The prediction of vibration in large electric machines

This thesis reports the development of a reliable method for the prediction of response to electromagnetically induced vibration in large electric machines. The machines of primary interest are DC ship-propulsion motors but much of the work reported has broader significance. The investigation has involved work in five principal areas. (1) The development and use of dynamic substructuring methods. (2) The development of special elements to represent individual machine components. (3) Laboratory scale investigations to establish empirical values for properties which affect machine vibration levels. (4) Experiments on machines on the factory test-bed to provide data for correlation with prediction. (5) Reasoning with regard to the effect of various design features. The limiting factor in producing good models for machines in vibration is the time required for an analysis to take place. Dynamic substructuring methods were adopted early in the project to maximise the efficiency of the analysis. A review of existing substructure- representation and composite-structure assembly methods includes comments on which are most suitable for this application. In three appendices to the main volume methods are presented which were developed by the author to accelerate analyses. Despite significant advances in this area, the limiting factor in machine analyses is still time. The representation of individual machine components was addressed as another means by which the time required for an analysis could be reduced. This has resulted in the development of special elements which are more efficient than their finite-element counterparts. The laboratory scale experiments reported were undertaken to establish empirical values for the properties of three distinct features - lamination stacks, bolted-flange joints in rings and cylinders and the shimmed pole-yoke joint. These are central to the preparation of an accurate machine model. The theoretical methods are tested numerically and correlated with tests on two machines (running and static). A system has been devised with which the general electromagnetic forcing may be split into its most fundamental components. This is used to draw some conclusions about the probable effects of various design features.

Risk assessment applied to comsumer products with reference to CE marking machines for use at work

New Approach’ Directives now govern the health and safety of most products whether destined for workplace or domestic use. These Directives have been enacted into UK law by various specific legislation principally relating to work equipment, machinery and consumer products. This research investigates whether the risk assessment approach used to ensure the safety of machinery may be applied to consumer products. Crucially, consumer products are subject to the Consumer Protection Act (CPA) 1987, where there is no direct reference to “assessing risk”. This contrasts with the law governing the safety of products used in the workplace, where risk assessment underpins the approach. New Approach Directives are supported by European harmonised standards, and in the case of machinery, further supported by the risk assessment standard, EN 1050. The system regulating consumer product safety is discussed, its key elements identified and a graphical model produced. This model incorporates such matters as conformity assessment, the system of regulation, near miss and accident reporting. A key finding of the research is that New Approach Directives have a common feature of specifying essential performance requirements that provide a hazard prompt-list that can form the basis for a risk assessment (the hazard identification stage). Drawing upon 272 prosecution cases, and with thirty examples examined in detail, this research provides evidence that despite the high degree of regulation, unsafe consumer products still find their way onto the market. The research presents a number of risk assessment tools to help Trading Standards Officers (TSOs) prioritise their work at the initial inspection stage when dealing with subsequent enforcement action.

A converter compensator for power factor control in 3-phase induction machines

The advent of the harmonic neutralised shunt Converter Compensator as a practical means of reactive power compensation in power transmission systems has cleared ground for wider application of this type of equipment. An experimental 24-pulse voltage sourced convector has been successfully applied in controlling the terminal power factor of a 1.5kW, 240V three phase cage rotor induction motor, whose winding has been used in place of the usual phase shifting transformers. To achieve this, modifications have been made to the conventional stator winding of the induction machine. These include an unconventional phase spread and facilitation of compensator connections to selected tapping points between stator coils to give a three phase winding with a twelve phase connection to the twenty four pulse converter. Theoretical and experimental assessments of the impact of these modifications and attachment of the compensator have shown that there is a slight reduction in the torque developed at a given slip and in the combined system efficiency. There is also an increase in the noise level, also a consequence of the harmonics. The stator leakage inductance gave inadequate coupling reactance between the converter and the effective voltage source, necessitating the use of external inductors in each of the twelve phases. The terminal power factor is fully controllable when the induction machine is used either as a motor or as a generator.

