WO2025201642A1

WO2025201642A1 - Mining rope diagnostics

Info

Publication number: WO2025201642A1
Application number: PCT/EP2024/058351
Authority: WO
Inventors: Krystof Kryniski; Mike Davis; Tim Gartner; Daniel NOLKRANTZ; Sean Martin
Original assignee: ABB Schweiz AG
Current assignee: ABB Schweiz AG
Priority date: 2024-03-27
Filing date: 2024-03-27
Publication date: 2025-10-02
Anticipated expiration: 2026-09-27

Abstract

The present invention generally relates to a computer-implemented method for rope diagnostics in a mine hoist system comprising a powered drum, at least one sheave with multiple wheels, and one rope for each wheel, the ropes being guided by the wheels and moved by the drum to transfer a load, the method comprising: providing (S102) a dynamic model (126) that relates stress in a wheel (106) to a rope tension under a given load, acquiring (S104) mechanical stress data, measured by stress sensors (108) mounted on the wheels (106), indicative of mechanical stress in each of the wheels (106), determining (S106) a rope tension parameter value for each rope (110) based on the stress data and the dynamic model (126), detecting (S108) a relative change between rope tension parameter values for at least two ropes, determining (S110) a rope deterioration output when the relative change fulfills a predetermined criterion, and providing (S112) an output message (M) comprising the rope deterioration output.

Description

MINING ROPE DIAGNOSTICS

Field of the Invention

The present invention generally relates to a method for rope diagnostics in a mine hoist system, to a control unit for executing the method, to a computer program product and to a mine hoist system.

Background

Mine rope hoisting system are used for underground vertical transportation of heavy loads. To ensure safety, the mining ropes may be manually inspected at low operation speed or even a complete stop of the hoist system at regular intervals such as weekly or monthly. More rarely, the ropes are inspected using for example magnetic rope testing techniques.

Overall, the present techniques lead to unwanted downtime and to infrequent testing.

Accordingly, it would be desirable to increase the mining rope frequency while at the same time reducing the downtime required for testing.

Summary

In view of the above-mentioned and other drawbacks of the prior art, it is an object of the present invention to provide improvements with regards to mining rope diagnostics.

According to a first aspect of the invention, there is provided a computer- implemented method for rope diagnostics in a mine hoist system comprising a powered drum, at least one sheave with multiple wheels, and one rope for each wheel, the ropes being guided by the wheels and moved by the drum to transfer a load, the method comprising: providing a dynamic model that relates stress in a wheel to a rope tension under a given load, acquiring mechanical stress data, measured by stress sensors mounted on the wheels, indicative of mechanical stress in each of the wheels, determining a rope tension parameter value for each rope based on the stress data and the dynamic model, detecting a relative change between rope tension parameter values for at least two ropes, determining a rope deterioration output when the relative change fulfills a predetermined criterion, and providing an output message comprising the rope deterioration output.

The present invention is at least partly based on the realization of a dynamic model that relates the stress in the wheels to the tension of the ropes. Thus, by measuring the mechanical stress on the wheels, the rope tension can be determined from the dynamic model frequently and without the need for planned downtime.

The loads on the ropes are dynamic and so are the stresses on the wheels. The dynamic model can thus provide insight in the typical stress distributions on the wheels and rope tension behavior under normal conditions. Deviations in the stress distributions can be related to changes between rope tension parameters, inter- or intra-rope, and provides indications that a rope condition is not optimal and may need service or replacement.

A powered drum is herein meant to provide hoisting power for the mine hoist system. As the drum is rotated, powered by a motor, the ropes are moved to transport a load up or down. The drum may also store rope.

A sheave comprises multiple parallel wheels where each wheel has a circumferential groove for receiving and guiding a rope. The wheels are rotatable about their center axis.

The mechanical stress data may be acquired per each operational cycle of the hoist. One operational cycle is one lowering or one lifting operation.

