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Arch. Min. Sci., Vol. 55 (2010), No 1, p. 217–231
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ANDRZEJ OLEKSY*, ZYGMUNT SZYMAŃSKI**
MODERN METHODS CONTROL AND DIAGNOSTICS OF HOISTING-MACHINES
WITH APPLICATION OF ARTIFICIAL INTELLIGENCE METHODS
NOWOCZESNE METODY STEROWANIA I DIAGNOSTYKI MASZYN WYCIĄGOWYCH
Z WYKORZYSTANIEM METOD SZTUCZNEJ INTELIGENCJI
The paper present’s an analysis of the possibility an application of chosen artificial intelligence
methods in control, automatics and diagnostics systems of hoisting-machines The analysis is limited
to: fuzzy logic control, genetic algorithms, and modern neural networks II and III generation methods.
These methods assure realization of complicated algorithms a control of hoisting -machine with assurance
of energy-saving operating conditions, monitoring of exploitive parameters, and predictive diagnostics
of technical state a hoisting -machine, reducing a number of damage states. In paper present’s an idea of
control system and diagnostics of machine basing on method: fuzzy- logic neuro system of the control
circuit (fuzzy logic control in neural networks). In the paper present’s a chosen of control algorithms, and
results of computer simulations of chosen mathematical models of hoisting -machine.
Keywords: hoisting machine, artificial intelligence, fuzzy-logic control, neural net
Eksploatacja maszyn transportu poziomego i pionowego stosowanych w podziemnych zakładach
górniczych wymaga spełnienia warunków: energooszczędności, niezawodności oraz bezpieczeństwa pracy.
W napędach górniczych wyraźną poprawę wskaźników energetycznych i ekonomicznych uzyskuje się
przez: zastosowanie nowoczesnych zasilaczy przekształtnikowych sterowanych układami mikroprocesorowymi, sterowanie optymalne pracą górniczej maszyny transportowej, zastosowanie metod sztucznej
inteligencji w obwodach sterowania i diagnostyki. Wprowadzenie do obwodów siłowych maszyn wyciągowych zasilaczy przekształtnikowych zapewnia budowę płynną i ekonomiczną regulację parametrów
zasilania silnika napędowego. Układy zasilania są sterowane z inteligentnych sterowników wyposażonych
w regulatory ACN (artificial control network). W zależności od stopnia automatyzacji stosowane są różne
systemy sterowania: sterowanie rozmyte, systemy sieci neuronowych, algorytmy genetyczne. Zastosowanie
techniki cyfrowej (cyfrowe regulatory jazdy, czujniki i przetworniki cyfrowe) zapewni sterowanie pracą
maszyny wyciągowej w czasie rzeczywistym, przy bieżącej kontroli parametrów eksploatacyjnych. Komputery przemysłowe zapewniają monitoring oraz diagnostykę pracy maszyny wyciągowej, co umożliwi
wcześniejsze wykrywanie stanów awaryjnych i zwiększy bezpieczeństwo pracy. Nowoczesne algorytmy
*
**
INSTYTUT TECHNIKI GÓRNICZEJ KOMAG, UL. PSZCZYŃSKA 37, 44-100 GLIWICE, POLAND
SILESIAN UNIVERSITY OF TECHNOLOGY, UL. AKADEMICKA 2, 44-100 GLIWICE, POLAND
218
sterowania, uwzględniające obowiązujące przepisy górnicze, umożliwią automatyczne, suboptymalne
sterowanie pracą maszyn wyciągowych (skipowych i klatkowych). W referacie przedstawiono analizę
celowości wprowadzania napędów energooszczędnych do układów maszyn wyciągowych, potrzebę
zastosowania metod sztucznej inteligencji w układach sterowania i diagnostyki, wybrane algorytmy
i kryteria sterowania energooszczędnego, oraz koncepcję układu sterowania i diagnostyki maszyny bazującej na metodzie: fuzzy-logic neuro net control system (sterowanie rozmyte w sieciach neuronowych).
