Fault Repair Professional Secrets Book

 

📺 Top 10 Common LED TV Problems and How to Fix Them at Home

By Imran Ashraf – Electronics Repair Guide

LED TVs are an essential part of every home, but like all electronics, they can develop faults over time. If your LED TV is giving trouble, don’t worry — many problems can be fixed at home with some basic tools and knowledge. Here are the 10 most common LED TV problems, their causes, and easy fixes.

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1️⃣ TV Turns On but No Picture

Cause: Faulty backlight, damaged T-CON board, or loose LVDS cable.
Fix: Shine a flashlight on the screen — if you see a faint image, the backlight is faulty. Check LVDS cables. Replace LED strips or T-CON board if needed.

2️⃣ No Sound but Picture is OK

Cause: Audio IC failure, damaged speakers, or settings issue.
Fix: Check sound settings, test with headphones, replace speakers if necessary.

3️⃣ TV Stuck on Logo / Boot Loop

Cause: Corrupt firmware or faulty main board.
Fix: Update firmware via USB. If it fails, replace or repair the main board.

4️⃣ Remote Control Not Working

Cause: Dead batteries, dirty IR sensor, or faulty remote.
Fix: Replace batteries, clean IR sensor, test remote using mobile camera.

5️⃣ Vertical or Horizontal Lines on Screen

Cause: T-CON board failure or panel issue.
Fix: Reseat ribbon cables. Replace T-CON board if needed.

6️⃣ Colors Look Distorted

Cause: Faulty T-CON, gamma IC, or wrong picture settings.
Fix: Reset picture settings. Replace gamma IC if required.

7️⃣ TV Not Turning On (No Power)

Cause: Faulty power board or blown fuse.
Fix: Check fuses with a multimeter. Replace power board if needed.

8️⃣ Backlight Flickering

Cause: LED strips or power supply problem.
Fix: Replace LED strips. Check voltage output to backlight.

9️⃣ TV Turns Off by Itself

Cause: Overheating, faulty power supply, or software glitch.
Fix: Clean ventilation holes, update firmware, replace capacitors if needed.

🔟 HDMI Ports Not Working

Cause: HDMI IC failure or damaged port.
Fix: Try different HDMI cables. Replace HDMI IC if necessary.

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🛠 Tools Needed for Bas

IF you want a complete LCD/LED TV screen voltage diagnosis guide that explains:

• What each voltage is called

• What its normal range is

• Where to measure it

• How to know which one is missing

• How to fix it

Here’s the full technician-level explanation.

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📺 LCD/LED TV Screen Voltage Diagnosis & Repair Guide

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1️⃣ Understanding Screen Power System

The screen (panel) in an LCD/LED TV needs multiple voltages to operate, generated mostly on the T-CON board (or integrated into the main board in some TVs).

Typical main voltages:

Voltage Name	Symbol	Typical Range	Function
Panel VCC	VCC / VDD	3.3V – 12V (model-dependent)	Main power for logic circuits
VGH	Gate High	+22V – +32V	Turns ON TFT pixels (row selection)
VGL	Gate Low	–5V to –12V	Turns OFF TFT pixels
AVDD	Analog VDD	12V – 16V	Powers column drivers
VCOM	Common Voltage	~4V – 7V	Pixel reference voltage
Gamma Voltages	V1–V14	Stepped levels	Control grayscale accuracy
VREF	Reference Voltage	~1.2V – 3.3V	For ADC/DAC circuits in panel
LED Backlight Voltage	LED+ / LED–	20V – 200V (depends on strips)	Powers LED strips

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2️⃣ Where to Measure Voltages

• Main Panel Supply (VCC) → At T-CON input fuse (label F1/F100).

• VGH, VGL, AVDD, VCOM → Near T-CON power IC (often marked VGH, VGL, VCOM on PCB).

• Gamma Voltages → On Gamma IC pins (AS15, GM8284, etc.).

• LED Voltage → On LED driver output (often part of power board).

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3️⃣ Step-by-Step Voltage Testing

Step 1 — Check Panel VCC

• Location: T-CON fuse input.

• Normal: 3.3V / 5V / 12V depending on panel type.

• If missing:

  • Check main board MOSFET switch circuit.

