision-making, and shorten the risk response time. Attached Figure Description

[0019] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments;

[0020] Figure 1 This is a schematic diagram of the intelligent non-destructive monitoring system for tension of mining hoisting steel wire ropes in this invention.

[0021] Figure 2 This is a schematic diagram of the intelligent non-destructive monitoring device for tension of mining hoisting steel wire rope in this invention.

[0022] Figure 3 This is a schematic diagram of a floor-mounted friction lifting system in an embodiment of the present invention.

[0023] Figure 4 This is a schematic diagram of the tension distribution of the lifting wire rope in a ground-mounted friction lifting system.

[0024] Figure 5 This is a flowchart for establishing a tension monitoring model for steel wire ropes.

[0025] Explanation of reference numerals in the attached drawings: 1-Intelligent non-destructive monitoring device for tension of mining hoisting wire rope; 100-Shell; 110-Channel; 120-Hall sensor group; 130-Permanent magnet; 140-Armature; 150-Magnetic focusing device; 160-Thermistor sensor; 170-AC inductor coil; 180-Guide wheel; 190-Rotating encoder wheel; 2-Information transmission module; 3-Upper computer processing module; 4-Hoisting wire rope; 5-Friction wheel; 6-Lower guide wheel; 7-Upper guide wheel; 8-Derrick; 9-Unloaded hoisting container; 10-Heavy-loaded hoisting container. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the described embodiments of the present invention are within the scope of protection of the present invention.

[0027] Please refer to Figures 1-2 ,in, Figure 1 This is a schematic diagram of the intelligent non-destructive monitoring device for the tension of mining hoisting steel wire ropes in this invention. Figure 2 This is a schematic diagram of the intelligent non-destructive monitoring device for the tension of mining hoisting wire ropes according to the present invention. The present invention proposes an intelligent non-destructive monitoring device 1 for the tension of mining hoisting wire ropes, comprising a housing 100, a Hall sensor group 120, a permanent magnet 130, a magnetic focusing device 150, a thermistor sensor 160, an AC inductor coil, a guide wheel 180, and a rotating encoder wheel 190. The housing 100 has a channel 110 at its center for the hoisting wire rope 4 to pass through. The housing 100 is formed by two identical half-housings joined together, with the two half-housings hinged on one side. The housing 100 is mainly made of aluminum alloy to ensure the monitoring device is waterproof, impact-resistant, and vibration-resistant, thus improving its service life. The channel 110 is made of nylon bushing to prevent damage to the hoisting wire rope 4 caused by the monitoring device. Four guide wheels 180 are provided, respectively installed at the front and rear ends of the housing 100, and roll in contact with the hoisting wire rope 4. An encoder is installed on one of the guide wheels 180, serving as the rotating encoder wheel 190, for measuring the hoisting height of the hoisting wire rope 4. The rotating encoder wheel 190 moves synchronously with the lifting wire rope 4. Each rotation generates a pulse signal for counting, recording the lifting / lowering height of the wire rope in real time. The guide wheel 180 moves synchronously with the wire rope, playing a crucial role in guidance, positioning, and stabilizing the monitoring environment. Two permanent magnets 130 are respectively positioned inside the front and rear ends of the housing 100, with a channel 110 passing through the middle of the permanent magnets 130, which are generally disc-shaped. A Hall sensor group 120, located between the two permanent magnets 130, is used to acquire the magnetic flux of the lifting wire rope 4. The Hall sensor group 120 consists of multiple Hall sensors, evenly arranged circumferentially around the outer periphery of the channel 110. Magnetizing devices 150 are positioned on both sides of the Hall sensor group 120, connected to the permanent magnets 130 by armatures 140.