Mixed-frequency testing of induction machines using inverters

This work has concentrated on the testing of induction machines to determine their temperature rise at full-load without mechanically coupling to a load machine. The achievements of this work are outlined as follows. 1. Four distinct categories of mixed-frequency test using an inverter have been identified by the author. The simulation results of these tests as well as the conventional 2-supply test have been analysed in detail. 2. Experimental work on mixed-frequency tests has been done on a small (4 kW) squirrel cage induction machine using a voltage source PWM inverter. Two out of the four categories of test suggested have been tested and the temperature rise results were found to be similar to the results of a direct loading test. Further, one of the categories of test proposed has been performed on a 3.3 kW slip-ring induction machine for the conformation of the rotor values. 3. A low current supply mixed-frequency test-rig has been proposed. For this purpose, a resonant bank was connected to the DC link of the inverter in order to maintain the exchange of power between the test machine and the resonant bank instead of between the main supply and the test machine. The resonant bank was then replaced with a special electro-mechanical energy storage unit. The current of the main power supply was then reduced in amplitude. 4. A variable inertia test for full load temperature rise testing of induction machines has been introduced. This test is purely mechanical in nature and does not require any electrical connection of the test machine to any other machine. It has the advantage of drawing very little net power from the supply.

Direct current ripple compensation for multi-phase fault-tolerant machines

A second-harmonic direct current (DC) ripple compensation technique is presented for a multi-phase, fault-tolerant, permanent magnet machine. The analysis has been undertaken in a general manner for any pair of phases in operation with the remaining phases inactive. The compensation technique determines the required alternating currents in the machine to eliminate the second-harmonic DC-link current, while at the same time minimising the total rms current in the windings. An additional benefit of the compensation technique is a reduction in the magnitude of the electromagnetic torque ripple. Practical results are included from a 70 kW, five-phase generator system to validate the analysis and illustrate the performance of the compensation technique.

Computational capabilities of multilayer committee machines

We obtained an analytical expression for the computational complexity of many layered committee machines with a finite number of hidden layers (L < 8) using the generalization complexity measure introduced by Franco et al (2006) IEEE Trans. Neural Netw. 17 578. Although our result is valid in the large-size limit and for an overlap synaptic matrix that is ultrametric, it provides a useful tool for inferring the appropriate architecture a network must have to reproduce an arbitrary realizable Boolean function.

Load losses in synchronous machines:a study of the pole face loss caused by armature reaction M.M.F. harmonics

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Learning in ultrametric committee machines

The problem of learning by examples in ultrametric committee machines (UCMs) is studied within the framework of statistical mechanics. Using the replica formalism we calculate the average generalization error in UCMs with L hidden layers and for a large enough number of units. In most of the regimes studied we find that the generalization error, as a function of the number of examples presented, develops a discontinuous drop at a critical value of the load parameter. We also find that when L>1 a number of teacher networks with the same number of hidden layers and different overlaps induce learning processes with the same critical points.

A novel framework of training hidden Markov support vector machines from lightly-annotated data

Natural language understanding (NLU) aims to map sentences to their semantic mean representations. Statistical approaches to NLU normally require fully-annotated training data where each sentence is paired with its word-level semantic annotations. In this paper, we propose a novel learning framework which trains the Hidden Markov Support Vector Machines (HM-SVMs) without the use of expensive fully-annotated data. In particular, our learning approach takes as input a training set of sentences labeled with abstract semantic annotations encoding underlying embedded structural relations and automatically induces derivation rules that map sentences to their semantic meaning representations. The proposed approach has been tested on the DARPA Communicator Data and achieved 93.18% in F-measure, which outperforms the previously proposed approaches of training the hidden vector state model or conditional random fields from unaligned data, with a relative error reduction rate of 43.3% and 10.6% being achieved.

Steps and bumps:precision extraction of discrete states of molecular machines

We report statistical time-series analysis tools providing improvements in the rapid, precision extraction of discrete state dynamics from time traces of experimental observations of molecular machines. By building physical knowledge and statistical innovations into analysis tools, we provide techniques for estimating discrete state transitions buried in highly correlated molecular noise. We demonstrate the effectiveness of our approach on simulated and real examples of steplike rotation of the bacterial flagellar motor and the F1-ATPase enzyme. We show that our method can clearly identify molecular steps, periodicities and cascaded processes that are too weak for existing algorithms to detect, and can do so much faster than existing algorithms. Our techniques represent a step in the direction toward automated analysis of high-sample-rate, molecular-machine dynamics. Modular, open-source software that implements these techniques is provided.

The characterisation and emulation of rotary mechanical machines

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A study of stray load losses in core clamp plates of salient pole synchronous machines

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The use of electronic techniques in the construction of machines which can learn

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Storage capacity of ultrametric committee machines

The problem of computing the storage capacity of a feed-forward network, with L hidden layers, N inputs, and K units in the first hidden layer, is analyzed using techniques from statistical mechanics. We found that the storage capacity strongly depends on the network architecture αc ∼ (log K)1-1/2L and that the number of units K limits the number of possible hidden layers L through the relationship 2L - 1 < 2log K. © 2014 IOP Publishing Ltd.