Intelligent nondestructive monitoring device, system and method for tension of mining hoisting steel wire rope

Abstract

The invention discloses a mine hoisting steel wire rope tension intelligent nondestructive monitoring device, system and method, the monitoring device comprises a shell formed by folding two half shells, the center of the shell is provided with a channel for a hoisting steel wire rope to pass through, the inner sides of the front and rear ends of the shell are provided with permanent magnets, and the middle of the shell is annularly provided with a Hall sensor group; magnetic gathering devices are arranged on two sides of the Hall sensor, and the permanent magnet is connected with the magnetic gathering devices through armatures; the device further comprises a guide wheel, a rotary encoding wheel with an encoder, a thermistor sensor and an alternating current inductance coil, and each core component is formed by combining half bodies and is arranged in two half shells respectively. A magnetic flux monitoring technology is combined with a tension monitoring model, so that the monitoring precision and the anti-interference capability are improved, the system adapts to a complex mining environment, nondestructive monitoring and dynamic alarm can be realized, and the safety of a lifting system is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of wire rope tension monitoring, and in particular to an intelligent non-destructive monitoring device, system and method for monitoring the tension of a mine hoisting wire rope. Background Art

[0002] During mine hoisting, the stress on the wire rope is influenced by the load weight, its inherent characteristics (length, diameter, wear, etc.), the operating state of the hoisting system (acceleration, drum and sheave parameters), and environmental factors (temperature, humidity, etc.). These factors intertwine and cause complex variations in the wire rope tension. In severe cases, this can even lead to fatigue deformation, breakage, or slippage of the wire rope. Once a wire rope breaks or slips, it can cause serious safety accidents, resulting in damage to the mine hoisting mechanism and casualties. To ensure production safety, wire rope tension monitoring technology has made significant progress in recent years. Among the previously disclosed technologies, Chinese patent publication number CN118913520A discloses a force analysis system and analysis method for a lateral pressure sensor. This system uses the strain of an elastic body to derive the force applied, and calculates the force based on the resistance change of an elastic strain gauge, thereby enabling wire rope tension monitoring. However, the system has problems such as complex structure, difficult installation, and low monitoring accuracy, and it will also cause damage to the wire rope itself. The Chinese patent with publication number CN119880228A discloses a wire rope tension monitoring method and a wire rope tension monitoring device. Based on machine vision methods, it collects wire rope movement videos in real time and combines them with tension monitoring models to obtain wire rope force. However, the device cannot adapt to the actual wire rope operating environment, such as insufficient lighting, 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 online. Summary of the Invention

[0003] The purpose of the present invention is to propose an intelligent non-destructive monitoring device, system and method for the tension of mining hoisting wire ropes, so as to overcome the problems of low monitoring efficiency, low monitoring accuracy, poor environmental applicability and inability to accurately perceive the tension of wire ropes in real time and non-destructively online in the prior art.

[0004] The technical solution adopted by the present invention is: in the first aspect, the present invention proposes an intelligent non-destructive monitoring device for the tension of a mining hoisting wire rope, comprising a shell with a channel for the lifting wire rope to pass through the center; permanent magnets are respectively arranged on the inner sides of the front and rear ends of the shell, and the channel passes through the Hall sensor group from the middle of the permanent magnet, is located between the two permanent magnets, and is arranged circumferentially on the outer periphery of the channel; a magnetic focusing device is arranged on both sides of the Hall sensor group, and an armature is used to connect the magnetic focusing device and the permanent magnet; the shell is composed of two half shells; the channel, the Hall sensor group, the permanent magnet and the magnetic focusing device are all composed of two half bodies, and are separately installed in the two half shells; guide wheels are respectively installed at the front and rear ends of the shell, and are in rolling contact with the lifting wire rope; the rotating encoding wheel is a guide wheel equipped with an encoder, and the encoder is located on one of the guide wheels.

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

[0006] As a further improvement of the present invention, the monitoring device further includes an AC inductor coil, which is wound on the channel between the permanent magnet and the shell.