In embodiments, the method may comprise acquiring stress data, measured by stress sensors mounted on the wheels, wherein the dynamic model further relates stress in a wheel to motion of the wheel, wherein the rope tension parameters are further determined based on the motion and/or stress of the wheel. That is, the stress data may also reveal the motion of the wheel, such as rotational motion, axial motion, or transversal motion. Since the loads on the ropes are dynamic as well as rope tension characteristics, analyzing the motion of the wheels may provide an improved accuracy in detecting rope deterioration.

In embodiments, the relative change between rope tension parameter values may be at least one of a relative phase change(s) between the parameter values or a relative magnitude(s) change between the parameter values. If the magnitude and/or phase in a rope tension parameter suddenly changes, this may serve as an indication of a rope deterioration. Similarly, since the multiple ropes on one sheave carry the same load, a phase change between ropes indicates that one or more ropes are carrying more weight than the one or more other ropes, that is, a weight shift has occurred. This also indicates a rope deterioration or rope slippage on the drum.

The output message may include phase change and magnitude change data.

In embodiments, stress data may be acquired continuously per each hoist cycle, or over each operational cycle so that the rope deterioration output can be continuously determined. A sampling rate for the stress data may be about 1 kHz. In some embodiments, the output message is provided only when the predetermined criterion is fulfilled.

In embodiments, the method may comprise determining an origin/location of a rope deterioration indicative of a potential rope failure from evaluating the relative change between rope tension parameter values. That is, by relative change between rope tension parameter values a weight shift for carrying the load can be estimated or localized, so that the malfunction rope can be identified, or a drum overload detected. For example, the origin may be determined from at least one of repeatability and magnitude of the relative change between rope tension parameter values, and the relative positions of the wheels within the hoist system from which the stress data and/or motion data was measured. For example, when a rope deterioration is determined, the time during since the detection and the size of the wheel and revolution rate of the wheel can be used for calculating how far the deterioration has travelled from the wheel.

In preferred embodiments the stress sensors may be mounted on spokes of the wheels where the stress is more prominent.

In embodiments, the method may comprise, calculating a differential motion and differential stress distribution of the sheaves and drum under a dynamic load, and determine the model by deriving a relationship between the differential motion and differential stress distribution and the rope’s tension. That is, the model is preferably and advantageously derived for the individual mining hoist system to best reflect the present system. The model may for example be a finite element model that is used to establish the stress relationships. The dynamic model is then used to evaluate potential tension differences to trigger an alarm. A predetermined algorithm is used for detecting the differences and initialize analysis of tension variation. That is, the algorithm may detect a deviation in the stress data, such as a phase or magnitude change directly in the stress data, and in response, the dynamic model is used for converting stress data to rope tension parameter values, such that relative changes between the rope tension parameter values can be evaluated to determine the rope deterioration output.

The dynamic model may be digital twin of the mine hoist system.

In embodiments, a relative change between rope tension parameter values includes a relative change for a single rope.

In embodiments, a relative change between rope tension parameter values may include a relative change between two or more ropes.

There is further provided a control unit configured to execute the method of any one of the herein disclosed or derived embodiments.

There is further provided a computer program product comprising program code for performing the method of any one of the herein disclosed or derived embodiments when executed by the control unit.

According to a second aspect of the invention, there is provided a mine hoist system comprising a powered drum, at least one sheave with multiple wheels equipped with stress sensors, one rope for each wheel, the ropes being guided by the wheels and moved by the drum to transfer a load, and a control unit configured to execute the method of any one of the herein disclosed or derived methods.

Further effects and features of the second aspect of the invention are largely analogous to those described above in connection with the first aspect of the invention. Further features of, and advantages with, the present invention will become apparent when studying the appended claims and the following description. The skilled person realizes that different features of the present invention may be combined to create embodiments other than those described in the following, without departing from the scope of the present invention.