[0028] The magnetic focusing device 150 includes a magnetic focusing ring and a magnetic bridge circuit, both made of high-permeability materials (such as soft iron, permalloy, ferrite, etc.). The magnetic focusing ring is ring-shaped or ring-like and its main function is to converge and guide the dispersed external magnetic field to the magnetic bridge circuit region. The magnetic bridge circuit is a bridge-like magnetic conductor connecting magnetic components (such as the two magnetic focusing rings), which can construct a magnetic field path, adjust the magnetic field distribution, and balance the magnetic flux. The Hall sensor assembly 120 is located in the middle of the magnetic bridge circuit between the two magnetic focusing rings, forming a "sandwich" structure: "one magnetic focusing ring → magnetic bridge circuit → Hall element → other magnetic bridge circuit → other magnetic focusing ring". This design makes the magnetic bridge circuit a necessary channel for magnetic field lines, effectively increasing the magnetic flux density at the sensor. When an external magnetic field acts, the two magnetic focusing rings form a closed magnetic circuit through the magnetic bridge circuit: magnetic field lines enter the magnetic bridge circuit from one magnetic focusing ring, pass through the Hall sensor assembly 120, and return to the other magnetic focusing ring through the other magnetic bridge circuit, forming a complete loop. This closed design can reduce magnetic resistance by more than 50%, and compared with the single magnetic ring structure, the magnetic field strength at the sensor can be increased by 2-3 times.

[0029] The armature 140 is in close contact with the surface of the lifting wire rope 4, which can reduce the loss of magnetic field during transmission and enhance the collection and utilization of leakage magnetic field, thereby reducing magnetic resistance and enhancing the magnetic concentration effect.

[0030] In this embodiment, the channel 110, the Hall sensor group 120, the permanent magnet 130 and the magnetic focusing device 150 are all composed of the same half-body assembly and are installed in two half-shells.

[0031] In this intelligent non-destructive monitoring device 1 for the tension of hoisting steel wire ropes in mines, permanent magnets 130 are disposed on the inner sides of the front and rear ends of the housing 100, and a channel 110 passes through the middle of the permanent magnets 130. Magnetizing devices 150 are located on both sides of the Hall sensor group 120, and are connected to the permanent magnets 130 and the magnetizing devices 150 via armatures 140, forming a closed magnetic field path. The permanent magnets 130 serve as the magnetic field source, providing the initial magnetic field. The armatures 140 are in close contact with the surface of the hoisting steel wire rope 4, reducing magnetic field loss during transmission and enhancing the collection and utilization of leakage magnetic fields, thus reducing magnetic resistance and enhancing magnetizing.

[0032] Thermistor sensors 160 are respectively disposed on both sides of Hall sensor group 120 and symmetrically arranged inside housing 100 to monitor the operating temperature of Hall sensor group 120 in real time, which is used to establish a temperature compensation model and improve tension monitoring accuracy. The average value of the two thermistor sensors 160 is used as the final output value.

[0033] An AC inductor coil 170 is wound around the channel 110 between the permanent magnet 130 and the housing 100 to demagnetize the hoisting wire rope 4, ensuring that the magnetic signal of the wire rope mainly originates from the change in magnetic length signal caused by tension variations. When AC current is applied to the AC inductor coil 170, it generates an alternating magnetic field with continuously changing direction and gradually decreasing intensity. When this alternating magnetic field acts on the hoisting wire rope 4, it gradually disrupts the ordered magnetic domains (the root cause of residual magnetic flux) originally formed by magnetization within the wire rope, making their orientation disordered, thereby gradually weakening and eliminating the inherent magnetic flux carried by the wire rope itself. Specifically, the AC frequency is selected to be 10-30Hz, and the current intensity is 50-240A.

[0034] Please refer to Figure 1 This invention also proposes an intelligent non-destructive monitoring system for the tension of mining hoisting wire ropes, including an intelligent non-destructive monitoring device 1, an information transmission module 2, a host computer processing module 3, and a visualization module (not shown in the figure). The information transmission module 2 is electrically connected to a Hall sensor group 120, a rotating encoder wheel 190, and a thermistor sensor 160, respectively, and is used to transmit the signals measured by the Hall sensor group 120, the rotating encoder wheel 190, and the thermistor sensor 160 to the host computer processing module 3 in real time. In some other embodiments, the information transmission module 2 can also transmit information wirelessly. The host computer processing module 3 can receive and process the signals measured by the Hall sensor group 120, the rotating encoder wheel 190, and the thermistor sensor 160 transmitted by the information transmission module 2 in real time to obtain the wire rope tension at different hoisting heights. The visualization module is used to display the real-time tension data of the hoisting wire rope 4.

