• Journal of the Korea Society of Computer and Information
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• v.24 no.2
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• pp.139-147
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• 2019

A false alarm, which is an incorrect report of an emergency, could trigger an unnecessary action. The predictive maintenance framework developed in our previous work has a feature whereby a machine alarm is triggered based on sensor data evaluation. The sensor data evaluator performs three essential evaluation steps. First, it evaluates each sensor data value based on its threshold (lower and upper bound) and labels the data value as "alarm" when the threshold is exceeded. Second, it calculates the duration of the occurrence of the alarm. Finally, in the third step, a domain expert is required to assess the results from the previous two steps and to determine, thereby, whether the alarm is true or false. There are drawbacks of the current evaluation method. It suffers from a high false-alarm ratio, and moreover, given the vast amount of sensor data to be assessed by the domain expert, the process of evaluation is prolonged and inefficient. In this paper, we propose a method for automatic false-alarm labeling that mimics how the domain expert determines false alarms. The domain expert determines false alarms by evaluating two critical factors, specifically the duration of alarm occurrence and identification of anomalies before or while the alarm occurs. In our proposed method, Hierarchical Temporal Memory (HTM) is utilized to detect anomalies. It is an unsupervised approach that is suitable to our main data characteristic, which is the lack of an example of the normal form of sensor data. The result shows that the technique is effective for automatic labeling of false alarms in sensor data.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.54 no.6
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• pp.262-268
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• 2005

In this work, to obtain the detailed information about lightning electromagnetic field waveforms, the LabVIEW based-measurement system of time-changing magnetic fields was designed and constructed. The frequency bandwidth of the magnetic field measuring system ranges from 300 [Hz] to 1 [MHz], and the response sensitivity is 2.78 [mV/nT]. Data acquisition system with the resolution of 12 bits and memory capacity of 32 [Mbyte] was triggered by the magnetic field to be measured. The properties and parameters of the magnetic fields produced by cloud discharges were statistically investigated. The magnetic field waveforms radiated from cloud lighting discharges tend to be bipolar, with two or more narrow and several pulses superimposed on the initial front part. The recording length of the magnetic field measurement system is about 10 [ms]. The mean duration of cloud discharges is 1.3 [ms], and the number of outburst pulses for the period is 8 in average. The front times of the magnetic fields are 6.15 [$\mu$s] in average. The the zero-to-zero crossing times that is the initial half-cycle duration is widely dispersed and the mean value is 9.61 [$\mu$s], and the mean value of percentage depth of dip to opposite polarity is 41.1 [$\%$].