CN111061705A - Effective data cleaning method, device, medium and terminal equipment - Google Patents
Effective data cleaning method, device, medium and terminal equipment Download PDFInfo
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Abstract
The invention discloses an effective data cleaning method, which comprises the following steps: acquiring operation data of a ship equipment system in real time according to a preset acquisition frequency; respectively carrying out differential comparison calculation on the operation data to obtain a fluctuation differential amplitude value, collecting the data of which the fluctuation differential amplitude value is not larger than a preset value to obtain a first data set, and carrying out set switching on the data of which the fluctuation differential amplitude value is larger than the preset value to obtain a second data set; performing invalid data cleaning processing on data of conventional start-stop transition or system switching action generated by the system when the data in the second data set is judged to be generated; storing the data after data cleaning and the data of the first data set; according to the method, the normal continuous data in the real-time data are merged by calculating the fluctuation difference amplitude value of the operation data, and the reasonable process data are cleaned, so that the storage quality of the ship data is improved, and the use efficiency of the intelligent ship data in operation is improved.
Description
Technical Field
The invention relates to the field of big data processing, in particular to an effective data cleaning method, device, medium and terminal equipment.
Background
At present, ship operation data need to be acquired in the ship operation process so as to record the ship condition in real time and ensure the operation safety of the ship. The acquisition and storage of the ship operation data are usually acquired and stored in real time, because the number of ship equipment and systems is large, the number of signal acquisition points is large, and the storage data in the database is massive data along with the passage of time, which causes difficulty in query, calling and analysis. Aiming at the requirements of data storage, transmission, analysis and tracking of the future intelligent ship, the light weight and effectiveness of ship system data always restrict the efficiency of data analysis and transmission of the intelligent ship. In order to improve the use efficiency of ship data, reducing data capacity and improving data quality become the core technical key points of ship data processing.
Therefore, the traditional ship operation data processing method directly stores the data in an overlapping manner, so that data redundancy is caused, subsequent extraction and analysis of the data are influenced, and the working efficiency is reduced.
Disclosure of Invention
The invention provides an effective data cleaning method, an effective data cleaning device, an effective data cleaning medium and a terminal device.
In order to solve the above technical problem, an embodiment of the present invention provides an effective data cleaning method, including:
acquiring operation data of a ship equipment system in real time according to a preset acquisition frequency;
respectively carrying out differential comparison calculation on the operation data to obtain a fluctuation differential amplitude value, collecting data of which the fluctuation differential amplitude value is not more than a preset value in the operation data to obtain a first data set, and collecting data of which the fluctuation differential amplitude value is more than the preset value in the operation data to obtain a second data set;
judging whether the system generates transition actions such as conventional start-stop or switching actions when the data in the second data set are generated, and performing invalid data cleaning processing on normal fluctuation data generated when the second data set belongs to the conventional start-stop or switching actions of the system;
and storing the data of the second data set and the data of the first data set after data cleaning.
Preferably, the data acquisition and storage is performed once in a frequency of 15 seconds to 5 minutes; the frequency of the invalid data cleaning treatment is executed once within 6 to 8 hours; the preset value is 5%.
Preferably, the normal switching action comprises a start-stop switching action or a plate cooler backwashing action.
Preferably, after the obtaining the first data set, the method further includes: counting the fluctuation difference amplitude values of the data in the first data set, calculating an average value, and taking the average value as a mark value in the time period;
the calculation formula of the fluctuation difference amplitude value is as follows:
wherein D ist1Is an operational data value; dt0The sign value of the collected data in the last period of time or the initial set value of the system, and △ the fluctuation difference amplitude value of the operation data.
The embodiment of the invention provides an effective data cleaning device, which comprises:
the data acquisition unit is used for acquiring the operation data of the ship equipment system in real time according to a preset acquisition frequency;
the data comparison unit is used for respectively carrying out differential comparison calculation on the operating data to obtain a fluctuation differential amplitude value, collecting data of which the fluctuation differential amplitude value is not more than a preset value in the operating data to obtain a first data set, and collecting data of which the fluctuation differential amplitude value is more than the preset value in the operating data to obtain a second data set;
the data filtering unit is used for judging whether the system generates a conventional switching action when the data in the second data set are generated, and cleaning invalid data of the data generated when the system generates the conventional switching action in the second data set;
and the data storage unit is used for storing the data of the second data set and the data of the first data set after data cleaning.
