Continuous monitoring system of the cavitation phenomena for at least one submerged part of a boat

Abstract

Continuous monitoring system for cavitation phenomena for at least one submerged part (1) of a boat (2), comprising an underwater monitoring module (3). The monitoring module (3) is permanently attached to the hull (20) of the boat (2) near the said submerged part (1) and consists of a watertight case (4) equipped with one or more sensors and one or more lighting elements (5). The said sensors comprise at least one camera (6) and at least one light intensity sensor (7), with a control unit also configured to activate the said lighting elements (5) when the said light intensity sensor (7) detects insufficient lighting conditions for the said camera (6).

Description

[0001] The invention relates to a system for continuously monitoring the submerged parts of a boat.

[0002] In particular, the invention concerns a system for continuously monitoring cavitation for at least one submerged part of a boat, comprising an underwater monitoring module.

[0003] In the shipbuilding industry, monitoring the submerged parts of boats is essential to ensure safety and operational efficiency. Currently, such operations are mainly carried out in tests prior to the delivery of a new vessel or during scheduled inspection and maintenance periods when the vessel is taken out of the water. However, during the operational period, with the vessel in the water, it is not easy to obtain continuous and up-to-date data on the condition of submerged parts, such as the propeller or the rudder. This limitation implies a potential risk to the safety and efficiency of the vessel.

[0004] Cavitation is one of the most damaging phenomena for the submerged parts of a vessel, such as the propeller, bow thrusters, or stabilizer fins. This phenomenon occurs when the water pressure near a moving surface, such as propeller blades, falls below the vapor pressure of the water itself, causing vapor bubbles to form. These bubbles, carried by the water flow, collapse rapidly when they move into areas of higher pressure, generating high-intensity shock waves.

[0005] Cavitation is mainly caused by high propeller rotation speeds, suboptimal operating conditions, design imperfections, or the installation of submerged parts, which create low-pressure areas. Other factors contributing to cavitation include water temperature variations and ship trim.

[0006] The collapse of bubbles generates high-speed, high-pressure micro-jets, which can cause erosion and damage to metal surfaces. On the propeller, this results in the formation of pinpoint erosion, which, over time, can lead to cracks and breakage. In bow thrusters and stabilizing fins, cavitation can compromise operational effectiveness and generate strong vibrations, with consequences for efficiency and comfort during navigation.

[0007] In addition to physical damage, cavitation significantly reduces the efficiency of the propulsion system, causing loss of thrust and increased fuel consumption. Due to its damaging potential, cavitation should require continuous monitoring and timely intervention to mitigate its effects.

[0008] There are various state-of-the-art underwater monitoring systems for boats.

[0009] Document CN107071366A describes a real-time video monitoring system for a ship's pod-type propeller, comprising an underwater camera connected to a display system in the cabin.

[0010] Document US20090128623A1 describes a video monitoring system for a ship's underwater equipment, with a camera attached to the hull and connected to a video monitor in the wheelhouse.

[0011] Document US7599614 describes a camera system for marine propulsion mechanisms, mounted on outboard motors.

[0012] However, these systems are not specifically designed to monitor cavitation, nor are they capable of implementing procedures aimed at reducing or eliminating this phenomenon. In particular, none of the above documents describes a set of sensors sufficient to ensure continuous monitoring and enable advanced data processing and automatic control functions.

[0013] The invention aims to solve the problem of the lack of continuous, real-time monitoring of the submerged parts of a vessel during its operational life in relation to cavitation, allowing up-to-date data to be collected and processed to improve the safety and efficiency of naval operations.

[0014] The invention aims to achieve these goals and overcome the drawbacks of currently known state-of-the-art systems with a system as described at the beginning, in which the underwater monitoring module is also permanently coupled to the hull of the vessel near the submerged part and consists of a watertight case equipped with one or more sensors and one or more lighting elements, said sensors including at least one camera and at least one light intensity sensor, a control unit also being provided to activate said lighting elements when said light intensity sensor detects lighting conditions that are insufficient for said camera.

