CN113478500A - Ship cabin multi-source data collection system based on intelligent inspection robot - Google Patents
Ship cabin multi-source data collection system based on intelligent inspection robot Download PDFInfo
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- CN113478500A CN113478500A CN202110785431.3A CN202110785431A CN113478500A CN 113478500 A CN113478500 A CN 113478500A CN 202110785431 A CN202110785431 A CN 202110785431A CN 113478500 A CN113478500 A CN 113478500A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J11/00—Manipulators not otherwise provided for
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1602—Programme controls characterised by the control system, structure, architecture
- B25J9/161—Hardware, e.g. neural networks, fuzzy logic, interfaces, processor
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1656—Programme controls characterised by programming, planning systems for manipulators
- B25J9/1661—Programme controls characterised by programming, planning systems for manipulators characterised by task planning, object-oriented languages
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Abstract
The invention discloses a ship engine room multi-source data collection system based on an intelligent inspection robot, which utilizes the inspection robot to replace manual inspection and is combined with a traditional sensor and a camera to form the multi-source data collection system, and the functions of accurately collecting engine room data, timely early warning and the like during failure are realized by the technical means of intelligently planning a path, autonomously monitoring a failure point and the like. The invention reduces the labor cost brought by manually collecting data, reduces the frequency of data recording errors by using the robot to autonomously plan the path patrol and autonomously monitor the fault point, and greatly improves the monitoring speed and precision of the fault. The data collected by the fixed sensor and the inspection robot are fused with each other and compared with the preset upper and lower limit values and the average value, and when the data fluctuation is large or the data fluctuation exceeds the upper and lower limit values, an early warning can be sent out to remind workers to detect and maintain the relevant parts of the engine room.
Description
Technical Field
The invention relates to a ship engine room multi-source data collecting system based on an intelligent inspection robot and an operation method, and belongs to the technical field of ship engine rooms in ship and ocean engineering.
Background
Under the industrial background of ship intellectualization, the intelligent engine room technology is rising rapidly, and compared with the traditional engine room, the intelligent engine room can obviously reduce the requirements of manpower and material resources, so that the intelligent engine room has great potential value, and particularly has great research significance on the problems of engine room safety and unmanned engine room. The core problem of engine room intellectualization is that an artificial intelligence technology is applied to an engine room system in a relatively fitting manner, and the deep learning technology is utilized to train and test models without leaving engine room operation data, so that how to collect a large amount of accurate engine room operation data becomes an important premise of ship engine room intellectualization.
The existing ship engine room data collecting system mainly monitors important equipment or areas in an engine room in real time by a sensor and a camera which are fixed at fixed positions, and in most cases, turbine workers are required to carry out routing inspection, so that all-weather real-time monitoring cannot be realized; meanwhile, manual data collection is time-consuming and labor-consuming, and the risk of data recording errors is increased.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention provides a ship cabin multi-source data collection system based on an intelligent inspection robot, so that the functions of cabin fixed equipment parameter monitoring, cabin dynamic information collection, multi-source data fusion and the like are realized, the timeliness and the accuracy of cabin data collection are better ensured, the labor cost is saved, and the risk of mistakenly recording data caused by manual inspection is reduced.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows: a ship engine room multi-source data collection system based on an intelligent inspection robot comprises a fixed position data collection subsystem, a robot inspection subsystem and a data fusion subsystem; the data fusion subsystem is respectively connected with the fixed position data collection subsystem and the robot patrol subsystem through a wireless local area network;
the fixed position data collection subsystem comprises a temperature data collection module, a pressure data collection module, an oil data collection module, a rotating speed data collection module and an engine room vision module;
the robot patrol subsystem comprises a combustible gas concentration detection module, a noise monitoring module and a robot vision module;
the temperature data collection module collects data of the temperature of an engine room exhaust system, the temperature of a lubricating oil system, the temperature of a cooling water system, the temperature of a fuel system and the temperature of a power station and an electric propulsion system by using a temperature sensor and transmits the data to the data fusion subsystem through a wireless local area network;
the pressure data collection module monitors the pressure of a lubricating oil system, the pressure of a cooling water system, the pressure of a fuel system and the pressure of a pressurization system in real time by using a pressure sensor and transmits the pressure to the data fusion subsystem through a wireless local area network;
the oil data collection module monitors the water level of the boiler and the oil level of the heavy oil daily cabinet in real time through a liquid level sensor and transmits the oil level and the oil level to the data fusion subsystem through a wireless local area network;
the rotating speed data collection module monitors the rotating speed of the main machine and the auxiliary machine in real time through a rotating speed sensor and transmits the rotating speed to the data fusion subsystem through a wireless local area network;
the cabin visual module comprises an in-cabin monitoring device, a data transmission device and a control room monitoring screen, wherein the in-cabin monitoring device is distributed in a ship host region, a ship auxiliary engine region, a shafting region, a pipeline region, a lighting device region and a water tank region, and is used for carrying out real-time visual monitoring on all parts of the cabin.