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

[0008] In the second aspect, the present invention also proposes an intelligent non-destructive monitoring system for the tension of a mine hoisting wire rope, comprising: an intelligent non-destructive monitoring device for the tension of a mine hoisting wire rope as described above; an information transmission module, which is respectively connected to the Hall sensor group, the rotating encoder wheel and the thermistor sensor by wire or wirelessly, and is used to transmit the signals measured by the Hall sensor group, the rotating encoder wheel and the thermistor sensor to the host computer processing module in real time.

[0009] In a third aspect, the present invention proposes a method for intelligent non-destructive monitoring of the tension of a mine hoisting wire rope. Based on the above-mentioned intelligent non-destructive monitoring system for the tension of a mine hoisting wire rope, the method comprises the following steps:

[0010] Step S1: Two intelligent non-destructive monitoring devices for the tension of a mining hoisting wire rope are respectively installed on the left and right vertical rope sections of the hoisting wire rope on both sides of the friction wheel, and fixed on the derrick; Step S2: After the hoisting wire rope is running, two AC inductance coils are used to demagnetize the hoisting wire rope to remove the magnetic flux of the hoisting wire rope itself; Step S3: A Hall sensor group is used to obtain the magnetic flux signal of the hoisting wire rope after demagnetization; Step S4: A thermistor sensor is used to obtain the working temperature of the Hall sensor group and correct the magnetic flux signal; Step S5: The magnetic flux signal of the hoisting wire rope is transmitted from the information transmission module to the upper computer processing module, and the magnetic flux signal is pre-processed and the characteristic value is extracted; Step S6: A wire rope tension monitoring model is established, and the obtained magnetic flux signal of the hoisting wire rope is converted into wire rope tension data in real time through the wire rope tension monitoring model; Step S7: The tension of the hoisting wire rope is evaluated and a graded alarm is issued.

[0011] As a further improvement of the present invention, in step S4, the magnetic flux signal is corrected, and the correction formula is: ,in, is the temperature-corrected magnetic flux, is the magnetic flux at the reference temperature T0, is 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, placing the hoisting wire rope to be tested on a universal tensile testing machine, and installing the intelligent non-destructive monitoring device for the tension of the mining hoisting wire rope on the hoisting wire rope to be tested; step S62, using the universal tensile testing machine to apply different tensions to the hoisting wire rope to be tested step by step until the wire rope breaks and is scrapped; step S63, obtaining the magnetic flux signal of the wire rope at different tensions through the intelligent non-destructive monitoring device for the tension of the mining hoisting wire rope, and obtaining the working temperature of the Hall sensor through the thermistor sensor; step S64, preprocessing the magnetic flux signal of the wire rope and extracting the eigenvalues; step S65, establishing a deep learning database of the eigenvalues ​​of the magnetic flux signal of the wire rope, the corresponding tension data and the temperature data; step S66, establishing a CNN-LSTM fused wire rope tension monitoring model based on the deep learning database.

[0013] As a further improvement of the present invention, in step S7, the tension of the lifting wire rope is evaluated and graded alarms are performed, including load safety evaluation and graded alarms, and the specific steps are: S711, setting tension threshold I and tension threshold II for the wire rope tension, respectively, wherein tension threshold I is 50% of the minimum breaking tension of the wire rope, and tension threshold II is the minimum breaking tension of the wire rope; S712, if the wire rope tension is less than tension threshold I, then output that the wire rope load-bearing state is good; S713, if the wire rope tension is greater than tension threshold I, but less than tension threshold II, then output a first-level alarm and record the wire rope lifting height; S714, if the wire rope tension is greater than tension threshold II, then 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 alarm is performed, which also includes anti-slip safety evaluation and graded alarm. The specific steps are: S721, the tension of the left vertical rope segment and the right vertical rope segment of the lifting wire rope are differentially processed, and the tension difference threshold I and the tension difference threshold II are set respectively, wherein the tension difference threshold I is 50% of the maximum tension difference of the wire rope without slipping, and the 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 is that the anti-slip state of the wire rope is good; 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 the 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 the tension difference threshold II, then the second level alarm is output and the wire rope is repaired.