[0015] The stable coupling of the underwater monitoring module to the hull allows constant monitoring of the operating conditions of the submerged parts. This continuous monitoring allows phenomena such as cavitation to be detected promptly, reducing the risk of damage to critical parts and optimizing the boat's performance. The watertight case protects the sensors and lighting elements from the marine environment, preserving their integrity and functionality even in adverse conditions such as high pressure and high salinity. The monitoring module thus consists of a fixed ceiling light installed on the hull of the boat and connected by electrical contacts, or by wireless communication, to the interior of the boat itself.

[0016] The presence of a camera among the sensors allows high-resolution visual data to be obtained, which is essential for monitoring the condition of the submerged parts and accurately identifying any anomalies or damage caused by cavitation. The camera also provides a complete view of the surrounding area, improving the monitoring of operating conditions.

[0017] The inclusion of a light intensity sensor allows the system to assess underwater lighting conditions in real time and automatically activate lighting elements when necessary. This ensures that the camera always receives adequate light, even in poor visibility conditions, such as at night or in muddy waters.

[0018] The combination of sensors and lighting ensures constant, high-quality monitoring, allowing early identification of cavitation or other critical issues. This allows for rapid intervention, avoiding extensive damage to submerged components and improving the service life of the propeller and other submerged parts, resulting in reduced maintenance and repair costs. Automation by the control unit reduces the need for manual intervention, ensuring optimal operation in all conditions.

[0019] In an executive example, the submerged part is a propeller and the camera's acquisition frequency is variable, as the control unit is configured to synchronize the camera's acquisition frequency with the propeller's rotation frequency.

[0020] Synchronization between the camera's acquisition frequency and the propeller's rotation frequency allows for clear and detailed images of the propeller, reducing the blurring or distortion effect caused by rapid movement. Thanks to synchronization, the camera can capture images of the propeller as if it were stationary, allowing the propeller's operating conditions to be analyzed even during movement, without having to interrupt operations.

[0021] In a further executive example, the lighting elements are stroboscopic.

[0022] The stroboscopic effect allows for sharp images of the propeller even in low underwater lighting conditions or in murky water.

[0023] In a further embodiment, the submerged part is a propeller and the lighting elements have a variable stroboscopic frequency, the control unit being configured to synchronize the emission frequency of the lighting elements with the rotation frequency of the propeller.

[0024] Synchronizing the strobe frequency with the rotation of the propeller allows the propeller to be illuminated exactly when a clear shot is needed, ensuring a video of the propeller as if it were stationary even when it is rotating at high speed. Thanks to the dynamic synchronization of the strobe frequency with the movement of the propeller, it becomes possible to accurately detect any cavitation phenomena during rapid movement, without distortion or blurring, with a clear view of the paths of the vapor bubbles, as well as any cracks or damage on the blades.

[0025] According to one embodiment, the camera has a field of view greater than 60°, preferably 80°, and can be oriented by rotating around two axes perpendicular to each other.

[0026] This allows the camera to monitor a large area around the submerged part, such as the propeller or other components, reducing the number of cameras required and improving the efficiency of the system. The camera's ability to rotate around two perpendicular axes allows for a complete view in all directions, significantly improving the dynamic monitoring of submerged parts. This allows the control unit to orient the camera towards critical areas or potential anomalies.

[0027] In a further embodiment, the lighting elements are configured to emit blue light.

[0028] Blue light has a wavelength that allows it to penetrate water better than other wavelengths, such as red or green. This improves the illumination of submerged parts, such as the propeller, especially at greater depths or in more muddy waters. Blue light also reduces scattering caused by particles suspended in the water, ensuring clearer and more defined visibility of the area surrounding the submerged parts, resulting in sharper images from the monitoring cameras. Blue light can therefore help to highlight phenomena such as cavitation, making vapor bubbles more visible as they form and collapse. It also provides better contrast for the underwater camera, especially in low light conditions or in deep water.