Further, the temperature sensor is selected from a PT100 thermistor sensor.
Further, the pressure sensor is composed of a pressure sensitive element and a signal processing unit.
Further, the liquid level sensor is based on the principle that the measured static pressure of the liquid is proportional to the height of the liquid, an isolation type diffused silicon sensitive element or a ceramic capacitance pressure sensitive sensor is adopted to convert the static pressure into an electric signal, and the electric signal is converted into a standard electric signal for transmission through temperature compensation and linear correction.
Furthermore, the rotating speed sensor is a non-contact magnetoelectric rotating speed monitoring device, and the rotating speed is measured through magnetic pulse signal conversion.
Further, the data fusion subsystem fuses the data obtained by the fixed position data collection subsystem and the robot patrol subsystem, and analyzes and displays the data, and the specific steps are as follows:
a1, real-time monitoring and displaying the operation parameters of the equipment collected by the fixed position data collection subsystem and the robot patrol subsystem, and displaying all cabin parameters according to a certain regular sequence through a list, wherein the cabin parameters comprise parameter serial numbers, monitoring point names, variable names, actual measurement values, units and upper and lower limit values;
and A2, displaying relevant parameters of a host machine, auxiliary machines and other auxiliary systems in the engine room in the form of virtual meters, wherein the relevant parameters comprise the exhaust temperature of the host machine, the outlet temperature of cooling water, the pressure of lubricating oil entering the engine and the relevant pressure and temperature of a generator set.
Further, the robot patrol sub-system realizes the functions of autonomously planning a path, autonomously monitoring a fault point and recording fault data, and the specific method comprises the following steps:
b1, modeling and abstracting the cabin environment into a simple graph model in a graph theory, abstracting all equipment of the cabin into nodes, and abstracting a route between the equipment into edges;
b2, presetting an initial patrol path, wherein the path can traverse all nodes of the equipment to be detected;
b3, if the flammable gas concentration monitoring module and the noise monitoring module monitor abnormal constant values, turning to step B4, otherwise, turning to step B6;
b4, the patrol robot takes reinforcement learning as a basis, and takes combustible gas concentration and noise decibel as excitation to enable the patrol robot to move to an area with high combustible gas concentration or high noise decibel;
b5, recording data of an area with high combustible gas concentration or high noise decibel, photographing, and finally uploading to the data fusion subsystem;
b6, whether all equipment to be detected is traversed; if yes, go to step B8; otherwise go to step B7;
b7, replanning the path under the planning of a heuristic algorithm, and turning to the step B3;
b8, returning to the initial point, and ending the patrol.
Compared with the prior art, the invention has the following beneficial effects:
1. the invention provides a multi-source data collection system which is formed by replacing manual inspection with an inspection robot and combining the inspection robot with a traditional sensor and a camera, and the functions of accurately collecting cabin data, timely early warning and the like during faults are realized by the technical means of intelligently planning paths, autonomously monitoring fault points and the like.
2. According to the invention, data are collected by combining the traditional fixed position sensor with the inspection robot for automatically planning the route, so that the labor cost caused by manually collecting the data is reduced, meanwhile, the frequency of data recording errors is reduced by using the robot to autonomously plan the route inspection and autonomously monitor the fault point, and the monitoring speed and precision of the fault are greatly improved. The data collected by the fixed sensor and the inspection robot are fused with each other and compared with the preset upper and lower limit values and the average value, and when the data fluctuation is large or the data fluctuation exceeds the upper and lower limit values, an early warning can be sent out to remind workers to detect and maintain the relevant parts of the engine room.
