Pcb defects

Online PCB Defect Detector On a New PCB Defect Dataset

PCB from single layer to multilayer,flex,keep ourselves strong development. These years tend to high precision,high density,high reliably and small size to reduce cost and improve functions,PCB industry keep strong vitality in future electronic devices development. A nalysis of PCB board common defects.

Various defects happened in usage follow PCB circuit complicate and components integrated. We summarized four common defects:. The flow chart indicated common process,from graphic we know the first step is inspect PCB structure and appearance,then make test for the important discrete components and IC integrated circuit.

Repair or replace failure components after found out defect parts,use instrument to re-test PCB. From artificial observation to instrument measure.

pcb defects

All components connected by surface circuit in PCB, So the fist thing we can observe appearance by magnifier or microscope when it happened errors. Most damages can find through above initial observation and differentiate.

In general we touch the burning hot parts and find out damages when power cord works. If the parts works then we need check and debug each components compared input and output parameter. From outside to inside. The ratio failure components lead to PCB defects is large from above analysis,so how to find out the failure components is very important.

Components at outside major used in driver,inverter,isolation,protecting and communication for easy connection with inner circuit. They always be impacted from current surging,vibrating and external power lead to noise and dust,thus failure happened to this outside components. Components placed inside are major used in generate,amplify,transmit signal. Check the inside components after eliminated components at outside. There related some test technology in PCB inspection,we follow rules:from easy to complicated in checking process.

Circuit Simulation is an effective way to reduce design period and cost. But simulation is in perfection condition ,it ignored all interferences at actually works,so shield all interferences before test is necessary. In general way shielding interferences is short of crystal oscillator and dismantle CUP avoid testing hamper. From easy to complicated in special test way.

We use exclusive method to check it one by one and record it. Retest that error caution PCBs to guarantee accuracy. We consider it important suspect for the PCBs failed test. Complementary test method between different method. From static to dynamic. All the methods above mentioned multimeter and other methods are static inspection.

Integrated IC always use this method to check. If you want know about PCB technology, please visit www.Previous works for PCB defect detection based on image difference and image processing techniques have already achieved promising performance. However, they sometimes fall short because of the unaccounted defect patterns or over-sensitivity about some hyper-parameters. In this work, we design a deep model that accurately detects PCB defects from an input pair of a detect-free template and a defective tested image.

A novel group pyramid pooling module is proposed to efficiently extract features of a large range of resolutions, which are merged by group to predict PCB defect of corresponding scales. To train the deep model, a dataset is established, namely DeepPCB, which contains 1, image pairs with annotations including positions of 6 common types of PCB defects.

Experiment results validate the effectiveness and efficiency of the proposed model by achieving PCB manufacturing has drawn more and more attention as the rapid development of the consumer electronic products.

Generally, manual visual inspection is one of the biggest expense in PCB manufacturing. As popular and non-contact methods, recent researches [ 123 ] propose to process both a defect-free template and a defective tested image to localise and classify defects on the tested image.

However, those image-based PCB defect detecting algorithms are often challenged by lacking of sufficient data with elaborated annotations to validate their effectiveness, which also prevents the researches from training an advanced detector, e. Earlier works on PCB defect detection focus on wavelet-based algorithms [ 45678 ]which decreases the computation time compared to those based on image difference operation. Recently, [ 2 ] develops a hybrid algorithm to detect PCB defects by using morphological segmentation and simple image processing technique.

However, those algorithms relying on image difference and logic inference sometimes fail due to: a the complicated or unaccounted defect patterns; b irregular image distortion and offset between the template and tested image pair; c over-sensitivity of hyper-parameters, e. Recently, deep neural network has shown its strong generalization aiblity on object detection task [ 13141516 ]. PCB defect detection is essentially a kind of object detection task with two slight differences: 1 object as the PCB defect and 2 the pair-wise input including a defect-free template image and a defective tested image.

As for object detection models based on convolutional networks, [ 14 ] proposes a two stage object detection framework, in which a Region Proposal Network RPN is first deployed to generate high-quality region proposals that are used by Fast R-CNN for detection. Besides, [ 18 ] provides a feature pyramid network to merge features from different resolutions in a bottom-up manner, which is also a promising structure to detect objects in various scale.

To train an advanced deep model for PCB defect detection, in this work, we first set up a dataset, namely DeepPCB, which includes 1, pairs of template and tested images with annotations of position and class of 6 types of PCB defects. To the best of our knowledge, this is the first public dataset for PCB defect detection. As illustrated in Fig 1this dataset enjoys several advantages. We believe that this dataset will be greatly beneficial to the research in PCB defect detection.