Przedstawiono wybrane algorytmy sterowania oraz wyniki obliczeń komputerowych wybranych stanu
pracy maszyny wyciągowej.
Słowa kluczowe: maszyna wyciągowa, sztuczna inteligencja, sterowanie rozmyte, sieci neuronowe
1. Introduction
The exploitation of machines of the transport horizontal and perpendicular in underground
mine demands realizations of conditions: energy-savings, reliabilities and work safeties. In mining-drives the distinct improvement of coefficients: energy and economic, obtains by: application
of modern supply inverters controlled with microprocessor controller, optimal control of the work
a mine transportation machine, application of the artificial intelligence methods in control circuits
and diagnostics. The application in power circuits of hoisting machines an inverter supply system
assures the realization a smooth and economic regulation of power supply parameters driving
motor. Supply systems are controlled from intelligent sensors and converters and controllers
ACN (artificial control network). Depending on the degree of automation are practical different
control systems: the fuzzy logic control, systems of neural networks, genetic algorithms. The
application of digital technique (digital regulators of drive, sensors and digital transducers) will
assure a control with the work of hoisting machine in real time, at the current monitoring of exploitive parameters. Industrial computers assure monitoring and diagnostics of hoisting -machine
work, what will enable the earlier detection of damage states and will enlarge the work safety.
Modern algorithms of the control enable: operative regulations of mine machine, will automatic
and suboptimal control work of hoisting machine (cable lift or cage lift) In the paper present’s
an analysis of advisability an application energy-saving drives to hoisting -machines system,
necessity of the application an artificial intelligence methods in control and diagnostics systems,
chosen algorithms and criteria of energy-saving control, and the idea of control and diagnostics
system of machine, basing on methods: fuzzy-logic neuro the circuit control the system (the fuzzy
control in neural networks). The paper present’s an chosen algorithms of control, and results of
computer calculations a different state of the winding-machine.
2. Modern supply systems of hoisting-machine
In Polish mines are applied a systems of exploitation leaning on the high concentration of
the coal. It require application an effective cutting machines and reliable transportation systems:
horizontal and perpendicular transport. Systems of horizontal transport should work impromptu
continuous and assure continuous coal haulage to loading stations on shaft station or directly on
the surface. Systems of the perpendicular transport (cable lift hoisting shafts, descend shafts)
should be coordinated with the inflow of coal and with descend rides of miner. On main hoisting shafts are applied a hoisting machine drive separately-excited direct current motor, supplied
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from rectifier supplier (Glinka, 2000; Szymański, 2003). Rated power of driving motors of the
hoisting-machines attain the level: (1000-6000) kW (Szymanski. 2003). Hoisting -machines are
supplied with separate of the main mine a three-phase network about rated voltage 6kV, by lowering transformer: 110 kV/6 kV, at power short circuit networks exceeding 300 MVA. A consequence, are large voltage drops of in mains hoisting machines. The application of inverter supply
system causes the enlargement of the degree of the voltage and current deformation of the power
supply (generating higher harmonic), large voltage fluctuations of the network as result of jump
changes of reactive power, the break down commutation of supply voltage, comparatively the
cheapness of the power factor (cosφ ≈ 0,55-0,60). They can affect on other drives supplied from
of the same switching station, causing disturbances of their work (disturbances of the work of
funs of main airing driven with synchronous motors, or drives with inductive wound rotor motors
in the system of the subsynchronous cascade. For the limitation of negative results of influence
an inverter distorsion on the supply network belongs: to enlarge the short circuit power of the
network, to application of filters higher harmonic (static or active), and apply an compensation
system of the dynamic reactive power. To the power supply of the drive motor of hoisting -machine
uses the system: the single thyristor rectifier or two symmetrical rectifiers 6T in the system to
parallels. The schema of the supply system of drive motor drive hoisting -machine is presented
on Fig. 1. On Fig. 2 is presented an electric schematic diagram of hoisting -machine inverter
supply system, instead on Fig. 3 the schema of the module bi thyristor creating supply system
of thyristor rectifier. The schema of the hoisting -machine drive system with the synchronous
motor is presented on Fig. 4.