Drawings
FIG. 1 is a block diagram of the present invention.
Fig. 2 is a robot patrol flowchart.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the present invention will be further described in detail with reference to the accompanying drawings in the embodiments of the present invention. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As shown in fig. 1-2, a working method of a ship cabin multi-source data collection system based on an intelligent inspection robot specifically includes the following steps:
s1: fixed location data collection phase
The fixed position data acquisition device comprises a temperature sensor, a pressure sensor, a rotating speed sensor, a liquid level sensor, a camera and the like. The device collects temperature, pressure, rotating speed, liquid level and video data from an exhaust system, a lubricating oil system, a cooling water system, a fuel system, a power station and an electric propulsion system, and transmits the data to the data collection subsystem through the wireless local area network.
S2: data collection phase for robot patrol
The data inspection phase of the robot mainly comprises a map building phase, an initial path presetting phase, a fault point automatic monitoring phase and a path re-planning phase. The invention utilizes the known environmental information in the cabin to construct a simple graph model in the map building stage. Abstracting all equipment to be detected as nodes in the graph, and abstracting paths among the equipment to be detected as edges in the graph.
The initial path presetting stage of the invention can be regarded as the problem of randomly generating a path traversing all the equipment to be detected. Since the cabin environment has been abstracted to a simple graph model in the previous stage, traversing all equipment problems to be examined can be abstracted to finding the smallest support tree problem in a simple graph.
In the invention, a reinforcement learning method is utilized in the fault point automatic monitoring stage, so that the robot has the functions of automatically searching and detecting fault points. When the combustible gas sensor and the noise sensor carried by the robot at the current position detect that the concentration of the combustible gas and the noise decibel are close to the set upper limit value and the set lower limit value, a reward and punishment mechanism in reinforcement learning can provide a reward function with a positive value of a value function, the concentration and the noise decibel which are close to the combustible gas at the fault point generally are larger, the robot can be closer and closer to the final fault point, meanwhile, the concentration value and the noise decibel value of the combustible gas at the fault point are recorded by the robot, the fault point is photographed through the carried camera, and then the fault point is transmitted to the data fusion subsystem.
The path re-planning stage of the invention means that the robot takes a fault node as a starting point after reaching the fault node, and re-plans the path by using a heuristic algorithm until all the equipment to be detected is traversed, and if other fault equipment is detected, the process of the previous stage is repeated, and the specific process is shown in fig. 2.
S3: data fusion phase
And the data fusion subsystem integrates and visualizes the data after receiving the data of the fixed position collection subsystem and the robot patrol subsystem, and displays the data on a display screen for workers to check in real time. In the process, the data fusion subsystem also compares the received data value with the preset upper and lower limit values, and the staff is warned when the data value exceeds the preset upper and lower limit values.
The steps S1 and S2 may be performed simultaneously, and the map building, initial path presetting, fault point autonomous monitoring, and path re-planning stages in the step S2 are performed sequentially according to a flowchart.
Claims (7)
1. The utility model provides a marine engine room multisource data collection system based on robot is patrolled and examined to intelligence which characterized in that: the system comprises a fixed position data collection subsystem, a robot patrol subsystem and a data fusion subsystem; the data fusion subsystem is respectively connected with the fixed position data collection subsystem and the robot patrol subsystem through a wireless local area network;
the fixed position data collection subsystem comprises a temperature data collection module, a pressure data collection module, an oil data collection module, a rotating speed data collection module and an engine room vision module;
the robot patrol subsystem comprises a combustible gas concentration detection module, a noise monitoring module and a robot vision module;
the temperature data collection module collects data of the temperature of an engine room exhaust system, the temperature of a lubricating oil system, the temperature of a cooling water system, the temperature of a fuel system and the temperature of a power station and an electric propulsion system by using a temperature sensor and transmits the data to the data fusion subsystem through a wireless local area network;
the pressure data collection module monitors the pressure of a lubricating oil system, the pressure of a cooling water system, the pressure of a fuel system and the pressure of a pressurization system in real time by using a pressure sensor and transmits the pressure to the data fusion subsystem through a wireless local area network;
the oil data collection module monitors the water level of the boiler and the oil level of the heavy oil daily cabinet in real time through a liquid level sensor and transmits the oil level and the oil level to the data fusion subsystem through a wireless local area network;
the rotating speed data collection module monitors the rotating speed of the main machine and the auxiliary machine in real time through a rotating speed sensor and transmits the rotating speed to the data fusion subsystem through a wireless local area network;
the cabin visual module comprises an in-cabin monitoring device, a data transmission device and a control room monitoring screen, wherein the in-cabin monitoring device is distributed in a ship host region, a ship auxiliary engine region, a shafting region, a pipeline region, a lighting device region and a water tank region, and is used for carrying out real-time visual monitoring on all parts of the cabin.