[0035] Please combine Figure 3 and Figure 4 , Figure 3 This is a schematic diagram of a floor-mounted friction lifting system according to an embodiment of the present invention. Figure 4This is a schematic diagram of the tension distribution of the hoisting wire rope in a ground-mounted friction hoisting system. This invention proposes an intelligent non-destructive monitoring method for the tension of mining hoisting wire ropes, comprising the following steps: Step S1: Install two intelligent non-destructive monitoring devices 1 for the tension of mining hoisting wire ropes on the left and right vertical rope sections of the hoisting wire rope 4, and fix them to the derrick 8 of the ground-mounted friction hoisting system. The hoisting wire rope 4 passes through the two intelligent non-destructive monitoring devices 1. The ground-mounted friction hoisting system includes a friction wheel 5, a hoisting wire rope 4, a lower guide wheel 6, an upper guide wheel 7, a derrick 8, an unloaded hoisting container 9, and a heavy-loaded hoisting container 10. The hoisting wire rope 4 passes around the friction wheel 5 and is fixedly connected to the unloaded hoisting container 9 and the heavy-loaded hoisting container 10 via the lower guide wheel 6 and the upper guide wheel 7 respectively. The friction wheel 5 is driven by friction with the hoisting wire rope 4 to realize the raising and lowering of the unloaded hoisting container 9 and the heavy-loaded hoisting container 10. The left vertical rope section is connected to the unloaded hoisting container 9, and the right vertical rope section is connected to the heavy-load hoisting container 10. One intelligent non-destructive monitoring device 1 for the tension of the mining hoisting wire rope is installed on the hoisting wire rope 4 to the left of the upper guide wheel 7, i.e., on the left vertical rope section. Another intelligent non-destructive monitoring device 1 for the tension of the mining hoisting wire rope is installed on the hoisting wire rope 4 to the left of the lower guide wheel 6, i.e., on the right vertical rope section.

[0036] Step S2: During the operation of the lifting wire rope 4, the two AC inductors 170 demagnetize the lifting wire rope 4, removing the magnetic signal of the wire rope itself. This ensures that the magnetic flux signal acquired by the Hall sensor group 120 is mainly from the change in permeability of the wire rope under tension (rather than its own residual magnetism), thereby improving the accuracy of tension monitoring and providing a reliable original signal basis for tension calculation based on changes in magnetic flux.

[0037] Step S3: Acquire the magnetic flux signal of the wire rope based on the Hall sensor group 120. Since the Hall sensor group 120 consists of multiple Hall sensors, the average value of the magnetic flux acquired by multiple Hall sensors is used as the final output value, resulting in a more accurate acquisition of the magnetic flux of the lifting wire rope 4. The rotating encoder wheel 190 moves synchronously with the lifting wire rope 4 to acquire the lifting height of the wire rope in real time.

[0038] Step S4: Obtain the temperature of the Hall sensor group 120 based on the thermistor sensor 160. The temperature data is used for subsequent signal correction to eliminate interference from temperature changes on the output signal of the Hall sensor group 120, ensuring that the magnetic flux signal accurately reflects the tension state of the wire rope. The temperature measured by the thermistor sensor 160 needs to correct the magnetic flux signal; the correction formula is as follows: ,in, This is the temperature-corrected magnetic flux. The magnetic flux at the reference temperature T0 Here, T represents the temperature coefficient (determined experimentally), and T represents the real-time measured temperature. The reference temperature T0 is the natural temperature of the friction lifting system before operation (e.g., 25°C), and the temperature will rise after operation.