[0029] Blue light is also less disturbing to many marine species than other light frequencies, reducing the environmental impact of the system, especially in sensitive or protected areas.

[0030] According to an executive example, the submerged part is a propeller and the sensors include at least two pressure probes configured to detect the phase and frequency of rotation of the propeller.

[0031] The frequency of detection of the pressure wave fronts and the delay in detection between the two probes allows the phase and frequency of rotation of the propeller to be accurately detected, providing accurate data on its movement in real time. The ability to continuously monitor the rotation frequency allows the system to predict and prevent cavitation phenomena: if the propeller rotation reaches critical conditions, the system can signal a risk of cavitation or automatically activate corrections to optimize speed.

[0032] In an executive example, the sensors include at least one turbidimeter.

[0033] The turbidimeter measures the turbidity of the water around the submerged part, providing information on the amount of suspended particles in the water. This is useful for assessing the environmental conditions in which the propeller and other submerged parts operate. Turbidity monitoring can detect critical conditions such as increased debris or sediment that can negatively affect propeller efficiency, reducing thrust or increasing blade wear. Thanks to the turbidimeter, the system can dynamically adapt data acquisition modes based on water turbidity, improving the performance of other sensors, such as the camera, which may require more lighting in high turbidity conditions. For this or other purposes, the control unit can increase the emission intensity of the lighting elements.

[0034] In one example, the sensors comprise at least one thermometer.

[0035] The thermometer detects the temperature of the water in which the propeller and other submerged parts operate, providing essential information for monitoring environmental conditions and the boat's operating behavior. Since cavitation is influenced by water temperature, the thermometer helps predict and prevent cavitation phenomena, as an increase in temperature reduces the vapor pressure of water, increasing the risk of cavitation. Temperature measurement allows the system to adapt the operating parameters of the propeller and other components, optimizing their efficiency based on the detected thermal conditions, ensuring optimal operation even in hot or cold marine environments.

[0036] In addition, abnormal temperature variations can indicate operational or environmental problems, such as overheating or warm currents, allowing for the timely diagnosis of conditions that are potentially harmful to submerged parts and the launch of predictive maintenance interventions. Temperature variations affect not only the efficiency of the propeller but also the overall behavior of the vessel.

[0037] In an executive example, the sensors include at least one salinity meter.

[0038] The salinity meter provides accurate data on the concentration of salts in the water, allowing the environmental conditions in which the propeller and other submerged parts operate to be assessed. Salinity directly affects the physical properties of water, such as density and conductivity, and its measurement is crucial for optimizing boat performance. Variations in salinity can affect cavitation and other operational dynamics of the vessel. High salinity can accelerate corrosion of submerged metal parts, such as the propeller or stabilizing fins. The salinity meter allows you to monitor these conditions in real time and initiate appropriate maintenance or protection measures to reduce damage caused by highly saline water. Salinity also affects the hydrodynamic characteristics of the water: by monitoring salinity, the system can adjust the propeller's operating parameters to ensure optimal performance, adapting the thrust according to changes in water density. Continuous salinity data helps predict the need for maintenance and prevent premature wear.

[0039] In an executive example, the sensors comprise at least one accelerometer.

[0040] The accelerometer is capable of detecting in real time the vibrations generated by the propeller or other submerged parts, such as bow thrusters or stabilizing fins. This data allows for the identification of any anomalies or imbalances in the propulsion system or submerged structures, such as misalignment or propeller wear, signaling the need for maintenance before more serious failures occur.

[0041] Vibrations can affect comfort on board, particularly in areas dedicated to passengers or crew. The accelerometer allows vibrations to be continuously monitored and operating parameters to be adjusted to reduce vibrations, thus improving comfort and compliance with vibration limits imposed by maritime regulations.

[0042] The accelerometer can also detect sudden changes in vibrations caused by cavitation.