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

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

[0017] (2) Comprehensive dynamic alarm and safety assessment capabilities: Combined with the lifting height data obtained by the rotating encoder wheel, the host computer processing module can dynamically 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 (load safety assessment) and tension difference thresholds (anti-slip safety assessment) to form a hierarchical 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 slipping, and ensure the safety of the lifting system.

[0018] (3) Real-time and efficient dynamic response: The information transmission module supports wired or wireless real-time transmission. The host computer processing module can perform real-time pre-processing and feature extraction of magnetic flux signals. It can realize dynamic synchronous monitoring of tension by combining lifting height data, and can instantly capture tension mutations, provide data support for emergency decision-making, and shorten risk response time. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0020] Figure 1 It is a schematic diagram of the intelligent non-destructive monitoring system for the tension of the mining hoisting wire rope in the present invention.

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

[0022] Figure 3 Schematic diagram of a floor-type friction lifting system in an embodiment of the present invention.

[0023] Figure 4 It is a schematic diagram of the tension distribution of the lifting wire rope in the floor-type friction lifting system.

[0024] Figure 5 It is a flow chart for establishing a tension monitoring model for lifting wire ropes.

[0025] Explanation of the accompanying drawings: 1-intelligent non-destructive monitoring device for the tension of the mining hoisting wire rope, 100-housing, 110-channel, 120-Hall sensor group, 130-permanent magnet, 140-armature, 150-magnetic focusing device, 160-thermistor sensor, 170-AC inductance 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-empty hoisting container, 10-heavy-load hoisting container. DETAILED DESCRIPTION

[0026] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the described embodiments of the present invention, all other embodiments derived by persons of ordinary skill in the art are within the scope of protection of the present invention.

[0027] Please refer to Figure 1-Figure 2 ,in, Figure 1 This is a schematic diagram of the intelligent non-destructive monitoring device for the tension of a mining hoisting wire rope in the present invention. Figure 2 This is a schematic diagram of an intelligent, nondestructive monitoring device for the tension of a mining hoisting wire rope according to the present invention. The device 1 comprises a housing 100, a Hall effect sensor assembly 120, a permanent magnet 130, a magnetic field concentrator 150, a thermistor sensor 160, an AC inductor coil 170, a guide pulley 180, and a rotary encoder wheel 190. A channel 110 is centrally located within the housing 100, through which the hoisting wire rope 4 passes. The housing 100 is constructed from two identical halves hinged at one side. The housing 100 is primarily fabricated from aluminum alloy, ensuring the monitoring device's waterproof, impact-resistant, and vibration-resistant capabilities, thereby extending its service life. The channel 110 is constructed with a nylon bushing to prevent damage to the hoisting wire rope 4. Four guide pulleys 180 are mounted at the front and rear ends of the housing 100, respectively, in rolling contact with the hoisting wire rope 4. An encoder is mounted on one of the guide pulleys 180, serving as the rotary encoder wheel 190, to measure the hoisting height of the hoisting wire rope 4. The rotating encoder wheel 190 keeps in sync with the lifting wire rope 4. The encoder generates a pulse signal and counts once for each rotation, recording the lifting / lowering height of the wire rope in real time. The guide wheel 180 keeps in sync with the wire rope and plays a key role in guiding, positioning and stabilizing the monitoring environment. Two permanent magnets 130 are respectively arranged on the inner side of the front and rear ends of the shell 100. The channel 110 passes through the middle of the permanent magnet 130. The permanent magnet 130 is disc-shaped as a whole. The Hall sensor group 120 is used to obtain the magnetic flux of the lifting wire rope 4. It is located between the two permanent magnets 130. The Hall sensor group 120 is composed of a plurality of Hall sensors, which are evenly arranged circumferentially around the outer periphery of the channel 110. The magnetic focusing device 150 is arranged on both sides of the Hall sensor group 120, and the armature 140 is used to connect the magnetic focusing device 150 and the permanent magnet 130.

