Potassium ion electrochemical detection method and system based on electric signal enhancement and key feature focusing technology
Through electrical signal enhancement and key feature focusing technology, the problems of poor signal repeatability and low detection accuracy of complex samples in electrochemical measurements are solved, and efficient and low-cost potassium ion concentration detection is achieved.
CN120232960APending Publication Date: 2025-07-01HARBIN INST OF TECH
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Patent Information
- Application Number
- CN202510241859.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-03-03
- Publication Date
- 2025-07-01
AI Technical Summary
Technical Problem
Existing electrochemical measurement methods ignore key features in dynamic changes in complex samples, resulting in limited model performance, poor repetition of ISE signals, high cost and complex operation.
Method used
Through electrical signal enhancement and key feature focus technologies, including signal acquisition, data set enhancement, and key feature focus neural network, dedrift, time series decomposition and attention mechanisms are used to improve signal quality and form an efficient potassium ion concentration detection method.
Benefits of technology
It improves the repeatability and detection accuracy of electrode signals, reduces operational complexity, and improves the detection accuracy of the model in complex samples.
✦ Generated by Eureka AI based on patent content.
Abstract
The invention discloses a potassium ion electrochemical detection method and system through an electric signal enhancement and key feature focusing technology, and relates to the field of electrochemical detection. The problems that in an existing electrochemical measurement method, a data set of electrochemical signals is limited, a neural network model only pays attention to the steady-state value of the signals, and the transformation trend is ignored are solved. The method comprises the following steps: step 1, detecting electric signals in signal acquisition equipment, detecting potassium ion solutions with different concentrations one by one by adopting an ion selective electrode, and storing the detected electric signals to form an electric signal data set; 2, enhancing the electric signal data set stored in the step 1 to form a data set capable of supporting neural network training; and step 3, inputting the dataset capable of supporting neural network training formed in the step 2 into the key feature focusing neural network to obtain the potassium ion concentration corresponding to the electric signal. The method is also suitable for the fields of rapid evaluation of soil nutrients or monitoring of electrolyte levels of patients.
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