The debugging of laboratory bottle washing machines is a key link to ensure their efficient operation and long-term stability, requiring refined operations from multiple dimensions such as mechanical structure, electrical system, program parameters, and performance verification. The following is a detailed debugging process and precautions:

1、 Basic preparation before debugging

1. Installation environment confirmation

-Ensure that the equipment is placed in a dry and ventilated area, avoiding moisture, high temperatures, or direct sunlight.

-Check that the power supply voltage is consistent with the machine nameplate, the grounding is reliable, and the insulation resistance is ≥ 2M Ω.

2. Inspection of water and gas pipelines

-Confirm that the connection between the pure water inlet pipe and the tap water inlet pipe is intact, and the water source valve should be in the open position during use.

-Check that the drainage screen is not blocked by debris to avoid affecting drainage efficiency.

2、 Debugging of core component functions

1. Mechanical structure calibration

-Spray arm debugging: Check whether the rotation of each layer of spray arm is smooth, and the direction of the water outlet hole should be aligned with the inner wall of the vessel. Missing or damaged spray arms must be replaced.

-Transmission system test: manually rotate the bottle wheel to confirm that the clutch position is normal and there is no jamming phenomenon.

2. Program parameter optimization

-Select the appropriate washing program (such as "dirty water" or "dirty oil" mode) based on the type of vessel (such as volumetric flask or conical flask), and adjust the parameters to match actual needs.

-Verify the timed start function to ensure that the device runs automatically at the preset time.

3. Verification of Security Protection Mechanisms

-Simulate a leakage scenario and test whether the leakage protection device immediately cuts off the power supply.

-Check the sealing of the cabin door to prevent water leakage during operation.

3、 Performance validation and quality control

1. Cleaning effect test

-Conduct full process cleaning tests using standard contaminated samples (such as oils, fats, and inorganic salts), and evaluate cleanliness through visual observation or chemical testing methods.

-For experiments requiring high cleanliness (such as trace analysis), it is recommended to conduct blank testing to ensure no residual interference.

2. Efficiency and energy consumption balance

-Record the water and electricity consumption of a single cycle, adjust parameters to achieve energy-saving goals.

4、 Key points for debugging in special scenarios

1. Complex matrix processing

-For residual organic reagents, use a dedicated solvent cleaning module; Heavy metal pollution requires the addition of EDTA Na ₂ washing solution to enhance the chelating effect.

-During the flushing stage with injection water, it is necessary to monitor the water quality conductivity to be ≤ 1 μ S/cm.

2. Integrated device collaboration

-If the bottle washing machine is linked with the sterilization oven, the signal interface needs to be debugged to ensure that the drying program is automatically triggered after cleaning is completed

-Verify the PLC program logic to avoid process conflicts that may cause downtime.

5、 Daily maintenance and fault prevention

1. Periodic maintenance plan

-Clean the drainage screen and spray arm residue daily, and disassemble the nozzle for ultrasonic cleaning every week.

-Check the scaling condition of the heating tube every month and replace the aging sealing ring in a timely manner.

2. Common troubleshooting

-Unclean cleaning: Prioritize troubleshooting for clogged spray arms or insufficient concentration of cleaning agents.

-Equipment abnormal noise: Check the wear of transmission gears or the lubrication status of bearings.

The debugging of laboratory bottle washing machines should be carried out throughout the entire installation, operation, and maintenance cycle, with a focus on mechanical accuracy, program adaptability, and safety. Through standardized processes and targeted optimization, cleaning efficiency can be significantly improved and the risk of experimental errors can be reduced.