[0028] The magnetic field concentrating device 150 comprises a magnetic concentrating ring and a magnetic bridge, both made of high-permeability materials (such as soft iron, Permalloy, or ferrite). The magnetic concentrating ring is annular or quasi-annular in shape, primarily concentrating and guiding the external scattered magnetic field to the magnetic bridge. The magnetic bridge, a bridge-like magnetic conductor connecting magnetic components (such as the two concentrating rings), creates a magnetic field path, regulates magnetic field distribution, and balances magnetic flux. The Hall sensor assembly 120 is located between the two concentrating rings in the magnetic bridge, forming a "sandwich" structure: concentrating ring on one side → magnetic bridge → Hall element → magnetic bridge → magnetic concentrating ring on the other side. This design ensures that the magnetic bridge becomes a necessary path for magnetic flux, effectively increasing the magnetic flux density at the sensor. When an external magnetic field is applied, the concentrating rings on both sides form a closed magnetic circuit through the magnetic bridge: magnetic flux enters the magnetic bridge from one concentrating ring, passes through the Hall sensor assembly 120, and then returns to the other concentrating ring through the magnetic bridge, completing the circuit. This closed design can reduce magnetic resistance by more than 50%. Compared with a 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 the magnetic field during transmission, and at the same time enhance the collection and utilization of the leakage magnetic field, thereby reducing the 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 field concentrating device 150 are all composed of the same half bodies and are separately installed in two half shells.

[0031] In this intelligent nondestructive monitoring device 1 for hoisting wire rope tension in mining, permanent magnets 130 are positioned inside the front and rear ends of housing 100. Channel 110 passes through the center of permanent magnets 130. A magnetic field focusing device 150 is located on either side of Hall sensor group 120. An armature 140 connects permanent magnets 130 and magnetic field focusing device 150, forming a closed magnetic field path. Permanent magnets 130 act as a magnetic field source to provide an initial magnetic field. Armature 140 adheres closely to the surface of hoisting wire rope 4, reducing magnetic field losses during transmission and enhancing the collection and utilization of leakage magnetic fields, thereby reducing magnetic resistance and enhancing magnetic field focusing.

[0032] Thermistor sensors 160 are positioned symmetrically on either side of the Hall sensor assembly 120 within the housing 100. They monitor the operating temperature of the Hall sensor assembly 120 in real time, 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 170, wound around the channel 110 between the permanent magnet 130 and the housing 100, demagnetizes the hoisting wire rope 4 to ensure that the wire rope's magnetic signal primarily originates from changes in the magnetic length signal caused by tension variations. When AC current is applied to the AC inductor 170, it generates an alternating magnetic field with alternating directions and gradually decreasing intensity. This alternating magnetic field, acting on the hoisting wire rope 4, gradually disrupts the ordered magnetic domains (the source of residual magnetic flux) formed by magnetization within the wire rope, causing their orientation to become disordered, thereby gradually weakening and eliminating the inherent magnetic flux carried by the wire rope. Specifically, the AC frequency is selected to be 10-30 Hz, and the current intensity is selected to be 50-240 A.

[0034] Please refer to Figure 1 The present invention also proposes an intelligent, nondestructive monitoring system for the tension of a mine hoisting wire rope, comprising an intelligent, nondestructive monitoring device 1 for the tension of a mine hoisting wire rope, an information transmission module 2, a host computer processing module 3, and a visualization module (not shown). The information transmission module 2 is electrically connected to the Hall sensor group 120, the rotary encoder wheel 190, and the thermistor sensor 160, respectively, and is configured to transmit 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. In other embodiments, the information transmission module 2 may also transmit information wirelessly. The host computer processing module 3 is capable of receiving and processing the signals measured by the Hall sensor group 120, the rotary 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 configured to display real-time tension data of the hoisting wire rope 4.