2. The intelligent inspection robot-based marine engine room multi-source data collection system according to claim 1, wherein: the temperature sensor is selected from a PT100 thermistor sensor.
3. The intelligent inspection robot-based marine engine room multi-source data collection system according to claim 1, wherein: the pressure sensor consists of a pressure sensitive element and a signal processing unit.
4. The intelligent inspection robot-based marine engine room multi-source data collection system according to claim 1, wherein: the liquid level sensor is based on the principle that the measured static pressure of liquid is proportional to the height of the liquid, an isolation type diffused silicon sensitive element or a ceramic capacitance pressure sensitive sensor is adopted to convert the static pressure into an electric signal, and the electric signal is converted into a standard electric signal for transmission through temperature compensation and linear correction.
5. The intelligent inspection robot-based marine engine room multi-source data collection system according to claim 1, wherein: the rotating speed sensor is a non-contact magnetoelectric rotating speed monitoring device, and the rotating speed is measured through magnetic pulse signal conversion.
6. The intelligent inspection robot-based marine engine room multi-source data collection system according to claim 1, wherein: the data fusion subsystem fuses data obtained by the fixed position data collection subsystem and the robot patrol subsystem, analyzes and displays the data, and comprises the following specific steps:
a1, real-time monitoring and displaying the operation parameters of the equipment collected by the fixed position data collection subsystem and the robot patrol subsystem, and displaying all cabin parameters according to a certain regular sequence through a list, wherein the cabin parameters comprise parameter serial numbers, monitoring point names, variable names, actual measurement values, units and upper and lower limit values;
and A2, displaying relevant parameters of a host machine, auxiliary machines and other auxiliary systems in the engine room in the form of virtual meters, wherein the relevant parameters comprise the exhaust temperature of the host machine, the outlet temperature of cooling water, the pressure of lubricating oil entering the engine and the relevant pressure and temperature of a generator set.
7. The intelligent inspection robot-based marine engine room multi-source data collection system according to claim 1, wherein: the robot patrol subsystem realizes the functions of independently planning a path, autonomously monitoring a fault point and recording fault data, and the specific method comprises the following steps:
b1, modeling and abstracting the cabin environment into a simple graph model in a graph theory, abstracting all equipment of the cabin into nodes, and abstracting a route between the equipment into edges;
b2, presetting an initial patrol path, wherein the path can traverse all nodes of the equipment to be detected;
b3, if the flammable gas concentration monitoring module and the noise monitoring module monitor abnormal constant values, turning to step B4, otherwise, turning to step B6;
b4, the patrol robot takes reinforcement learning as a basis, and takes combustible gas concentration and noise decibel as excitation to enable the patrol robot to move to an area with high combustible gas concentration or high noise decibel;
b5, recording data of an area with high combustible gas concentration or high noise decibel, photographing, and finally uploading to the data fusion subsystem;
b6, whether all equipment to be detected is traversed; if yes, go to step B8; otherwise go to step B7;
b7, replanning the path under the planning of a heuristic algorithm, and turning to the step B3;
b8, returning to the initial point, and ending the patrol.
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Cited By (3)
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| CN114140994A (en) * | 2021-11-12 | 2022-03-04 | 易站智联科技(广州)有限公司 | Intelligent monitoring method and system for ship |
| CN117841028A (en) * | 2024-03-08 | 2024-04-09 | 安徽国智数据技术有限公司 | Comprehensive pipe gallery inspection robot based on artificial intelligence |
| CN117911196B (en) * | 2024-03-19 | 2024-05-28 | 百脉英华科技有限公司 | Ring main unit full-period operation data supervision system and method based on artificial intelligence |
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