Broken axle monitoring device for wheel axle of cart running mechanism

Abstract

The invention discloses a cart running mechanism wheel axle breakage monitoring device, which relates to the technical field of hoisting machinery wheel axle breakage fault diagnosis, and comprises the steps of monitoring the running speed of a cart running mechanism in real time, calculating the acceleration and the acceleration change rate of the cart running mechanism, and calculating characteristic indexes based on the strain value and stress of each wheel axle when the running speed and the acceleration change rate are stable. When the characteristic index exceeds a first preset threshold value and lasts for a first preset time, after a preliminary abnormity judgment signal is generated, the state of the cart running mechanism is kept unchanged, the cart running mechanism is controlled to apply a traction force increment which is slightly increased relative to the current traction force, and the vehicle enters a verification working condition; and executing the broken shaft risk judgment strategy, outputting a risk type, and executing a corresponding security strategy. According to the invention, the problems of high false alarm rate and low sensitivity of online detection of the wheel axle of the crane running mechanism of the bridge type crane are solved.

Description

Technical Field

[0001] This invention relates to the field of fault diagnosis technology for broken wheel axles of crane machinery, specifically a broken wheel axle monitoring device for trolley traveling mechanisms. Background Technology

[0002] In the field of industrial wheel and axle health monitoring, both high-speed rail vehicles and low-speed, heavy-load bridge-type cranes employ both offline and online monitoring methods. Offline monitoring involves professional personnel conducting manual inspections at regular intervals using non-destructive testing equipment. This method has a long inspection cycle, is highly subjective, and cannot meet the safety early warning requirements for continuous operation. Online, real-time proactive monitoring is gradually becoming the major trend.

[0003] While online monitoring technology is maturing in fields such as high-speed rail vehicles, its direct application to lifting machinery faces significant challenges. On one hand, while acoustic emission detection technology is highly sensitive to crack initiation and propagation, the extremely strong background noise at crane sites easily masks or confuses the actual acoustic emission signals from cracks, leading to a high false alarm rate and imposing stringent requirements on the acoustic environment and signal processing. On the other hand, vibration analysis-based methods are highly effective for high-speed rotating machinery, but for cranes operating at lower speeds, the vibration characteristic frequencies excited by crack propagation are extremely low and the energy is weak, easily drowned out by strong structural vibrations and operational impacts, resulting in severely insufficient monitoring sensitivity and difficulty in achieving early warning. Existing online solutions are ill-suited to the special working conditions of gantry cranes operating at low speeds and under heavy loads.

[0004] Therefore, it is essential to design a broken axle monitoring device for the trolley traveling mechanism of a bridge crane that combines high reliability and sensitivity. Summary of the Invention

[0005] The purpose of this invention is to provide a device for monitoring broken axles of trolley running mechanisms to solve the problems mentioned in the background art.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a wheel axle breakage monitoring device for a trolley traveling mechanism, comprising the following steps: Step S100: Real-time monitoring of the operating speed of the trolley traveling mechanism. Calculate the acceleration of the trolley traveling mechanism. and rate of change of acceleration ; Step S200: When the rate of change of acceleration At that time, the threshold of the rate of change of acceleration The value range is 0.05-0.1 m / s³. The strain value and stress of each wheel axle of the trolley traveling mechanism are detected. The wheel axles of the trolley traveling mechanism include N driving wheel axles with driving torque transmitted by motors and M driven wheel axles without driving torque transmitted by motors. Step S300: Based on the strain value and stress of each wheel axle, calculate the characteristic index. When the characteristic index exceeds the first preset threshold and lasts for a first preset time, generate a preliminary abnormal judgment signal, keep the trolley running mechanism unchanged, control the trolley running mechanism to apply a traction force increment that is slightly increased relative to the current traction force, so that the vehicle enters the verification working condition, lasts for a second preset time, and then recovers. Step S400: Under the verification condition, execute the shaft breakage risk assessment strategy, output the risk type, and execute the corresponding safety strategy.