[0035] Please combine Figure 3 and Figure 4 , Figure 3 is a schematic diagram of a floor-type friction lifting system in an embodiment of the present invention, Figure 4The diagram is a schematic diagram of the tension distribution of the hoisting wire rope in a floor-type friction hoisting system. The present invention proposes a method for intelligent, nondestructive monitoring of the tension of mining hoisting wire ropes, comprising the following steps: Step S1: Two intelligent, nondestructive monitoring devices 1 for the tension of mining hoisting wire ropes are installed on the left and right vertical rope segments of the hoisting wire rope 4 and fixed to the derrick 8 of the floor-type friction hoisting system. The hoisting wire rope 4 passes through the two intelligent, nondestructive monitoring devices 1 for the tension of mining hoisting wire ropes. The floor-type 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 empty hoisting container 9, and a loaded hoisting container 10. The hoisting wire rope 4 passes around the friction wheel 5, through the lower guide wheel 6 and the upper guide wheel 7, and is fixedly connected to the empty hoisting container 9 and the loaded hoisting container 10. The friction wheel 5 is driven by friction with the hoisting wire rope 4, thereby raising and lowering the empty hoisting container 9 and the loaded hoisting container 10. The left vertical rope section is connected to an empty hoisting container 9, and the right vertical rope section is connected to a loaded hoisting container 10. One intelligent non-destructive monitoring device 1 for the tension of a mining hoisting wire rope is installed on the hoisting wire rope 4 on the left side of the upper guide wheel 7, that is, on the left vertical rope section. Another intelligent non-destructive monitoring device 1 for the tension of a mining hoisting wire rope is installed on the hoisting wire rope 4 on the left side of the lower guide wheel 6, that is, on the right vertical rope section.

[0036] Step S2: During the operation of the lifting wire rope 4, the two AC inductor coils 170 demagnetize the lifting wire rope 4 to remove the magnetic signal of the wire rope itself, thereby ensuring that the magnetic flux signal subsequently obtained by the Hall sensor group 120 mainly comes from the change in magnetic permeability caused by the tension of the wire rope (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 magnetic flux changes.

[0037] Step S3: Obtain the wire rope magnetic flux signal based on the Hall effect sensor group 120. Since the Hall effect sensor group 120 is composed of multiple Hall effect sensors, the average value of the magnetic flux obtained by these sensors is used as the final output value, which provides a more accurate magnetic flux measurement of the hoisting wire rope 4. The rotating encoder wheel 190 moves synchronously with the hoisting wire rope 4 to obtain the wire rope hoist height 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 the interference of temperature changes on the output signal of the Hall sensor group 120 and ensure that the magnetic flux signal can truly reflect the tension state of the wire rope. The temperature measured by the thermistor sensor 160 needs to be corrected for the magnetic flux signal. The correction formula is: ,in, is the temperature-corrected magnetic flux, is the magnetic flux at the reference temperature T0, is the temperature coefficient (determined by experiment), and T is the real-time measured temperature. The reference temperature T0 is the natural temperature before the friction lifting system is operated (e.g., 25°C). The temperature will rise after operation.

[0039] In step S5, the wire rope magnetic flux signal 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 to address noise and errors in the raw magnetic flux signal. This includes filtering electromagnetic interference (EMI) and correcting for temperature drift to ensure the magnetic flux data reflects the true physical state. This typically involves filtering (wavelet denoising, low-pass filtering) and phase-sensitive detection, directly processing the raw magnetic flux signal. Feature processing focuses on "information extraction," mining features strongly correlated with tension from the cleaned data. The peak value, slope, and frequency components of the magnetic flux are extracted to provide quantifiable and highly discriminative input for the tension model.

[0040] Step S6: Based on the obtained 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 obtained based on the rotating encoder wheel 190, the tension of the wire rope at different lifting heights is obtained in real time; the magnetic flux characteristic value corrected by temperature compensation is input into the CNN-LSTM fused lifting wire rope tension monitoring model, and then combined with the lifting height parameter to achieve accurate calculation of the lifting wire rope tension at different positions, 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: by analyzing the magnetic flux signal of the wire rope to infer the tension value, when the wire rope is subjected to different tensions, the change in internal stress state will cause the magnetic permeability to change, and then the magnetic flux signal will show regular changes. By capturing this correlation, the model can convert the pre-processed magnetic flux signal into corresponding tension data, realize real-time monitoring of wire rope tension, and provide 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 affects magnetic flux, can be expressed by the following relationship: ,in, is the magnetic flux (Wb), B is the magnetic induction intensity (T), is the magnetic permeability of the wire rope (H / m, changes with tension), H is the magnetic field intensity (A / m), and S is the cross-sectional area of ​​the magnetic circuit (m²). When the tension F changes, the magnetic permeability It can be approximately expressed as , is the magnetic permeability without tension, and k is the tension influence coefficient), so 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 changes under actual working conditions and ensure the stability of subsequent tension application and signal acquisition; 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; the specifications of the hoisting wire rope to be tested are the same as those of the hoisting wire rope 4.

