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Author: admin | 23.12.2014 | Category: Ringing In The Ears Causes

Risk shall mean the combination of the overall probability, or frequency of occurrence of a harmful effect induced by a hazard and the severity of that effect. Risk assessment is performed to determine the magnitude of risk and to establish whether measures are needed to contain it within defined limits.
Amendments to several Annexes to the Chicago Convention applicable since November 2009 introduced harmonised requirements for the implementation of Safety Management Systems (SMS) by aviation service providers.
Aircraft operators and aviation service providers shall also define those levels of management with authority to make decisions regarding safety risks tolerability. Risk assessment is based on the evaluation of the following criteria: the severity of a hazard, the probability (frequency) of its occurrence and tolerability of its effects.
The ultimate criterion used to assess the severity of hazards is the impact on the safety of an aircraft and its occupants and other persons who may be directly affected.
The severity of hazards will be determined by the credible effects on the safety of aircraft, when the outcome of all the weaknesses, potential failures and safeguards (barriers) which may exist in the relevant operational environment have been taken into consideration.
A credible assessment of the severity of hazard effects requires detailed knowledge of the environment of operations and the services (functions) to be performed.
An example of hazard severity classification matrix is provided in the related article on hazard identification. The estimation of the probability of a hazard occurring (or in other words the interval of exposure in which a hazard effect may manifest itself) is usually achieved by means of structured review using a standard classification scheme.
In some cases, data may be available that will allow the making of direct numerical estimate of the probability of occurrence. However, the estimation of the probability of occurrence of hazards (and their effects) which are associated with human error is not straightforward.
The probability classification scheme shown below is extracted from ICAO Doc 9859 - Safety Management Manual. Both probability of occurrence of a hazard effect and the severity potential of that effect, need to be taken into account when deciding on the tolerability (acceptability) of a risk. Numerical values may be assigned in order to weigh the relative importance of each level of severity and probability. Throughout the aviation industry, many different versions of risk assessment matrices are available. The output from risk classification is used to determine the risks the organisation should act upon. Various strategies and approaches can be used by aircraft operators and aviation service providers in order to reduce the unacceptable risks to tolerable levels. According ICAO Doc 9859 - Safety Management Manual, there are many options - formal and less formal - to approach the analytical aspects of risk assessment.
Risk assessment does not represent an end in itself, but should contribute to controlling risks to an acceptable or tolerable level. Aircraft operators and other aviation service provider organisations should establish and apply a formal risk management process within the framework of the organisational SMS. Once hazards and their effects have been determined during the first step by means of hazard identification, an analysis is required to assess the probability of the hazard effects occurring and the severity of these effects on aircraft operation.
Elements to be considered in the severity assessment would include a number of indicators, such as crew workload, exposure time to the hazard, aggravating factors etc. For example, the most severe effect (consequence) will only be chosen in such cases when the total system has exhausted its possibilities to affect what continues to happen and only chance determines the outcome, for example the ingestion by aircraft engines of birds greater than they are designed and certificated to withstand and continue functioning where this occurs simultaneously to more than one engine. This is usually the case when estimating the probability of failure of hardware components of a system. Unless there is a very high capture rate of relevant occurrence data which has been appropriately stratified, it may be difficult to find meaningful empirical data and subjective assessment will then be all that is possible. It specifies the probability as qualitative categories, but also includes numerical values for the probabilities associated with each category. It is a common practice to use a risk classification matrix in support of this two-dimensional judgement. A composite assessment of risk, to assist in comparing risks, may then be derived by multiplying the severity and probability values. Decision making will require clearly defined criteria about acceptable or tolerable risk and unacceptable risk (see “Acceptable Level of Safety” in Safety Planning article). This third and very important step of risk management is discussed further in the Risk Mitigation article. For some risks, the number of variables and the availability of both suitable data and mathematical models may lead to credible results with quantitative methods (requiring mathematical analysis of specific data).


Over time, quantitative data may support or alter the determinations of severity and probability, but the initial risk determinations will most likely be qualitative in nature, based on experience and judgment more than factual data. Risk management shall ensure that risks are systematically analysed (in terms of probability of occurrence and severity of hazard effects), assessed (in terms of tolerability) and controlled to an acceptable level (by implementation of mitigation measures).