[0007] According to the above technical solution, step S200 further includes: Step S210: Establish a baseline database for each of the N drive axles in a healthy state, the baseline database including the torsional strain-traction force curve of each drive axle. Stress kurtosis benchmark Includes mean and standard deviation ; Step S220: When the rate of change of acceleration Furthermore, when the duration exceeds 3 seconds, the strain and stress values ​​of the drive wheel axle are measured. The strain values ​​include torsional strain values. and bending strain value , The stress , where E and G are the Young's modulus and shear modulus of the drive wheel shaft, respectively.

[0008] According to the above technical solution, step S300 further includes: Step S310: Calculate the stress kurtosis of the i-th driving wheel axle. When stress kurtosis Greater than the threshold When the condition persists for a first preset time, a preliminary anomaly detection signal is generated. Step S320: Keep the current operating state of the trolley traveling mechanism unchanged, and apply the current traction force to the i-th drive wheel axle. Apply traction increments on the basis The process continues for a second preset time and then resumes, where the value of k ranges from 5% to 10%.

[0009] According to the above technical solution, step S400 further includes: Step S410: Calculate the incremental traction force applied to the i-th driving axle under healthy conditions. At that time, the expected strain response value and healthy torsional stiffness , where R is the wheel radius and A is the axle cross-sectional area; Step S420: Detect the incremental traction force applied to the i-th drive axle At that time, the torsional strain increment is The dynamic torsional stiffness was calculated. Compared with dynamic stiffness ; Step S421: When the ratio of dynamic stiffness If the value is less than or equal to 0.3, a broken shaft alarm will be issued, and the machine will be stopped for inspection and replacement. Step S422: When the ratio of dynamic stiffness When the value is greater than 0.3 and less than or equal to 0.85, a wheel axle crack warning will be issued, and staff will be notified to carry out inspection or strengthen monitoring; Step S423: Calculate the difference in bending strain between the applied traction force increment after recovery and before application as the residual strain. When the residual strain This indicates plastic deformation of the wheel axle.

[0010] According to the above technical solution, step S200 further includes: Step S210': Establish a baseline database for each of the M driven wheel axles in a healthy state, the baseline database including the bending strain-traction force curve of each driven wheel axle. Bending strain kurtosis benchmark Includes mean and standard deviation ; Step S220': When the rate of change of acceleration Furthermore, when the duration exceeds 3 seconds, the bending strain value of the driven wheel shaft is measured. , .

[0011] According to the above technical solution, step S300 further includes: Step S310': Calculate the bending strain kurtosis of the j-th driven wheel axle. When bending strain kurtosis Greater than the threshold When the condition persists for a first preset time, a preliminary anomaly detection signal is generated. Step S320': Keep the current operating state of the trolley traveling mechanism unchanged, and apply the current traction force to the entire trolley traveling mechanism. Apply traction increments on the basis The process continues for a second preset time and then resumes, where the value of k ranges from 5% to 10%.

[0012] According to the above technical solution, step S400 further includes: Step S410': The transfer function relationship between the bending strain response of the j-th driven wheel axle and the incremental traction force of the driving wheel axle under healthy conditions is expressed as follows: The healthy bending response coefficient was calculated. ; Step S420': Detect the incremental traction force applied to the j-th driven wheel axle When, the increment of the bending strain value is The measured bending response coefficient was calculated. and bending response deviation ; Step S421': When the bending response deviates from the degree When the value is greater than or equal to 100%, a warning of permanent bending deformation of the wheel axle will be issued, and staff will be notified to carry out maintenance. Step S422': When the bending response deviates from the degree If the percentage is greater than 40% but less than 100%, staff should be informed to strengthen monitoring. Step S423': Monitor the torsional strain value of the driven wheel shaft. When the parasitic torque of the driven wheel axle increases When the value is greater than zero, it indicates that there may be a fault in the wheel bearing or track, and informs the staff to carry out maintenance.