[0044] Step S62: Use a universal tensile testing machine to apply different tensions to the hoisting wire rope under test step by step, covering the full range from normal working tension to ultimate breaking tension, until the wire rope breaks and becomes scrapped, so as to obtain complete data including various tension states, especially focusing on signal collection at critical tension points, laying the foundation for the model's limit state recognition capability.

[0045] Step S63: Synchronously collect the magnetic flux signals of the wire rope under different tensions through the intelligent non-destructive monitoring device 1 for the tension of the mining hoisting wire rope, and record the ambient temperature in conjunction with the temperature monitoring module during the entire 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 collected wire rope magnetic flux signal (bandpass filtering and phase-sensitive detection) and extract characteristic values ​​(such as peak values, valley values, waveform slope, spectral characteristics, etc.) to extract key characteristic parameters that can effectively reflect tension changes from the original signal, reducing the data dimension while retaining the core information.

[0047] Step S65: Based on the above processing results, a deep learning database is established that includes the characteristic values ​​of the wire rope magnetic flux signal, 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 wire rope tension monitoring model is constructed. CNN (convolutional neural network) is good at extracting local features of magnetic flux signals (such as instantaneous fluctuation features), while LSTM (long short-term memory network) can capture the temporal dependency of signals with tension changes (such as signal trends during tension gradient changes). The fusion of the two can fully explore the complex nonlinear relationship between magnetic flux and tension, so that the model has high tension recognition accuracy and generalization ability, and can adapt to the tension monitoring needs of different working conditions in actual applications. In order to more clearly illustrate how the CNN-LSTM fusion model can achieve accurate mapping of the relationship between magnetic flux signals and tension, the core components of the model will be specifically explained below, including the extraction of local features by CNN, the capture of temporal features by LSTM, and the implementation of the final tension prediction output. At the same time, the accuracy evaluation method used in the model training process is explained: (I) CNN local feature extraction: The output formula of the convolution layer is: ,in, is the jth feature map of the lth layer, M j Input feature map set, is the convolution kernel weight, is the bias, is the activation function (such as ReLU).

[0049] (2) LSTM time series feature capture: The cell state update formula is: , , where f t (Forget Gate), i t (Input gate), o t (Output gate) controls the forgetting, input and output of information respectively, c t is the cell state, is the candidate cell state, h t is the hidden layer output, which is used to capture the temporal dependence of magnetic flux on tension.

[0050] (3) Tension prediction output: The formula for the model's final output tension F is: , where h T is the hidden layer output of LSTM at the last moment, w and b are the linear layer parameters, and the mapping relationship between magnetic flux characteristics and tension is fitted through training.

[0051] The mean square error (MSE) is used to evaluate the prediction accuracy during the training process. The formula is:

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

[0053] Step S7: Evaluate the tension of the lifting wire rope and issue an alarm.

[0054] First, the method evaluates the load-bearing safety of the wire rope and determines the load-bearing status 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 intelligent non-destructive monitoring devices 1 for the tension of the lifting wire rope 4, respectively, where tension threshold I is 50% of the minimum breaking tension of the wire rope, and tension threshold II is the minimum breaking tension of the wire rope.

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

[0056] Step S713: If any of the tension F1 of the intelligent non-destructive monitoring device 1 for the tension of the mine hoisting wire rope and the tension F2 of the intelligent non-destructive monitoring device 1 for the tension of the mine hoisting wire rope is greater than the tension threshold I but less than the tension threshold II, a first-level alarm is output and the lifting height is recorded, indicating that there is a potential overload risk and attention should be paid to the tension changes at this position.

