Maija Uusitalo, Metso Automation Inc., Finland
Risto Saarinen, Foster Wheeler Energia Oy, Finland
Competitive and environmental needs have put new demands on boilers and have created a need for optimized plant operation. Integrating boiler life monitoring systems into a plant’s information management system can provide operators and manufacturers with a tool to respond to these needs.
In today’s competitive environment very few power plants can operate in the pure base load mode. Continual output changes are common due to market demands and more and more boilers need to operate in multiple modes. This means stressing the boiler components far beyond the traditional design criteria. Boiler maintenance and design therefore have to be adapted to cater for the new requirements.
Boiler life monitoring is in the interest of both the operating and maintenance personnel of a power plant and the boiler manufacturer. Real-time knowledge concerning the exhaustion level of different boiler components provides an operator with a tool that contributes to better scheduling of maintenance activities that will extend boiler service life. At the same time, data gleaned from boiler operation history enables the boiler manufacturer to better service the boiler, while providing valuable knowledge for future development.
Monitoring systems, such as Metso’s Boiler Life Monitoring application, can therefore be an important part of a power plant information management system. Information management systems consist of various applications and are becoming a more integrated part of process equipment manufacturers’ supply. A boiler life monitoring application can be a fixed part of the supply that is automatically delivered with the equipment to a new plant. In addition, new remote access IT technologies make it possible to utilize these systems irrespective of their actual location.
The purpose of boiler life monitoring, as part of power plant information management system, is to store and process measured data of selected pressurized components into condition related parameters such as temperature gradient, mean wall temperature, stress and exhaustion level.
Exhaustion analysis includes the two major damage mechanisms: creep and fatigue. The first means material degradation of stressed components due to high temperatures, the latter is induced by load (stress) cycles.
The input data of analysis includes component internal pressure, metal temperatures inside component wall and component geometrical data. Temperatures in the component wall are measured with typically two thermocouples, one near the inner wall and the second in the mid wall.
A typical case would consist of about 25 boiler components, 20 of which are thick-walled components (e.g. the steam drum, superheater outlet and inlet headers) and the rest are superheaters and reheaters. The steam drum typically needs 12 temperature wells to be drilled: three measurement couples (inner and middle) located in the upper part of the drum and another three measurement couples located in the lower part of the drum. The superheater inlet and outlet headers usually have either one or two measurement couples. The fatigue and creep analysis is carried out separately for each measurement couple. For example, the exhaustion level of the boiler drum is calculated separately in six locations. The surface temperature of the superheater and reheater tubes is measured in 20-40 locations. These temperatures are presented in temperature profile display.
Fatigue and creep analysis is carried out for thick-walled components. The temperature gradient, Δv, across the wall is calculated, based upon the measurements of metal temperatures.
υi= Inner surface temperature of wall (°C)
υm= Mean wall temperature (°C)
υzi = Measured temperature of inner thermocouple (°C)
υzm = Measured temperature of middle thermocouple (°C)
fk = Correction factor (function of geometrical values).
Similarly, the mean wall temperature is calculated from
fkm= correction factor (function of geometrical values).
The time varying total stress consists of two parts: the mechanical stress caused by internal pressure and the thermal stress induced by thermal gradients. The stresses are calculated at the largest hole edge, because it is a determining factor to service life. The total hole edge stress, σi, is defined by
σi = Total hole edge stress (N/mm2)
am = Stress concentration factor for mechanical stresses
ρ = Internal pressure (N/mm2)
dm = Mean diameter of component (mm)
sb = Design wall thickness (mm)
av = Stress concentration factor for thermal stresses
βLv = Differential thermal expansion coefficient (1/°C)
Ev = Modulus of elasticity (N/mm2)
υ = Poisson’s ratio.
In order to calculate the exhaustion level due to fatigue, the start and stop point of each stress cycle is determined by the Rainflow method, which checks as a real time analysis, whether the calculated stress value is a minimum or maximum and determines the superimposed stress cycles.
The incipient crack formation load cycle number, Ni, for each stress cycle is derived from an appropriate S-N-fatigue curve.
The exhaustion level due to fatigue, Dfa, is calculated on the basis of the linear damage rule.
In case of creep, the mean wall temperature and the stress of a component determine service life under certain operating conditions. The service life is iterated from the tables of creep rupture strength. The creep rupture strength values for materials are interpolated and extrapolated from accepted values in standards and data sheets using Larson-Miller parameter.
The exhaustion level due to creep, Dcr, is obtained from
Dcr = Exhaustion level due to creep
ti = Operating time in conditions i (h)
Li = Service life in conditions (h).
And further, remaining service life in hours (h) can be estimated based on history data of total operating hours and total exhaustion.
The application platform of Metso’s Boiler Life Monitoring (BLM) application consists of three main components: database, on-line calculation and user interface. The measured data (temperatures and pressures) are collected from digital control system to Metso’s DNAhistorian database. The calculations take place in the DNAproCalc calculation environment, which automatically reads the measured data from DNAhistorian, runs the calculations and writes the results of calculations to DNAhistorian.
The calculation cycle is typically one minute. The results of calculations are stored in DNAhistorian for a defined time period. The saving time for different type of data can be freely chosen, a common saving time for measured data being one year and for exhaustion levels, 10-20 years. The data can also be archived to tapes and later on retrieved back to DNAhistorian. The results of calculations are presented in displays and reports, which are built in DNAprocessExplorer, a tool for making process graphics, and Microsoft Excel.
Knowledge concerning service life consumption and the other parameters related to it, contributes to optimized plant operation and a reduction in maintenance cost. Continuous monitoring of temperature gradients and stresses enables shorter start-up times and quicker load changes, which in turn leads to increase in output.
Figure 2. Metso’s Boiler Life Monitoring application can help operators and manufacturers meet the demands of today’s competitive market
It is also possible to compare what effect different operational modes have on the service life of the boiler. Moreover, the boiler life monitoring system can warn operating personnel when exceeding allowable temperature limits.
For example, if a power plant does not have a boiler life monitoring system, the operator will not get any warnings about exceeding allowable temperature limits. If the plant’s allowable temperature limit of 530°C is exceeded by 20°C during 20 per cent of the operating time and the header is manufactured from material 10CrMo910, a service life of about 125 000 h should be expected instead of the designed 200 000 h.
If, however, a power plant does have a boiler life monitoring system, the operator will get warnings and the allowable temperature limit will not be exceeded. This increases service life to the design value.
Estimations of remaining service lives of different components can enable optimized scheduling of maintenance. Boiler life monitoring provides the operating personnel with a tool which can help in decision-making: whether to postpone an inspection or reduce both the extent of an inspection and the resulting maintenance work. Better knowledge gained about the exhaustion level and consumption of service life also reduces the risk of the unscheduled shutdowns, which can result in remarkable costs.
Towards further development
The design and manufacture of boilers can be improved by obtaining historical data concerning the behaviour of the boiler and its critical components. A better understanding of conditions in the boiler helps to avoid excessive margins in design and helps to optimized and enhance the reliability of boilers.
Information management systems consisting of various applications, such as boiler life monitoring, performance monitoring or emission monitoring are becoming more integrated part of process equipment manufacturer’s supply. The collection and storage of boiler data together with boiler life monitoring application can be a fixed part of the supply that is automatically delivered with the equipment to a power plant. New remote access IT technologies make it possible to utilize these systems irrespective of the actual location of each system and hence enable better support for the customers.