🧊 Detailed Plan for Refrigerator Dynamic Detection System
一、📌 Project Background and Objectives
With the rapid development of the refrigerator manufacturing industry, traditional static detection methods (such as long-term temperature recording) can no longer meet the needs of efficient production. The dynamic detection system achieves fast and reliable performance evaluation by real-time collecting operating parameters and comparing them with preset models.
Goal：
Improve detection efficiency and shorten the test cycle
Achieve automatic judgment and reduce human error
Support comprehensive evaluation of multiple parameters and improve detection accuracy
二、🔧 System Architecture Design
1. System Composition
Module |
Function Description |
|---|---|
Sensor Acquisition Module |
Real-time collection of parameters such as temperature, current, and power |
Data Processing Module |
Filter and normalize the collected data |
|
Model Comparison Module |
Compare with the standard performance model to determine qualification |
|
Control and Feedback Module |
Control the test process and output the detection results |
User Interface Module |
Display real-time data and detection status, and support operations and queries |
2. Architecture Form
Adopt a C/S architecture（Client/Server）：
Client：Used for operation interface and data display
Server：Responsible for data processing, model comparison, and result storage
三、📊 Detection Parameters and Model Design
1. Key Detection Parameters
Refrigerator Compartment Temperature
Freezer Compartment Temperature
Intake Pipe Temperature
Exhaust Pipe Temperature
Compressor Operating Power
Current Fluctuation Status
2. Model Comparison Mechanism
Establish a standard refrigerator operation model (based on historical qualified samples)
Set parameter range thresholds (e.g., the refrigerator compartment temperature should be between 2°C and 8°C)
Compare real-time collected data with the model
If all parameters are within the specified ranges, determine it as "qualified"
四、⚙️ Technical Implementation Details
1. Hardware Selection
Component |
Model/Specification |
|---|---|
Main Control Chip |
STM32F103C8T6 |
Temperature Sensor |
DS18B20 |
Current Sensor |
ACS712 |
Display Module |
0.96-inch OLED |
Communication Module |
RS485 or Wi-Fi |
Motor Driver |
TB6612FNG（Used for simulating gating） |
2. Software Function Modules
Data Acquisition Thread (Timed Sampling)
Anomaly Detection Algorithm (e.g., sudden temperature changes, power abnormalities)
Model Matching Algorithm (Based on Multi-Parameter Weighted Scoring)
Alarm Mechanism (LED/Buzzer Notification)
Data Storage and Export (CSV Format Supported)
五、🧪 Test Process and Application Scenarios
1. Test Process
Connect the refrigerator to the test line and power it on for operation
The system starts collecting parameters
Compare with the model in real time to determine qualification
Output test results (Qualified/Unqualified)
Archive data for subsequent traceability
2. Application Scenarios
Rapid Detection for Refrigerator Production Lines
Smart Refrigerator Self-Test System
Auxiliary Diagnosis for After-Sales Maintenance
Laboratory Performance Evaluation
六、📈 Advantages and Prospects
✅ Advantages
The detection cycle is shortened to within 5 minutes
High degree of automation, reducing manual intervention
Strong scalability, supporting multiple models of refrigerators
🔮 Prospects
In the future, it can integrate AI algorithms for fault prediction, support remote detection and cloud-based data analysis, and realize "intelligent detection" in the true sense.