  • Replace blown fuse.

  • Trace supply from main board regulator.

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Step 2 — Check AVDD

• Location: Output pin of T-CON DC-DC boost converter.

• Normal: 12–16V.

• If missing:

  • Check T-CON boost IC (MP2363, RT8293, etc.).

  • Test inductor & diode for shorts.

  • Replace faulty IC.

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Step 3 — Check VGH

• Location: Marked pad on T-CON, or on ribbon to panel.

• Normal: +22V – +32V.

• If missing:

  • DC-DC boost for VGH faulty.

  • Check for short on gate driver IC in panel.

  • Replace boost IC or repair short.

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Step 4 — Check VGL

• Location: Near same area as VGH.

• Normal: –5V to –12V.

• If missing:

  • Negative voltage generator faulty.

  • Check boost capacitor/diode.

  • If shorted to ground, gate driver IC inside panel is bad.

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Step 5 — Check VCOM

• Location: VCOM test point on T-CON or panel ribbon.

• Normal: Around ½ of AVDD (~5–7V).

• If unstable/missing:

  • Adjust in service menu or via T-CON potentiometer.

  • Bad op-amp in T-CON may cause lines/flicker.

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Step 6 — Check Gamma Voltages

• Location: Pins of Gamma IC (AS15, etc.).

• Normal: Gradual step-down voltages (V1 highest, V14 lowest).

• If one step jumps abnormally:

  • Gamma IC faulty → replace.

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Step 7 — Check LED Backlight Voltage

• Location: LED driver output on power board.

• Normal: Depends on number of LED strips (e.g., 80V for 4 strips, 180V for 10 strips).

• If missing:

  • Driver IC or MOSFET faulty.

  • Open LED strip → backlight won’t start.

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4️⃣ Common Fault Symptoms & Missing Voltage Clues

Symptom	Likely Missing Voltage
TV on, backlight works, but no display	AVDD / VGH / VGL
White screen	Missing VGL or VCOM
Faint picture, needs torch to see	LED backlight voltage
Colored vertical lines	One Gamma voltage abnormal
Logo freeze	Panel VCC drops during boot

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5️⃣ Quick Reference Voltage Table

Voltage	Range	If Missing → Check
VCC	3.3–12V	Fuse, MOSFET, regulator
AVDD	12–16V	Boost converter, diode, inductor
VGH	22–32V	Boost IC, gate driver short
VGL	–5 to –12V	Negative pump, short to GND
VCOM	~5–7V	Op-amp, adjustment
Gamma	Steps from AVDD to 0V	Gamma IC
LED+	20–200V	Driver IC, LED strips

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6️⃣ Repair Tips

• Always measure with TV powered ON and T-CON connected.

• Use digital multimeter in DC mode.

• If a voltage is present but drops after 1–2 seconds → load fault (short).

• Isolate panel by disconnecting one ribbon at a time to see if voltages stabilize (panel half short).

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If you want color-coded voltage diagram for LCD TV T-CON boards showing exactly where to put your probes and what voltages to expect — that makes real repairs much faster you need to buy my Printed Book Online it's a complete repairing course for your repair shop.

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How to Reset Your TV if your tv accidentally Switched into WEB OS

Your TV was switched into WebOS demo/store mode (or the software UI got stuck), and now you can’t get back to the normal TV functions.

The reset steps depend on the exact brand/model (LG and some other brands use WebOS), but here are the most common working methods:

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1️⃣ Soft Reset (No Data Loss)

1. Unplug the TV from the wall.

2. Press and hold the power button on the TV (not the remote) for 20–30 seconds.

3. Plug the TV back in and turn it on — sometimes this exits the stuck state.

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2️⃣ Factory Reset from Settings (If You Can Access Menu)

If the remote still works and you can open the settings:

1. Press the Settings or Gear button on the remote.

2. Go to:

   • All Settings → General → Reset to Initial Settings
     (On some models: Settings → Support → Reset to Initial Settings)

3. Enter the PIN (default is often 0000 or 1234,0413,0416

4. Confirm the reset — TV will restart fresh.

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3️⃣ Using the Remote Key Sequence (If Settings Not Accessible)

On many LG WebOS TVs:

1. Press and hold OK (center button) on the remote and OK on the TV panel at the same time for about 5–10 seconds until the reset menu appears.