[0013] The above technical solution includes an operation status monitoring module, a wheel and axle strain detection module, an anomaly diagnosis module, and a safety execution module: The operation status monitoring module is configured to monitor the operating speed of the trolley traveling mechanism in real time, and calculate the real-time acceleration and the rate of change of acceleration based on the operating speed; The wheel axle strain detection module is communicatively connected to the operation status monitoring module and is configured to start detecting the strain values ​​of all wheel axles of the trolley running mechanism when the absolute value of the acceleration change rate is not greater than a preset stable working condition threshold. The wheel axles include N motor-driven active wheel axles and M motor-free driven passive wheel axles. The anomaly diagnosis module is communicatively connected to the operation status monitoring module and the wheel axle strain detection module, and is configured to generate a preliminary anomaly judgment signal for the wheel axle when any characteristic index of the wheel axle exceeds its corresponding first preset threshold and lasts for a first preset time. The security execution module is communicatively connected to the anomaly diagnosis module and is configured to execute a predetermined security strategy corresponding to the risk level and risk type based on the received diagnosis results. Furthermore, the anomaly diagnosis module is configured to, after generating a preliminary anomaly determination signal, apply a traction force increment that is slightly higher than the current traction force, causing the vehicle to enter the verification condition, perform axle breakage risk confirmation judgment, and output a diagnosis result, which at least includes the risk level and risk type. According to the above technical solution, the strain value includes torsional strain value and bending strain value, which are obtained by detecting the connection between the wheel axle and the wheel, and the connection between the wheel axle and the bearing, respectively.

[0014] According to the above technical solution, the torsional strain value is determined by the stress on the same cross-section of the wheel axle along a line perpendicular to the axis. Four strain gauges were pasted in the direction of the object and connected to form a Wheatstone full-bridge circuit for measurement. The bending strain value is measured by a Wheatstone full-bridge circuit formed by attaching two axial strain gauges to the upper and lower surfaces of the wheel axle, which are in contact with the bearing support point, along the axial direction.

[0015] Compared with the prior art, the beneficial effects achieved by the present invention are: (1) By monitoring the strain of the wheel axle, the structural state can be directly perceived from the mechanical essence to realize the monitoring of broken axle. After the initial detection of the abnormality, a controlled traction force increment is actively applied to create a verification working condition. It can effectively distinguish between the real crack response synchronized with the load and the random instantaneous interference, thereby achieving the unity of high sensitivity perception and high reliability judgment of early faults.

[0016] (2) By analyzing the dynamic stiffness ratio and residual strain of the active wheel shaft under the verification working condition, and monitoring the bending response deviation and parasitic torque of the driven wheel shaft, the accurate differentiation and graded early warning of shaft breakage, crack propagation, plastic deformation and related system failures are realized, achieving high sensitivity perception and high reliability early warning, significantly improving the accuracy of diagnosis and the pertinence of maintenance. Attached Figure Description

[0017] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings: Figure 1 This is a schematic diagram of the method steps of the present invention; Figure 2 This is a schematic diagram of the system module composition of the present invention; Figure 3 This is a diagram showing the location of the strain sensor when detecting torsional strain values ​​according to an embodiment of the present invention; Figure 4 This is a diagram showing the location of the strain sensor when detecting bending strain values ​​according to an embodiment of the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Example 1 Please see Figure 1 This invention provides a technical solution: a device for monitoring broken axle of a trolley running mechanism, comprising the following steps: Step S100: Real-time monitoring of the operating speed of the trolley traveling mechanism. Calculate the acceleration of the trolley traveling mechanism. and rate of change of acceleration ; Step S200: When the rate of change of acceleration At that time, the threshold of the rate of change of acceleration The value range is 0.05-0.1 m / s³. The strain values ​​of each wheel axle of the trolley traveling mechanism are then measured. and stress The wheel axles of the trolley running mechanism include N driving wheel axles whose driving torque is transmitted by a motor and M driven wheel axles whose driving torque is not transmitted by a motor; Step S300: Based on the strain values ​​of each wheel axle and stress Calculate the characteristic index. When the characteristic index exceeds the first preset threshold and lasts for a first preset time, generate a preliminary anomaly judgment signal, keep the trolley running mechanism unchanged, control the trolley running mechanism to apply a traction force increment that is slightly increased relative to the current traction force, so that the vehicle enters the verification working condition, lasts for a second preset time, and then recovers. Step S400: Under the verification condition, execute the shaft breakage risk assessment strategy, output the risk type, and execute the corresponding safety strategy.