ICAO Doc 9859 - Safety Management Manual highlights the importance of distinguishing between hazards (the potential to cause harm) and risk (the likelihood of that harm being realised during a specified amount of risk exposure). Another group factors to be taken into account are the means of mitigation that are considered acceptable by the safety regulator, for example the effective use of TCAS as mitigation means for mid-air collision hazard. As with the estimation of the`severity of a hazard, the development of informed judgments from a structured review by people with extensive experience in their respective fields applied to a standard classification scheme will be the best substitute for absolute values.
Severity is ranked as Catastrophic, Hazardous, Major or Minor, with a descriptor for each indicating the potential severity of consequences. Examples of Risk Assessment and Mitigation in ATM from EUROCONTROL and Predictive Risk Matrix used by FAA for airline operations can be viewed here. The assessment of tolerability (acceptability) is critical in making rational decisions to allocate the limited organisational resources against those risks posing greatest threats and this process often may require a cost-benefit analysis. However, ICAO states that few hazards in aviation lend themselves to credible analysis solely through quantitative methods. Probability of occurrence is ranked through five different levels of qualitative definitions, and descriptors are provided for each probability of occurrence.
Typically, these analyses are supplemented qualitatively through critical and logical analysis of the known facts and their relationships. The analyzed variables are: current and torque peaks, and speed loss in transient and steady states.
The severity of these effects is analyzed with 14640 voltage sags, both at the beginning of the voltage sag and when the voltage is recovered, by changing the type, magnitude, duration, and initial-point-of-wave.
Four mechanical torque loads were used for the analysis, three with constant behavior and one with quadratic behavior. The results show the durations and initial-point-of-wave with more severe effects for each type of voltage sag.
Finally, a classification that depends on the type of voltage sag and the variable of interest is obtained. Los resultados muestran las duraciones y los puntos de la onda inicial que tienen efectos más severos para cada tipo de hueco.
Single-line-to-ground, phase-to-phase or two-phase-to-ground faults cause unsymmetrical sags. Their reaction to voltage sag may generate speed loss, high current peaks or high torque peaks, which produce unwanted activations in the electrical protection system in production plants, stopping the processes and causing major economic losses.
As for power quality, if the motors are high power, the consequences of the current peaks and torque produced by voltage sags may cause other electromagnetic disturbances at the nearest point of common connection (PCC) such as swells, fluctuations or even other voltage sags. However, the effects of other parameters of voltage sags have not been studied, nor has their codependence or the effect of a massive amount of sags for each variable.
Other studies have omitted the effect of loads and transients generated when the voltage sag starts and when it returns to its initial value.
This is because the model of the motor used is a single-cage rotor, which is only suitable for analysis at points close to the rated operating point of the motor.
The following procedure analyzes the current and torque peaks, and the speed loss in the induction motor, in transient and steady states, for 14640 different cases of voltage sags, taking into account the parameters of the sags: type, magnitude, duration and initial point-on-wave, and thus codependence, and the effects produced when the sag starts (ds-zone) and when it ends (as-zone). Induction motor The motor selected for analysis is a 75 kW three-phase induction motor, with squirrel cage rotor, 3300 V supply (isolated delta), 50 Hz, rated current = 13,62 A, rated torque = 401,5 Nm, moment of inertia = 1,2 kg?m2 and rated speed = 1464 rpm. In order to prove that the model represents a suitable behavior of the motor, the behavior obtained with the estimated parameters is validated with experimental data of the torque-speed curve of motor. Induction motor model The model selected for analysis is a double-cage rotor (D-C) since the voltage sags can cause the motor to run at speeds far from the nominal operating point, where a single-cage model does not properly represent the behavior of the motor. Electrical and mechanical equations of D-C model The electrical equations of the D-C model are shown in matrix form in (1). Subsequently, the solution in the original variables is obtained by applying the inverse Ku transform to the found solution. In induction motors with squirrel-cage rotor, the windings of the rotor are shorted, so the Homopolar current in the rotor is zero. The Forward and Backward voltages (both stator and rotor) are complex conjugated with each other; this implies that only the Forward equations of the rotor and stator are necessary for the resolution of the system. Electric parameters of the D-C model After determining the electrical and mechanical equations of the system, the values of the parameters of the model of Fig.