Fig. 1. Electric schematic diagram of the supply system of the winding-machine drive motor
Supply systems assure the reversing work of hoisting machine at utilization of electric
brake, assuring recuperation of electric energy to supply source. The change a direction of rotation can be realized by the change of direction an excitation current, or by the push-pull system
of armature motor circuit. supply system.
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Fig. 2. The electric schematic diagram of jnverter supply system of the hoisting machine
Fig. 3. Schema of the Bi thyristor supply system
3. The analysis of advisability application of artificial
intelligence methods to control systems of mine- hoisting
machines
The mine-transport system, this is a well ordered internally gathering of objects being found
on the surface and in undergrounds of the mine, along with relations existing between these
objects and their proprieties, whose the activity is subordinate to the success of the established
transportation aim. The degree of productive process automations and the complex diagnostics
of machines and devices is in Polish mines considerably limited (Tadeusiewicz, 1993; Kowalski,
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Fig. 4. Hoisting machine drive system with synchronous motor
2006). Practical are applied a systems automatic system of: local stations supplying with transformer, rectifier supply system, series of belt conveyors, hoisting -machines at the transport of
the coal, and partly cutting machines: wall shearer harvesters, coal planes. In the most of mines
are applied a conventional solutions in which the man as the operator is necessary to starting and
switch off a machines, control of exploitive parameters and to estimation of the total correctness
of the work of machines of horizontal and perpendicular transport. The knowledge of the operator and his superiors, leaning on the experience, contracted in directions, and in regulations and
requirements decides about the quality of the work of mine machines. The huge knowledge of
the personnel of the technical mine should create the base of intelligent systems of the real-time
control – KBS (knowledge based the system), leaning on computer databases and knowledge
bases (Tadeusiewicz, 1993).
The system KBS will make possible the monitoring of processes the real time, diagnostic of
technical state a hoisting-machine, prognoses of following production cycles and the automatic
control of the all industrial process or his neuralgic elements. To the realization of the expert
control: superior (SECS – supervisory expert control the system), or simple (DECS – direct
expert control the system) one ought to use systems of the artificial intelligence: ACN (artificial
control network) and ANN (artificial neural network). To the realization of expert systems and
the optimum-control we can use: the fuzzy control (Tadeusiewicz, 1993; Kowalski, 2006; Pasko
& Walczak. 2007), neural networks or control systems of adaptive containing the combination of
the fuzzy-logic control and neural networks with application of genetic algorithms (Kowalski,
2006) It demands application of large scale processors, quick and the great memory (Pasko &
Walczak, 2007).
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The fuzzy logic control consists in the exchange of continuous sizes master on fuzzy leaning
sizes on linguistic dependences, to utilization of expert system to conclude decision (the conclude machine, the rule base, the database) and the elaboration of the continuous signal realizing
come to a decision in the real control circuit. The example-schema of the fuzzy regulator FKBC
(fuzzy knowledge based control) one introduced on Fig. 5. The input signal of the controller is
subjected to the process of the standardization, and is then fuzzyfied in fuzzyfication process.
Using the knowledge base and variable linguistic one marks sections of variable changes decision
and recommended signal level of exit which after sharpening and the denormalization is given
on the exit of the controller fuzzy-logic and to the executive control impromptu rational, enable
different unforeseeable situations.
Fig. 5. Structural scheme of fuzzy logic FKBC controller
The control with system of neural networks consists in the image of the real control system
with the system of neurons (intelligent decisions cells the equipped microprocessor into transducers A/C and C/A and modules of operation memory: RAM, ROM, EEPROM, joint with synapses
(two-way- transmission bus connection). The process of the control consists of two stages:
I stage – the education stage (insertion to the memory of the processor of the information
contracted in knowledge bases and in databases, and forcing of the function of limitations),
II stage – the deduction and decision undertake stage (the realization of the control process
at the utilization of knowledge bases). The control system demands usages of processors
about the high speed of calculations and the great operation memory, he is practical to
the control of very complicated production cycles. The simplified schema of the neuronal
controller is presented on Fig. 6.