[0020] This invention overcomes the problem of insufficient sensitivity in vibration analysis under low-speed conditions by directly sensing the structural state from the mechanical essence through monitoring wheel and axle strain. Furthermore, after initial anomaly detection, a controlled traction force increment is actively applied to create a verification condition, effectively distinguishing between real crack responses synchronized with the load and random transient disturbances. This solves the reliability bottleneck caused by strong on-site noise and susceptibility to false alarms, thus achieving a unified high-sensitivity detection and high-reliability judgment of early faults, providing precise and effective online protection for the safe operation of the trolley traveling mechanism.

[0021] Specifically, for the drive axle, step S200 further includes: Step S210: Establish a baseline database for each of the N drive axles in a healthy state, the baseline database including the torsional strain-traction force curve of each drive axle. Bending strain-traction force curve Stress kurtosis benchmark Includes mean and standard deviation The reference data includes models of uniform or uniformly accelerated motion under various working conditions, such as horizontal or sloping surfaces.

[0022] Step S220: When the rate of change of acceleration Furthermore, when the duration exceeds 3 seconds, the strain and stress values ​​of the drive wheel axle are measured. The strain values ​​include torsional strain values. and bending strain value , The stress Where E and G are the Young's modulus and shear modulus of the drive wheel axle, respectively. By ensuring that the rate of change of acceleration remains below the threshold and this stable state is maintained for more than 3 seconds, transient processes such as crane start-up and braking are effectively avoided, ensuring that strain values ​​are collected during the stable operation phase, providing a reliable data foundation for subsequent anomaly diagnosis.

[0023] Specifically, step S300 further includes: Step S310: Calculate the stress kurtosis of the i-th driving wheel axle. When stress kurtosis Greater than the threshold When, and for a duration of a first preset time, a preliminary anomaly detection signal is generated; wherein This is the mean.

[0024] Step S320: Keep the current operating state of the trolley traveling mechanism unchanged, and apply the current traction force to the i-th drive wheel axle. Apply traction increments on the basis The process continues for a second preset time and then resumes, where the value of k ranges from 5% to 10%. That is, it maintains this running state unchanged under either a constant-speed running state with zero acceleration or a uniformly accelerated running state with a fixed acceleration value.

[0025] For example, when the wheel axles of the trolley traveling mechanism are running at a constant speed during the stable phase, the stress on the i-th driving wheel axle is approximately a sinusoidal function with the wheel rotation period as the fundamental frequency. When a transient impact such as crack opening or closing occurs, the kurtosis is sensitive to this impact signal; that is, even if this damage signal is almost completely submerged by noise in the time-domain waveform, it will still cause the kurtosis value to increase significantly, thus achieving early warning. Maintaining the operating state unchanged, active stress is then applied to this driving wheel axle. This allows the drive axle to enter a verification condition within a second preset time range to further verify this initial anomaly.

[0026] Specifically, step S400 further includes: Step S410: Calculate the incremental traction force applied to the i-th driving axle under healthy conditions. At that time, the expected strain response value and healthy torsional stiffness , where R is the wheel radius and A is the axle cross-sectional area; Step S420: Detect the incremental traction force applied to the i-th drive axle At that time, the torsional strain increment is The dynamic torsional stiffness was calculated. Compared with dynamic stiffness ; Step S421: When the ratio of dynamic stiffness When the value is less than or equal to 0.3, a broken axle alarm is issued, and the machine is stopped for inspection and replacement. When the drive wheel axle has cracks or breaks, its effective load-bearing cross-sectional area decreases. When the stiffness drops by more than 70%, the wheel axle structure has seriously failed and there is an immediate safety risk.

[0027] Step S422: When the ratio of dynamic stiffness When the value is greater than 0.3 and less than or equal to 0.85, a wheel axle crack warning is issued, and staff are notified to carry out maintenance or strengthen monitoring. By identifying performance degradation in advance during the crack propagation stage before wheel axle fracture, a critical time window is provided for planned maintenance, playing an early warning role.