PCB defect detectors based on the advanced deep models usually are faced with the dilemma of the accuracy and the efficiency. High accuracy requires much deeper models with tens and hundreds of layers to obtain higher level features in larger respective field, while high efficiency needs much fewer parameters as well as the less depth structure. To reduce the contradiction, we propose a novel module, namely group pyramid pooling GPPwhich merges features in various resolutions from grouped pooling and up sampling.

Each group in GPP carries both local and much larger range of context information and takes responsibility for predicting PCB defects in corresponding scales.

This paper makes three contributions. Each pair consists a x defect-free template image and a defective tested image. We separate 1, image pairs as training set and the remaining image pairs as test set. Following the common industrial settings, all the images in this dataset is obtained from a linear scan CCD in resolution around 48 pixels per 1 millimetre. The defect-free template image is manually checked and cleaned from a sampled image in the above manner. The original size of the template and tested image is around 16k x 16k pixels.

Then they are clipped into sub-images with size of x and aligned through template matching techniques by reducing the translation and rotation offset between the image pairs. Next, a threshold is carefully selected to employ binarization to avoid illumination disturbance. Although there are different prepocessing methods according to the specific PCB defect detecting algorithm, the image registration and thresholding are common techniques for high-accuracy PCB defect localization and classification [ 19 ].

We use the axis-aligned bounding box with a class ID for each defect in the tested images. As illustrated in Fig. Since there are only a few defects in the real tested image, we manually argument some artificial defects on each tested image according to the PCB defect patterns [ 20 ]which leads to around 3 to 12 defects in each x image. The number of PCB defects is shown in Fig.I read a lot of science blogs, if warp drives existed and were that tiny, I would most certainly know.

Component warping can results from a variety of causes. Mechanical mishandling occasionally causes bending. This can create a bubble inside packaging or force a casing askew. However, the most common cause is thermal issues.

Rework may cause warping in your components during reflow processing, or a thermal mismatch between the packaging and solder can cause warping when materials experience thermal expansion at different rates.

Heating during reflow is one of the most causes of component warping.

Zoom Into a Microchip

Ideally, your PCB will be produced with uniform laminates and good pressing procedures. That should give you a very planar surface, and a consistent surface to apply solder paste for component soldering during reflow. In my opinion, the worst case is when it weakens a solder joint enough to cause a premature, but impossible to detect, failure.

pcb defects

Most often, these electrical issues will show up in ball grid arrays, where components have a large surface area to be affected by warping. When the warpage increases distance between the PCB and casing, there are a couple possible outcomes. That results in an open circuit. Otherwise, the solder ball will stretch to make the connection. You see a circuit, but the solder in the join is thinned, and sometimes weirdly shaped, making the joint will be less reliable over time.

The Surface Mount Technology Association has a great presentation about warpageand if you check the images on page 6, you can see these issues in ball joints. It will often squish off of the pad, bridging to other solder pads and shorting them together, like you see in the image below. The impacts of warping are much worse as you decrease the pitch of the pads. With a warped component, solder can stretch, breaking a connection, or spill over onto other pads in ball grid arrays, shorting connections together.

Fortunately, there are a few options to mitigate warping. First, use solder mask defined pads because non-solder mask defined pads will have much lower molten solder height. You can also adjust the process materials and temperatures, often bringing temperatures down, or reducing the thermal mismatch between a leadless solder and components can dramatically improve your outcomes.GitHub is home to over 40 million developers working together to host and review code, manage projects, and build software together.

If nothing happens, download GitHub Desktop and try again. If nothing happens, download Xcode and try again. If nothing happens, download the GitHub extension for Visual Studio and try again. DeepPCB: a dataset contains 1, image pairs, each of which consists of a defect-free template image and an aligned tested image with annotations including positions of 6 most common types of PCB defects: open, short, mousebite, spur, pin hole and spurious copper.

All the images in this dataset are obtained from a linear scan CCD in resolution around 48 pixels per 1 millimetre. The defect-free template images are manually checked and cleaned from sampled images in the above manner.

The original size of the template and tested image is around 16k x 16k pixels. Then they are cropped into many sub-images with size of x and aligned through template matching techniques. Next, a threshold is carefully selected to employ binarization to avoid illumination disturbance. Notice that pre-processing algorithms can be various according to the specific PCB defect detection algorithms, however, the image registration and thresholding techniques are common process for high-accuracy PCB defect localization and classification.

