Circuit board fault diagnosis system based on infrared imaging

Abstract

The invention discloses a circuit board fault diagnosis system based on infrared imaging, which comprises an acquisition layer, a control layer and a data processing layer which are connected in sequence, and is characterized in that the acquisition layer comprises an infrared thermal imager, a visible light camera and a multi-degree-of-freedom mechanical arm, and the infrared thermal imager and the visible light camera are assembled on the multi-degree-of-freedom mechanical arm; the control layer comprises a measurement and control instrument unit, a power supply and distribution unit and a self-inspection adapter unit, the measurement and control instrument unit receives data of the acquisition layer, the power supply and distribution unit provides a power supply for the acquisition layer, and the self-inspection adapter unit performs fault injection and signal conditioning on the acquisition layer; the data processing layer comprises a GPU server and a data storage unit. According to the invention, a layered distributed architecture is adopted, and an infrared thermal imager and a visible light camera are adopted to carry out effective fault diagnosis on the circuit board.

Description

Technical Field

[0001] This invention belongs to the field of infrared detection and relates to a circuit board fault diagnosis system based on infrared imaging. Background Technology

[0002] With the continuous development and maturation of infrared imaging technology, infrared thermal imagers are becoming increasingly cheaper, more efficient, and more widely used. Based on infrared radiation theory and the temperature measurement principle of infrared thermal imagers, an infrared thermal imager is a device that uses an infrared detector and an optical imaging lens to receive the infrared radiation emitted by the target object. It reflects the infrared radiation energy distribution pattern of targets at different temperatures onto the photosensitive element of the infrared detector, thus obtaining an infrared thermal image. This thermal image corresponds to the heat distribution field of the object's surface. Simply put, an infrared thermal imager is a camera that receives infrared light, converting the invisible infrared energy emitted by an object into a visible thermal image. Different colors on the thermal image represent different temperatures of the measured object. Infrared thermal imagers are entirely passive receiving instruments, causing no interference to other precision electronic instruments and equipment. They can perform non-contact, high-resolution temperature measurements, generating high-quality heat distribution field images, providing a wealth of information about the measured target, compensating for the limitations of the human eye. They are widely used in military fields, as well as in the power, petrochemical, transportation, and disaster relief industries, and their future development prospects are limitless.

[0003] Infrared thermal imagers capture infrared thermal images that are invisible to the human eye. These images are completely different from the visible light images we usually see. Visible light images are images of the surface features of objects that are familiar to people, almost identical to what the human eye sees. The images are clear and can intuitively represent the characteristics of objects, such as photographs taken by cameras. Infrared thermal images, on the other hand, are images of the temperature distribution on the surface of an object. It is important to emphasize that this is an image of the temperature distribution on the surface of the object, not inside the object. Its amazing feature is that the surface temperature of an object can be "seen," and can be displayed in grayscale or pseudo-color as an image that the human eye can recognize.

[0004] Infrared image diagnosis of circuit board faults utilizes an infrared thermal imager to measure the infrared radiation temperature of each electronic component on the circuit board during operation. This temperature information is then used to determine whether a fault has occurred and its location. Since many electronic components on a circuit board generate heat to varying degrees during operation, circuit board faults are often accompanied by changes in the heating state of these components. By measuring these changes in heating state, the operating status of each electronic component can be preliminarily determined, and the possible location of the fault can be identified.

[0005] Infrared image diagnostics of circuit board faults has been applied in some fields. However, compared with visible light images, infrared thermal images lack depth and three-dimensionality, and their clarity is far inferior to that of visible light images. Therefore, when using infrared thermal images to analyze problems, manual judgment and location of temperature anomalies are often required. Furthermore, since infrared thermal images do not conform to people's daily visual habits, it is difficult to accurately locate the corresponding positions of temperature anomalies identified on the actual circuit board. Summary of the Invention

[0006] Based on the above problems, the technical solution of the present invention is: a circuit board fault diagnosis system based on infrared imaging, comprising a data acquisition layer, a control layer, and a data processing layer connected in sequence, wherein, The acquisition layer includes an infrared thermal imager, a visible light camera, and a multi-degree-of-freedom robotic arm, with the infrared thermal imager and the visible light camera mounted on the multi-degree-of-freedom robotic arm. The control layer includes a measurement and control instrument unit, a power supply and distribution unit, and a self-test adapter unit. The measurement and control instrument unit receives data from the acquisition layer, the power supply and distribution unit provides power to the acquisition layer, and the self-test adapter unit performs fault injection and signal conditioning on the acquisition layer. The data processing layer includes a GPU server and a data storage unit.

[0007] Preferably, the visible light camera includes an AI camera and an AOI camera.

