Bottom-Sediment Classification Using Depth-Proportional Ultrasonic Pulses
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing bottom-sediment classification methods using ultrasonic waves face accuracy issues in shallow water due to the influence of pulse width and depth, leading to unreliable classification results and the need for real-time classification, which is not feasible with current technologies.
Innovation Solution
A device and method that transmit ultrasonic pulses with widths proportional to water-bottom depth, extract and normalize amplitude data at intervals corresponding to depth, and calculate feature quantities to generate classification information, using neural networks for accurate classification independent of depth.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional bottom-sediment classification methods are used, then classification can be performed, but accuracy deteriorates in shallow water due to pulse width and depth influence
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the pulse width based on water depth. Specifically, the pulse width is set to be proportional to the water depth (e.g., pulse width = k × depth, where k is a constant). This parameter adjustment compensates for the depth-related degradation in echo signal characteristics, maintaining consistent classification accuracy across different water depths including shallow water conditions.
2Productivity
If conventional methods are used, then classification results can be obtained, but real-time classification is not feasible due to computational complexity
Solution Approach 1:
The patent extracts and utilizes only the most critical features from the echo signals for classification, rather than processing the entire signal spectrum. By focusing on key parameters such as pulse width, amplitude characteristics, and selected frequency components, the system achieves real-time classification capability while significantly reducing computational complexity compared to comprehensive signal analysis methods.
3Reliability
If pulse width is increased to improve signal detection, then detection capability improves, but classification accuracy deteriorates due to depth-related distortion
Solution Approach 1:
The patent implements a dynamic pulse width adjustment mechanism where the pulse width is not fixed but is dynamically adapted based on the measured water depth. The system continuously adjusts the pulse width parameter to maintain an optimal relationship with depth (proportional relationship), ensuring that the pulse is wide enough for reliable detection in deep water while remaining narrow enough to maintain accuracy in shallow water, thus resolving the contradiction between detection capability and classification accuracy.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The solution provides accurate and real-time bottom-sediment classification by normalizing amplitude data and calculating feature quantities based on depth, improving classification accuracy and reducing dependency on water-bottom depth, enabling effective classification in both shallow and deep water areas.
Implementation Method 1
transmits a pulse of an ultrasonic wave from a transducer to a water bottom, and receives water-bottom echo signals by the transducer
Implementation Method 2
analyzes a water-bottom echo of the transmission pulse to obtain the bottom sediment information
Data Source
AI summary
A device and method for determining bottom sediment is provided. The method includes transmitting a pulse of a pulse width corresponding to a water-bottom depth, extracting a series of amplitude data of water-bottom echo signals from predetermined signals among the water-bottom echo signals received by the transducer at a predetermined time interval, normalizing the extracted series of amplitude data after TVG-processed, calculating two or more feature quantities based on the normalized series of amplitude data in each of segments of the normalized series of amplitude data, and a value corresponding to the water-bottom depth, and generating bottom-sediment classification information indicating the bottom sediment based on the two or more feature quantities.