An example pair in DeepPCB dataset is illustrated in the following figure, where the right one is the defect-free template image and the left one is the defective tested image with the ground truth annotations.

We use the axis-aligned bounding box with a class ID for each defect in the tested images. As illustrated in the above, we annotate six common types of PCB defects: open, short, mousebite, spur, pin hole and spurious copper. Since there is only a few defects in the real tested image, we manually argument some artificial defects on each tested image according to the PCB defect patterns, which leads to around 3 to 12 defects in each x image.

The number of PCB defects is shown in the following figure. We separate 1, images as training set and the remains as test set.

Each annotated image owns an annotation file with the same filename, e. Each defect on the tested image are annotated as the format: x1,y1,x2,y2,typewhere x1,y1 and x2,y2 is the top left and the bottom right corner of the bounding box of the defect. The annotation tool is now available with the source code in the. The average precision rate and F-score are used for evaluation.

A detection is correct only if the intersection of unit IoU between the detected bounding box and any of the ground truth box with the same class is larger than 0. Notice that F-score is threshold-sensitive, which means you could adjust your score threshold to obtain a better result. Although F-score is not as fair as the mAP criteria but more practical since a threshold should always be given when deploying the model and not all of the algorithms have a score evaluation for the target.

Thus, F-score and mAP are both under consideration in the benchmarks. The evaluation script for mAP and F-score are borrowed from Icdar evaluation scripts with small modification You may first register an account.Printed circuit boards PCB are essential components of many electrical devices today, connecting different components to one another through a complex array of circuits.

The complexity of the PCB designing and manufacturing processes means there are numerous opportunities for PCB failure issues to arise. Some of these failures are a result of design oversights, such as insufficient clearances or incorrect measurements, which can negatively affect the functionality of the finished product.

Others may result from problems in the manufacturing process, such as drilling errors or over-etching, which can be equally catastrophic.

Fortunately, most of these errors can be avoided with knowledge and consideration for the manufacturing process, as well as awareness of the more common PCB manufacturing issues. Plated thru-holes are copper-coated holes in a printed circuit board. These holes allow electricity to be carried from one side of the circuit board to the other. To create these holes, the PCB fabricator drills holes through the circuit board, puncturing the material all the way through.

A layer of copper is then added to the surface of the material and along the walls of these holes through an electroplating process. This process deposits a thin layer of electroless copper onto the circuit board in a process called deposition.

After this step, extra layers of copper are added and etched to create the circuit image. While effective, the deposition process is not perfect, and under certain circumstances can result in voids in the plating. Plating voids are effectively gaps or holes in the plating of the circuit board and are usually the result of problems during the deposition process.

These plating voids are particularly problematic because imperfections in the plating of a thru-hole prevent an electrical current from passing through the hole, resulting in a defective product. These plating voids happen because, for one reason or another, the material does not coat evenly during the deposition process.

The reasons for this include contamination of the material, air bubbles caught in the material, insufficient cleaning of the holes, insufficient catalyzation of the copper in the deposition process or rough hole drilling. Any of these problems can result in plating voids along the walls of the circuit holes. Defects as a result of contamination, air bubbles or insufficient cleaning can be avoided by cleaning the material properly after drilling.

Both problems can be avoided by hiring a well-qualified and experienced PCB manufacturing company. Copper is an incredibly conductive metal, which is used as an active component of PCBs. However, copper is also relatively soft and vulnerable to corrosion.

pcb defects

To prevent corrosion and protect the copper from interacting with its environment, this copper is covered with other materials. However, when a PCB is trimmed, if the copper is too close to the edge, part of this coating can be trimmed as well, exposing the copper layer underneath.

This can cause numerous problems in the functionality of the board.Before getting into details of printed circuit board PCBthere are some basics you need to know about circuits. Electricity: It is the power provided to every instrument ranging from small lights to heavy machinery.

Electricity is just a flow of electron from one level to other upper level to lower mostly. So in an electrical circuit, there is always a voltage or current source, components of circuit and electricity always go from a positive voltage level to negative voltage level.

Voltage, current, resistorscapacitors and inductors are considered as primary elements of any electrical scenario called circuit. Electrical current can be in two forms either a sinusoid AC alternating current or simply a straight line called direct or DC current. In hardware development of electrical circuit, to get all the components of circuit on one single place or board is called PCB designing.

pcb defects

In history, PCBs were been developed by going through a complicated procedure of point-to-point wiring and these circuits were highly exposed to get failure or damage.