[0008] Preferably, the AI ​​camera uses a deep learning algorithm to detect soldering defects and missing components on the circuit board in real time.

[0009] Preferably, the AOI camera detects the shape of the solder joints and the amount of solder paste based on a rule-based algorithm.

[0010] Preferably, the measurement and control instrument unit includes a signal generator, a data acquisition card, a programmable power supply, and a digital I / O controller connected in sequence.

[0011] Preferably, the signal generator includes an AD9833 chip and an OP27 operational amplifier.

[0012] Preferably, the data acquisition card includes an AD7606 chip and an STM32 MCU.

[0013] Preferably, the digital I / O controller includes a complex programmable logic device (EPM570) chip and an optocoupler-isolated TLP521 chip.

[0014] Preferably, the power supply and distribution unit includes a main power supply, a backup battery, a power distribution board, and a DC-DC converter board. The main power supply is connected to the backup battery and the power distribution board respectively, and the power distribution board is also connected to the DC-DC converter board.

[0015] Preferably, the self-test adapter unit includes a standard load board, a fault injection module, a signal conditioning circuit, and an MCU controller connected in sequence.

[0016] Compared with the prior art, the beneficial effects of the present invention include at least the following: overcoming the technical bias of the prior art that mainly applies external thermal imaging technology to fields such as medicine and alarms, and cleverly applying infrared thermal imaging technology to circuit board fault detection, thereby realizing effective detection of circuit board faults, which is convenient to operate, highly accurate, time-saving and labor-saving, meets actual needs, has outstanding substantive features and significant progress, and is suitable for large-scale promotion and application. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the structure of a circuit board fault diagnosis system based on infrared imaging according to an embodiment of the present invention; Figure 2 This is a block diagram of the measurement and control instrument unit structure of the circuit board fault diagnosis system based on infrared imaging, according to a specific embodiment of the present invention. Figure 3 This is a structural block diagram of the self-test adapter unit of the circuit board fault diagnosis system based on infrared imaging, according to a specific embodiment of the present invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0019] Conversely, this invention encompasses any substitutions, modifications, equivalent methods, and solutions made within the spirit and scope of the invention as defined in the claims. Furthermore, to provide a better understanding of the invention, certain specific details are described in detail below. However, those skilled in the art will fully understand the invention even without these detailed descriptions.

[0020] See Figure 1 It includes a data acquisition layer 10, a control layer, and a data processing layer connected in sequence, wherein, The acquisition layer 10 includes an infrared thermal imager, a visible light camera, and a multi-degree-of-freedom robotic arm. The infrared thermal imager and the visible light camera are mounted on the multi-degree-of-freedom robotic arm. The control layer includes a measurement and control instrument unit 21, a power supply and distribution unit 22, and a self-test adapter unit 23. The measurement and control instrument unit 21 receives data from the acquisition layer 10, the power supply and distribution unit 22 provides power to the acquisition layer 10, and the self-test adapter unit 23 performs fault injection and signal conditioning on the acquisition layer 10. The data processing layer includes GPU servers and data storage units.

[0021] The laser barcode scanner 12 is used to scan the ID of the circuit board. The acquisition layer 10 is connected to the measurement and control instrument unit 21 and the power supply and distribution unit 22 of the control layer through the common test interface 11.

[0022] Visible light cameras include AI cameras and AOI cameras. AI cameras use deep learning algorithms to detect soldering defects and missing components on circuit boards in real time. They feature adaptive detection capabilities, dynamically adjusting exposure and focal length to adapt to the imaging needs of different materials (such as highly reflective BGA pads). They can achieve data closed-loop integration, enabling defect classification statistics and process optimization feedback. In specific selection, computing power requirements are: ≥4 TOPS computing power is needed to detect complex defects (such as QFN package soldering). Spectral compatibility: If infrared-assisted detection (such as thermal distribution analysis) is required, choose a model that supports multiple spectra. Interface protocols: Prioritize cameras that support GigE Vision or USB3 Vision to ensure compatibility with Halcon / OpenCV. AOI cameras use rule-based algorithms to detect solder joint shape and solder paste amount, achieving high-speed full-area scanning of the PCB board (typical speed 0.5m / s) using a line scan camera, providing SPC statistical reports to monitor soldering process fluctuations. In specific selection, resolution is: ≥5MP for 0402 packages and ≥12MP for 0201 packages. Light source configuration: Select a programmable multi-color light source (such as red, blue, and green IR) to enhance contrast. Optical distortion: Lens distortion must be <0.1% (requires a telecentric lens).

