WO2023025392A1 - Procédé de surveillance de l'état d'un treuil - Google Patents

Procédé de surveillance de l'état d'un treuil Download PDF

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Publication number
WO2023025392A1
WO2023025392A1 PCT/EP2021/073662 EP2021073662W WO2023025392A1 WO 2023025392 A1 WO2023025392 A1 WO 2023025392A1 EP 2021073662 W EP2021073662 W EP 2021073662W WO 2023025392 A1 WO2023025392 A1 WO 2023025392A1
Authority
WO
WIPO (PCT)
Prior art keywords
hoist
measured
state variables
foe
determining
Prior art date
Application number
PCT/EP2021/073662
Other languages
English (en)
Inventor
Krystof Kryniski
Kari Saarinen
Original Assignee
Abb Schweiz Ag
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Abb Schweiz Ag filed Critical Abb Schweiz Ag
Priority to PCT/EP2021/073662 priority Critical patent/WO2023025392A1/fr
Publication of WO2023025392A1 publication Critical patent/WO2023025392A1/fr

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Classifications

    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B66—HOISTING; LIFTING; HAULING
    • B66D—CAPSTANS; WINCHES; TACKLES, e.g. PULLEY BLOCKS; HOISTS
    • B66D1/00—Rope, cable, or chain winding mechanisms; Capstans
    • B66D1/54—Safety gear
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M13/00—Testing of machine parts
    • G01M13/04—Bearings
    • G01M13/045—Acoustic or vibration analysis
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/34—Testing dynamo-electric machines
    • G01R31/343—Testing dynamo-electric machines in operation
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/50—Testing of electric apparatus, lines, cables or components for short-circuits, continuity, leakage current or incorrect line connections
    • G01R31/52—Testing for short-circuits, leakage current or ground faults