Preferably, the data acquisition and storage is performed once in a frequency of 15 seconds to 5 minutes; the frequency of the invalid data cleaning treatment is executed once within 6 to 8 hours; the preset value is 5%.
Preferably, the start-stop or switching action of the conventional system equipment comprises the conventional actions of equipment in the system, such as start-stop switching action or plate cooler backwashing action.
Preferably, the data comparison unit is further configured to: after the first data set is obtained, counting fluctuation difference amplitude values of data in the first data set and calculating an average value, wherein the average value is used as a mark value in the time period;
the calculation formula of the fluctuation difference amplitude value is as follows:
wherein D ist1Is an operational data value; dt0The sign value of the collected data in the last period of time or the initial set value of the system, and △ the fluctuation difference amplitude value of the operation data.
An embodiment of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium includes a stored computer program; wherein the computer program, when executed, controls an apparatus in which the computer-readable storage medium is located to perform the efficient data cleansing method as defined in any one of the above.
An embodiment of the present invention further provides a terminal device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, where the processor implements the effective data cleansing method according to any one of the above items when executing the computer program.
Compared with the prior art, the embodiment of the invention has the following beneficial effects:
according to the method, the conventional continuous data in the real-time data are merged by calculating the fluctuation difference amplitude value of the operation data, and the reasonable process data are cleaned at the same time, so that the problems of large data acquisition and storage capacity of the existing ship are solved, the ship data storage quality is improved, and the use efficiency of the intelligent ship data in operation is improved.
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FIG. 1: the invention is a flow chart of steps of an effective data cleaning method;
FIG. 2: the structure of the effective data cleaning device is shown schematically.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, a preferred embodiment of the present invention provides an effective data cleaning method, including:
s1, acquiring the operation data of the ship equipment system in real time according to a preset acquisition frequency; the operation data comprises seawater pump pressure discharge data, seawater pump suction port vacuum pressure data, pump motor working current data, plate cold inlet seawater temperature data, plate cold outlet seawater temperature data and the like. In this embodiment, the data acquisition and storage is performed once in a frequency of 15 seconds to 5 minutes.
It should be noted that the acquisition of the operation data may be performed by periodically acquiring and recording the working data of each system sensor of the ship through the signal acquisition module, and the data acquisition means is only one implementation manner in this embodiment and is not used to limit this technical solution.
S2, respectively carrying out differential comparison calculation on the operation data to obtain fluctuation differential amplitude values, collecting data of which the fluctuation differential amplitude values are not larger than a preset value in the operation data to obtain a first data set, carrying out statistics on the fluctuation differential amplitude values of the data in the first data set and calculating an average value, and taking the average value as a mark value in the time period; collecting data with the amplitude value of the fluctuation difference larger than a preset value in the running data to obtain a second data set; in the present embodiment, the preset value is 5%.
Wherein, the calculation formula of the fluctuation difference amplitude value is as follows:
wherein D ist1Is an operational data value; dt0The sign value of the collected data in the last period of time or the initial set value of the system, and △ the fluctuation difference amplitude value of the operation data.
S3, judging whether the system generates transition actions such as conventional start-stop or switching actions when the data in the second data set are generated, and performing invalid data cleaning processing on normal fluctuation data generated when the second data set belongs to the system generating the conventional start-stop or switching actions; the frequency of the invalid data cleaning treatment is executed once within 6 to 8 hours; in this embodiment, the normal switching action includes a start-stop switching action or a stave cooler backwash action.
And S4, storing the data of the second data set and the data of the first data set after data cleaning.
The process of the present invention will be described in detail with reference to specific examples.
Taking the operation data of the marine seawater cooling system as an example,
the method comprises the following steps: the working data of each system sensor of the ship is regularly collected and recorded through a signal collection module to obtain the operation data of the seawater cooling system of the ship; wherein, the data acquisition point contains: the pressure of a seawater pump is discharged, the vacuum pressure of a suction port of the seawater pump, the working current of a pump motor, the temperature of seawater at a plate cold inlet, the temperature of seawater at a plate cold outlet and the like, and the data acquisition and storage frequency is once in 15 seconds to 5 minutes.
Receiving the collected data, wherein under a normal working condition, the fluctuation amplitude △ of the data collected at each point of the system is not higher than 5%, and the data comparison unit takes the average value of the values of the fluctuation amplitude △ of the measured data in continuous time which is less than 5% as the mark value in the time period, wherein the calculation formula of the fluctuation difference amplitude value is as follows:
wherein D ist1Is an operational data value; dt0The sign value of the collected data in the last period of time or the initial set value of the system, and △ the fluctuation difference amplitude value of the operation data.