2. Choose Factory Reset.

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4️⃣ Hard Reset Without Menu Access

If your TV is unresponsive:

1. Turn off the TV.

2. Hold down the Volume Down + Power buttons on the TV panel.

3. Keep holding until the LG (or WebOS) logo shows and the TV restarts.

4. Release the buttons — you should be prompted for setup again.

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⚠ Note: If the TV was accidentally flashed with the wrong WebOS firmware or is stuck in a firmware loop, the above may not work — in that case, you’d need a USB firmware reinstall.

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Do you know your exact TV brand and model?
If you tell me that, I can give you the precise reset and USB firmware method for your unit what's app me +923139292880 Imran Ashraf 

Here is a Next Topic for Understanding CPU AND GPU

Great question 👍 Let me explain in simple terms:

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CPU (Central Processing Unit)

• The CPU is the "brain" of a computer.

• It handles general tasks like running the operating system, applications, and managing input/output.

• It works best with tasks that require logic, decision-making, and sequential steps.

• Example: Opening a browser, typing a document, checking emails.

🔑 Key features:

• Few cores (usually 4–16 in consumer PCs).

• Very powerful per core.

• Designed for versatility, not just one type of work.

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GPU (Graphics Processing Unit)

• The GPU is like a specialized assistant for the CPU.

• Originally made for graphics and images (games, videos, 3D rendering).

• It handles many small tasks at the same time (parallel processing).

• Example: Drawing every pixel on your screen, processing video, or training AI models.

🔑 Key features:

• Thousands of smaller cores.

• Extremely fast at repeating simple tasks in parallel.

• Not good at decision-making but excellent at massive data crunching.

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Main Differences

Feature	CPU	GPU
Purpose	General-purpose computing	Specialized in parallel tasks (graphics, AI, simulations)
Cores	Few, powerful	Thousands, smaller
Speed	Great for single tasks	Great for massive parallel tasks
Examples	Running Windows, Word, browsing	Gaming graphics, video editing, AI, crypto mining

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👉 Analogy:

• Think of a CPU as a professor who can solve very complex problems one at a time.

• A GPU is like a classroom full of students, each solving a smaller part of the problem at the same time.

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Master's of the Topic

 This is on that gets to the heart of modern computing. Let's break down the differences between a CPU (Central Processing Unit) and a GPU (Graphics Processing Unit) in a clear and structured way.

The High-Level Analogy: The Specialist vs. The Army

Think of a task: building a house.

· The CPU (Central Processing Unit) is like a world-class general contractor. They are incredibly smart, can handle any complex task (plumbing, electrical, structural design), and are excellent at managing a sequence of different jobs. However, they only have two hands. They can do each task exceptionally well, but only one or two at a time.

· The GPU (Graphics Processing Unit) is like a thousand-person construction crew. Each worker is not as individually powerful or knowledgeable as the general contractor. But if you need to paint every wall, lay every brick, or nail every floorboard—tasks that are simple but need to be done a million times—the crew will finish the job orders of magnitude faster.

The CPU is designed for complex, sequential tasks. The GPU is designed for simple, parallel tasks.

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Detailed Breakdown

Here’s a side-by-side comparison of their core characteristics:

Feature CPU (Central Processing Unit) GPU (Graphics Processing Unit)

Core Purpose General-purpose computing. The "brain" of the computer. Handles the operating system, applications, logic, and I/O operations. Specialized computing. Originally for Graphics Processing, now for massive parallel processing (GPGPU).

Core Design Fewer, more powerful cores. A modern consumer CPU might have 8 to 32 complex cores optimized for speed on a single task. Thousands of simpler, smaller cores. A modern GPU has thousands of cores designed to work efficiently on many small tasks at once.

Workload Type Excellent at sequential, serial processing. Perfect for tasks where Step B cannot start until Step A is finished. Excellent at parallel processing. Perfect for tasks where a simple operation can be applied to a huge dataset simultaneously.

Best For Running the operating system, web browsing, spreadsheets, code compilation, complex physics simulations (e.g., game logic). Rendering 3D graphics, video editing & encoding, machine learning & AI, scientific simulations, cryptocurrency mining.