Brief of the

These and other aspects of the present invention will now be described in more detail, with reference to the appended drawings showing an example embodiment of the invention, wherein:

Fig. 1 schematically illustrates a mine hoist system according to an embodiment of the invention;

Fig. 2 is a flow-chart of method steps according to embodiments of the present invention;

Fig. 3A illustrates an example the stress distribution in a wheel according to embodiments of the present invention;

Fig. 3B is a block-diagram of a model with input and output according to embodiments of the present invention; and

Fig. 4 illustrates an example sheave with ropes and example rope tensions according to embodiments of the present invention.

Detailed Description of Example Embodiments

In the present detailed description, various embodiments of the present invention are herein described with reference to specific implementations. In describing embodiments, specific terminology is employed for the sake of clarity. However, the invention is not intended to be limited to the specific terminology so selected. While specific exemplary embodiments are discussed, it should be understood that this is done for illustration purposes only. A person skilled in the relevant art will recognize that other components and configurations can be used without parting from the scope of the invention.

Fig. 1 schematically illustrates a mine hoist system 100 comprising a powered drum 102, at least one sheave 104 with multiple wheels 106 equipped with stress sensors 108, and one rope 110 for each wheel. The ropes 110 are guided by the wheels 106 and moved by the powered drum 102 to transfer a load 112. The stress sensors 108 are arranged on spokes 114 of the wheels 106. Note that there may be stress sensors on more than the here shown two spokes 114, and on each of the wheels 106. That is, each wheel 106 is preferably equipped with stress sensors 108.

A control unit 115 is configured to receive and evaluate stress measurements from stress sensors as laid out in the present disclosure.

The control unit 115 has access to a computer program product 116 on a non-transitory data memory 118 comprising program code for performing the method discussed herein.

The loads 112 in underground mining are heavy and the deterioration of the ropes 110 and sheaves 104 must be monitored. Traditionally, monitoring is done by manual inspection a few weeks apart and/or by magnetic testing on more rare occasions and especially on steel wires. The present disclosure is set out to enable more frequent, or even continuous monitoring or the sheaves and ropes, without, or at least with reduced need for pausing operation of the hoist system.

Embodiments of the present invention apply to various kinds of min hoist systems such as single and multi-rope drum hoists and friction hoists. Typical operation conditions are at depths 150 m to 2000 m underground varying weights up to 24000 kg or more, depending on the configuration.

Fig. 2 is a flow-chart of method steps according to embodiments of the present invention.

In step S102, providing a dynamic model that relates stress in a wheel to a rope tension under a given load.

In the hoist system 100, the drum 102 and sheaves 104 support and guide the mining ropes 110. Thus, the stress distribution in these components affects a structural integrity and overall performance due to direct relation to contact stresses, bending stresses and material properties.

The ropes 110 exert pressure on the guiding surface of the drums 102 and sheaves 104 due to the friction required for hoisting operations. The contact stresses between the ropes 110 and the drum 102 and sheaves 104 can be significant, especially during heavy loads or rapid acceleration/deceleration. Drums 102 and sheaves 104 are also subject to bending stresses due to the curvature of the rope 110 as it wraps around them. The bending stresses are highest at the points where the rope 110 contacts with the drums 102 or sheaves 104.

It is reasonable to assume the tension distribution among the ropes 110 is similar under typical operating conditions, such as load and hoisting speed and acceleration. Since the ropes 1100 may be assumed to exhibit similar stiffness characteristics, their displacements can be considered comparable. However, if a section of the rope 110 weakens for any reason, the displacement in that section temporarily increases, requiring the remaining ropes 110 to compensate for the additional load. This behavior is expected to be reflected in the direct measurements of the differential sheaves motion and stresses. In other words, there is a relationship between rope tension and sheave stress.

The relationship between the rope’s tensions and load/stress distribution in the sheaves can be derived through a classic Castigliano's Theorem known as the principle of virtual work. It assumes linear behavior and small deflections. For a more accurate model, the finite element analysis (FEA) may be used for predicting the structural behavior of the components of sheave 104 under dynamic loading conditions.

