Vibration Sensor Threshold Adjustment Using Event History
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Solution Overview
Problem
Adjusting the vibration detection threshold for building sensors is complex and time-consuming, often leading to suboptimal operation due to false alarms or missed alerts, and is influenced by the sensor's environment, requiring manual trial and error adjustments.
Innovation Solution
A method for adjusting the detection threshold based on the sensor's detection history, which includes classifying events by intensity and allowing for remote adjustment through a home automation device, with options for manual, semi-automatic, or automatic threshold setting using historical data analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the detection threshold is set low to detect all intrusion attempts, then detection sensitivity is improved, but false alarm rate increases
Solution Approach 1:
The system performs preliminary classification of vibration events by intensity level before triggering alerts. Events are sorted into multiple intensity categories (first level, second level, etc.), and only events exceeding a dynamically determined threshold generate alerts. This preliminary sorting action allows the system to distinguish between significant intrusions and minor disturbances, maintaining high detection sensitivity while reducing false alarms.
Solution Approach 2:
The detection threshold is not fixed but dynamically adjusted based on the distribution of detected event intensities. The system analyzes the frequency distribution of vibration events across different intensity levels and automatically sets the threshold at an optimal level (e.g., at the boundary between the most frequent intensity level and the next higher level). This parameter adaptation resolves the contradiction by making the threshold sensitive enough to detect intrusions while high enough to filter out common false alarm sources.
2Object-generated harmful factors
If the detection threshold is set high to reduce false alarms, then false alarm rate decreases, but detection sensitivity is reduced
Solution Approach 1:
The system dynamically adjusts the detection threshold based on the statistical distribution of detected events rather than using a fixed high threshold. By analyzing the frequency distribution across multiple intensity levels and selecting the threshold at an optimal boundary (such as between the most frequent level and the next level), the system maintains high detection sensitivity while naturally filtering out false alarms through the data-driven threshold selection.
Solution Approach 2:
The system continuously monitors the distribution of vibration event intensities and uses this feedback to automatically adjust the detection threshold. The threshold setting process incorporates feedback from the actual event distribution data, allowing the system to adapt to changing environmental conditions and maintain optimal detection performance without manual intervention.
3Adaptability or versatility
If manual adjustment of the detection threshold is performed through trial and error, then the threshold can be adapted to the sensor environment, but adjustment time increases
Solution Approach 1:
The system performs self-adjustment of the detection threshold by automatically analyzing the distribution of detected vibration events and determining the optimal threshold value. The sensor system itself, through its processing unit, carries out the adaptation to the installation environment without requiring external manual intervention. The system collects event data, classifies events by intensity, analyzes the distribution pattern, and autonomously sets the threshold, thereby achieving environmental adaptation instantly without time-consuming manual trial and error.
Solution Approach 2:
The system performs preliminary classification and analysis of vibration events immediately upon detection, sorting events into intensity levels and analyzing their distribution before final threshold determination. This preliminary processing action enables the system to quickly adapt to the environment and establish an optimal threshold without requiring extended manual adjustment periods.
4Device complexity
If the detection threshold is permanently set at the factory, then device complexity is reduced, but adaptability to different installation environments is lost
Solution Approach 1:
The detection threshold transitions from a static factory-set value to a dynamic value that automatically adapts to the installation environment. The system continuously or periodically analyzes the distribution of detected vibration events and adjusts the threshold accordingly. This dynamic adjustment mechanism allows the same simple device structure to adapt to different environments (residential, commercial, industrial, different building materials) without increasing physical complexity, as the adaptation is achieved through software-based statistical analysis rather than hardware modifications.
Data Source
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AI summary
A method for adjusting a vibration detection system applied to an object, comprising: a) setting a first detection threshold beyond which a signal is emitted, b) dividing the measurement range of the detection system into n intervals, each interval corresponding to a range of vibration intensity, c) associating an event counter with each interval, d) assigning a value to each event, e) counting the vibration events in the counters according to their intensity during a given period of time so as to obtain a history of the events detected by the system during the given time, f) processing the values of the counters to determine a second detection threshold adapted to the vibrational environment of the system, g) determining a second detection threshold, h) adjusting said detection system with the second detection threshold.