Latency vs. Throughput Low-Latency: Optimized to minimize the time to complete a single task. (Getting one answer fast). High-Throughput: Optimized to maximize the number of tasks completed in a given time. (Getting a billion answers at once).

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Architecture Visualization

This image perfectly illustrates the fundamental architectural difference:

```

    CPU Architecture: Fewer, powerful ALUs + Large Cache + Complex Control

    ┌─────────────────────────────────────────────────────────────────┐

    │                            CPU CORE                            │

    │  ┌─────────────┐  ┌─────────────┐  ┌─────────────────────────┐  │

    │  │     ALU     │  │     ALU     │  │         Cache          │  │

    │  │ (Arithmetic │  │ (Arithmetic │  │    (L1, L2, L3...)     │  │

    │  │  Logic Unit)│  │  Logic Unit)│  │                         │  │

    │  └─────────────┘  └─────────────┘  └─────────────────────────┘  │

    │  ┌─────────────────────────────────────────────────────────┐  │

    │  │                    Control Unit                         │  │

    │  └─────────────────────────────────────────────────────────┘  │

    └─────────────────────────────────────────────────────────────────┘

    GPU Architecture: Many, simpler ALUs + Small Cache + Simple Control

    ┌─────────────────────────────────────────────────────────────────┐

    │                             GPU                                │

    │  ┌─────┐┌─────┐┌─────┐┌─────┐┌─────┐┌─────┐┌─────┐┌─────┐      │

    │  │ ALU ││ ALU ││ ALU ││ ALU ││ ALU ││ ALU ││ ALU ││ ALU │ ...  │

    │  └─────┘└─────┘└─────┘└─────┘└─────┘└─────┘└─────┘└─────┘      │

    │  ┌─────┐┌─────┐┌─────┐┌─────┐┌─────┐┌─────┐┌─────┐┌─────┐      │

    │  │ ALU ││ ALU ││ ALU ││ ALU ││ ALU ││ ALU ││ ALU ││ ALU │ ...  │

    │  └─────┘└─────┘└─────┘└─────┘└─────┘└─────┘└─────┘└─────┘      │

    │  ┌─────────────────────────────────────────────────────────┐  │

    │  │                     Shared Cache                        │  │

    │  └─────────────────────────────────────────────────────────┘  │

    │  ┌─────────────────────────────────────────────────────────┐  │

    │  │                     Control Logic                       │  │

    │  └─────────────────────────────────────────────────────────┘  │

    └─────────────────────────────────────────────────────────────────┘

```

· ALU (Arithmetic Logic Unit): The part of the core that actually performs mathematical calculations.

· Cache: A very small and fast memory pool. CPUs need large caches to store all the immediate data for the complex tasks they're working on. GPUs have a much smaller cache relative to their core count because their tasks are simpler and they are designed to stream huge amounts of data.

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How They Work Together: The Perfect Partnership

You don't choose between a CPU and a GPU; a modern system uses both for what they're best at.

1. The CPU is the Manager: The CPU runs the main program (e.g., a video game). It handles the game's logic, player input, AI for non-player characters, and prepares the instructions for the graphics rendering.

2. The GPU is the Workforce: The CPU sends these instructions and all the data (3D models, textures, lighting info) to the GPU. The GPU's thousands of cores then spring into action simultaneously to:

   · Calculate the color of millions of pixels for the next frame.

   · Apply lighting and shadow effects to every surface.

   · Apply complex filters (shaders).

3. The Result: The finished frame is sent to your monitor. This process repeats 60+ times per second to create a smooth image.

This same manager/workforce relationship applies to non-graphics tasks like training an AI model. The CPU manages the training process, while the GPU performs the trillions of simple calculations required to adjust the model's parameters.

Summary

 CPU GPU

Role Generalist Brain Specialized Muscle

Goal Task Speed (Low Latency) Task Volume (High Throughput)

Method Complex Sequential Processing Massive Parallel Processing

In essence, the CPU is your computer's versatile command center, while the GPU is a monstrously powerful calculator for specific, highly parallelizable workloads. The evolution of computing is increasingly about offloading parallelizable tasks from the CPU to the GPU to achieve incredible performance gains.