In the field of non-ferrous metal smelting, the electrolysis process is the core link of metal purification,
which directly affects product quality and production costs. The traditional electrolysis workshop relies
on manual experience to regulate tank voltage, current density and other parameters, which has high
energy consumption, large fluctuations in efficiency, and many safety hazards and other pain points.
With the deep integration of industrial Internet of Things, big data analysis and other technologies,
the gold electrolysis process is undergoing a subversive change from experience-driven to data-driven,
driving the industry towards a new stage of high precision, low energy consumption and intelligence.
Technical bottlenecks and upgrading needs of gold refining
electrolysis process
Non-ferrous metal electrolysis involves the extraction and refining of key metals such as copper, zinc,
nickel, cobalt, etc., and the complexity of the process is growing exponentially:
Sloppy energy-efficiency management: DC power consumption of electrolysis tanks accounts for
40%-60% of the total cost of production, and the traditional control mode results in the fluctuation
of the current efficiency in the range of 85%-92% only;
The lagging of the process parameters: manual inspections are conducted once every hour, and they
can't capture the electrolyte concentration, temperature, and temperature of electrolyte in real time.
Process parameter lagging: manual inspection for 1 hour cannot capture the dynamic changes of
electrolyte concentration, temperature and metal ion concentration in real time;
Anode passivation problem: the thickening speed of the oxide layer on the surface of the anode plate
does not match the current density, resulting in the increase of tank voltage by 10%-15%;
Pressure of environmental protection management: the risk of exceeding the standard of acid mist
fugitive, heavy metal wastewater and other pollutant emission increases the cost of end-of-pipe treatment.
The penetration of automation technology is reconfiguring the electrolysis production system from
three major dimensions: process optimization, equipment operation and maintenance, and energy management.
Four technical pillars of automation of gold refining electrolysis
1. Intelligent regulation system of electrolysis process
Multi-parameter dynamic modeling:
Through the tank pH sensor, infrared thermal imager, electrochemical workstation and other equipment,
real-time collection of 20+ process parameters, to build the kinetic model of electrolysis reaction. The system
updates the recommended value of optimal current density every 5 seconds, which stabilizes the current
efficiency above 95%.
Anode Passivation Early Warning Module:
Using high-frequency impedance spectrum analysis technology, it monitors changes in the anode polarization
curve, predicts the passivation threshold 12 hours in advance, automatically triggers the mechanical scraping
device to clean up the surface of the anode, and reduces the fluctuation of the tank voltage to within ±2%.
2. Digital twin operation and maintenance platform
Three-dimensional visualization monitoring:
maps the physical entity of electrolysis workshop into a digital twin, displays the operation status of 2000+
electrolysis tanks in real time, and shortens the response speed of locating abnormal tanks from 30
minutes to 30 seconds.
Predictive Maintenance System:
analyzes cathode/anode plate corrosion data, busbar temperature curve and other historical records, warns
of electrode loss risk 72 hours in advance, and reduces the rate of unplanned equipment downtime by 60%.
3. Fine control of energy flow
Multi-level power scheduling algorithm:
Automatically plans the output power of DC power source according to the time-sharing tariff of the power
grid and the load characteristics of the electrolyzer, compression of the proportion of power consumption
in the peak hours from 45% to 28%, and reduction of power consumption of tons of metal by 8%-12%.
Waste heat recovery network:
Low-temperature waste heat of 60℃-80℃ is recovered during the electrolyte circulation process and
converted into process hot water through lithium bromide unit, saving steam consumption of
over 5,000 tons per year.
4. Pollutant Source Control Technology
Acid Mist Intelligent Capture System:
Negative-pressure air curtains are arranged on the tank surface, which, together with laser dust sensors,
realize the acid mist capture efficiency of ≥98%, and the air quality of the workshop reaches GBZ 2.1 standard.
Online retention of heavy metal ions:
electrolysis waste liquid flows through the selective ion exchange membrane, the recovery rate of copper,
nickel and other metal ions is increased to 99.5%, and the wastewater reuse rate exceeds 90%.
Technological Innovation Direction of Key Equipment
High-precision Electrolyzer Sensor
Development of solid-state ion-selective electrodes resistant to strong acid corrosion, with measurement
error narrowed from ±5% to ±0.5% and service life extended to more than 3 years.
Adaptive DC power supply
Adopting silicon carbide (SiC) power devices, the power conversion efficiency is increased from 92% to
97%, and the output ripple coefficient is <0.1%.
Modularized electrolytic cell set
The standard unit design supports rapid tandem reconfiguration, and the capacity of a single set can
be flexibly adjusted within the range of 50-200 tons/day to meet the needs of multi-species production.
Practical Challenges of Industry Transformation
Process Data Barriers
Electrolysis parameter optimization relies on long-term production data accumulation, and SMEs generally
face the modeling dilemma of insufficient data samples.
Interdisciplinary talent gap
Composite teams that simultaneously master metallurgical engineering, automatic control, and data
science are needed, and the transformation training cycle for existing practitioners is as long as 6-12 months.
Lack of standardization system
electrolysis tank communication protocols, data interfaces have not yet been unified, and there are
technical barriers to the interoperability of cross-brand equipment.
Future Technology Evolution Trends
Quantum Computing Process Optimization
The use of quantum algorithms to solve multivariate electrolysis reaction equations, with a 1000-fold
increase in computation speed compared to traditional methods, realizes global optimization of
process parameters.
Self-repairing electrolyzer coating
Intelligent materials can actively release repair components under electrolyte erosion, extending the
service life of cathode plates by 3-5 times.
Green Hydrogen Coupled Electrolysis System
Photovoltaic hydrogen production is linked to the electrolysis process, replacing part of the
electrochemical reduction reaction with hydrogen reduction, reducing the comprehensive
carbon reduction intensity by 40%.
Conclusion
Automation of electrolysis in gold refining is reshaping the value chain of nonferrous metal smelting.
Through the system integration of real-time optimization of process parameters, full life cycle
management of equipment, intelligent scheduling of energy network and other technologies, the
enterprise not only realizes the reduction of production cost and product quality, but also occupies the
first-mover advantage in low-carbon transformation. With the improvement of new infrastructures such
as 5G private network and digital twin, the electrolysis workshop of the future will evolve into a “smart
factory” with autonomous decision-making, injecting sustainable kinetic energy into the global
metal supply chain.