[0028] Step S423: Calculate the difference in bending strain between the applied traction force increment after recovery and before application as the residual strain. When the residual strain This indicates plastic deformation of the wheel axle. By detecting residual strain, it identifies irreversible plastic deformations such as those caused by overload impacts.

[0029] This invention achieves precise fault classification and type identification through multi-index fusion and quantification thresholds. Targeting the characteristics of the drive axle, it uses dynamic stiffness ratio to quantify the degree of bearing capacity degradation, distinguishing between two risk levels: axle breakage and crack propagation, and triggering differentiated response strategies. Residual strain is incorporated as an auxiliary criterion, effectively identifying plastic deformation damage. This entire set of criteria constitutes a complete and operable decision-making system from emergency shutdown due to severe faults to early damage warning, significantly improving the accuracy of diagnosis and the targeted nature of maintenance.

[0030] Specifically, for the driven wheel shaft, step S200 further includes: Step S210': Establish a baseline database for each of the M driven wheel axles in a healthy state, the baseline database including the bending strain-traction force curve of each driven wheel axle. Bending strain kurtosis benchmark Includes mean and standard deviation ; Step S220': When the rate of change of acceleration Furthermore, when the duration exceeds 3 seconds, the bending strain value of the driven wheel shaft is measured. , Since the driven wheel shaft is theoretically not driven by a motor and mainly bears bending loads, the copper drum core monitors its bending strain to achieve monitoring.

[0031] Specifically, step S300 further includes: Step S310': Calculate the bending strain kurtosis of the j-th driven wheel axle. When bending strain kurtosis Greater than the threshold When the condition persists for a first preset time, a preliminary anomaly detection signal is generated. Step S320': Keep the current operating state of the trolley traveling mechanism unchanged, and apply the current traction force to the entire trolley traveling mechanism. Apply traction increments on the basis The process continues for a second preset time and then resumes, where the value of k ranges from 5% to 10%. Utilizing the overall integrity of the crane structure, when an incremental traction force is applied to the entire trolley mechanism... At this time, the force will be transmitted to all driven wheel axles through the frame in the form of additional bending moment and shear force. If a driven wheel axle has a crack or damage, its local stiffness will be reduced, and it will produce an abnormally amplified bending strain response under the same additional load. Therefore, by monitoring and analyzing the bending strain changes of each driven wheel axle under the verification condition, its structural integrity can be indirectly assessed.

[0032] Specifically, step S400 further includes: Step S410': The transfer function relationship between the bending strain response of the j-th driven wheel axle and the incremental traction force of the driving wheel axle under healthy conditions is expressed as follows: The healthy bending response coefficient was calculated. ; Step S420': Detect the incremental traction force applied to the j-th driven wheel axle When, the increment of the bending strain value is The measured bending response coefficient was calculated. and bending response deviation ; Step S421': When the bending response deviates from the degree When the value is greater than or equal to 100%, a warning of permanent bending deformation of the wheel axle will be issued, and staff will be notified to carry out maintenance. Step S422': When the bending response deviates from the degree If the percentage is greater than 40% but less than 100%, staff should be informed to strengthen monitoring. Step S423': Monitor the torsional strain value of the driven wheel shaft. When the parasitic torque of the driven wheel axle increases When the value is greater than zero, it indicates that there may be a fault in the wheel bearing or track, and informs the staff to carry out maintenance.

[0033] Step S410': The transfer function relationship between the bending strain response of the j-th driven wheel axle and the incremental traction force of the driving wheel axle under healthy conditions is expressed as follows: The healthy bending response coefficient was calculated. ; Step S420': Detect the incremental traction force applied to the j-th driven wheel axle When, the increment of the bending strain value is The measured bending response coefficient was calculated. and bending response deviation ; Step S421': When the bending response deviates from the degree When the value is greater than or equal to 100%, a warning of permanent bending deformation of the wheel axle is issued, and the staff is notified to carry out maintenance; when the driven wheel axle undergoes permanent bending plastic deformation, this high threshold can reliably warn of structural damage caused by permanent bending plastic deformation.

[0034] Step S422': When the bending response deviates from the degree When the rate is greater than 40% but less than 100%, staff should be informed to strengthen monitoring; by identifying performance degradation in advance during the crack propagation stage before wheel axle fracture, an early warning function can be achieved.

