Human adaptive mechatronics methods for mobile working machines

Despite the trend of increasing automation degree in control systems, human operators are still needed in applications such as aviation and surgery, or machines used in remote mining, forestry, construction, and agriculture, just to name a few. Although there are research results showing that the performance between the operators of working machines differ significantly, there are currently no means to improve the performance of the human-machine system automatically based on the skill and working differences of the operators. Traditionally the human-machine systems are designed so that the machine is "constant" for every operator. On the contrary, the Human Adaptive Mechatronics (HAM) approach focuses on individual design, taking into account the skill differences and preferences of the operators. This thesis proposes a new type of a HAM system for mobile working machines called Human Adaptive Mechatronics and Coaching (HAMC) system that is designed to account for the challenges regarding to the measurement capability and the work complexity in the real-life machines. Moreover, the related subproblems including intent recognition, skill evaluation, human operator modeling, intelligent coaching and skill adaptivity are described. The intent recognition is solved using a Hidden Markov model (HMM) based work cycle modeling method, which is a basis for the skill evaluation. The methods are implemented in three industrial applications. The human operator modeling problem is studied from the structural models' perspective. The structural models can be used to describe a continuum of human operator models with respect to the operating points of the controlled machine. Several extensions and new approaches which enable more efficient parameter estimation using the experimental data are described for the conventional Modified Optimal Control Model (MOCM) of human operator. The human operator modeling methods are implemented to model a human operator controlling a trolley crane simulator. Finally, the concept of human adaptive Human-Machine Interface (HMI) is described. The analytic and knowledge-based approaches for realizing the HMI adaptation are presented and implemented for trolley crane simulator control

Puun rungon syöttöprosessin suorituskyvyn arviointi Markovin piilomallien avulla

Tämän diplomityön tavoitteena on kehittää menetelmiä joilla voidaan analysoida tavaralajimenetelmässä käytetyn harvesterin puun rungon syöttöprosessin suorituskykyä koneessa valmiiksi olevalla mittauslaitteistolla. Syöttöprosessista tallennettavat mittausvektorit koostuvat diskreeteistä tapahtumista. Lisäksi vektorien pituudet vaihtelevat satunnaisesti. Mittausaineiston analysointiin kehitetään Markovin piilomalleihin perustuva menetelmä. Olosuhteiden vaikutusta suorituskykymittauksiin pyritään pienentämään tilastollisesti luokittelemalla mittaukset harvesteripään toimintapisteen mukaan. Suorituskyvyn parannuspotentiaalin visualisointiin kehitetään useita menetelmiä. Lisäksi menetelmiä normalisoitujen suorituskykyindeksien yhdistämistä yhdeksi pääindeksiksi kehitetään ja kokeillaan. Työn tulosten perusteella voidaan arvioida kuinka paljon puun rungon syöttöprosessin suorituskykyä voidaan parantaa. Kehitettyjen menetelmien avulla voidaan havaita miten prosessissa mahdollisesti esiintyvät ongelmat ilmenevät, joka voi auttaa suorituskyvyn parantamiseen tähtäävien korjaavien toimenpiteiden kohdistamisessa

Modeling ship energy flow with multi-domain simulation

Ship energy efficiency is becoming more and more attractive to ship owners, builders and researchers due to the increasingly high fuel cost and the accumulatively strict international maritime rules. It is especially evident for modern ships with complex power plants including mechanical, electrical and thermohydraulic systems. Marine engines, as the heart of ship power plant, play a key role in the fuel energy utilization. But, even for a very efficient marine engine, only less than 50% fuel energy can be converted to useful work. The other over 50% of fuel energy is mainly taken away in a form of heat energy by engine cooling water system and exhaust gas system during the combustion process. Practically, quite a many methods, such as waste heat recovery, have been already developed to enhance the total efficiency of ship power plants. However, there still is not a clear and thorough understanding of the operating efficiency of different processes due to their complexities, which is specifically true for the steam powered systems. In this paper, a new method is introduced to model the ship energy flow for thoroughly understanding the dynamic energy distribution of the marine energy systems. Due to the involvement of different physical domains in the energy processes, the multi-domain simulation method is employed to model the energy flow within Matlab/Simscape environment. The energy processes are described as multi-domain energy flow as function of time. All the main energy processes are to be modeled as subsystems only at a general and system level, and to be built as simple but comprehensive as possible to facilitate the simulation interaction among different main subsystems. For each subsystem, the developed model contains rather simple description of the energy processes involved. The operation and load profiles from real operation data can be given as inputs to examine the dynamic energy balance during the operation. The validation results have positively shown the feasibility and reliability of the energy flow simulation method. The developed energy flow simulation method could further help people better monitor the ship energy flow and understand ship energy systems. More importantly, it could give some valuable insights into how to design an energy-efficient ship power plant and how to operate the vessel efficiently. Furthermore, it could be easily utilized to test and verify new technologies, and hence to find possible ways to improve the energy efficiency of both the existing and new-building ships.©CIMA