In other words, providing the dynamic model may comprise step S102a of translating a differential stress distribution of the sheaves 104 and drum 102 under a given load, and step S102b of determining the dynamic model by deriving a relationship between the differential stress distribution and the rope’s tension and vice versa.

Here, a finite element model may be used to calculate the stress distribution 120 exemplified in fig. 3A on an example wheel 104. Here, the stress distribution has a maximum point 122 close to one of the spokes 114 on one side of the wheel 104 whereas the opposite side has little stress. The maximum point 122 is where the rope exerts the highest stress on the wheel and is also where a rope deterioration is most likely to occur. The dynamic model which includes a finite element model relates the calculated stress distribution 120 to different rope tensions and loads.

Fig. 3B schematically illustrates use of the dynamic model 126 which allows input of stress data 128 from stress sensors 108 mounted to the spokes of a wheel 104, and output of rope tension parameters values 130. The dynamic model 126 is accessible to the control unit 115.

It is advantageous to develop a dynamic model 126 that is specific to a present hoist system 100. That is, stress distributions are calculated for a specific hoist system so that the dynamic model mimics the present hoist system as close as possible, also referred to as a digital twin model.

Turning back to fig. 2, in step S104, acquiring mechanical stress data for each operational cycle, measured by stress sensors 108 mounted on the wheels 106, indicative of mechanical stress in each of the wheels 106. The stress sensors 108 may be strain gauge sensors 108 mounted to the spokes 114 of the wheels 106.

In step S106, determining a rope tension parameter value 130 for each rope 110 based on the stress data 128 and the dynamic model 126. A rope stress parameter value may be a tension value given as a force or it can be rope’s expansion for example due to a weakening in the rope 110. The stress values in the stress data are thus converted to rope tension using the dynamic model.

In step S108, detecting a relative change between rope tension parameter values for at least two ropes. Since the ropes on a sheave 104 are expected to experience similar load and therefore also tension, a relative change between them is indicative of a condition that deviates from normal rope behavior. The relative change may be in terms of magnitude and/or phase.

In step S110 determining a rope deterioration output when the relative change fulfills a predetermined criterion. That is, only a minor relative change may not trigger an alarm. However, a relative change that fulfills the predetermined criterion triggers an alarm. The rope deterioration is determined by assessing the relative change between the rope tension parameters in view of the predetermined criterion. Any redistribution of loads within the multi-rope system can lead to fluctuations in the stresses detected on the differential sheaves. Variances in tension among the ropes will cause discrepancies in the stretch, which in turn will manifest as phase differences in the differential sheave rotation. If these variations surpass a predefined threshold or criterion, the occurrence will be recorded and subjected to thorough analysis to ascertain repeatability and consistency. The alert or alarm indicators will be activated when the values cross predefined limits. It should be understood that the limits of thresholds, or criterions are set according to the hoist system configuration at hand.

Finally, in step S112, an output message M is provided comprising the rope deterioration output. The output message M may include the relative change between rope tension parameter values.

Preferably, stress data is acquired for each operation cycle so that the rope deterioration output can be continuously determined. That is, the method is again repeated from step S104 until it is manually interrupted.

However, messages and or alerts are registered for each operational cycle in step S116, for analysis to determine the extent and location of a rope deterioration event. For example, amplitudes and phases of the tensions and stresses may be recorded.

The sampling frequency of acquiring stress data may be around 500 Hz or higher to capture the stress changes occurring at less than 1 deg of the wheel rotation.

Preferably, the method is a wireless, embedded system, implemented method. That is, the control unit 114 receives measurements wirelessly from the stress sensors 108 and performs the evaluation including using the dynamic model 126.