[0035] Step S423': Monitor the torsional strain value of the driven wheel shaft. When the parasitic torque of the driven wheel axle increases A value greater than zero indicates a potential fault in the wheel bearing or track, and prompts staff to inspect and repair it. Ideally, a healthy driven wheel axle should only withstand bending. The presence of parasitic torque directly indicates an abnormally increased rotational resistance, usually stemming from a surge in frictional torque due to bearing failure or severe track unevenness or jamming forcing torsional deformation of the wheel axle. This is detected by monitoring a non-zero value. This can effectively indicate associated faults in these support and mobility systems. This invention establishes a transfer function relationship between the bending strain of the driven wheel axle and the incremental traction force of the driving wheel axle. During detection, it actively applies the incremental traction force and calculates the driven wheel axle's response and deviation from the benchmark, thereby effectively distinguishing and classifying permanent bending plastic deformation from fatigue crack propagation. Simultaneously, by monitoring and verifying the presence of parasitic torque increments that should not occur under the current operating conditions, it can indirectly diagnose related faults such as wheel bearing damage or track jamming. This solution achieves a comprehensive and quantitative assessment of the condition of the driven wheel axle and its support system, solving the problem of condition perception and accurate diagnosis when the driven wheel axle lacks a direct excitation source.

[0036] Example 2 See Figure 2 The present invention also provides a wheel axle breakage monitoring device for a trolley traveling mechanism, including an operating status monitoring module, a wheel axle strain detection module, an anomaly diagnosis module, and a safety execution module: The operation status monitoring module is configured to monitor the operating speed of the trolley traveling mechanism in real time, and calculate the real-time acceleration and the rate of change of acceleration based on the operating speed; The wheel axle strain detection module is communicatively connected to the operation status monitoring module and is configured to start detecting the strain values ​​of all wheel axles of the trolley running mechanism when the absolute value of the acceleration change rate is not greater than a preset stable working condition threshold. The wheel axles include N motor-driven active wheel axles and M motor-free driven passive wheel axles. The anomaly diagnosis module is communicatively connected to the operation status monitoring module and the wheel axle strain detection module, and is configured to generate a preliminary anomaly judgment signal for the axle when the characteristic index of any of the active wheel axles exceeds its corresponding first preset threshold and lasts for a first preset time. The security execution module is communicatively connected to the anomaly diagnosis and verification control module and is configured to execute a predetermined security strategy corresponding to the risk level and risk type based on the received diagnosis results. Furthermore, the anomaly diagnosis module is also configured to apply a traction force increment that is slightly increased relative to the current traction force after generating a preliminary anomaly judgment signal, so that the vehicle enters the verification condition, performs the axle breakage risk confirmation judgment, and outputs the diagnosis result, which includes at least the risk level and risk type.

[0037] Specifically, the strain values ​​include torsional strain and bending strain. The torsional strain value is obtained by detecting the connection between the wheel axle and the wheel. When the axle transmits torque, the maximum shear stress on its surface (directly related to torsional strain) is basically uniform across the entire axle, but it is least affected by other loads near the point of torque application, i.e., the wheel.

[0038] Specifically, such as Figure 3 As shown, the torsional strain value is determined by the stress on the same cross-section of the wheel axle along a line perpendicular to the axis. Four strain gauges were attached in the direction of the curve and connected to form a Wheatstone full-bridge circuit for measurement.

[0039] The bending strain value is obtained by testing the connection between the wheel axle and the bearing. The bearing housing is the main support point of the wheel axle, bearing the vertical force and possible lateral force from the crane structure; this is the area with the largest bending moment.

[0040] Specifically, such as Figure 4 As shown, the bending strain value is measured by a Wheatstone full-bridge circuit formed by attaching two axial strain gauges to the upper and lower surfaces of the wheel axle, which are in contact with the bearing support point, along the axial direction.

