Early fire detection using temperature and smoke sensing

Communications: electrical – Condition responsive indicating system – Specific condition

Reexamination Certificate

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C340S511000, C340S522000, C340S578000, C340S628000

Reexamination Certificate

active

06195011

ABSTRACT:

BACKGROUND OF THE INVENTION
Most fire detection systems generate an alarm condition in response to a measured environmental factor that indicates the existence of a fire. Photoelectric smoke detectors, for example, determine a light obscuration level in sampled air and trigger an alarm condition when this obscuration exceeds some predetermined threshold. In most cases, the obscuration is due to smoke in the atmosphere. Many thermal fire detectors operate on a similar principle. They will trigger the alarm when the measured ambient temperature reaches 130° F., for example.
One improvement to these threshold-based detector systems is the maintenance of a running average or quiescent value against which each current sample is compared. For example, in the smoke detectors, a long-term running average, over 24 hours for example, is kept for the detected obscuration levels, and the current sample is compared against this average. An alarm condition is generated when a current sample exceeds this average obscuration by the threshold, which does not change in time. The advantage of this approach is that the smoke detectors will maintain substantially the same sensitivity over time, mitigating the effects of aging and dirt accumulation in the detection chamber.
A similar approach is taken with the heat detectors. The time period over which the running average is kept, however, tends to be shorter to account for the fact that the temperatures within buildings change across a 24 hour period. Thus, the smoke detector will have substantially the same sensitivity at night, when the building is cold, and during the day when the building tends to be hotter.
In order to improve early detection capabilities, various systems have been proposed that generate alarms based not upon the net level of the sampled physical phenomenon but on the changes or trends in the sampled data. One of the earliest examples of this type of system is disclosed in U.S. Pat. No. 4,254,414 to Street, et al. The disclosed processor-aided fire detector tracks the sample-to-sample changes in the detected obscuration levels. The detector generates various levels of alarms based upon the time over which the atmospheric obscuration has been continuously increasing. Rate-of-rise temperature detectors rely on a similar approach. These devices generate an alarm when the temperature is increasing quickly over a defined period of time. The assumption is that this rapid temperature rise is, with high probability, initiated by fire.
In general, these trend-based devices tend to have good early detection characteristics, but can be subject to higher instances of false alarms. It is problematic to filter the data to ensure that random events occurring over the course of years do not satisfy the trend criteria necessary to activate the alarm.
In order to improve the fire detector's resistance to false alarms and improve uniformity over a wide range of fire types, a number of different approaches have focused on generating alarms based upon the outputs of two or more sensors. Researchers have studied the cross correlations between the changes in temperature; smoke density according to extinction effects or scattering effects; effects on ion flow in a measuring ionization chamber; and concentrations of carbon monoxide, carbon dioxide, total hydrocarbons, and oxides of nitrogen as predictors of fire. See
Fire Detection Using Signal Cross Correlation Techniques
, by G. Heskestad, et al., Factory Mutual Research Corporation.
SUMMARY OF THE INVENTION
Fire detection systems that rely on the response signals of multiple sensors can have excellent early fire detection capabilities for specific fires. Based upon the nature and contents of a protected area, a detector that monitors the trends in the data from multiple sensors can be selected to sensitize the system to a typical fire in that location.
In some instances, the characteristics and nature of a potential fire can be predictable. Certain physical phenomena, such as heat and smoke, show definite correlated trends in known directions. The use of cross correlation or covariance type functions can utilize this feature to provide an excellent early warning response. However, a cross correlation type detection scheme that is optimized for one type of fire will not work as well for other types. In situations where a fire does not create significant levels of either of the physical phenomena which are sensed by the detector, the case may arrive that the correlation scheme will not work as rapidly as the conventional threshold or rate of rise schemes or it might not work at all. For example, in a given location, there may be a high risk of a wood consuming fire. A cross correlation between changes in carbon monoxide concentrations and changes in ionization would be an excellent basis for early detection for this type of fire. If the fire source were ethanol, however, this cross correlation would perform poorly. In some cases, it may respond more slowly than conventional detection systems. Such a tradeoff is unacceptable.
The present invention solves this problem by comparing the responses of different sensors over time to achieve the early-detection characteristics associated with this type of system. This can be achieved with a cross correlation or covariance function, for example. The system, however, also performs conventional threshold or rate of rise type detection. If the thresholds are surpassed for any one of the sensors, the alarm condition will be set. Effectively the invention incorporates each type of detection scheme: threshold, rate of rise, and a cross correlation type function, and continually tests for an alarm condition generated by any one of them. As a result, the detection characteristics of the resulting system can achieve the early detection associated with a cross correlation or covariance type function but still rely on the conventional threshold or rate of rise type detection. Thus, it achieves the best performance characteristics of both approaches.
In general, according to one aspect, the invention features a fire alarm system. This system includes at least two sensing units that detect different physical quantities associated with fire. In specific embodiments, the units detect smoke and temperature. An alarm condition may be set if either physical quantity exceeds the associated thresholds for the quantities. A controller, however, additionally compares the changes in the detected quantities over time. An alarm condition will be set if these changes are indicative of a fire. Thus, an alarm condition may be triggered upon the occurrence of any one of three events.
In other embodiments, the smoke detection may be made less subject to false alarms due to transient smoke by only setting the alarm condition after detecting smoke for longer than a single sampling period.
In still other embodiments, rate of temperature rise detection may also be used. Here again, false alarm immunity may be added by only setting the alarm condition after the threshold rate of rise has been exceeded for longer than a single sampling period.
The invention may also be characterized as a method for detecting fire and setting a fire alarm condition. This method includes detecting a first physical quantity associated with fire, smoke for example, and setting an alarm condition if the first physical quantity exceeds a first threshold. A second physical quantity associated with fire, temperature for example, is also detected and an alarm condition set if the second physical quantity exceeds a second threshold. Finally, the changes in the detected first and second physical quantities are compared to each other. An alarm condition is also set if the changes are indicative of a fire.
The above and other features of the invention including various novel details of construction and combinations of parts, and other advantages, will now be more particularly described with reference to the accompanying drawings and pointed out in the claims. It will be understood that the particular method and devi

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