Fig. 4 illustrates an example sheave 104 having three parallel wheels 106 equipped with stress sensors 108 on their spokes 114. There is further shown graphs 140, 142, 144 illustrating example tension parameter value for a respective rope 110a, 110b, 110c as a function of time. Assuming that the ropes 1 10a-c are fully functional the tension in the ropes 110a-c should be in phase and with similar magnitudes. The modulation of the tension in the ropes is due to unwinding of the ropes 110a-c from the drum 102.

However, if one of the ropes, here assuming rope 110a, is weakened or in in some way deteriorated, the magnitude in the tension is varied compared to the other ropes 110b-c, as the loads must be redistributed accordingly to the principles of virtual work.

For example, a relative change in phase 146 between the tension in the rope 110a and the other two ropes 110b-c indicates a rope deterioration. The weakening of rope 110a cause the other two ropes to carry more weight, and the weakened rope cause a rope displacement and a momentarily reduced load to carry, and consequently a phase shift in rope tension compared to the other rope’s tensions. In a similar way, a relative change in tension magnitudes indicates a rope deterioration. That is, at the time t1 when the rope deterioration is assumed to have occurred, the overall tension magnitude T1 in the rope 110a dropped to T1 ’ whereas the tension magnitudes T2, T3 in the ropes 110b and 110c increased to T2’ and T3’. Thus, the relative change in rope tension parameter values may be a phase shift in tensions in different ropes or a relative magnitude(s) change between the tension parameter value.

The relative changes may be between ropes, or for a single rope. For example, when the phase changes at time t1 for the rope 110a, this may alone serve as an indication of a rope weakness due to rope structure deterioration. This may be particularly useful for drum hoists where a single rope is typically used.

Furthermore, as discussed above, the relative change may be between rope tension parameters of different ropes, e.g., two or more ropes. This is especially useful for so-called friction hoists where typically multiple ropes are used in parallel.

With reference again to the flow-chart in fig. 2, the method may optionally include a step S109 of determining an origin/location of a rope deterioration indicative of a potential rope failure from evaluating the relative change between rope tension parameter values. That is, by registering the phase shift and/or magnitude shift as well as the location along the rope length it is possible to draw conclusions on what caused the issue. First, based on which wheel the sensors are located it can be determined which rope is experiencing deterioration. Thus, relative positions of the wheels within the hoist system from which the stress data and/or data was measured are beneficial for localizing the deterioration. Secondly, since the deterioration most likely to occur at the wheel, and phase information is available from the tension parameter value graphs 140-144, one can calculate how far from the wheel 106 the deterioration has travelled based on the revolution rate of the sheave 104 and by tracking the number of revolutions until time t1 where the deterioration occurred.

Furthermore, if the relative change between rope tension parameter values repeats itself with a repeatability, it can be determined whether it is a single deterioration or multiple deterioration based on knowledge of the length of the rope and the rope speed or revolution rate of the sheave. Also, the magnitude of the relative change of the tension parameter values may be used for determining the origin of the rope deterioration.

In one embodiment, the dynamic model further relates stress in a wheel 104 to motion of the wheel. This allows that the rope tension parameters are further determined based on the motion of the wheel 104. Uneven load distribution between ropes, or changes to load distributions due to rope deterioration may cause movement of the sheaves and wheels in axial direction 150 (see fig. 3A), parallel with the rotation axis of the wheel 104, and transverse directions 152, perpendicular to the rotation axis of the wheel 104. Movements in those directions cause stress distribution changes to the wheel which may be related to rope tension.

A control unit may include a microprocessor, microcontroller, programmable digital signal processor or another programmable device. The control unit may also, or instead, include an application specific integrated circuit, a programmable gate array or programmable array logic, a programmable logic device, or a digital signal processor. Where the control unit includes a programmable device such as the microprocessor, microcontroller or programmable digital signal processor mentioned above, the processor may further include computer executable code that controls operation of the programmable device.

