CN111308015A - Automatic identification method for suspected peak of ship tail gas telemetry data - Google Patents

Automatic identification method for suspected peak of ship tail gas telemetry data Download PDF

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CN111308015A
CN111308015A CN202010040893.8A CN202010040893A CN111308015A CN 111308015 A CN111308015 A CN 111308015A CN 202010040893 A CN202010040893 A CN 202010040893A CN 111308015 A CN111308015 A CN 111308015A
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time
suspected
tail gas
peak
data
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CN111308015B (en
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彭士涛
苏宁
胡健波
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Tianjin Research Institute for Water Transport Engineering MOT
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/0004—Gaseous mixtures, e.g. polluted air
    • G01N33/0009—General constructional details of gas analysers, e.g. portable test equipment
    • G01N33/0062—General constructional details of gas analysers, e.g. portable test equipment concerning the measuring method or the display, e.g. intermittent measurement or digital display
    • G01N33/0067—General constructional details of gas analysers, e.g. portable test equipment concerning the measuring method or the display, e.g. intermittent measurement or digital display by measuring the rate of variation of the concentration
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/0004—Gaseous mixtures, e.g. polluted air
    • G01N33/0009—General constructional details of gas analysers, e.g. portable test equipment
    • G01N33/0027—General constructional details of gas analysers, e.g. portable test equipment concerning the detector
    • G01N33/0036—General constructional details of gas analysers, e.g. portable test equipment concerning the detector specially adapted to detect a particular component
    • G01N33/004—CO or CO2
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/0004—Gaseous mixtures, e.g. polluted air
    • G01N33/0009—General constructional details of gas analysers, e.g. portable test equipment
    • G01N33/0027—General constructional details of gas analysers, e.g. portable test equipment concerning the detector
    • G01N33/0036—General constructional details of gas analysers, e.g. portable test equipment concerning the detector specially adapted to detect a particular component
    • G01N33/0042—SO2 or SO3

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Abstract

The invention discloses a method for automatically identifying suspected wave crests of ship tail gas telemetering data2、CO2Giving out a correlation judgment index by the concentration time-varying correlation, and giving out a comprehensive judgment index by integrating the concentration time-varying correlation and the correlation judgment index for judging the ship tail gas SO2、CO2The suspected peak in the time course of the concentration telemetering data solves the problems of large workload of artificial identification of the suspected peak, inaccurate identification result and no quantitative basis, and can automatically identify the SO2The suspected ship with excessive emission provides basis and support for maritime supervision.