Definitions

  • the present disclosure relates to a method for monitoring a condition of a hoist, particularly a mining hoist.
  • Embodiments relate to a hoist monitoring system for monitoring a condition of a hoist.
  • a condition c.g. a bearing condition of di fferent types of machines.
  • analysis of ⁇ ibralion signals is commonly used.
  • stable machine operation conditions are required.
  • Hoists are used in various applications, including mining. Since hoists and especially their bearings are subject to wear or electrical current-induced damage, it is desired to monitor the condition of the hoist. For example, conditions of a hoist may be ctetermined by analyzing vibration signals collected on the hoist. Commonly, a spectral analysis of the vibration signals is employed by using a Fourier analysis technique. This is especially useful in the case of production hoists, which usually operate in long cycles. In this case, there can be sufficiently long time periods of stable speed and load. Defect frequencies may be analyzed accurately, using for example data block processing based on fast Fourier transform algorithms.
  • foe vibration signal s frequency components related to the rotation speed are typically low and they are affected by rotation speed variations. Consequently, defect frequencies of hoist components, like e.g. bearings, are typically also low.
  • An accurate estimation using Fourier analysis is likely to require several rotations of the hoist’s drum, i.e. a long acquisition time.
  • both loads and rotation speeds of foe hoist may vary.
  • foe rotation speed can vary even within a single cycle.
  • hoists are operated at changing load and speed. Moreover, they may be operated in short cycles. In such a case, there may not be enough time to collect sufficiently stable vibration records and to achieve a required frequency resolution tracing the fault. In addition such variations of speed or load, also electrical interferences or a noisy environment may negatively affect the frequency resolution and even completely mask the bearing signals.
  • a method for monitoring a condition of a hoist is prov ided.
  • the hoist includes a motor driving a shaft of the hoist and a variable-frequency drive for controlling the motor.
  • the method includes: measuring an output frequency of the variable-frequency drive, measuring v ibration signals on the hoist, and extracting state x ariablcs from the measured vibration signals.
  • the state variables include excitation parameters for excitations at selected frequencies, the selected frequencies being determined based on the measured output frequency.
  • the method further includes determining at least one key performance indicator for the hoist, based on the extracted state variables.
  • a monitoring system for monitoring a condition of a hoist according to the features of claim 14 is provided.
  • Fig. 1 is a flow chart illustrating a method for monitoring a condition of a hoist, according to aspects of the present disclosure
  • Fig, 2 is a schematic view of a hoist system according tO aspects of the present disclosure.
  • Fig. 1 is a chart illustrating a method for monitoring a condition of a hoist, according to aspects of the present disclosure.
  • the hoist is preferably a mining hoist.
  • the hoist comprises a motor driving a shaft of the hoist and a variable-frequency drive for controlling the motor.
  • An exemplary hoist is described further below with regard to Fig. 2,
  • the hoist may include a hoist component being and or interacting with a l at least partially ) rotating clement.
  • the hoist’s shaft may drive the rotating element.
  • the component can be or include a rotating component such as a rotor of the motor, a shaft, or a rotating bearing part, and/or a stationary component interacting with a rotating component, such as a stator of the motor or a stationary bearing part
  • a rotating component such as a stator of the motor or a stationary bearing part
  • I he hoist component may include or be a bearing, particularly a rolling bearing.
  • the method includes, in block 102, measuring an output frequency of the variable-frequeiKy drive.
  • the method further includes, in block 104, measuring vibration signals on the hoist.
  • the vibrations are measured on the hoist component. More particularly, the vibration signals are measured by a vibration sensor.
  • the vibration sensor may include at least one of an acoustic sensor, accelerometer, optical vibration sensor, shock pulse sensor, strain gauge, microphone, or electrical sensor.
  • the acoustic sensor may operate in semi or ultrasonic range.
  • the electrical sensor may be a Rogowski coil.
  • the method further includes, in block 106, extracting state variables from the measured vibration signals.
  • the state variables may include excitation parameters indicative of (vibrational) excitations at selected frequencies.
  • the selected frequencies may include for example at least one suspected fruit frequency of the hoist component.
  • the excitation frequencies may be discrete excitation frequencies, for example at most 12, 10 or 8 discrete frequencies.
  • the selected frequencies may be determined based on the measured output frequency, e.g., as (integer and/or non-integer) multiples thereof and/or as (integer and/or non-integer) multiples of a rotation frequency of the drive determined from the measured output frequency.
  • the selected frequencies are related to and in particular proportional to a rotation frequency of the hoist’ s shaft.
  • the selected frequencies may scale with the rotation frequency and may, in preferable embodiments, allow tracking particular harmonics of the rotation frequency.
  • the state variables may be extracted from the measured v ibration signals by applying a Kalman filter to the measured vibration signals as a function of the measured output frequency.
  • a Kalman filter is an algorithm producing estimates of predefined state v ariables from measurement data.
  • a Kalman filter may produce estimates and uncertainties of current state variables and update the estimates based on subsequently measured data using a weighted average. The weighting particularly depends on the uncertainties of the estimates.
  • An adv antage of the Kalman filter is that signal components having a known structure may be accurately tracked in a signal further including noise or signal components ha ⁇ ing a different structure.
  • the Kalman filter may be a Vold-Kalman filter, particularly a Vold-Kalman Order Tracking Filter.
  • Order tracking may be understood as extracting the periodic (sinusoidal) content of measurement data from a system under periodic loading or excitation. Periodic loading produces orders or hamionies at frequencies that are multiples of a fundamental lone. The orders may be regarded as amplitude and phase modulated carrier waves.
  • the demodulation function may be called a complex envelope.
  • Applying a Vold- Kalman filter particularly includes defining as a constraint that the unknown complex envelopes arc smooth and that the sum of the ei ders approximates the total measured signal.
  • Kalman filter uses a small set of state variables (compared to Fourier transform techniques w h ich al low a continuous set of excitations), the Kalman filter is able to achieve a fast response rime and determine the state v ariables quickly.
  • the Kalman filter technique is constantly adjusted.
  • the problems mentioned in the introductory section are solved at least to some degree .
