Production Line Good-Product Inspection Analysis Solution

An Intelligent Upgrade Solution Based on the Holographic Sound Field Inspection Instrument

I. Core Limitations of Conventional Solutions

In conventional production line acoustic inspection, microphone arrays or single-point sensors are typically used for fixed-point measurement. This approach suffers from several insurmountable bottlenecks:

First, a limited field of view. The viewing angle of a conventional microphone array is typically less than 90°, giving extremely limited coverage within the confined space of a production line and leaving numerous “viewing blind zones.” To cover the complete inspection area, multiple sensors must often be deployed or the equipment position repeatedly adjusted, with low efficiency.

Second, severe background noise interference. A production line environment typically contains multiple noise sources such as equipment operation, airflow, and conveyor belts, making the signal-to-noise ratio extremely poor. Weak product abnormal-noise signals (such as impeller friction or foreign-object intrusion) are very easily submerged by background noise, resulting in a failure to “catch” critical anomalies.

Third, transient signals are hard to capture. The abnormal noise produced by many product defects is random and transient in nature (such as BSR noise—Buzz, Squeak, Rattle), and conventional time-domain analysis methods struggle to effectively lock onto such signals.

Fourth, a single judgment dimension. Conventional solutions rely on spectral analysis or gross-value judgment at a limited number of measurement points, making it difficult to obtain the product’s acoustic characteristics in all respects and offering insufficient capability to recognize complex fault patterns.

It is precisely in response to these limitations that the team has introduced a next-generation production line inspection solution centered on the holographic sound field inspection instrument, achieving a leapfrog upgrade from “single-point scanning” to “holographic intelligent perception.”

II. Holographic Sound Field Inspection Instrument: Core Technical Breakthroughs

2.1 Hardware Architecture: Native 360° Blind-Zone-Free Coverage

The holographic sound field inspection instrument employs a 64-element spherical high-signal-to-noise-ratio microphone array, based on a design in which microphones are uniformly distributed over the surface of a rigid sphere. A single unit, with no need for pan-tilt coordination, achieves blind-zone-free holographic sound field coverage of 360° horizontal × 180° vertical. Its core parameters are as follows:

Notes: (1) The sensitivity figure is quoted as −24 dB; its reference basis (e.g., re 1 V/Pa or dBFS) is to be specified. (2) The 80 dB SNR figure describes the microphone array; whether it is a per-channel, array-level, or system-level value is to be specified. (3) The 25 Hz figure is the sound field imaging refresh rate; it is not the acquisition sample rate relevant to transient capture (see the appendix, Section 3, item 3).

This hardware design fundamentally resolves the problem of a “limited field of view” in conventional solutions—a single deployment enables synchronous capture of acoustic signals across the entire space of the production line inspection area.

2.2 AI Algorithm Engine: Breaking Through Complex-Environment Bottlenecks

Based on a multi-task deep learning model and a convolutional neural network architecture, the holographic sound field inspection instrument has built full-chain AI acoustic processing capability:

AI panoramic sound field reconstruction: through an AI model, it completes intelligent computation of holographic sound images across different frequencies and spatial grids, deeply mining spatial–frequency–temporal acoustic features across all dimensions to achieve 4° ultra-high-resolution visualized sound field restoration.

AI multi-source Blind Source Separation (BSS): based on a deep neural network source separation algorithm, it achieves precise separation of multiple sources at a 12 dB signal-to-interference ratio. This means that even amid the strong background noise of a production line, the system can precisely extract the product’s own weak abnormal-noise signal from the mixed acoustic signals—equivalent to achieving 12 dB of equivalent noise reduction, bringing signals that were originally submerged “to the surface.”

AI intelligent abnormal-sound recognition: a built-in anomaly classification model trained on massive industrial acoustic data automatically performs recognition, classification, and risk-level determination of abnormal sound signals, achieving an upgrade from “seeing sound” to “reading sound.”

2.3 Multimodal Fusion: What You See Is What You Get

The device carries a synchronized panoramic camera. Through an AI image stitching algorithm it completes real-time synthesis of a panoramic optical image, and achieves pixel-level precise fusion of the panoramic acoustic image with the visible-light image, transforming the intangible sound field into an intuitive colored sound field contour map. Inspection personnel can see at a glance where the sound comes from, what type of sound it is, and whether it is acceptable.