[0039] Step S5: The magnetic flux signal of the wire rope is amplified by the information transmission module 2 and transmitted to the host computer processing module 3 for preprocessing and feature extraction. Preprocessing focuses on data cleaning, addressing noise and error issues in the original magnetic flux signal. This includes filtering electromagnetic interference noise and correcting temperature drift to ensure the magnetic flux data reflects the true physical state. Common preprocessing methods include filtering (wavelet denoising, low-pass filtering) and phase-sensitive detection, directly processing the original magnetic flux signal. Feature processing revolves around "information extraction," mining features strongly correlated with tension from the cleaned data, extracting peak values, slopes, and frequency components of the magnetic flux, providing quantifiable and highly discriminative input for the tension model.

[0040] Step S6: Based on the acquired wire rope magnetic flux signal and the operating temperature of the Hall sensor group 120, combined with the wire rope tension monitoring model and the wire rope lifting height data acquired based on the rotating encoder wheel 190, the tension of the wire rope at different lifting heights is acquired in real time; the magnetic flux feature value corrected by temperature compensation is input into the CNN-LSTM fused lifting wire rope tension monitoring model, and combined with the lifting height parameter, the tension of the lifting wire rope at different positions is accurately calculated, forming tension distribution data in the spatial dimension.

[0041] The tension monitoring model is the core algorithm framework for achieving real-time and accurate identification of wire rope tension. Its principle is as follows: by analyzing the magnetic flux signal of the wire rope, the tension value is deduced. When the wire rope is subjected to different tensions, the change in internal stress state will lead to a change in magnetic permeability, which in turn will cause the magnetic flux signal to show a regular change. By capturing this correlation, the model can convert the pre-processed magnetic flux signal into corresponding tension data, thereby realizing real-time monitoring of wire rope tension and providing a direct basis for subsequent safety assessment.

[0042] The principle that changes in wire rope tension lead to changes in magnetic permeability, which in turn affect magnetic flux, can be expressed by the following relationship: ,in, Wb is the magnetic flux, and B is the magnetic flux density (T). Let F be the magnetic permeability of the wire rope (H / m, varying with tension), H be the magnetic field strength (A / m), and S be the cross-sectional area of ​​the magnetic circuit (m²). As the tension F changes, the magnetic permeability... It can be approximated as , (where k is the permeability without tension and k is the tension influence coefficient), therefore, there is a nonlinear relationship between magnetic flux and tension.

[0043] Please refer to Figure 5 The method for establishing the tension monitoring model is as follows: Step S61: Place the hoisting wire rope to be tested on a universal tensile testing machine to simulate the tension change under actual working conditions and ensure the stability of subsequent tension application and signal acquisition; install the intelligent non-destructive monitoring device 1 for mine hoisting wire rope tension on the hoisting wire rope to be tested; the hoisting wire rope to be tested has the same specifications as the hoisting wire rope 4.

[0044] Step S62: Using a universal tensile testing machine, apply different tensions to the tested hoisting wire rope step by step, covering the full range from normal working tension to ultimate breaking tension, until the wire rope breaks and is scrapped. This obtains complete data containing various tension states, with particular emphasis on signal acquisition at critical tension points, laying the foundation for the model's ability to identify ultimate states.

[0045] Step S63: The intelligent non-destructive monitoring device 1 for the tension of mining hoisting wire rope synchronously collects the magnetic flux signal of the wire rope under different tensions, and records the ambient temperature in conjunction with the temperature monitoring module throughout the monitoring process to eliminate the interference of temperature on the magnetic flux signal and ensure that the collected signal is only related to the tension change.

[0046] Step S64: Preprocess the acquired wire rope magnetic flux signal (bandpass filtering and phase-sensitive detection) and extract feature values ​​(such as peak value, valley value, waveform slope, spectral features, etc.) to extract key feature parameters that can effectively reflect tension changes from the original signal, reducing data dimensionality while retaining core information.

[0047] Step S65: Based on the above processing results, establish a deep learning database containing the feature values ​​of the magnetic flux signal of the wire rope, the corresponding actual tension data, and the synchronously recorded temperature data. Through data annotation, the three are made to form a one-to-one correspondence, providing a high-quality sample set for model training.