[0043] In an executive example, the sensors comprise at least one hydrophone.

[0044] The hydrophone is capable of picking up the characteristic sounds produced by cavitation, such as the crackling generated by the implosion of vapor bubbles. This allows the phenomenon to be identified in a timely manner, even in its early stages, improving the prevention of damage to the propeller and other submerged parts. Cavitation tends to intensify when the propeller operates under high load or speed conditions, or in the presence of particular physical conditions such as increased water temperature or pressure variations. The hydrophone can monitor the variations in sound intensity that occur as these parameters change, providing an accurate indication of the severity of cavitation in real time.

[0045] The hydrophone can also pick up engine noise, providing useful data for monitoring operating conditions and identifying any acoustic anomalies that could indicate mechanical problems or propulsion inefficiencies. In addition to engine noise, the hydrophone can detect sounds that indicate wear or mechanical malfunctions in submerged parts, such as the propeller or bow thrusters. This data helps plan predictive maintenance, reducing repair costs and preventing sudden breakdowns during operation.

[0046] The hydrophone can also be used to detect and monitor underwater noise levels generated by the vessel, helping to reduce the acoustic impact on the marine environment and protect noise-sensitive marine fauna, such as cetaceans and other vulnerable species.

[0047] According to one embodiment, the camera is equipped with an automatic cleaning device installed near the camera lens and designed to remove debris, encrustations, or other materials that settle on the lens surface.

[0048] This automatic cleaning device ensures that the camera lens is constantly free of debris, encrustations, or other impurities that could obstruct visibility. This allows for continuous and clear monitoring of submerged parts, without interruptions due to the presence of foreign materials. The automatic cleaning system eliminates the need for frequent manual cleaning of the lens, especially in harsh environments where debris can accumulate quickly, and prevents the build-up of deposits that, in the long term, could damage the lens material or compromise the quality of the images captured by the camera.

[0049] The monitoring module can be housed in a niche in the hull, equipped with a closure to protect the camera and / or additional sensors when the monitoring module is not in use.

[0050] In one embodiment, the monitoring module is connected to the boat's control panel to allow real-time viewing and / or processing of the data collected by the sensors.

[0051] The connection of the monitoring module to the control panel allows real-time viewing and analysis of data, in particular video data generated by the camera, enabling the crew to intervene immediately in the event of anomalies, such as cavitation or malfunctions of submerged parts. Onboard personnel can make quick and informed decisions to optimize vessel performance or prevent damage to submerged components. The real-time connection also allows for immediate diagnostics of the vessel's operating conditions, providing data on temperature, salinity, pressure, and vibrations, and allowing for the optimization of navigation parameters to improve energy efficiency. The ability to view and analyze data in real time allows potential problems to be detected before they become critical, improving the operational safety of the vessel and reducing the risk of serious damage or costly repairs.

[0052] According to a further embodiment, the control unit is configured to execute artificial intelligence algorithms to analyze the data detected by said sensors and provide operational suggestions to the vessel's crew to reduce or eliminate cavitation for said submerged part.

[0053] The use of artificial intelligence (AI) algorithms allows for quick and accurate analysis of data from sensors, such as pressure, vibrations, and images, precisely identifying cavitation and its causes, even in complex conditions. Al algorithms can provide detailed and specific operational suggestions to the crew, such as adjusting the engine speed and therefore the propeller or other operating parameters, helping to mitigate or prevent cavitation effectively, without necessarily requiring advanced experience in data interpretation on the part of the personnel.

[0054] Intelligent automatic analysis reduces the risk of human error and allows optimal operating conditions to be identified in order to prevent cavitation, reducing wear on submerged parts and improving energy efficiency and the overall service life of mechanical components. Al algorithms can also identify patterns that indicate the onset of cavitation, allowing the crew to take preventive action or plan maintenance operations before the phenomenon causes significant damage.