  • the state variables include excitation parameters at frequencies that scale with the rotational frequency of the hoist’s shaft
  • the Kalman filter technique is able to take into account machine speed and possibly other parameters. Thereby, a continuous stream of reliable data may be provided.
  • Results of the application of the filter may be directly synchronized with a controller, for example using an Open Platform Coinniunications (OPC) standard.
  • OPC Open Platform Coinniunications
  • a quasi-instantaneous state of the hoist may be captured, even during changes of rotation speed.
  • the selected frequencies may include integer and/or non-integer multiples of a frequency corresponding to the measured output frequency
  • the selected frequencies can include harmonics of a rotation frequency corresponding to the measured output frequency.
  • the selected frequencies may include sidebands of the harmonics, particularly as non-integer multiples of a frequency corresponding to the measured output frequency
  • the excitation parameters may include a phase and amplitude information of the excitations at the selected frequencies.
  • the method further includes, in block 1 OS, determining at least one key performance indicator ( KPJ ) for the hoist, based on the extracted state c ariablcs
  • the KPI allows to provide an insight into hoist performance, which may be monitored over time.
  • the use of a KPI allows unified monitoring, displaying and establishing alarms.
  • the determined KPI may be streamed continuously and reflect dynamic behavior of the hoist at any instance of its operation.
  • the determining of the at least one key performance indicator may include determining a vibration energy of the vibrations for at least one of the selected frequencies.
  • determining of the at least one key performance indicator may include determining respective vibration energies for at least some of the selected frequencies, for example at least 2, 3, or 5 of the selected frequencies.
  • rhe determining of the at least one key performance indicator may include weighted summing of the determined vibration energies.
  • the determining of the at least one key performance indicator may include determining at least two performance indicators by weighted summing of the determined vibration energies with different weights.
  • the at least one key performance indicator l KPI may have the following general form: where: o harmonics weight p sidebands weight
  • the method may include determining in-phase and quadrature components of the state variables.
  • the method may include passing the measured vibration signals through a band-pass and multi-notcli filter and a demodulator.
  • the method may further include evaluating at least one alarm condition for the at least one key performance indicator.
  • the at least one alarm condition corresponds to a respective damage type for the hoist.
  • the damage type includes at least one of wear, fatigue, plastic flow, fracture, electrical erosion or plastic deformation.
  • the method may further include issuing an alarm signal when the at least one alarm condition is satisfied.
  • the method monitors the condition of a hoist component being and/or interacting with a (partially) rotating element ofthe hoist, wherein the key performance indicator is indicative of the condition of the hoist component.
  • the rotational speed of the rotating element may be at most for example 100, 80, or 60 rpm.
  • the method may further include determining a leakage (discharging) current through a bearing of the shaft.
  • the determination of the leakage current may be performed indirectly by tracing a floating ground voltage with an accelerometer, particularly a dummy accelerometer including or consisting of a fixed capacitor.
  • the leakage current may be detected by a sensor, e.g. the vibration sensor or any other sensor, because the leakage current affects the sensor signal of a broad variety of sensors.
  • the sensor may be tuned to the line or sw itching frequency and/or its harmonics. This tuning can be performed by measuring signals (e.g.
  • the method may include notching out electrical frequencies interfering with measured vibration signals, based on the detected leakage current.
  • the method may further include determining a sipial to noise ratio of the measured vibration signals .
  • the KPIs include a dedicated KPI based on the at least one additional state variable and/or representing the amount of leakage current.
  • the method may further include determining an electrical insulation status, e,g. failure, of the bearing based on the determined leakage current.
  • Fig. 2 is a schematic view of a hoist system according to aspects of the present disclosure.
  • the hoist system includes a hoist and a hoist monitoring system for monitoring a condition of a hoist.
  • the hoist includes a motor 202 and a variable frequency drive 220 for controlling the motor 202,
  • the motor 202 may be connected to a gear box 204 via a first shaft 208.
  • the hoist may further include a drum 200 connected to the gear box 204 via a second shaft 210.
  • the hoist may further include a hoist component being and/or interacting with a rotating element.
  • the hoist component is for example a first bearing 212.
  • the second shaft 210 is a shaft of the hoist component In particular, the second shaft 210 drives the rotating element of the hoist component.
  • the hoist may further include a second bearing 214.
  • the hoist monitoring system further includes a vibration sensor 224 for measuring vibration signals on the hoist.
  • the vibrations are measured on the hoist component.
  • the vibration sensor 224 may be attached t> the hoist component.
  • the hoist monitoring system may include at least one additional vibration sensor.
  • an additional vibration sensor 228 may be atached to the second bearing 214 of the hoist.
  • the hoist monitoring system further includes a measurement device 222 for measuring an output frequency of the variable-frequency drive 220.
  • the hoist monitoring system further includes a controller 230.
  • the controller 230 is connected to the measurement device 222 for receiving the measured output frequency.
  • the controller 226 is connected to the vibration sensor 224 for receiving the measured vibration signals.
  • the measurement device 222 and the r ibration sensor 224 max be connected to the controller 23(1 xx i re less 1 y or via respective cables (not shown).
  • the vibration sensor may include at least one of an acoustic emission sensor,accelerometer, optical vibration sensor, shock pulse sensor, strain gauge, microphone, or electrical sensor.
  • the acoustic emission sensor can be for example an ultrasonic sensor.
  • the electrical sensor can be for example a Rogowski coil.
  • the controller is configured for extracting state variables from the measured vibration signals.
  • the state variables including excitation parameters for excitations at selected frequencies, the selected frequencies being determined based on the measured output frequency.
  • the state variables may be extracted by applying a Kalman filter to the measured vibration signals as a function of the measured output frequency.
  • the controller is further configured for determining at least one key performance indicator for the hoist, based on the extracted state variables.
  • the controller may be configured to perform a method for monitoring a condition of a hoist as described herein, particularly with regard to Fig. 1.