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Fig. 6. Neural set controller
Control with application of genetic algorithms consists in the exchange of the real control
system with the system genetic, composite from: cells, tissues, networks of connections of inter
cell and superior and local decision units The single cell contains: two microprocessors, transducers A/C and C/A, transmition registers, and operation memory. The cell copies the physically
definite fragment of the real control circuit. Describing according to plan dependences happening among each elements of the control circuit and the controller we build the network of connections among each cells (with genes) of the system. It makes possible this model of physical
phenomena happening in the real control system. The control system require application of more
microprocessor drivers and is advisable at the control of extensive and complicated processes
technical and productive. The use of expert systems in control systems of mine transportation
machines will assure: the energy-saving manner of the power supply and the control the work
of: belt conveyors and rail transport, the running inspection of exploitive parameters, the diagnostics local and total of machines of transportation system, and optimal control with the work
of cutting machines.
4. The diagnostics of the mining- hoisting-machine
drive system
The reliability of the work of mine transportation machine drive system with direct current
motor or with induction motors depends greatly from the correct estimation of the technical
state of circuits: electric, electromechanical and mechanical. The estimation can be realized
impromptu total – using the central diagnostic position, or to a limited extent – using diagnostic
elements installed in the machine. The total diagnostics should be move impromptu periodic (in
time-limits consequential from the exploitation or after the damage of the machine) (Glinka,
2000; Szymanski, 2003). The local estimation should be realized before every actuation of the
machine. Within the framework of the local diagnostics comes true the technical state: the drive
motor, supply system, control and protections circuits, and effectiveness of the braking system.
For the obtainment of the possibly full automation of diagnostic research of drive system: dis-
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tribution of measuring-circuits from supply circuits, control circuits and protections circuits;
the removal of supervisory- measuring circuits to multiconnector joint situated in the operator
cabin, the optoelectronic separation of measuring-circuits, application of the RS-485 C interface
to communication with the external computer, application of the transmission bus enable the data
transmission and being up to the UIC556 mark card. The central diagnostic post controlled from
main microcomputer should be equipped into devices making possible the realization of technical
research: the mechanical system and the braking system. All results of measurement will be save
in the microcomputer memory. The special simulation program and suitable measuring-transducers
enable a realization of measurement automatic or manual. Results of calculations are presented
tabular and graphic on-screen of the monitor and printed in form of the official record a diagnostic
research. The estimation a technical state of the direct current motor is realized from measuring
of: the isolation resistance of armature and excitation windings, estimate of sogginess degree
of isolating system, resistance of the isolation of brush holder system and the commutator, and
measuring a resistance of motor windings, estimate the degree of the commutation of the motor
and the technical state of brushes. At detailed research we can check the bearing system of the
motor and the trembling and vibrations a corps of the motor. The estimation a technical state of
the direct current motor (Glinka, 2000; Głowacz & Zdrojewski, 2006), we can realized also with
the acoustic method using a system of neural networks. The method consists in the teaching of
the regulator of the neuronal diagnostics of normal and damage of work states on the bases of
analyses a sounds generated by the driving system. The process of the diagnostics of the sound
consists of the teaching process and the identification process with sampling of the Hammings
window. Then, data are exchanged by the algorithm LPC, and for every category are appointive
of linear prediction coefficients. From counted values of coefficients prediction built is the vector
of mark. Proces of teaching and the identification leaning on algorithms of the data processing is presented on the Fig. 7, 8. The leaning classification is on the algorithm of the backward
Fig. 7. The Block scheme of the teaching process
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Fig. 8. The Block scheme of the identification of process
propagation of errors, in the use to the definite neural network. Her result is relative to the value
obtained on the exit-neuron. The process of identification a signal contains following stages:
the registration of the acoustic signal, the partition of the sound-track, sampling, digitizer, the
normalization of the amplitude, the filtration, extraction the mark, the classification. Differences
between typical sounds are a result of differences in well ordered sequences. The classification
bases herself on the neural network with the algorithm of the backward propagation of errors.