[0048] Step S66: Finally, based on the deep learning database, a CNN-LSTM fusion model for wire rope tension monitoring is constructed. CNN (Convolutional Neural Network) excels at extracting local features of magnetic flux signals (such as instantaneous fluctuation features), while LSTM (Long Short-Term Memory Network) can capture the temporal dependence of signals on tension changes (such as signal trends during the gradual tension change process). The fusion of the two can fully explore the complex nonlinear relationship between magnetic flux and tension, giving the model high tension recognition accuracy and generalization ability, and enabling it to adapt to the tension monitoring needs of different working conditions in practical applications. To more clearly illustrate how the CNN-LSTM fusion model achieves accurate mapping of the relationship between magnetic flux signals and tension, the following will elaborate on the core components of the model, including CNN's extraction of local features, LSTM's capture of temporal features, and the implementation method of the final tension prediction output. The accuracy evaluation method used during model training will also be explained: (I) CNN Local Feature Extraction: The output formula of the convolutional layer is: ,in, For the j-th feature map in the l-th layer, M j Input feature map set, For convolution kernel weights, For bias, For example, ReLU is an activation function.

[0049] (II) LSTM Temporal Feature Capture: The cell state update formula is: , , where f t (Forgotten Gate), i t (Input Gate), o t (Output gates) control the forgetting, input, and output of information respectively, c t In cellular state, For candidate cell states, h t This is the output of the hidden layer, used to capture the temporal dependence of magnetic flux as a function of tension.

[0050] (III) Tension Prediction Output: The formula for the final output tension F of the model is: In the formula, h T This is the hidden layer output of the LSTM at the last moment, where w and b are linear layer parameters. The mapping relationship between magnetic flux features and tension is fitted through training.

[0051] During training, mean squared error (MSE) is used to evaluate prediction accuracy, and the formula is as follows:

[0052] ,in, To predict tension for the model, The tensile testing machine measures the tension, and N is the number of samples. The model parameters are optimized by minimizing L.

[0053] Step S7: Assess and alarm the tension of the lifting wire rope.

[0054] Firstly, this method assesses the load-bearing safety of the wire rope and determines the load-bearing state through graded thresholds. The specific steps are as follows: Step S711: Set tension threshold I and tension threshold II for the tension F1 and tension F2 of the two mine hoisting wire rope tension intelligent non-destructive monitoring devices 1 for the hoisting wire rope 4, respectively. Among them, tension threshold I is 50% of the minimum breaking force of the wire rope, and tension threshold II is the minimum breaking force of the wire rope.

[0055] Step S712: If the tension F1 and the tension F2 of the intelligent non-destructive monitoring device 1 for the tension of the mining hoisting wire rope 4 are both less than the tension threshold I, the output "the wire rope is in good condition" indicates that the current tension is far below the risk value and can operate normally.

[0056] Step S713: If either the tension F1 or the tension F2 of the intelligent non-destructive monitoring device 1 for mine hoisting wire rope tension is greater than the tension threshold I but less than the tension threshold II, a first-level alarm will be output and the hoisting height will be recorded, indicating that there is a potential overload risk and that the tension change at this location needs to be monitored.

[0057] Step S714: If either the tension F1 or the tension F2 of the intelligent non-destructive monitoring device 1 for the tension of the mining hoisting wire rope 4 is greater than the tension threshold II, a level II alarm will be output and the wire rope will be replaced. At this time, the wire rope is close to or has reached its bearing limit and must be stopped immediately to avoid an accident.