[0055] In a further embodiment, the control unit is configured to automatically implement operational changes to the boat's control systems in order to reduce or eliminate cavitation for the submerged part, based on the analysis of data collected by the sensors using the artificial intelligence algorithms.

[0056] The control unit's ability to automatically implement operational changes on the vessel allows it to respond in real time to cavitation without the need for manual intervention. This is particularly useful in situations where a rapid response is crucial to prevent damage.

[0057] Based on real-time data analysis, the system can automatically adjust operating parameters, such as propeller speed, stabilizer fin angle, or propeller blade angle in the case of a variable pitch propeller, to keep the vessel in optimal condition and reduce the incidence of cavitation, thereby improving energy efficiency and performance. Because the system can autonomously manage operating conditions to prevent cavitation, the crew can focus on other tasks without having to continuously monitor sensor data or make manual adjustments. This dramatically reduces the risk of human error in adjustments and ensures that operational changes are based on accurate and thorough data analysis, guaranteeing precise and reliable decisions.

[0058] By automatically reducing or eliminating cavitation, the system helps to minimize wear and damage to submerged parts, thereby extending their service life and reducing maintenance and repair costs, maintaining the stability of the vessel, and preventing potentially dangerous situations due to vibration or sudden losses of propulsive efficiency, increasing overall operational safety.

[0059] These and other features and advantages of the present invention will become clearer from the following description of some examples illustrated in the attached drawings, in which: Figure 1 schematically illustrates the boat with the monitoring module positioned near the propeller; Figure 2 illustrates an example of the monitoring module.

[0060] The figures illustrate a preferred embodiment of the cavitation monitoring system for at least one submerged part 1 of a boat 2. The boat 2 may be, for example, a ship, a boat, a yacht, a ferry, a submarine, a motorboat, a catamaran, a fishing boat, a sailing ship, a tugboat, a barge, a dinghy, a hydrofoil, a boat, or other similar vessels. The submerged part may be, for example, a propeller, a bow thruster, a stabilizing fin, or any other underwater element of the vessel that may be subject to cavitation. In the example shown in the figures, the submerged part is a propeller 1.

[0061] The system comprises an underwater monitoring module 3 permanently attached to the hull 20 of the vessel 2 near the propeller.

[0062] The monitoring module 3 consists of a watertight case 4 equipped with one or more sensors and one or more lighting elements 5. The system also includes a control unit, not shown in the figures, which can be placed inside the case 4 or inside the hull 20.

[0063] It is possible to provide more than one monitoring module 3.

[0064] Case 4 consists of a flat part 40, fixed to the hull, and a hollow cover part 41. The flat part 40 is preferably substantially rectangular, but may be concave or of any shape to better fit the shape of the portion of the hull to which it is fixed. The cover part 41 engages with the flat part 40 to form an internal space of the case 4 sealed from water. This sealing is ensured by a gasket 42 placed on the perimeter edges of the flat part 40. The cover 41 has openings for housing the sensors and lighting elements 5. The lighting elements are fixed to the flat part 40 and the cover 41 is equipped with a corresponding opening, closed by a transparent glass plate 50 that allows light to be emitted. The flat part 40 is provided with a hole 43 for cables to pass through to the inside of the hull 20.

[0065] This forms a ceiling light fixed to the hull 20 and facing with the sensors and lighting elements 5 towards the object to be monitored, in this case the propeller 1.

[0066] The sensors comprise a camera 6, designed to monitor the propeller 1 in real time, capturing images and videos to detect any anomalies, damage or phenomena such as cavitation.

[0067] The camera 6 has a field of view greater than 60°, preferably 80°, and can be adjusted by rotating around two axes perpendicular to each other. Alternatively, a fixed camera with a wide field of view, for example between 120° and 180°, can be used.

[0068] The monitoring module includes a scraper (cleaner / wiper), configured to automatically clean the lens of camera 6. This device removes debris and encrustations from the lens surface, ensuring constant and clear visibility for underwater monitoring, without requiring manual intervention.