Step three: acquiring data with the data change amplitude exceeding 5%, checking whether the seawater pump has system conventional switching actions such as start-stop switching action, plate cooler backwashing action and the like through time interlocking, if the actions exist, part of measured data is influenced, cleaning and filtering the relevant influenced measured data, and if the actions do not exist, keeping the relevant data; wherein, the cleaning time period is generally set as 6-8 hours as a conventional time period, and according to the 5-minute acquisition frequency as an example, the reduction of the conventional working condition data of 6 hours is 1/72, which is about 1.5%.
Step four: and storing the data after cleaning and the data with the data change amplitude not exceeding 5%.
The invention provides an effective data cleaning method for ship big data, which is characterized in that conventional continuous data in real-time data are combined by establishing a data cleaning model with data similarity and reasonable transition, and reasonable process data are cleaned at the same time, so that the problems of large storage capacity and acquisition of the existing ship data are solved, the ship data storage quality is improved, and the use efficiency of intelligent ship data in operation is improved.
Referring to fig. 2, an embodiment of the present invention provides an effective data cleaning apparatus, including:
the data acquisition unit is used for acquiring the operation data of the ship equipment system in real time according to a preset acquisition frequency; the frequency of the data acquisition and storage is performed once in 15 seconds to 5 minutes;
the data comparison unit is used for respectively carrying out differential comparison calculation on the operating data to obtain a fluctuation differential amplitude value, collecting data of which the fluctuation differential amplitude value is not more than a preset value in the operating data to obtain a first data set, and collecting data of which the fluctuation differential amplitude value is more than the preset value in the operating data to obtain a second data set; the preset value is 5%. In this embodiment, the data comparing unit is further configured to: after the first data set is obtained, counting fluctuation difference amplitude values of data in the first data set and calculating an average value, wherein the average value is used as a mark value in the time period;
the calculation formula of the fluctuation difference amplitude value is as follows:
wherein D ist1Is an operational data value; dt0The sign value of the collected data in the last period of time or the initial set value of the system, and △ the fluctuation difference amplitude value of the operation data.
The data filtering unit is used for judging whether the system generates a conventional switching action when the data in the second data set are generated, and cleaning invalid data of the data generated when the system generates the conventional switching action in the second data set; the frequency of the invalid data cleaning treatment is executed once within 6 to 8 hours; in this embodiment, the normal switching action includes a start-stop switching action or a stave cooler backwash action.
And the data storage unit is used for storing the data of the second data set and the data of the first data set after data cleaning.
Specifically, the data acquisition unit acquires and preliminarily stores real-time data of the operation of the ship equipment system and submits the real-time data to the data comparison unit; the data comparison unit is used for carrying out differential comparison on homologous continuous data, cleaning invalid data in a continuous time period on the data in a normal fluctuation range, and transmitting representative data in the time period to the operation data storage unit for storage; and the data comparison unit extracts the fluctuation or data jump beyond the normal range and transmits the fluctuation or data jump to the data filtering unit. The data filtering unit is calibrated according to the data time point, judges the process data to clean reasonable fluctuation data in process control, marks the fluctuation data in non-process control and transmits the fluctuation data to the data storage unit for storage.
The data comparison unit and the data filtering unit clean original data in the data acquisition unit through two data discrimination and cleaning methods, the cleaned data are stored in the data storage unit, data fluctuation in the fluctuation difference amplitude △ can be regarded as normal data fluctuation, reasonable data fluctuation in continuous time periods can be replaced by single sample data, a data cleaning function is realized, the data storage unit performs time period calibration storage on the cleaned data, and light weight of the data relative to an original real-time database is realized.
The apparatus of the present invention will be described in detail with reference to specific examples.