In one or more examples, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium and executed by a hardware-based processing unit. Computer-readable media may include computer-readable storage media, which correspond to tangible media such as data storage media, or communication media including any media that facilitate the transfer of a computer program from one place to another, e.g., according to a communication protocol. In this manner, computer-readable media generally may correspond to (1 ) tangible computer-readable storage media which are non-transitory or (2) a communication media such as signal or carrier waves. Data storage media may be any available media that can be accessed by one or more computers or one or more processors to retrieve instructions, code and/or data structures for implementation of the techniques described in this disclosure. A computer program product may include a computer-readable medium.

By way of example, and not limitation, such computer-readable storage media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage, or other magnetic storage devices, flash memory, or any other medium that can be used to store desired program code in the form of instructions or data structures and that can be accessed by a computer.

Even though the invention has been described with reference to specific exemplifying embodiments thereof, many different alterations, modifications and the like will become apparent for those skilled in the art.

Additionally, variations to the disclosed embodiments can be understood and effected by the skilled person in practicing the claimed invention, from a study of the drawings, the disclosure, and the appended claims. In the claims, the word "comprising" does not exclude other elements or steps, and the indefinite article "a" or "an" does not exclude a plurality. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage.

Claims

1. A computer-implemented method for rope diagnostics in a mine hoist system comprising a powered drum, at least one sheave with multiple wheels, and one rope for each wheel, the ropes being guided by the wheels and moved by the drum to transfer a load, the method comprising: providing (S102) a dynamic model (126) that relates stress in a wheel (106) to a rope tension under a given load, acquiring (S104) mechanical stress data, measured by stress sensors (108) mounted on the wheels (106), indicative of mechanical stress in each of the wheels (106), determining (S106) a rope tension parameter value for each rope (110) based on the stress data and the dynamic model (126), detecting (S108) a relative change between rope tension parameter values for at least two ropes, determining (S110) a rope deterioration output when the relative change fulfills a predetermined criterion, and providing (S112) an output message (M) comprising the rope deterioration output.

2. The method of claim 1 , comprising: acquiring stress data, measured by stress sensors mounted on the wheels, wherein the dynamic model further relates stress in a wheel to motion of the wheel, wherein the rope tension parameters are further determined based on the dynamic model and a motion of the wheel.

3. The method of any of claims 1 -2, wherein the relative change between rope tension parameter values is at least one of a relative phase change(s) between the parameter values or a relative magnitude(s) change between the parameter values.

4. The method of any of the preceding claims, wherein stress data is acquired continuously so that the rope deterioration output can be continuously determined.

5. The method of any of the preceding claims, comprising: determining (S109) an origin/location of a rope deterioration indicative of a potential rope failure from evaluating the relative change between rope tension parameter values.

6. The method of claim 5, wherein the origin is determined from at least one of repeatability and magnitude of the relative change between rope tension parameter values.

7. The method of any of the preceding claims, wherein the stress sensors are mounted on spokes of the wheels.

8. The method of any of the preceding claims, comprising: calculating (S102a) a differential motion and differential stress distribution of the sheaves and drum under a given load, determining (S102b) the model by deriving a relationship between the differential motion and differential stress distribution and the rope’s tension.

9. The method of any of the preceding claims, the dynamic model being a finite element model.

10. The method of any of the preceding claims, the dynamic model being a digital twin of the mine hoist system.

11 . The method of any of the preceding claims, wherein a relative change between rope tension parameter values includes a relative change for a single rope.

12. The method of any of the preceding claims, wherein a relative change between rope tension parameter values includes a relative change between two ropes.

13. A control unit (115) configured to execute the method of any one of the preceding claims.

14. A mine hoist system (100) comprising a powered drum (102), at least one sheave (104) with multiple wheels (106) equipped with stress sensors (108), one rope (110) for each wheel, the ropes being guided by the wheels and moved by the drum to transfer a load, and a control unit according to claim

13.

15. A computer program product (116) comprising program code for performing the method according to any one of claims 1 -12, when executed by a control unit.