[0069] The acquisition frequency of camera 6 is variable, and the control unit is configured to synchronize the acquisition frequency of camera 6 with the rotation frequency of propeller 1. This allows video to be captured with a still image of the propeller even at high rotation speeds of propeller 1.

[0070] The sensors include a light intensity sensor 7, and the control unit is configured to activate the lighting elements 5 when the light intensity sensor 7 detects insufficient lighting conditions for camera 6.

[0071] Insufficient lighting conditions for the camera 6 can be defined as a minimum brightness threshold of the underwater environment necessary to capture clear and sharp images, which threshold is known to those skilled in the art.

[0072] Certain quantitative reference values may define insufficient lighting conditions. Illumination below 10 lux corresponds to low light conditions, typical of a twilight or shaded underwater environment, where a camera may begin to lose sharpness and detail. Illumination below 5 lux corresponds to very dark conditions, similar to a nighttime environment or underwater depths with little sunlight penetration. Under these conditions, the camera would have great difficulty functioning properly without artificial lighting. Lighting below 1 lux corresponds to conditions of almost total darkness, in which the camera would not be able to capture useful images without the aid of artificial lighting. The threshold can therefore be identified based on the technical specifications of the camera and the underwater operating conditions (depth, water turbidity, etc.).

[0073] The lighting elements 5 are stroboscopic and have a variable stroboscopic frequency. The control unit is configured to synchronize the emission frequency of the lighting elements 5 with the rotation frequency of the propeller 1.

[0074] This allows the camera 6 to capture video with a still image of the propeller even at high rotation speeds of the propeller 1 and in conditions of low or no natural lighting.

[0075] The stroboscopic frequency of the lighting elements 5 and the acquisition frequency of the camera 6 are preferably adjusted to be the same, but it is also possible to have an acquisition frequency of the camera 6 that is double or a multiple of two compared to the stroboscopic frequency.

[0076] The lighting elements 5 are configured to emit blue light.

[0077] The sensors include at least two pressure probes 8 configured to detect the phase and rotation frequency of propeller 1.

[0078] The control unit is connected to the pressure probes 8 and also to the boat's on-board instrumentation and can therefore calculate the rotation frequency of propeller 1 based on both the pressure probe measurements and the engine revolutions.

[0079] The sensors include at least one turbidimeter, which detects water turbidity, providing information on the amount of suspended particles and helping to assess the quality of the underwater environment.

[0080] There is also at least one thermometer, which monitors water temperature, an important parameter for identifying conditions that may affect cavitation or the operational performance of the boat 2.

[0081] The system also includes at least one salinity meter, which is useful for determining the concentration of salts in the water.

[0082] The sensors also include at least one accelerometer, which detects and records vibrations in the submerged parts and the entire vessel 2, helping to diagnose problems such as imbalances or mechanical damage.

[0083] Finally, there is at least one hydrophone, which captures underwater sounds, useful for detecting cavitation thanks to the noises produced by bubbles or for monitoring engine noise, also with a view to protecting sound-sensitive marine fauna.

[0084] Thanks to the electrical connection of the monitoring module 3 to the interior of the hull 20, the system can operate in three different modes.

[0085] In the first operating mode, monitoring module 3 is simply connected to the control panel of the boat 2 to allow the data collected by the sensors to be viewed and / or processed in real time.

[0086] The various sensors in monitoring module 3 continuously collect video and information on critical parameters such as water temperature, turbidity, vibrations, and underwater noise. This data is transmitted in real time to the control panel, where it is displayed on dedicated screens or panels.

[0087] The crew can then constantly monitor the status of propeller 1, water conditions such as temperature and turbidity, and the overall efficiency of the propeller, detecting phenomena such as cavitation through pressure readings, vibrations, or sounds picked up by the hydrophone, as well as the stability conditions of boat 2, thanks to data from the accelerometers.