After those more accurate design techniques were developed which were more secure. These days composition of printed circuit board consists of four major components.

PCBs are multi layered because these days complexity of electrical circuit is also increased. Newly developed PCBs have high pitch parts in which most of the parts are unidentified, on testable and more they involve complex troubleshooting and repairing techniques. Older circuit boards were able to be repaired by using automatic test equipment but these days it is not possible. Techniques used for troubleshooting were.

Most of these techniques become non functional when they need to cope with modern circuit boards. A newly developed VI signature analysis technique which is best for troubleshooting of completed circuit elements.

How to Test & Fix the Printed Circuit Board (PCB) Defects?

One of the best essential device that is used for detailed analysis of faulty components in a circuit. It is one of the best choices to test PCB when component signatures or documentation has been lost. This test require no power supply so it is best when we want to check faulty or dead boards as it is not safe to power them up.

A sine wave is provided to particular component under test using two probes. Resulting currents, voltages and shifts in phase are displayed on LCD.Almost every electronic device has one of these self-contained modules of complex interconnected electronic components, which include resistors, capacitors, transistors, diodes and fuses.

Printed circuit boards can cover a single task or multiple functions. PCBs come in three major types:. The electronics industry drives toward more miniaturization, requiring design engineers to produce faster, smaller — and more complex — circuit board technology, which has a higher quality and costs less.

It is important for a printed circuit board to perform its function and support the larger electronic device. Consequently, PCB manufacturers must have a system in place that monitors and tests each component to ensure that it meets various standards and delivers maximum performance.

When a component fails, analysts must utilize various processes, tools and techniques. With accuracy, they must determine why the device failed and how to prevent future failures. The following processes present unique challenges for electronics failure analysis:. The fabrication of a complete PCB assembly requires an array of machines and materials, which include:. Some machines have automated features that perform checks at various points, and operators perform visual inspections before, during or immediately after the completion of a task.

PCB Failure Analysis

Nonetheless, many PCBs will fail the final test. When a problem does occur, it is important to perform an effective electronics failure analysis in order to obtain clear and precise details about the source of the problem — and to ensure that it does not happen again.

The technician must conduct a root cause analysis to identify the cause of the failure — not the symptoms — and take corrective action to fix the issue. Failure analysis also provides invaluable feedback to design engineers on how to:. Any company that produces electronic hardware strives to achieve zero-defect production.

To realize this objective, manufacturers must have the capability to perform some level of printed circuit board failure analysis.

Some companies rely on outside expertise for more complex problems. For many high reliability systems — such as oil rigs, space satellites, implantable medical devices and other systems — failures can be devastating. In the case of consumer products, a single failure mode, which can replicate thousands or millions of times, can have a huge impact on the bottom line. Electronic device failure analysis provides a systematic process to help organizations investigate and understand why an electronic part failed.

Depending on the nature of the failure, an effective investigation can identify the failure mode, mechanism and elements, such as stresses inducing the failure and other issues.

For example, solder joint defects make up a large percentage of PCB failures. Manufacturers can discover the root cause of the defective joints — such as a lack of solder paste, a gap between the PCB pad and component lead, or poor reflow profile — and then implement preventative measures. To eliminate future failures, possible solutions may be to avoid solder paste contamination or ensure the correct aspect ratio.

The methods used in the analysis depend on the severity of the failure and the type of issue. They can range from simple electrical measurements to the evaluation of sample cross-sections under a microscope. An effective and efficient root cause analysis ensures that manufacturers can initiate the necessary corrective action to prevent reoccurrence of the problem. Failure analysis processes evaluate the reliability of a component product under operation and determine how to improve the product.

There are a number of tests suitable for identifying defects. When the failure analyst understands the faults and how to prevent them, the company can improve the production process as well as the assemblies it manufactures. This technique employs a combination of external techniques, such as electrical testing, visual inspection, X-ray and cross-sectioning to the relevant area. Micro-sectioning Analysis Micro-sectioning, sometimes called Cross-sectioning or Metallographic Preparation, refers to a PCB testing method used to investigate:.

The failure analyst removes a two-dimensional slice out of a sample, which uncovers features within the board. Considered a destructive testing method, micro-sectioning analysis provides the technician with a precise technique that isolates the relevant electronic component and removes the part from the PCB sample.

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