Communications: electrical – Condition responsive indicating system – With particular system function
Patent
1998-09-30
2000-01-04
Crosland, Donnie L.
Communications: electrical
Condition responsive indicating system
With particular system function
340511, 340577, 340578, 340657, 706 8, G08B 2900
Patent
active
060114649
DESCRIPTION:
BRIEF SUMMARY
BACKGROUND OF THE INVENTION
The present invention relates to a method of analyzing the signal of a hazard detector by frequency analysis and fuzzy logic analysis and to a hazard detector for the implementation of this method. The hazard detector can for example be a flame detector, noise detector, fire detector, passive infrared detector or the like.
The output signals of hazard detectors are often characterised by typical frequency spectra. By analyzing these frequency spectra it is possible to determine the origin of the signals and in particular genuine alarm signals can be differentiated from interference signals and false alarms thus avoided. In particular in the case of flame detectors, the typical low-frequency flickering of a flame is analyzed in order to be able to distinguish the radiation of genuine flames from those of an interference source, such as for example reflected sunlight, or a flickering light source.
The output signals of hazard detectors are analyzed for example by Fourier analysis, fast Fourier analysis, the zero crossing method or the turning point method. The latter is described in GB-A 2 277 989 in the example of flame detectors where the time intervals between radiation maxima are measured and checked in respect of their regularities and irregularities, irregularly occurring radiation maxima being interpreted as a flame and regularly occurring radiation maxima as an interference.
Fuzzy logic is generally known. In the context of the present invention it is to be emphasised that signal values are assigned to so-called fuzzy sets or indeterminate quantities in accordance with an association function, the value of the association function or the degree of the association with an indeterminate quantity amounting to between zero and one. Here it is important that the association function should be able to be normalised, i.e. the sum of all the values of the association function should be one, whereby the fuzzy logic analysis permits a clearly defined interpretation of the signal.
In a flame detector described in EP-A 0 718 814, the frequency of the detected radiation is analyzed, differentiating between regular and irregular signals in specified frequency ranges. The analysis of the various signals in the given frequency ranges takes place in accordance with a plurality of fuzzy logic rules. This method permits a more precise differentiation between genuine flame signals and other interference signals and thus safeguards against false alarms. Here the frequency spectrum is generated for example by fast Fourier transformation, which is costly in terms of the time required for the transformation, the required processor and the processor costs. In part, up to three seconds are required for the determination of a detected signal. However, for specific applications a shorter analysis time and reaction time leading up to the alarm is desirable; in such cases although methods such as the zero crossing method or turning point method or wavelet analysis method speed up the decision process, they are less accurate.
SUMMARY OF THE INVENTION
The object of the invention is to provide a method for the frequency-analysis of a signal of a hazard detector which is combined with fuzzy logic analysis and compared to analysis methods of the prior art is performed with a smaller number of calculation steps so that a result of the same or improved accuracy is obtained in a shorter time.
Furthermore, the method is to be able to be carried out using a simpler processor and thus more cost-effectively.
This object is achieved in accordance with the invention in that a fast wavelet transformation is performed by way of frequency analysis, the original signal being conducted through a multi-stage filter cascade of pairs of high/low-pass filters, and that in each filter stage of the wavelet transformation, from the results of the high-pass filter an association function is in each case produced, which association function is used for the further analysis of the frequency signal in accordance with fuzzy logi
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Mufti M et al., "Automated Fault Detection and Identification Using a Fuzzy-Wavelet Analysis Technique", Conference Record Autotestcon '95, Atlanta, Aug. 8-10, 1995; vol. 31, Aug. 8, 1995, Institute of Electrical and Electronics Engineers, pp. 169-175, XP000555102, at pp. 170-171, Fig. 3.
Cerberus AG
Crosland Donnie L.
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