[0057] Step S714: If any one of the tension F1 and the tension F2 on the lifting wire rope 4 is greater than the tension threshold II, a secondary alarm is output and the wire rope is required to be replaced. At this time, the wire rope has approached or reached its load limit and must be stopped immediately to avoid accidents.

[0058] Secondly, the present method assesses the anti-slip safety of wire ropes. The specific steps are as follows: Step S721: The right tension F1 and the tension F2 of the intelligent non-destructive monitoring device 1 for the tension of the mine hoisting wire rope on both sides of the guide pulley of the same hoisting wire rope 4 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 for the wire rope to not slip, and tension difference threshold II is the maximum tension difference for not slipping. Based on the anti-slip mechanism of friction transmission, this method prevents safety accidents caused by slippage. The maximum tension difference for a friction hoisting system to not slip refers to the maximum tension difference allowed on both sides of the wire rope to ensure that relative slippage (i.e., no slip) does not occur between the wire rope and the friction pulley during operation of the friction hoisting system (such as a mine hoist system that relies on friction between the friction pulley 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 value I, the output wire rope is in 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, a first-level alarm is output and the lifting height of the wire rope is recorded, indicating that there is a risk of slipping and the guide wheel or wire rope status 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, a level 2 alarm is output and the wire rope is required to be repaired. At this time, the risk of slipping is extremely high and the machine must be shut down for repair to restore the anti-slip capability.

[0062] The embodiments of the present invention are described in detail above with reference to the accompanying drawings, but the present invention is not limited thereto. Various changes that can be made within the knowledge of technicians in the relevant technical field without departing from the spirit of the present invention are all within the scope of protection of the claims of the present invention.

Claims

1. An intelligent non-destructive monitoring device for the tension of a mining hoisting wire rope, characterized in that: include The housing (100) is provided with a passage (110) at the center for the lifting wire rope (4) to pass through; Permanent magnets (130) are respectively arranged 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); A Hall sensor group (120) is located between the two permanent magnets (130) and is arranged circumferentially around the outer periphery of the channel (110); A magnetic field focusing device (150) is provided on both sides of the Hall sensor group (120), and an armature (140) is used to connect the magnetic field focusing device (150) and the permanent magnet (130); The housing (100) is composed of two half-shells; the channel (110), the Hall sensor group (120), the permanent magnet (130) and the magnetic field focusing device (150) are all composed of two half-shells and are separately installed in the two half-shells; Guide wheels (180) are respectively mounted on the front and rear ends of the housing (100) and are in rolling contact with the lifting wire rope (4); The rotary encoder wheel (190) is a guide wheel (180) equipped with an encoder, and the encoder is located on one of the guide wheels (180).

2. The intelligent non-destructive monitoring device for the tension of a mining hoisting wire rope according to claim 1 is characterized in that: It also includes thermistor sensors (160) respectively arranged on both sides of the Hall sensor group (120).

3. The intelligent non-destructive monitoring device for the tension of a mining hoisting wire rope according to claim 1 is characterized in that: The invention also includes an AC inductor coil (170), which is wound on the channel (110) between the permanent magnet (130) and the housing (100).

4. The intelligent non-destructive monitoring device for the tension of a mining hoisting wire rope according to claim 1 is characterized in that: The channel (110) is made of a nylon bushing.

5. An intelligent non-destructive monitoring system for the tension of a mining hoisting wire rope, characterized in that: include: An intelligent non-destructive monitoring device (1) for tension of a mining hoisting wire rope according to any one of claims 1 to 4; The information transmission module (2) is connected to the Hall sensor group (120), the rotary encoder wheel (190) and the thermistor sensor (160) respectively by wire or wirelessly, and is used for transmitting 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.

