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Fault prediction system for headphone based on big data

A fault prediction, headphone technology, applied in the direction of earpiece/headphone accessories, electrical components, etc., can solve the problem of not having the adaptability of headphone

Pending Publication Date: 2022-04-29
深圳市烽火宏声科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to solve the problem that the existing headphone detection system does not have the function of detecting and analyzing the adaptability of the headphone in different application environments and predicting the faults that are likely to occur, and proposes a large-scale Data based failure prediction system for headphones

Method used

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  • Fault prediction system for headphone based on big data
  • Fault prediction system for headphone based on big data

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0034] First, analyze the tensile performance of the headphones through the hardware analysis module, and judge the mechanical properties of the headphones through the results of the tensile performance analysis. Headphones with unqualified tensile performance need to be returned to the factory for processing, while For headphones with qualified stretch performance, it is necessary to judge its applicability for different types of users. The analysis process of stretch performance includes: randomly selecting n headphones from the same batch of headphones As the detection object i, i, i=1, 2,..., n, n is a positive integer, select n human head models and mark them as auxiliary objects, arrange the auxiliary objects according to the head circumference value from small to large, and adjacent The difference between the head circumference value of the auxiliary object is 0.5cm, select the human head model with the same number as the detection object, and the equivalent value of the...

Embodiment 2

[0039] The overall performance detection of the headset is also particularly important. In this embodiment, the overall performance of the headset is detected and analyzed in combination with the hardware level in Embodiment 1 as a weight influencing factor. The process of performance detection and analysis is as follows: randomly select several headphones as the objects to be inspected, and obtain the impedance data ZK, sensitive data LM and power data GL of the objects to be inspected; the acquisition process of the impedance data ZK of the objects to be inspected includes: Under the test frequency of , use a multimeter to obtain the inductance DG of the object to be inspected, mark the resistance of the object to be inspected as DZ, and use the formula Obtain the impedance data ZK of the object to be inspected; the acquisition process of the sensitive data LM of the object to be inspected includes: obtaining the maximum and minimum values ​​of the sensitive range through th...

Embodiment 3

[0041] see figure 2 As shown, a fault prediction method for headphones based on big data includes the following steps:

[0042] Step 1: Detect and analyze the stretch performance of the headphones through the hardware analysis module, select several human head models with different head circumferences to match with the headphones to be tested, and obtain the stretching times of the headphones through the wearing test. Obtain the average number of times by obtaining the number of stretches, and judge whether the stretching performance of the headset is qualified according to the comparison result of the average number of times and the number of times threshold;

[0043] Step 2: Analyze the applicable performance of the headphones with qualified tensile performance, and obtain the applicable coefficient of the headphones through variance calculation. The applicable coefficient is used to reflect the tensile performance of the headphones when they are used on human head models w...

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Abstract

The invention relates to the technical field of headphone fault prediction, is used for solving the problem that an existing headphone detection system does not detect and analyze the adaptive capacity of a headphone in different application environments, and particularly relates to a big data-based headphone fault prediction system, which comprises a fault prediction platform, the fault prediction platform is in communication connection with a hardware analysis module, a hardware rating module, a performance detection module and a database, and the hardware analysis module is used for analyzing and predicting the tensile performance of a detection object i and obtaining the number of times of stretching; according to the invention, applicable performance detection is carried out on the headset which is qualified in stretching, so that the adaptive performance of the headset in different application environments can be simulated and analyzed, and the application scene of the headset can be matched through the applicable performance detection result; and the probability that headphones with different applicability have mechanical faults in different environments can be predicted and analyzed.

Description

technical field [0001] The invention relates to the technical field of headphone fault prediction, in particular to a big data-based fault prediction system for headphones. Background technique [0002] Headphones are worn on the head and not inserted into the ear canal. They are different from in-ear earplugs. They are composed of two parts, a signal transmitter and an earphone with a signal receiving and amplifying device (usually a moving coil type), the transmitter is connected to the signal source, and it can also be connected to a preamp or headphone amplifier in front of the transmitter to improve the sound quality and adjust the timbre. [0003] The existing headphones can only detect the parameters of the headphones when they leave the factory. However, the probability of mechanical failure of the headphones during use is also related to the application scenario and the user's usage. The test results of the headphone parameters cannot reflect the adaptability of th...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04R1/10H04R29/00
CPCH04R1/1008H04R29/001
Inventor 郭志平张帅郭星王国良
Owner 深圳市烽火宏声科技有限公司
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