Taking the operation data of the marine seawater cooling system as an example, a data acquisition point of a data acquisition unit comprises a seawater pump discharge pressure, a seawater pump suction port vacuum pressure, a pump motor working current, a plate cold inlet seawater temperature, a plate cold outlet seawater temperature and the like, the data acquisition and storage frequency is once in 15 seconds to 5 minutes, the acquired data is transmitted to a data comparison unit, under a normal working condition, the fluctuation amplitude △ of the acquired data of each point of the system is not higher than 5%, the data comparison unit takes an average value of values of the measured data fluctuation amplitude △ which is smaller than 5% in continuous time as a mark value in the time period, a cleaning time period is generally set to be 6-8 hours as a normal time period, according to the 5-minute acquisition frequency as an example, the reduction of the data of the normal working condition of 6 hours is 1/72 and about 1.5%, the cleaned data is transmitted to a data storage unit, the data of which has the data change amplitude of more than 5% is transmitted to a data filtering unit, whether the seawater pump has the plate type switching action, the plate type cooler action and the like is checked by the time interlock start-stop switching action, if the related data is not transmitted to the plate type cooler action, if the related data is not transmitted.
According to the invention, the effective value of the optimized ship data is obtained through the data cleaning unit, and the storage capacity of the ship data is greatly reduced on the premise of not influencing the use of the data, so that the problems of huge storage capacity of the existing ship and the technical problems of transmission and secondary analysis caused by huge primary data quantity are solved, the data transmission efficiency and safety are improved as much as possible, and the operation efficiency of an intelligent ship data system is further ensured.
An embodiment of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium includes a stored computer program; wherein the computer program, when running, controls the device on which the computer-readable storage medium is located to execute the effective data cleaning method according to any one of the above embodiments.
The embodiment of the present invention further provides a terminal device, where the terminal device includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and the processor implements the effective data cleansing method according to any one of the above embodiments when executing the computer program.
Preferably, the computer program may be divided into one or more modules/units (e.g., computer program) that are stored in the memory and executed by the processor to implement the invention. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used for describing the execution process of the computer program in the terminal device.
The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, a discrete hardware component, etc., the general purpose Processor may be a microprocessor, or the Processor may be any conventional Processor, the Processor is a control center of the terminal device, and various interfaces and lines are used to connect various parts of the terminal device.
The memory mainly includes a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required for at least one function, and the like, and the data storage area may store related data and the like. In addition, the memory may be a high speed random access memory, may also be a non-volatile memory, such as a plug-in hard disk, a Smart Memory Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, or may also be other volatile solid state memory devices.
It should be noted that the terminal device may include, but is not limited to, a processor and a memory, and those skilled in the art will understand that the terminal device is only an example and does not constitute a limitation of the terminal device, and may include more or less components, or combine some components, or different components.
The above-mentioned embodiments are provided to further explain the objects, technical solutions and advantages of the present invention in detail, and it should be understood that the above-mentioned embodiments are only examples of the present invention and are not intended to limit the scope of the present invention. It should be understood that any modifications, equivalents, improvements and the like, which come within the spirit and principle of the invention, may occur to those skilled in the art and are intended to be included within the scope of the invention.
Claims (10)
1. A method for efficient data cleansing, comprising:
acquiring operation data of a ship equipment system in real time according to a preset acquisition frequency;
respectively carrying out differential comparison calculation on the operation data to obtain a fluctuation differential amplitude value, collecting data of which the fluctuation differential amplitude value is not more than a preset value in the operation data to obtain a first data set, and collecting data of which the fluctuation differential amplitude value is more than the preset value in the operation data to obtain a second data set;
judging whether the system generates a conventional system start-stop or switching action when the data in the second data set are generated, and performing invalid data cleaning processing on the data generated when the second data set belongs to the system generating the conventional system start-stop or switching action;
and storing the data of the second data set and the data of the first data set after data cleaning.
2. The efficient data cleansing method of claim 1, wherein the data collection and storage is performed once at a frequency of 15 seconds to 5 minutes; the frequency of the invalid data cleaning treatment is executed once within 6 to 8 hours; the preset value is 5%.
3. The active data cleansing method of claim 1, wherein the normal switching action comprises a start-stop switching action or a stave cooler backwash action.
4. The efficient data cleansing method of claim 1, further comprising, after said obtaining the first data set: counting the fluctuation difference amplitude values of the data in the first data set, calculating an average value, and taking the average value as a mark value in the time period;
the calculation formula of the fluctuation difference amplitude value is as follows:
wherein D ist1Is an operational data value; dt0The sign value of the collected data in the last period of time or the initial set value of the system, and △ the fluctuation difference amplitude value of the operation data.