[0088] Real-time visualization allows operators to observe the operating conditions of vessel 2, manually intervening on the controls (e.g., adjusting propeller speed or changing the ship's trim) when they identify critical or potentially harmful conditions, such as cavitation or abnormal vibrations.

[0089] Furthermore, in some implementations, the module can not only display data but also process it: the system provides graphs, predictive analyses, or visual suggestions based on basic algorithms. These tools help the crew take informed operational decisions based on concrete and continuously updated data.

[0090] In a second operating mode, the control unit is also configured to execute artificial intelligence algorithms to analyze the data collected by the sensors and provide operational suggestions to the vessel's crew to reduce or eliminate cavitation for propeller 1.

[0091] In this scenario, the automation system not only collects data but, thanks to algorithms that use artificial intelligence, processes it autonomously to provide operational suggestions to the crew, with the aim of reducing or eliminating cavitation.

[0092] The data collected by the sensors is transmitted in real time to the control unit, which applies artificial intelligence algorithms to analyze the flow of information. The Al is trained to recognize specific patterns and data that indicate the presence of cavitation or other operational problems. For example, the trails of bubbles displayed around propeller 1 and their size can provide quantitative data on cavitation, which can be analyzed automatically. Similarly, an increase in vibrations can be linked to the onset of cavitation, just as an increase in underwater noise picked up by the hydrophone could indicate intense cavitation.

[0093] Once the data has been processed, artificial intelligence provides operational suggestions that are visible on the control panel interface. These suggestions may include specific actions such as reducing propeller speed to avoid entering a critical cavitation regime, increasing the angle of the stabilizing fins to improve boat stability and reduce water resistance, modifying the boat's trim to improve water flow around the propeller and prevent cavitation bubbles from forming, or other similar actions.

[0094] Operators on board receive these suggestions through a clear and intuitive display on the bridge and can decide to apply the suggestions proposed by the Al or manually adjust the operating parameters of the boat. In this way, the Al acts as a decision support system, assisting the crew in optimizing operating conditions and preventing cavitation.

[0095] In a third operating mode, the control unit is configured to automatically implement operational changes to the control systems of vessel 2 in order to reduce or eliminate cavitation for propeller 1, based on the analysis of data collected by sensors and processed by artificial intelligence algorithms.

[0096] The control unit, based on vibration, pressure, and acoustic noise data collected by sensors and analyzed by artificial intelligence algorithms, can automatically vary the rotation speed of propeller 1. When cavitation is detected, the algorithm identifies an optimal rotation speed to prevent the formation of cavitation bubbles and varies the speed of propeller 1 to prevent damage and improve propulsion efficiency.

[0097] If cavitation is detected near the stabilizing fins, the control unit can intervene by automatically changing the angle of incidence of the fins to optimize the flow of water around these parts. The goal is to reduce turbulence that can contribute to cavitation and improve the stability of the boat 2 in the water, without requiring manual intervention.

[0098] The Al algorithm can analyze the power delivered by the engine in relation to the speed of the boat and the surrounding water conditions. In the event of persistent cavitation, the control unit can automatically vary the power supply to the engine, decreasing the load on the propeller. This adjustment modifies the overall speed of the boat to eliminate cavitation while maintaining operational efficiency.

[0099] In response to cavitation data from multiple sensors, the control unit can automatically adjust the boat's trim 2 by varying the weight distribution or changing the tilt using stabilizers and balancing systems. Improved trim optimizes the water flow around the propeller 1 and other submerged parts, reducing the likelihood of cavitation.

[0100] When cavitation phenomena are detected near the rudder or propeller 1, the control unit can act on the rudder orientation to optimize water flow. By slightly changing the angle of the rudder, the system can alter the direction of water flow around propeller 1, reducing turbulence and thus the risk of cavitation. This improves both maneuverability and propulsion efficiency.

