Predictive Noise Alerts Using Equipment Acoustic Models
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Solution Overview
Problem
Existing noise monitoring systems in data centers rely on microphones, which are costly, prone to failure, and raise privacy concerns, and provide inaccurate readings due to placement limitations and environmental factors, leading to false safety label impressions.
Innovation Solution
A noise level model is created using acoustic models for each piece of equipment, estimating noise levels based on operational characteristics without microphones, and providing alerts when thresholds are exceeded, using visual, haptic, or auditory signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If microphones are used for noise monitoring, then noise level detection is provided, but cost increases and privacy concerns arise
Solution Approach 1:
The patent creates acoustic models that replicate the noise measurement function without using physical microphones. The models compute estimated noise levels based on equipment operational data, serving as a virtual copy of the measurement function that eliminates the need for expensive physical sensors while maintaining measurement capability
Solution Approach 2:
The patent replaces the mechanical/acoustic measurement system (microphones) with a computational system. Instead of physically capturing sound waves, the system uses algorithms to calculate noise levels from operational parameters, substituting a mechanical sensing approach with an information-processing approach
2Measurement precision
If microphones are used for noise monitoring, then noise level detection is provided, but reliability decreases due to placement limitations and environmental factors
Solution Approach 1:
The acoustic models create a virtual representation of noise measurement that is independent of physical placement constraints. By computing noise levels from equipment operational data rather than physically capturing sound, the system eliminates reliability issues related to microphone placement and environmental interference
Solution Approach 2:
The patent introduces operational characteristics data as an intermediary between the noise source and measurement. Instead of directly measuring sound waves that can be affected by placement and environment, the system uses equipment operational parameters as a mediator to infer noise levels, removing the direct dependency on physical measurement conditions
3Ease of manufacture
If static safety labels are used, then noise regulation compliance is achieved, but false impression of risk is conveyed
Solution Approach 1:
The patent transforms the static safety label into a dynamic alerting system that changes based on current operational conditions. Instead of displaying fixed worst-case scenarios, the system continuously updates noise level estimates and provides alerts only when actual thresholds are exceeded, making the risk information dynamic and condition-dependent rather than static and constant
Solution Approach 2:
The system changes the parameter of risk communication from fixed worst-case values to variable real-time estimates. By using operational characteristics to dynamically adjust the noise level assessment, the system provides accurate risk information that reflects current conditions rather than static maximum values, preventing false impressions while maintaining compliance
Data Source
AI summary
Computer-implemented methods for providing alerts of an estimated noise in a location are provided. Aspects include receiving operational characteristics from each of one or more of pieces of noise generating equipment in a location, inputting the operational characteristics into noise level models corresponding the one or more of pieces of noise generating equipment, and receiving a total estimated noise level for the location from the noise level model. Aspects also include comparing the total estimated noise level to one or more threshold levels and activating one or more alerts based on the comparison, wherein the one or more alerts indicate a risk level associated with exposure to the total estimated noise level.