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Mechanical Engineering (AREA)
  • Acoustics & Sound (AREA)
  • Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)

Abstract

L'invention concerne un procédé de surveillance de l'état d'un treuil. Le treuil comprend un moteur entraînant un arbre du treuil et un entraînement à fréquence variable pour commander le moteur. Le procédé consiste à : mesurer (102) une fréquence de sortie de l'entraînement à fréquence variable, mesurer (104) des signaux de vibration sur le treuil et extraire (106) des variables d'état à partir des signaux de vibration mesurés. Les variables d'état comprennent des paramètres d'excitation pour des excitations à des fréquences sélectionnées, les fréquences sélectionnées étant déterminées sur la base de la fréquence de sortie mesurée. Le procédé consiste en outre à déterminer (108) au moins un indicateur de performances clé pour le treuil, sur la base des variables d'état extraites.
PCT/EP2021/073662 2021-08-26 2021-08-26 Procédé de surveillance de l'état d'un treuil WO2023025392A1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
PCT/EP2021/073662 WO2023025392A1 (fr) 2021-08-26 2021-08-26 Procédé de surveillance de l'état d'un treuil

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/EP2021/073662 WO2023025392A1 (fr) 2021-08-26 2021-08-26 Procédé de surveillance de l'état d'un treuil

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WO2023025392A1 true WO2023025392A1 (fr) 2023-03-02

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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20140175953A1 (en) * 2011-02-27 2014-06-26 Voith Patent Gmbh Monitoring Device for a Double-Fed Asynchronous Machine
GB2560559A (en) * 2017-03-15 2018-09-19 Zenith Oilfield Tech Limited Methods and systems for monitoring the performance of electric motors
CN109484937B (zh) * 2018-09-14 2020-07-28 温州大学 一种矿井提升机状态检测的增强同步提取变换方法
EP3809109A1 (fr) * 2019-10-16 2021-04-21 Siemens Aktiengesellschaft Analyse intelligente des données d'un moteur à l'aide d'un algorithme en temps réel

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20140175953A1 (en) * 2011-02-27 2014-06-26 Voith Patent Gmbh Monitoring Device for a Double-Fed Asynchronous Machine
GB2560559A (en) * 2017-03-15 2018-09-19 Zenith Oilfield Tech Limited Methods and systems for monitoring the performance of electric motors
CN109484937B (zh) * 2018-09-14 2020-07-28 温州大学 一种矿井提升机状态检测的增强同步提取变换方法
EP3809109A1 (fr) * 2019-10-16 2021-04-21 Siemens Aktiengesellschaft Analyse intelligente des données d'un moteur à l'aide d'un algorithme en temps réel

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
GADE, S.HERLUFSEN, H.KONSTANTIN-HANSEN, H.VOLD, H: "Characteristics of the Vold-Kalman Order Tracking Filter", BRTTCL & KJAER TECHNICAL REVIEW, no. 1 - 1999, 1999
LI YONGBO ET AL: "Fault Diagnosis of Rolling Bearing Under Speed Fluctuation Condition Based on Vold-Kalman Filter and RCMFE", IEEE ACCESS, vol. 6, 4 June 2018 (2018-06-04), pages 37349 - 37360, XP011687492, DOI: 10.1109/ACCESS.2018.2851966 *
LU SILIANG ET AL: "Tacholess Speed Estimation in Order Tracking: A Review With Application to Rotating Machine Fault Diagnosis", IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, IEEE, USA, vol. 68, no. 7, 1 July 2019 (2019-07-01), pages 2315 - 2332, XP011728797, ISSN: 0018-9456, [retrieved on 20190606], DOI: 10.1109/TIM.2019.2902806 *

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