[0101] When the thermometer detects an increase in water temperature, the control unit can automatically adjust the propeller speed or engine power. At higher temperatures, the risk of cavitation increases as the vapor pressure of the water approaches the operating pressure of propeller 1. The artificial intelligence algorithm can identify such conditions and reduce propeller speed to maintain optimal balance, preventing cavitation from forming.

[0102] When the turbidimeter detects high water turbidity, which may indicate the presence of suspended particles or sediment, the control unit can automatically reduce propeller speed or alter the ship's trim. High turbidity increases water resistance and can cause accelerated wear on submerged parts, such as the propeller. Reducing operating speed in high turbidity conditions also reduces the risk of cavitation.

[0103] When the hydrophone detects noises characteristic of cavitation, the control unit intervenes by automatically adjusting the operating parameters. If the underwater noise level increases, signaling the implosion of cavitation bubbles, the system can reduce the speed of propeller 1 or adjust the angle of attack of the propeller blades in the case of a variable pitch propeller to minimize the phenomenon. The use of the hydrophone allows cavitation to be detected even in situations where it is not visually detectable.

[0104] When the salinity meter detects high levels of water salinity, the control unit can reduce the propeller speed or adjust other parameters to limit wear on the submerged parts. High salinity water can affect propeller behavior in terms of cavitation. The Al algorithm takes this data into account to optimize the operation of vessel 2, protecting propeller 1 from accelerated wear.

[0105] The accelerometer can detect abnormal vibrations in submerged parts, such as propeller 1, which may indicate the onset of cavitation or mechanical problems. In response to these vibrations, the control unit can automatically adjust operating parameters, such as propeller speed, to reduce instability and limit cavitation.

Claims

1. Continuous monitoring system for cavitation phenomena for at least one submerged part (1) of a boat (2), comprising a continuous underwater monitoring module (3), characterized by the fact that the monitoring module (3) is permanently coupled to the hull (20) of the boat (2) near the said submerged part (1) and consists of a watertight case (4) equipped with one or more sensors and one or more lighting elements (5), said sensors comprising at least one camera (6) and at least one light intensity sensor (7), a control unit being provided which is configured to activate said lighting elements (5) when said light intensity sensor (7) detects lighting conditions that are insufficient for said camera (6).

2. System according to claim 1, wherein the submerged part is a propeller (1) and the acquisition frequency of the camera (6) is variable, the control unit being configured to synchronize the acquisition frequency of the camera (6) with the rotation frequency of the propeller (1).

3. System according to claim 1 or 2, wherein the submerged part is a propeller (1) and the lighting elements (5) are stroboscopic and have a variable stroboscopic frequency, the control unit being configured to synchronize the emission frequency of the lighting elements (5) with the rotation frequency of the propeller (1).

4. System according to one or more of the previous claims, wherein the camera (6) has a field of view greater than 60°, preferably 80°, and can be oriented by rotation around two axes perpendicular to each other.

5. System according to one or more of the previous claims, wherein the lighting elements (5) are configured to emit blue light.

6. System according to one or more of the preceding claims, wherein the submerged part is a propeller (1) and said sensors comprise at least two pressure probes (8) configured to detect the phase and frequency of rotation of the propeller (1).

7. System according to one or more of the preceding claims, wherein said sensors comprise at least one turbidimeter and / or at least one thermometer, and / or at least one salinity meter and / or at least one accelerometer and / or at least one hydrophone.

8. System according to one or more of the preceding claims, wherein the monitoring module (3) is connected to a control panel of the vessel (2) to allow the display and / or processing of the data detected by said sensors in real time.

9. System according to one or more of the preceding claims, wherein the control unit is configured to execute artificial intelligence algorithms to analyze the data detected by said sensors and provide operational suggestions to the vessel's crew to reduce or eliminate the phenomenon of cavitation for said submerged part (1).

10. System according to claim 9, wherein the control unit is configured to automatically implement operational changes to the boat's control systems in order to reduce or eliminate cavitation for said submerged part (1), based on the analysis of the data collected by said sensors performed by said artificial intelligence algorithms.

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