5. A valid data cleansing apparatus, comprising:
the data acquisition unit is used for acquiring the operation data of the ship equipment system in real time according to a preset acquisition frequency;
the data comparison unit is used for respectively carrying out differential comparison calculation on the operating data to obtain a fluctuation differential amplitude value, collecting data of which the fluctuation differential amplitude value is not more than a preset value in the operating data to obtain a first data set, and collecting data of which the fluctuation differential amplitude value is more than the preset value in the operating data to obtain a second data set;
the data filtering unit is used for judging whether the system generates a conventional system start-stop or switching action when the data in the second data set are generated, and carrying out invalid data cleaning treatment on the data generated when the second data set belongs to the system generating the conventional system start-stop or switching action;
and the data storage unit is used for storing the data of the second data set and the data of the first data set after data cleaning.
6. The active data washer according to claim 5, wherein the data collection and storage is performed once at a frequency of 15 seconds to 5 minutes; the frequency of the invalid data cleaning treatment is executed once within 6 to 8 hours; the preset value is 5%.
7. The active data cleansing apparatus of claim 5, wherein the normal switching action comprises a start-stop switching action or a stave cooler backwash action.
8. The active data cleansing apparatus of claim 5, wherein the data comparison unit is further configured to: after the first data set is obtained, counting fluctuation difference amplitude values of data in the first data set and calculating an average value, wherein the average value is used as a mark value in the time period;
the calculation formula of the fluctuation difference amplitude value is as follows:
wherein D ist1Is an operational data value; dt0The sign value of the collected data in the last period of time or the initial set value of the system, and △ the fluctuation difference amplitude value of the operation data.
9. A computer-readable storage medium, characterized in that the computer-readable storage medium comprises a stored computer program; wherein the computer program, when executed, controls an apparatus in which the computer-readable storage medium is located to perform the efficient data cleansing method according to any one of claims 1 to 4.
10. A terminal device comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, the processor implementing the effective data cleansing method according to any one of claims 1 to 4 when executing the computer program.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113535697A (en) * | 2021-07-07 | 2021-10-22 | 广州三叠纪元智能科技有限公司 | Climbing frame data cleaning method, climbing frame control device and storage medium |
| CN114547018A (en) * | 2022-04-24 | 2022-05-27 | 西安热工研究院有限公司 | Method and system for automatically cleaning waste points of SIS real-time database |
| CN116095114A (en) * | 2023-01-11 | 2023-05-09 | 上海船舶运输科学研究所有限公司 | Ship-shore data transmission method based on Internet of things mode |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2018004623A1 (en) * | 2016-06-30 | 2018-01-04 | Intel Corporation | Sensor based data set method and apparatus |
| CN108563158A (en) * | 2018-01-11 | 2018-09-21 | 威海捷诺曼自动化股份有限公司 | Multi-source data acquiring system peculiar to vessel and ships data processing method |
| CN109800483A (en) * | 2018-12-29 | 2019-05-24 | 北京城市网邻信息技术有限公司 | A kind of prediction technique, device, electronic equipment and computer readable storage medium |
-
2019
- 2019-11-05 CN CN201911071843.XA patent/CN111061705B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2018004623A1 (en) * | 2016-06-30 | 2018-01-04 | Intel Corporation | Sensor based data set method and apparatus |
| CN108563158A (en) * | 2018-01-11 | 2018-09-21 | 威海捷诺曼自动化股份有限公司 | Multi-source data acquiring system peculiar to vessel and ships data processing method |
| CN109800483A (en) * | 2018-12-29 | 2019-05-24 | 北京城市网邻信息技术有限公司 | A kind of prediction technique, device, electronic equipment and computer readable storage medium |
Non-Patent Citations (1)
| Title |
|---|
| 尹奇志等: "船舶能效数据清洗方法研究", 《交通信息与安全》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113535697A (en) * | 2021-07-07 | 2021-10-22 | 广州三叠纪元智能科技有限公司 | Climbing frame data cleaning method, climbing frame control device and storage medium |
| CN113535697B (en) * | 2021-07-07 | 2024-05-24 | 广州三叠纪元智能科技有限公司 | Climbing frame data cleaning method, climbing frame control device and storage medium |
| CN114547018A (en) * | 2022-04-24 | 2022-05-27 | 西安热工研究院有限公司 | Method and system for automatically cleaning waste points of SIS real-time database |
| CN116095114A (en) * | 2023-01-11 | 2023-05-09 | 上海船舶运输科学研究所有限公司 | Ship-shore data transmission method based on Internet of things mode |
| CN116095114B (en) * | 2023-01-11 | 2023-11-03 | 上海船舶运输科学研究所有限公司 | Ship-shore data transmission method based on Internet of things mode |
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