Abnormal sound detection and analysis system

The terminal noise measurement and intelligent identification system of industrial products is a set of noise measurement and intelligent identification system integrating silent environment box, acoustic measurement, autonomous learning, data processing and automatic control. It is suitable for noise quality detection, data analysis, abnormal noise identification and prediction of industrial products on the production line. The system provides users with a very low background noise test environment, autonomous learning, collecting product noise time domain and frequency domain signals, a variety of weighted sound levels, etc. it has the functions of data post-processing, analysis, storage, detection and traceability, and automatically identifies qualified and unqualified noise products.

Product function

  • Contrast dimension

    Terminal noise measurement and intelligent identification system for industrial products

  • function

    Detection, data analysis, audio data storage, material traceability, early warning, automation, etc

  • Acoustic index

    When it is arranged on the production line with high noise and vibration, the background noise is lower than 20 dB, which has obvious advantages

  • Occupied space

    Small and flexible

  • Intellectualization

    Have intelligent learning ability and data analysis and processing ability

  • detection efficiency

    The automatic design is adopted, and the detection efficiency is improved by 5-10 times

  • manufacturing cost

    Compared with the traditional anechoic chamber, the cost is only 40% - 50%

  • Functional plasticity

    Relatively strong

product specification

end-of-line noise test and intelligent identification system for industrial products

Product parameters

Product configuration

Application scenarios

The customer groups are mainly distributed in the fields of automobile manufacturing, home appliance manufacturing, medical manufacturing, and other industrial equipment manufacturing.