[0023] See Figure 2 The measurement and control instrument unit 21 includes a signal generator 211, a data acquisition card 212, a programmable power supply 213, and a digital I / O controller 214 connected in sequence. The signal generator 211 includes an AD9833 chip and an OP27 operational amplifier. The data acquisition card 212 includes an AD7606 chip and an STM32 MCU. The digital I / O controller 214 includes an EPM570 complex programmable logic device chip and a TLP521 optocoupler chip.

[0024] The power supply and distribution unit 22 includes a main power supply, a backup battery, a power distribution board, and a DC-DC converter board. The main power supply is connected to the backup battery and the power distribution board respectively, and the power distribution board is also connected to the DC-DC converter board. The main power supply is an HRP-600-24 power supply module, the backup battery includes a lithium iron phosphate battery and a battery manager, and the power distribution board includes an EMI filter and transient voltage suppression diodes.

[0025] See Figure 3The self-test adapter unit includes a standard load board 221, a fault injection module 222, a signal conditioning circuit 223, and an MCU controller 224 connected in sequence. The standard load board 221 includes a precision resistor network PTF56 series; the fault injection module 222 includes a relay matrix and programmable resistors, supporting open circuit, short circuit, and parameter offset simulation; the signal conditioning circuit 223 includes an instrumentation amplifier AD8221 and a multiplexer ADG1419; and the MCU controller 224 includes an STM32 series controller and a CAN bus isolation ADM3054.

[0026] In a specific embodiment, the mechanical structure of the system includes: a three-axis motion platform: X / Y axis travel: 600mm×400mm (covering standard circuit board size), Z axis lifting range: 200mm (adapting to circuit boards of different thicknesses), and repeatability: ±0.05mm.

[0027] Modular fixture: pneumatic grippers (compatible with through-hole and surface mount component fixing), insulating gasket (1kV withstand voltage to prevent short circuit).

[0028] Optical components: ring LED light source (color temperature 6500K, no thermal radiation interference), beam splitter (to achieve coaxiality of visible light and infrared light paths).

[0029] Human-Computer Interaction Design: Touch Control Screen: 10.1-inch industrial-grade touch screen, displaying real-time thermal images and fault markers. Emergency Brake Button: Dual-circuit safety design, cutting off all power within 0.1 seconds of triggering.

[0030] Expansion interfaces: RS-485 interface: supports access of third-party devices (such as PLCs); Gigabit Ethernet: used for high-speed data transmission and remote diagnostics.

[0031] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An infrared imaging-based circuit board failure diagnosis system, characterized by comprising: The system comprises a collection layer, a control layer and a data processing layer connected in sequence, wherein, The collection layer comprises an infrared thermal imager, a visible light camera and a multi-degree-of-freedom mechanical arm, the infrared thermal imager and the visible light camera are assembled on the multi-degree-of-freedom mechanical arm; The control layer comprises a measurement and control instrument unit, a power supply and distribution unit and a self-checking adapter unit, the measurement and control instrument unit receives data of the collection layer, the power supply and distribution unit provides power supply for the collection layer, and the self-checking adapter unit performs fault injection and signal conditioning on the collection layer; The data processing layer comprises a GPU server and a data storage unit.

2. The infrared imaging-based circuit board failure diagnosis system according to claim 1, characterized by, The visible light camera comprises an AI camera and an AOI camera.

3. The infrared imaging-based circuit board fault diagnosis system according to claim 2, characterized by, The AI camera detects welding defects and component missing of the circuit board in real time through a deep learning algorithm.

4. The infrared imaging-based circuit board failure diagnosis system according to claim 2, characterized by, The AOI camera detects solder joint shape and solder paste amount based on a rule algorithm.

5. The infrared imaging-based circuit board fault diagnosis system according to claim 1, characterized by, The measurement and control instrument unit comprises a signal generator, a data acquisition card, a program-controlled power supply and a digital IO controller connected in sequence.

6. The infrared imaging-based circuit board fault diagnosis system according to claim 5, wherein The signal generator comprises an AD9833 chip and an OP27 operational amplifier.

7. The infrared imaging-based circuit board fault diagnostic system of claim 5, wherein, The data acquisition card comprises an AD7606 chip and an MCU of STM32 type.

8. The infrared imaging-based circuit board fault diagnostic system of claim 5, wherein, The digital IO controller comprises a complex programmable logic device EPM570 chip and an optocoupler isolation TLP521 chip.

9. The infrared imaging-based circuit board fault diagnostic system of claim 1, wherein, The power supply and distribution unit comprises a main power supply, a backup battery, a power distribution board and a DCDC conversion board, the main power supply is connected with the backup battery and the power distribution board respectively, and the power distribution board is further connected with the DCDC conversion board.

10. The infrared imaging-based circuit board fault diagnostic system of claim 1, wherein, The self-checking adapter unit comprises a standard load board, a fault injection module, a signal conditioning circuit and an MCU controller connected in sequence.

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