III. Production Line Inspection Application Scheme

3.1 System Architecture

With the holographic sound field inspection instrument as the core, a production line inspection system is built as follows:

3.2 Inspection Workflow

1. Panoramic sound field acquisition: after the product enters the inspection station, the holographic sound field inspection instrument completes full-space acoustic signal acquisition in a single pass, with no scanning or rotation required.

2. AI source separation: the AI algorithm precisely separates the acoustic signal radiated by the product itself from the production line background noise.

3. Sound field reconstruction and visualization: the AI model computes and outputs a 4°-resolution panoramic sound field contour map in real time.

4. Anomaly recognition and judgment: the AI anomaly classification model automatically identifies the type of abnormal noise (friction, knocking, looseness, etc.) and determines whether the product is OK or NG.

5. Result output and traceability: the judgment result is output to the production line control system through the communication interface and simultaneously stored in a database for subsequent traceability analysis.

3.3 Comparison with Conventional Solutions

Note: In the “transient signal capture” row, the 25 Hz figure denotes the sound field imaging refresh rate; transient capture capability is governed by the continuous acquisition sample rate, which is a separate specification (see the appendix, Section 3, item 3).

IV. Typical Application Scenarios

4.1 Home Appliance Production Line Abnormal-Noise Inspection (Refrigerators, Air Conditioners, etc.)

On home appliance production lines such as those for refrigerators and air conditioners, products often produce abnormal noise due to accessory or assembly problems. Conventional solutions place microphones inside a soundproof enclosure for fixed-point measurement. With the holographic sound field inspection instrument, a single unit completes full-space sound field acquisition, and the AI algorithm precisely separates the product’s abnormal-noise signal from the production line background noise, automatically identifying fault types such as fan foreign-object intrusion and impeller abnormality, at a high level of accuracy.

Note: The source document states “high level of accuracy” without providing a figure. In this document series, a detection accuracy of 99.99% is cited for air conditioner production line abnormal-noise inspection (see the companion document on near-field acoustic holography). The figure is to be confirmed before insertion; the translation does not supply it.

4.2 Automotive Component NVH Inspection

The holographic sound field inspection instrument has been widely applied in NVH testing of complete vehicles and components. At the production line end, it can be used for noise inspection of core components such as engines, transmissions, motors, and battery packs, precisely locating the noise source position through a high-resolution sound field contour map and determining whether the product is acceptable.

4.3 General Manufacturing Acoustic Quality Control

By virtue of its AI-empowered performance and strong environmental adaptability, the holographic sound field inspection instrument can broadly cover core acoustic monitoring scenarios across multiple industries, including NVH testing and intelligent O&M of industrial equipment, acoustic performance testing of rail transit vehicles, and abnormal-noise quality control on smart home appliance manufacturing lines.

Note: The source sentence ends with a stray punctuation mark (rendered in the source as “等-。”), which appears to be a typing error; the translation renders the list cleanly without it.

V. Summary of Solution Advantages

• Panoramic coverage, no blind zones or dead angles. A single unit achieves 360°×180° full-space sound field coverage, and a single deployment completes panoramic monitoring of the production line inspection area, improving work efficiency dramatically.

• AI empowerment, precise inspection in complex environments. A deep neural network-based source separation algorithm achieves precise multi-source separation at a 12 dB signal-to-interference ratio; even in a production line environment with strong background noise, it precisely extracts the product’s weak abnormal-noise signal.

• Intelligent recognition, from “hearing” to “reading.” A built-in anomaly classification model trained on massive industrial acoustic data automatically completes abnormal-noise recognition, classification, and judgment, with no need for manual configuration of complex limit curves or thresholds.

• Intuitive visualization, what you see is what you get. Acoustic–optical image fusion technology transforms intangible sound into a colored sound field contour map; inspection personnel can directly see the source position and type, reducing dependence on specialized acoustic expertise.

• Efficient deployment, flexible expansion. A single unit replaces a multi-sensor array for simple deployment; standard communication interfaces support seamless integration into existing automated production lines.

• Traceable data, continuous optimization. All inspection data can be stored in a database and retrieved and analyzed by dimensions such as time and batch, providing data support for product performance improvement and quality traceability.

With its entirely new technical system of “spherical hardware array + full-chain AI algorithm engine + acoustic–optical multimodal fusion,” the holographic sound field inspection instrument fundamentally resolves the four core pain points of conventional production line acoustic inspection—“limited field of view, noise interference, hard-to-capture transients, and coarse judgment”—achieving a leapfrog upgrade from “single-point scanning” to “holographic intelligent perception” and providing a more efficient, precise, and intelligent solution for production line good-product inspection.