[0041] In summary, this invention combines real-time strain monitoring with active load verification. Based on the mechanical response characteristics of wheel axles (including active and driven axles) under stable and controlled verification conditions, it transforms these characteristics into a graded fault determination and damage type identification based on dynamic thresholds and multi-index fusion. This achieves highly sensitive perception and high-reliability early warning of wheel axle fracture, early fatigue cracks, plastic deformation, and related system failures in noisy, low-speed, heavy-load industrial environments. This significantly improves the accuracy of online assessment of the operational safety status of large lifting equipment and the pertinence of maintenance decisions.

[0042] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0043] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0044] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0045] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims. All of these forms are within the protection scope of the present invention.

Claims

1. A device for monitoring broken axle of a trolley traveling mechanism, characterized in that, Includes the following steps: Step S100: Real-time monitoring of the operating speed of the trolley traveling mechanism. Calculate the acceleration of the trolley traveling mechanism. and rate of change of acceleration ; Step S200: When the rate of change of acceleration At that time, the threshold of the rate of change of acceleration The value range is 0.05-0.1 m / s³. The strain value and stress of each wheel axle of the trolley traveling mechanism are detected. The wheel axles of the trolley traveling mechanism include N driving wheel axles with driving torque transmitted by motors and M driven wheel axles without driving torque transmitted by motors. Step S300: Based on the strain value and stress of each wheel axle, calculate the characteristic index. When the characteristic index exceeds the first preset threshold and lasts for a first preset time, generate a preliminary abnormal judgment signal, keep the trolley running mechanism unchanged, control the trolley running mechanism to apply a traction force increment that is slightly increased relative to the current traction force, so that the vehicle enters the verification working condition, lasts for a second preset time, and then recovers. Step S400: Under the verification condition, execute the shaft breakage risk assessment strategy, output the risk type, and execute the corresponding safety strategy.

2. The wheel axle breakage monitoring device for a trolley traveling mechanism according to claim 1, characterized in that, Step S200 further includes: Step S210: Establish a baseline database for each of the N drive axles in a healthy state, the baseline database including the torsional strain-traction force curve of each drive axle. Stress kurtosis benchmark Includes mean and standard deviation ; Step S220: When the rate of change of acceleration Furthermore, when the duration exceeds 3 seconds, the strain and stress values ​​of the drive wheel axle are measured. The strain values ​​include torsional strain values. and bending strain value , The stress , where E and G are the Young's modulus and shear modulus of the drive wheel shaft, respectively.

3. The wheel axle breakage monitoring device for a trolley traveling mechanism according to claim 1, characterized in that, Step S300 further includes: Step S310: Calculate the stress kurtosis of the i-th driving wheel axle. When stress kurtosis Greater than the threshold When the condition persists for a first preset time, a preliminary anomaly detection signal is generated. Step S320: Keep the current operating state of the trolley traveling mechanism unchanged, and apply the current traction force to the i-th drive wheel axle. Apply traction increments on the basis The process continues for a second preset time and then resumes, where the value of k ranges from 5% to 10%.

4. The wheel axle breakage monitoring device for a trolley traveling mechanism according to claim 3, characterized in that, Step S400 further includes: Step S410: Calculate the incremental traction force applied to the i-th driving axle under healthy conditions. At that time, the expected strain response value and healthy torsional stiffness , where R is the wheel radius and A is the axle cross-sectional area; Step S420: Detect the incremental traction force applied to the i-th drive axle At that time, the torsional strain increment is The dynamic torsional stiffness was calculated. Compared with dynamic stiffness ; Step S421: When the ratio of dynamic stiffness If the value is less than or equal to 0.3, a broken shaft alarm will be issued, and the machine will be stopped for inspection and replacement. Step S422: When the ratio of dynamic stiffness When the value is greater than 0.3 and less than or equal to 0.85, a wheel axle crack warning will be issued, and staff will be notified to carry out inspection or strengthen monitoring; Step S423: Calculate the difference in bending strain between the applied traction force increment after recovery and before application as the residual strain. When the residual strain This indicates plastic deformation of the wheel axle.