[0058] Secondly, this method assesses the anti-slip safety of wire ropes, with the following specific steps: Step S721, the right tension F1 and the tension F2 of the intelligent non-destructive monitoring device 1 for the tension of the same hoisting wire rope 4 guide wheel are subtracted (F1-F2), and tension difference thresholds I and II are set respectively. Tension difference threshold I is 50% of the maximum tension difference without slippage of the wire rope, and tension difference threshold II is the maximum tension difference without slippage. Based on the anti-slip mechanism of friction transmission, this method prevents safety accidents caused by slippage. The maximum tension difference without slippage in a friction hoisting system refers to the maximum allowable tension difference between the two wire ropes during the operation of a friction hoisting system (such as a mine hoist that relies on the friction between the friction wheel and the wire rope to transmit power).

[0059] Step S722: If the tension difference of the lifting wire rope 4 is less than the tension difference threshold I, the output wire rope has good anti-slip condition, indicating that the friction force is sufficient to ensure normal transmission.

[0060] Step S723: If the tension difference of the lifting wire rope 4 is greater than the tension difference threshold I, but less than the tension difference threshold II, output a first-level alarm and record the lifting height of the wire rope, indicating that there is a risk of slippage and that the guide wheel or wire rope condition needs to be checked.

[0061] Step S724: If the tension difference of the lifting wire rope 4 is greater than the tension difference threshold II, output a level 2 alarm and require the wire rope to be inspected. At this time, the risk of slippage is extremely high, and the machine must be stopped for inspection to restore the anti-slip capability.

[0062] The embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited thereto. Various changes that can be made within the scope of knowledge possessed by those skilled in the art without departing from the spirit of the present invention are within the protection scope of the claims of the present invention.

Claims

1. A smart non-destructive monitoring device for the tension of mining hoisting wire ropes, characterized in that, include The housing (100) has a central channel (110) through which the lifting wire rope (4) passes; Permanent magnets (130) are respectively disposed on the inner sides of the front and rear ends of the housing (100), and the channel (110) passes through the middle of the permanent magnets (130); Hall sensor array (120) is located between two permanent magnets (130) and arranged circumferentially around the outer periphery of channel (110); A magnetic focusing device (150) is set on both sides of the Hall sensor group (120), and an armature (140) is used to connect the magnetic focusing device (150) and the permanent magnet (130); The housing (100) is composed of two half-housing units; the channel (110), the Hall sensor group (120), the permanent magnet (130) and the magnetic focusing device (150) are all composed of two half-units and are installed in the two half-housing units respectively; Guide wheels (180) are installed at the front and rear ends of the housing (100) respectively, and make rolling contact with the lifting wire rope (4); A rotating encoder wheel (190) is a guide wheel (180) on which an encoder is mounted, with the encoder located on one of the guide wheels (180); It also includes a thermistor sensor (160), which is respectively disposed on both sides of the Hall sensor group (120); It also includes an AC inductor (170) wound around a channel (110) between the permanent magnet (130) and the housing (100).

2. The intelligent non-destructive monitoring device for tension of mining hoisting wire ropes according to claim 1, characterized in that, The channel (110) is made of nylon bushing.

3. A smart non-destructive monitoring system for the tension of mining hoisting wire ropes, characterized in that, include: The intelligent non-destructive monitoring device for tension of mining hoisting steel wire rope as described in claim 1 or 2 (1); The information transmission module (2) is connected to the Hall sensor group (120), the rotary encoder wheel (190) and the thermistor sensor (160) via wired or wireless connection, respectively, and is used to transmit the signals measured by the Hall sensor group (120), the rotary encoder wheel (190) and the thermistor sensor (160) to the host computer processing module (3) in real time.