The neural network consists of the any number of neurons (elements converting the information).
Neurons are joint into network by means of connections with definite parameters (weights) modified under of the teaching process. After the realization of the teaching stage a neural network
with the algorithm of the backward propagation of errors, follows the identification on the base
the vector the mark of entering on entries of the neural network. If on the exit-neuron we will
obtain the value 0, then the system generates as the result the normal tone. If on the exit-neuron
we will obtain the value 1, then the system gives as the result the sound the damage. The method
of the diagnostics worked out by the prof. Głowacz with AGH Cracow, was verified on the special model of the direct current motor containing different damages. Results of the analysis are
satisfactory (Głowacz & Zdrojewski, 2006; Szklarski & Zarudzki, 2000).The estimation of the
technical state a supply system is realized checking: executive elements, short circuit protections
and realizing programs tested situated in the memory of the microprocessor (set in of over load
protections, short circuit protections, the inspection of the continuity of supply voltage and of
feedbacks driver circuits.
In hoisting-machines we should make a special attention on the technical state of: catenary
and equalizing wires, and the degree of the waste of brake-facings. To investigation of the degree
of the waste the wire used: inductive and supersonic methods (Głowacz & Zdrojewski, 2006).
Research takes part to pass before every the change mining passing the revision of machine drive
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(Głowacz & Zdrojewski, 2006; Szymanski, 2003). To the realization of diagnostic research of
the transportation machine applied a industrial controller, build on the basis of the industrial
equipped computer into modules of the driver of the type fuzzy-logic neuro the net control the
system. This controller can realize different functions: diagnostic, master, of communication and
records. He there is used in DC and AC drives with regulated rotational speed.
5.
Intelligent measuring-sensors in drive system of
hoisting-machines
In every mine finds several main hoisting shafts which performs the transport of the coal
from transfer stations to plant of mechanical coal reshaping. This are largely cable lift shafts
working in the runtime mode of semi-automatic or automatic, at the supervision of the properly
trained motor-driver. For the assurance of correct work system a cable lift hoisting-machine, she
must be equipped into suitable control systems of the drive motors, the regulator of the drive,
the safety circuit, system of the brake shunter and the brake safety system and also in control
circuits of the loading control a coal on the loading station of the cable lift, and the unloading
of coal on unloading station. On transfer stations must be situated marginal sensors, sensors of
the precise location of cable lift, sensors a mass of coal loaded to the cable lift. To check out
of hoisting-machine duty cycle are used analogous or digital drive regulators. Input sizes of
the regulator are: the signal of the rotational speed of the rotor, the linear speed of the dish, the
acceleration and spurt of the cable lift. The control is realized in function of the position of the
dish in the shaft. A signal proportional to way displaced by the cable lift, are signals generated
by magnetic mark on lines read by sensors of the position. These signals are controlled by magnetic transducers located on suitable levels in the gliding lute. In drive part are situated a sensors
controlled a temperature of the bearing system of the machine, the temperature of brake-facings,
and pressures in cylinders of the shunter brake. In electric circuits should be measured values:
motor excitation current, armature current, and temperature of: excitation winding, auxiliary
poles, and compensatory winding. The most of hoisting-machines is driven a motors exacting
foreign cooling, for that reason we should to measure the size of the expense of the air cooling
in fun system. The microprocessor technique enable nowadays enlargement of sensors number
situated in transportation machines (hoisting-machine cable lift or of cage) whose a function is
informing about state of the waste, or about the possibility of performance a damage of drives
(electric motor, system of drive transposition, bearing system, the catenary wire, capel). Most
often can be used thermo-sensors: drives, motor windings, gear, brake-facings , sensors of corps
twitches, and the motor shaft, electric transducers of the type LEM of current and tension voltage
of motor, sensors of the degree of the waste of friction-brakes facings and cracks of the driving
wheel. In the gliding lute should be installed sensors: damages of the line, the speed of dish traffic,