5. The wheel axle breakage monitoring device for a trolley traveling mechanism according to claim 1, characterized in that, Step S200 further includes: Step S210': Establish a baseline database for each of the M driven wheel axles in a healthy state, the baseline database including the bending strain-traction force curve of each driven wheel axle. Bending strain kurtosis benchmark Includes mean and standard deviation ; Step S220': When the rate of change of acceleration Furthermore, when the duration exceeds 3 seconds, the bending strain value of the driven wheel shaft is measured. , .

6. The wheel axle breakage monitoring device for a trolley traveling mechanism according to claim 5, characterized in that, Step S300 further includes: Step S310': Calculate the bending strain kurtosis of the j-th driven wheel axle. When bending strain kurtosis Greater than the threshold When the condition persists for a first preset time, a preliminary anomaly detection signal is generated. Step S320': Keep the current operating state of the trolley traveling mechanism unchanged, and apply the current traction force to the entire trolley traveling mechanism. Apply traction increments on the basis The process continues for a second preset time and then resumes, where the value of k ranges from 5% to 10%.

7. The wheel axle breakage monitoring device for a trolley traveling mechanism according to claim 6, characterized in that, Step S400 further includes: Step S410': The transfer function relationship between the bending strain response of the j-th driven wheel axle and the incremental traction force of the driving wheel axle under healthy conditions is expressed as follows: The healthy bending response coefficient was calculated. ; Step S420': Detect the incremental traction force applied to the j-th driven wheel axle When, the increment of the bending strain value is The measured bending response coefficient was calculated. and bending response deviation ; Step S421': When the bending response deviates from the degree When the value is greater than or equal to 100%, a warning of permanent bending deformation of the wheel axle will be issued, and staff will be notified to carry out maintenance. Step S422': When the bending response deviates from the degree If the percentage is greater than 40% but less than 100%, staff should be informed to strengthen monitoring. Step S423': Monitor the torsional strain value of the driven wheel shaft. When the parasitic torque of the driven wheel axle increases When the value is greater than zero, it indicates that there may be a fault in the wheel bearing or track, and informs the staff to carry out maintenance.

8. The wheel axle breakage monitoring device for a trolley traveling mechanism according to claim 7, comprising an operating status monitoring module, a wheel axle strain detection module, an anomaly diagnosis module, and a safety execution module, characterized in that: The operation status monitoring module is configured to monitor the operating speed of the trolley traveling mechanism in real time, and calculate the real-time acceleration and the rate of change of acceleration based on the operating speed; The wheel axle strain detection module is communicatively connected to the operation status monitoring module and is configured to start detecting the strain values ​​of all wheel axles of the trolley running mechanism when the absolute value of the acceleration change rate is not greater than a preset stable working condition threshold. The wheel axles include N motor-driven active wheel axles and M motor-free driven passive wheel axles. The anomaly diagnosis module is communicatively connected to the operation status monitoring module and the wheel axle strain detection module, and is configured to generate a preliminary anomaly judgment signal for the wheel axle when any characteristic index of the wheel axle exceeds its corresponding first preset threshold and lasts for a first preset time. The security execution module is communicatively connected to the anomaly diagnosis module and is configured to execute a predetermined security strategy corresponding to the risk level and risk type based on the received diagnosis results. Furthermore, the anomaly diagnosis module is also configured to apply a traction force increment that is slightly increased relative to the current traction force after generating a preliminary anomaly judgment signal, so that the vehicle enters the verification condition, performs the axle breakage risk confirmation judgment, and outputs the diagnosis result, which includes at least the risk level and risk type.

9. The axle breakage monitoring device for a trolley running mechanism according to claim 8, characterized in that: The strain values ​​include torsional strain values ​​and bending strain values, which are obtained by detecting the connection points between the wheel axle and the wheel, and between the wheel axle and the bearing, respectively.

10. The wheel axle breakage monitoring device for a trolley traveling mechanism according to claim 9, characterized in that: The torsional strain value is determined by the ratio of the strain values ​​on the same cross section of the wheel axle along the axis. Four strain gauges were pasted in the direction of the object and connected to form a Wheatstone full-bridge circuit for measurement. The bending strain value is measured by a Wheatstone full-bridge circuit formed by attaching two axial strain gauges to the upper and lower surfaces of the wheel axle, which are in contact with the bearing support point, along the axial direction.

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