4. A method for intelligent non-destructive monitoring of tension in mining hoisting wire ropes, based on the intelligent non-destructive monitoring system for tension in mining hoisting wire ropes as described in claim 3, characterized in that, The method includes the following steps: Step S1: Install the two mine hoisting wire rope tension intelligent non-destructive monitoring devices (1) on the left and right vertical rope sections of the hoisting wire rope (4) on both sides of the friction wheel (5), and fix them on the derrick (8); Step S2: After the hoisting wire rope (4) has been running, two AC inductors (170) are used to demagnetize the hoisting wire rope (4) to remove the magnetic flux of the hoisting wire rope (4) itself. Step S3: Use Hall sensor group (120) to obtain the magnetic flux signal of the hoisting wire rope (4) after demagnetization; Step S4: Use a thermistor sensor (160) to obtain the operating temperature of the Hall sensor group (120) and correct the magnetic flux signal; Step S5: The magnetic flux signal of the lifting wire rope (4) is transmitted from the information transmission module (2) to the host computer processing module (3) to preprocess the magnetic flux signal and extract its feature value. Step S6: Establish a wire rope tension monitoring model, and convert the magnetic flux signal of the lifting wire rope (4) obtained by the wire rope tension monitoring model into the tension data of the wire rope in real time. Step S7: Assess the tension of the lifting wire rope and issue a graded alarm.

5. The intelligent non-destructive monitoring method for tension of mining hoisting wire ropes according to claim 4, characterized in that, In step S4, the magnetic flux signal is corrected using the following formula: ， in, This is the temperature-corrected magnetic flux. The magnetic flux at the reference temperature T0 Here, T represents the temperature coefficient, and T is the real-time measured temperature.

6. The intelligent non-destructive monitoring method for tension of mining hoisting wire ropes according to claim 4, characterized in that, In step S6, the method for establishing the wire rope tension monitoring model is as follows: Step S61: Place the hoisting wire rope to be tested on the universal tensile testing machine, and install the intelligent non-destructive monitoring device (1) for the tension of the mining hoisting wire rope on the hoisting wire rope to be tested; Step S62: Apply different tensions to the tested hoisting wire rope using a universal tensile testing machine until the wire rope breaks and is scrapped. Step S63: The magnetic flux signal of the wire rope under different tensions is obtained by the intelligent non-destructive monitoring device (1) for the tension of the mining hoisting wire rope, and the working temperature of the Hall sensor group (120) is obtained by the thermistor sensor (160). Step S64: Preprocess and extract feature values ​​from the magnetic flux signal of the wire rope; Step S65: Establish a deep learning database of the characteristic values ​​of the magnetic flux signal of the wire rope, the corresponding tension data, and the temperature data; Step S66: Based on the deep learning database, establish a CNN-LSTM fusion model for monitoring wire rope tension.

7. The intelligent non-destructive monitoring method for tension of mining hoisting wire ropes according to claim 4, characterized in that, In step S7, the tension of the hoisting wire rope is assessed and a graded alarm is generated, including a load-bearing safety assessment and graded alarm generation. The specific steps are as follows: S711. Set tension threshold I and tension threshold II for the wire rope tension respectively, wherein tension threshold I is 50% of the minimum breaking tensile force of the wire rope and tension threshold II is the minimum breaking tensile force of the wire rope. S712. If the tension of the wire rope is less than the tension threshold I, then the output wire rope is in good condition. S713. If the tension of the wire rope is greater than the tension threshold I but less than the tension threshold II, then output a first-level alarm and record the lifting height of the wire rope. S714. If the tension of the wire rope is greater than the tension threshold II, a level II alarm will be output, and the wire rope will be replaced.

8. The intelligent non-destructive monitoring method for tension of mining hoisting wire ropes according to claim 4, characterized in that, In step S7, the tension of the hoisting wire rope is evaluated and graded with an alarm, which also includes an anti-slip safety evaluation and graded alarm. The specific steps are as follows: S721. The tension of the left and right vertical rope sections of the lifting wire rope (4) is differentially processed, and tension difference threshold I and tension difference threshold II are set respectively. Among them, tension difference threshold I is 50% of the maximum tension difference of the wire rope without slipping, and tension difference threshold II is the maximum tension difference without slipping. S722. If the tension difference of the wire rope is less than the tension difference threshold I, then the output wire rope has good anti-slip condition. S723. If the tension difference of the wire rope is greater than the tension difference threshold I, but less than the tension difference threshold II, then output a first-level alarm and record the lifting height of the wire rope. S724. If the tension difference of the wire rope is greater than the tension difference threshold II, a level II alarm will be output to inspect the wire rope.

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