2 illustrates 25 experimental data (ED) for the induction motor and the simulation of behavior obtained with the estimated parameters (D-C).This validation shows that the selected parameters generate a very accurate behavior throughout the motor operating range. All values are normalized to the rated value of each variable and the values are presented per unit (pu). A three-phase fault produces symmetrical sags (type A); single-line-to-ground, phase-to-phase or two-phase-to-ground faults cause unsymmetrical sags (types from B to G).
However, when the connection of the load is not grounded, voltage sags type G have identical equations and behavior as voltage sags type E. Sags characterization In this paper, the shape of voltage sags has been defined as rectangular, with initial time ti and recovery time tf, no phase jump occurs, and the voltage recovery is produced at the same time in the three phases. 3 illustrates a voltage sag type B in phase a, with ti = 0 s, h = 25%, Dt = 5,5 cycles, and y i = 0?.
Characteristics of analysis The transient effects of voltage sags on three-phase induction motors are analyzed in current and torque peaks, and speed loss. In this paper, the effects are analyzed in two zones: during sag (ds-zone) and after sag (as-zone).
Later, by using Dtmu and yimu, the effect of the duration and magnitude of the voltage sags is analyzed codependently, by simulating 14640 different cases of voltage sags, thus selecting 6 types of sags (A-F), 61 durations and 40 magnitudes.
For each voltage sag, the values of current and torque peaks, and speed loss are obtained. These data generate 3D surfaces for each variable, which are analyzed with their respective sensitivity curves. Finally, the analysis of the sensitivity curves leads to the classification of the voltage sags according to the severity of the effect on the induction motor. 7 show the current and torque peaks (y-axis), respectively with respect to the initial points-on-wave (x-axis) varying from 0? to 180?. For unsymmetrical sags, yi has a big influence on the current and torque peaks, but small influence on speed loss. The voltage sags type B, D, and F produce maximum current and torque peaks when yi = 90?, and the sags type C and E (and G) when yi = 0?. The values selected for yi and Dt, are the most unfavorable in each case, according to Table 3.
For each simulated sag, the algorithm calculates the values per unit of the transient variables: current peaks (ipeak), torque peaks (Tpeak) and speed loss (smax) of the motor by using eq. Analysis of sensitivity curves For each sag type, the matrices IX, TX, and SX can be represented as 3D surfaces. 9 shows the sensitivity curves of IX, and highlights two results: first, sags type B are the least severe sag since, with the same magnitudes and durations, all other types of sags generate higher current peaks. In this case, the types of sags can be grouped into four groups: Sags types C and D show the highest torque peaks, followed by sags type E and F, then sags type A, and finally sags type B.
In this case, sags type A have higher speed loss in most cases, followed by sags types E and F, and sags types C and D.
For example, for current peaks IMAX(h, Dt) = max {IA(h, Dt), IB(h, Dt), IC(h, Dt), ID(h, Dt), IE(h, Dt), IF(h, Dt)}.
Conclusions Using the double cage model, in this study, we analyzed the effects of voltage sags types A, B, C, D, E, F, and G on the variables: current and torque peaks, and speed loss in the induction motor. Each variable was analyzed using 14640 sags, for different magnitudes, durations and initial point-on-wave. The severity of each type of sag was obtained by calculating the distance between the 3D surface of peaks and the 3D surface of maximum peaks, for each analyzed variable. In fact, the most unfavorable values of duration of sags analyzed, have an effect on torque and current peaks when the voltage sag ends. Currently, he is a full professor in the Electrical Engineering Department of the URV, where he has been since 1990.
He is a full professor in the Department of Electrical Engineering, Universidad Distrital Francisco José de Caldas, where he currently teaches courses on analog circuits and power electronics. His main research interests include: modeling and control of power converters applied to the distributed generation and microgrids.



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