sensor denominative the quantity and the quality of transported coal, and detectors of metal-parts
transported with the coal. Signals from each sensors will be gathered in the computer data base and
used by the intelligent industrial computer treat of decisions on the quality of control, reliability
a work of the device, and the optimum-control with the transportation system. To estimation of
corrosion, the waste and cracks of steel-thin lines and wastes of brake-facings one ought to use
methods magnetically – inductive. (Kowalski, 2006; Pasko & Walczak, 2007)
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6. The microprocessor control system of transportation
machine with application of CAN controller
The control of hoisting machine work assuring the realization of definite transportation task
at established times of rides and with the economic drive, consist to calculation of electromagnetic
torque changes in the function road or times cycle, and calculation of speeds and acceleration
in the function road or times cycle. These sizes should not different from a given values, and
losses of the energy occur during their at elimination should be of minimum. The duty cycle
of the hoisting-machine contains: acceleration periods, drives with constant speed and brake of
both electric and mechanical. Changes temporary decision sizes: driving torque, length of route,
the travel speed, coal weight, give possibility the energy-saving drive at the use of methods of
expert systems and adaptive control of driving motor a machine. For the complexity of procedures
of adaptive control one used the algorithm of the fuzzy logic control with the driver of neural
networks of II degree to marking of the value of electromagnetic torque of the driving motor
a machine (Kowalski, 2006; Pasko & Walczak, 2007). The block scheme of the adaptive fuzzy
leaning regulator on the model of the object is presented on Fig. 9.
Fig. 9. The visual schema of the regulator fuzzy logic neuro the net control
At the elaboration of the verbal description of input variables and fuzzy rules of the inference one uses the knowledge base and the database of the hoisting-machines control. Actually are
applied different versions of regulators: the regulator celled TDLs (Time Delay Liner) on input
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FFNN (Feed-Forward Neural Network), system with the repetition of processes, and real-time
control. It can also apply system with the Wiener identification and linear approximation of dynamic states and non-linear approximation of static states. On Fig. 10 presented the block scheme
of the mathematical model of the hoisting- cable lift machine worked out with the utilization of
Matlab-Simulink and TCAD programs. Simulation model of hoisting machine contain: supply
system rated voltage 110kV, lowering transformer: 110/6kV, DC motor drive hoisting machine,
capacitor battery for compensation of reactive power, and drive system of the main airing fun
driven with synchronous motors, or drives with inductive wound rotor motors in the system of
the subsynchronous cascade. It’s simulation model is based on real existing supply system in one
of polish mines.The simulation model was used to verify of validation set a FLNS regulators.
Example-results of simulation calculations presented on the Fig. 11, 12, 13. Fig. 13 present’s
result’s of computer simulation realized for ZG Piekary hoisting machine data
Results of calculations confirmed the usefulness of ACN regulators in control systems of
hoisting-machines.
Fig. 10. Block scheme of hosting machine simulation model
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Fig. 11. Time diagram of rotation Speer of the motor and electromagnetic torque during
normal work state of hosting machine
Fig. 12. Time diagram of rotation Speer of
the motor and electromagnetic torque
during damage work state of hosting
machine
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Fig. 13. Result’s of computer simulation realized for ZG Piekary hoisting machine data
7. Conclusion
Application of expert control systems in control, inspections, and diagnostics of hoistingmachines demands put into each circuits of additional sensors and measuring-transducers, whose
output signals will make possible the realization of the optimum-control, the running inspection
of technical state a machine and the detection of possible damage states. The application of fuzzy
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logic control permits to take into account a control process of the hoisting-machine situations not
adequate in which difficulty to undertake the proper decision. The fuzzy logic control demands
however import to control systems of microprocessor system and the special software. Economic
impact a import of artificial intelligence methods is very profitable for normal economic conditions can however bring limited advantages in transformation
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Received: 04 November 2009