6. A method for intelligent non-destructive monitoring of the tension of a mine hoisting wire rope, based on the intelligent non-destructive monitoring system for the tension of a mine hoisting wire rope according to claim 5, characterized in that: The method comprises the following steps: Step S1, two intelligent non-destructive monitoring devices (1) for the tension of a hoisting wire rope for mining are respectively installed on the left vertical rope section and the right vertical rope section of the hoisting wire rope (4) on both sides of the friction wheel (5), and fixed on the derrick (8); Step S2: After the lifting wire rope (4) is running, two AC inductance coils (170) are used to demagnetize the lifting wire rope (4) to remove the magnetic flux of the lifting wire rope (4); Step S3, using the Hall sensor group (120) to obtain the magnetic flux signal of the lifting wire rope (4) after demagnetization; Step S4: using a thermistor sensor (160) to obtain the operating temperature of the Hall sensor group (120) and correcting the magnetic flux signal; Step S5: transmitting the magnetic flux signal of the lifting wire rope (4) from the information transmission module (2) to the host computer processing module (3), and performing preprocessing and feature value extraction on the magnetic flux signal; Step S6: establishing a wire rope tension monitoring model, and converting the acquired magnetic flux signal of the lifting wire rope (4) into wire rope tension data in real time through the wire rope tension monitoring model; Step S7: Evaluate the tension of the lifting wire rope and issue a graded alarm.

7. The intelligent non-destructive monitoring method for the tension of a mining hoisting wire rope according to claim 6, characterized in that: In step S4, the magnetic flux signal is corrected, and the correction formula is: , in, is the temperature-corrected magnetic flux, is the magnetic flux at the reference temperature T0, is the temperature coefficient, and T is the real-time measured temperature.

8. The intelligent non-destructive monitoring method for the tension of a mining hoisting wire rope according to claim 6, characterized in that: In step S6, the method for establishing the wire rope tension monitoring model is: Step S61: placing the hoisting wire rope to be tested on a universal tensile testing machine, and installing 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: Using a universal tensile testing machine, applying different tensions to the hoisting wire rope to be tested step by step until the wire rope breaks and becomes scrapped; Step S63: obtaining magnetic flux signals of the wire rope at different tensions through the intelligent non-destructive monitoring device (1) for the tension of the mining hoisting wire rope, and obtaining the operating temperature of the Hall sensor group (120) through the thermistor sensor (160); Step S64: preprocessing and extracting characteristic values ​​of the wire rope magnetic flux signal; Step S65: Establish a deep learning database of the wire rope magnetic flux signal characteristic values, corresponding tension data and temperature data; Step S66: Based on the deep learning database, a CNN-LSTM fusion wire rope tension monitoring model is established.

9. The intelligent non-destructive monitoring method for the tension of a mining hoisting wire rope according to claim 6, characterized in that: In step S7, the tension of the hoisting wire rope is evaluated and graded alarms are issued, including load safety evaluation and graded alarms. The specific steps are as follows: S711. Set tension threshold I and tension threshold II for the wire rope tension, respectively, where 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; S712: If the wire rope tension is less than the tension threshold I, the output wire rope load-bearing state is good; S713: If the wire rope tension is greater than tension threshold I but less than tension threshold II, a level 1 alarm is output and the wire rope lifting height is recorded; S714: If the wire rope tension is greater than the tension threshold II, a level 2 alarm is output and the wire rope is replaced.

10. The intelligent non-destructive monitoring method for the tension of a mining hoisting wire rope according to claim 6, characterized in that: In step S7, the tension of the hoisting wire rope is evaluated and graded alarms are issued, which also includes anti-slip safety evaluation and graded alarms. The specific steps are as follows: S721, performing a tension difference process on the left vertical rope segment and the right vertical rope segment of the lifting wire rope (4), and setting a tension difference threshold I and a tension difference threshold II respectively, wherein the tension difference threshold I is 50% of the maximum tension difference of the wire rope without slipping, and the tension difference threshold II is the maximum tension difference without slipping; S722: If the wire rope tension difference is less than the tension difference threshold value I, output that the wire rope anti-slip state is good; S723: If the wire rope tension difference is greater than tension difference threshold I but less than tension difference threshold II, a level 1 alarm is output and the wire rope lifting height is recorded; S724: If the wire rope tension difference is greater than the tension difference threshold II, a level 2 alarm is output and the wire rope is inspected.

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