In the electrolytic copper refining process, the contamination of metal impurities and suspended particles has
always been a technical problem plaguing the industry. The traditional manual cleaning method is inefficient,
costly, and difficult to cope with the demand of modern industry for high standard copper material with purity
above 99.99%. In this paper, we will analyze the three core pain points of electrolytic copper impurity treatment,
and systematically dismantle the configuration of the automated copper particle cleaning system, to help
enterprises achieve efficient cleaning and quality upgrade.
The technical difficulties of electrolytic copper impurity treatment
The impurities in the electrolyte can be divided into two categories: physical impurities (anode mud, copper particles)
and chemical impurities (iron, nickel and other ions). The traditional process faces a triple challenge:
Low impurity capture efficiency: suspended copper particles with a particle size <50μm are easy to attach to the cathode,
resulting in rough surface crystallization;
High cost of cleaning cycle: the electrolyzer needs to be shut down and cleaned up every 3-5 days, with an average daily
production capacity loss of 8%-15%;
Risk of secondary contamination: manual slagging tends to disrupt the chemical balance of the electrolyte and increase
the probability of exceeding the standard for metal ions.
Data show that the degradation rate of copper cathode due to impurity problems is as high as 6.3%, and the annual loss
of a single 100,000-ton production line exceeds 20 million yuan. The industry urgently needs to build a continuous
operation of the intelligent cleaning system.
Three steps to build an automated copper particle cleaning system
The first step: intelligent monitoring system in the pretreatment stage
Multi-dimensional sensing network deployed at the front end of the electrolyzer to realize dynamic tracking of impurities:
Optical Turbidity Sensor: real-time monitoring of the turbidity of the electrolyte to capture changes in the concentration
of particles > 10μm;
Electrochemical Probe: detecting the content of metal ions, such as Fe ² +, Ni ² + and other early warning of the critical
value of chemical contamination;
Flow Control System Flow control system: regulates the circulating speed of electrolyte through frequency conversion
pump to reduce the probability of impurity settling.
This stage needs to be configured with edge computing gateway, which compresses and transmits the detection data
to the central control system, with the delay controlled within 50ms, providing data support for dynamic cleanup decision-making.
Step 2: Co-configuration of core cleaning module
Adopting the dual-path design of "physical interception + chemical regulation":
Cyclone separation device
A three-stage conical cyclone is installed in the circulating pipeline of the electrolyte to generate a centrifugal force field at a
tangential flow rate of 15-20m/s, which can separate 98% of copper particles of a particle size of >20μm. The modular
design supports quick disassembly for cleaning and extends the maintenance cycle to 30 days.
Electromagnetic Adsorption Matrix
A permanent magnetic array (magnetic field strength 0.8-1.2T) is arranged on both sides of the cathode plate to utilize the
weak magnetic characteristics of copper particles for adsorption capture. With the reciprocating scraper mechanism, the
surface of the magnetic pole is automatically cleaned every 2 hours, and the purity of the recovered copper particles
reaches 99.5%, which can be directly returned to the furnace for remelting.
Intelligent replenishment system
According to the ion concentration detection data, it automatically injects complexing agent (such as thiourea, gelatin)
to form a protective film and inhibit impurity ions from being deposited at the cathode. The dosing precision is
controlled at ±0.5mL/min to avoid excessive additives affecting the electrolysis efficiency.
Step 3: In-depth optimization of closed-loop management system
Build a data center to realize the intelligent regulation of the whole process:
Digital twin model: Reduce the fluid state of the electrolysis tank through 3D modeling, and prejudge the impurity-rich area;
Adaptive algorithm: Dynamically adjust the rotor speed and electromagnetic field strength according to the parameters
of the current density (220-280A/m²), temperature (55-65℃), etc.;
Energy-efficiency analysis module: Compare the energy consumption and impurity treatment gain of the cleanup, and
compare the energy consumption and impurity treatment gain. Energy efficiency analysis module: comparing the
energy consumption and impurity treatment gain, automatically selecting the best economic program.
Measured data from a large smelter shows that the system increases the rate of copper cathode grade A from 91.7%
to 98.2%, and extends the cleaning frequency of electrolyzer from 72 hours/times to 480 hours/times.
Comprehensive benefit analysis of the automation system
Production efficiency improvement: continuous operation mode reduces downtime loss and annual effective
production time increases by 600 hours;
Operation cost reduction: labor involvement is reduced by 80%, auxiliary material consumption is reduced by
35%, and the cost of copper processing per ton is saved by 42 yuan;
Environmental protection value highlights: copper particle recovery rate is >95%, and solid content of wastewater
is reduced to less than 50mg/L, which is better than the industry's emission standards.
Technology Iteration Direction and Suggestions
With the development of machine vision and high-gradient magnetic separation technology, the system can
be further upgraded in the future:
Introducing AI image recognition technology to achieve accurate positioning and removal of 5-μm particles;
Developing a pulsed electromagnetic field device to improve the efficiency of capturing fine particles under low energy consumption;
Building a cloud platform for multi-base data linkage to optimize the global production strategy.
When deploying an automated cleaning system, companies need to focus on evaluating electrolysis process parameters,
capacity scale and impurity characteristics, and select a scalable modular architecture. It is recommended to cooperate
with intelligent service providers with metallurgical engineering experience to implement technical transformation in
phases, and system integration and ROI recovery can usually be completed in 6-8 months.