Description

Automatic identification method for suspected peak of ship tail gas telemetry data
Technical Field
The invention relates to the technical field of atmospheric environment protection detection, in particular to an automatic identification method for suspected wave crests of ship tail gas telemetering data.
Background
The sniffing method can pass SO in the ship exhaust2、CO2The concentration effectively calculates the sulfur content in the ship fuel oil, and can be applied to ship fuel oil supervision. At present, monitoring of ship tail gas SO is formed2、CO2The ship tail gas telemeter with concentration is usually arranged on a necessary path for ship navigation and is used for collecting SO in tail gas of passing ships2、 CO2The concentration estimates the sulfur content in the fuel.
However, ship exhaust SO2、CO2The concentration telemetry data time sequence data is large in quantity, background noise changes are complex and random, and suspected peaks of the concentration telemetry data time sequence data have remarkable asynchronization. At present, a data acquisition platform is formed, data needs to be analyzed, judged and calculated manually, and no ship tail gas SO is available at present2、CO2And (4) an automatic identification algorithm of the suspected peak of the telemetry data.
Therefore, the accurate ship tail gas SO is provided2、CO2The suspected peak automatic identification method of the telemetering data is a problem which needs to be solved urgently by technical personnel in the field.
Disclosure of Invention
In view of the above, the invention provides an automatic identification method for suspected peaks of ship tail gas telemetry data, which is used for automatically identifying suspected ships using fuel oil with overproof sulfur content according to the ship tail gas telemetry data and solves the problems that the workload for artificially identifying the suspected peaks is large, the identification result is not accurate and no quantitative basis exists.
In order to achieve the purpose, the invention adopts the following technical scheme:
a method for automatically identifying suspected peak of ship tail gas telemetering data comprises the following steps:
1) obtaining SO in monitoring point location time T2And CO2Data C of concentration with timeS(tk) And CC(tk) Wherein k is 1,2, …, N; t is tkK and delta T are time sequences, delta T is a sampling time interval, and N and T/delta T are data lengths;
2) determining a time scale TpP is the data length corresponding to the time scale; to CS(tk) Noise reduction filtering is carried out according to the following formula to obtain C'S(tj) Wherein j is 1,2, …, N; t is tjJ Δ t is a time sequence,
Figure BDA0002367715500000021
wherein m is 1,2, …, and N is a discrete sequence;
3) calculating SO2Increment discrimination index DS(tj) The calculation formula is as follows:
Figure BDA0002367715500000022
wherein when DS(tj)<At 0 time, take DS(tj)＝0；
4) Calculating CO2、SO2Correlation determination index RCS(tj) The calculation formula is as follows:
Figure BDA0002367715500000023
wherein, deltajPK ∈ Z | max (1, j-P/2) ≦ k ≦ min (N, j + P/2) }, time tkAt time tjA nearby temporal neighborhood; when R isCS(tj)<When 0, take RCS(tj)＝0；
5) Calculating the comprehensive judgment index I (t)j) The calculation formula is as follows:
Figure BDA0002367715500000024
6) the comprehensive judgment index I (t)j) Exceeds a threshold value I0And the interval exceeds TpMarking the peak time as a suspected peak and marking the time tqiWherein i ═ 1,2, …, Q; q is the number of suspected peaks identified, QiAnd marking the time sequence number corresponding to the moment for the ith suspected peak.
Further, the data length N and the data length P corresponding to the time scale are both even numbers.
By adopting the scheme, the invention has the beneficial effects that:
the invention firstly filters the telemetering data and differentiates the telemetering data to give an increment judgment index, and then combines the increment judgment index with SO2、CO2Giving out a correlation judgment index by the concentration time-varying correlation, and giving out a comprehensive judgment index by integrating the concentration time-varying correlation and the correlation judgment index for judging the shipShip tail gas SO2、CO2Suspect wave crest in the time course of concentration telemetering data, the problem that the workload of artificially identifying the suspect wave crest is large, the identification result is not accurate and the basis is not quantized is solved, the suspect ship with SO2 exceeding the standard for discharge can be automatically identified, and the basis and the support are provided for maritime supervision.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
FIG. 1 is a timing diagram of an incremental decision metric provided by the present invention;
FIG. 2 is a time chart of the correlation determination index provided by the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be described clearly and completely with reference to the accompanying 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.
The embodiment of the invention discloses a method for automatically identifying suspected peak of ship tail gas telemetering data, which comprises the following steps in sequence:
1) obtaining SO in monitoring point location time T2And CO2Data C of concentration with timeS(tk) And CC(tk) Wherein k is 1,2, …, N; t is tkK and delta T are time sequences, delta T is a sampling time interval, and N and T/delta T are data lengths;
2) determining a time scale TpP is the data length corresponding to the time scale;to CS(tk) Noise reduction filtering is carried out according to the following formula to obtain C'S(tj) Wherein j is 1,2, …, N; t is tjJ Δ t is a time sequence,
Figure BDA0002367715500000041
wherein m is 1,2, …, and N is a discrete sequence;
3) calculating SO2Increment discrimination index DS(tj) The calculation formula is as follows:
Figure BDA0002367715500000042
wherein when DS(tj)<At 0 time, take DS(tj)＝0；
4) Calculating CO2、SO2Correlation determination index RCS(tj) The calculation formula is as follows:
Figure BDA0002367715500000043
wherein, deltajPK ∈ Z | max (1, j-P/2) ≦ k ≦ min (N, j + P/2) }, time tkAt time tjA nearby temporal neighborhood; when R isCS(tj)<When 0, take RCS(tj)＝0；
5) Calculating the comprehensive judgment index I (t)j) The calculation formula is as follows:
Figure BDA0002367715500000044
6) the comprehensive judgment index I (t)j) Exceeds a threshold value I0And the interval exceeds TpMarking the peak time as a suspected peak and marking the time tqiWherein i ═ 1,2, …, Q; q is the number of suspected peaks identified, QiAnd marking the time sequence number corresponding to the moment for the ith suspected peak.
The invention firstly aims atThe telemetering data is filtered and differentiated to give an increment discrimination index, and then combined with SO2、CO2Giving out a correlation judgment index by the concentration time-varying correlation, and giving out a comprehensive judgment index by integrating the concentration time-varying correlation and the correlation judgment index for judging the ship tail gas SO2、CO2Suspect wave crest in the time course of concentration telemetering data, the problem that the workload of artificially identifying the suspect wave crest is large, the identification result is not accurate and the basis is not quantized is solved, the suspect ship with SO2 exceeding the standard for discharge can be automatically identified, and the basis and the support are provided for maritime supervision.
Specifically, the data length N and the data length P corresponding to the time scale are both even numbers.
The application case is as follows:
as shown in fig. 1-2, SO in ship tail gas collected by a ship tail gas telemeter of sutong bridge2、CO2And identifying the concentration time course. Δ T ═ 5s, time scale Tp200s, threshold I0Take 0.05.
Firstly, filtering is carried out through the step 2), an increment judgment index is solved through the step 3), a correlation judgment index is solved through the step 4), a comprehensive judgment index is solved through the step 5), and the time of a suspected peak is identified according to the threshold I0.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims (2)

1. A suspected peak automatic identification method of ship tail gas telemetry data is characterized by comprising the following steps:
1) obtaining SO in monitoring point location time T2And CO2Data C of concentration with timeS(tk) And CC(tk) Wherein k is 1,2, …, N; t is tkK and delta T are time sequences, delta T is a sampling time interval, and N and T/delta T are data lengths;
2) determining a time scale TpP is the data length corresponding to the time scale; to CS(tk) Noise reduction filtering is carried out according to the following formula to obtain C'S(tj) Wherein j is 1,2, …, N; t is tjJ Δ t is a time series,
Figure FDA0002367715490000011
wherein m is 1,2, …, and N is a discrete sequence;
3) calculating SO2Increment discrimination index DS(tj) The calculation formula is as follows:
Figure FDA0002367715490000012
wherein when DS(tj)<At 0 time, take DS(tj)＝0；
4) Calculating CO2、SO2Correlation determination index RCS(tj) The calculation formula is as follows:
Figure FDA0002367715490000013
wherein, deltajPK ∈ Z | max (1, j-P/2) ≦ k ≦ min (N, j + P/2) }, time tkAt time tjA nearby temporal neighborhood; when R isCS(tj)<When 0, take RCS(tj)＝0；
5) Calculating the comprehensive judgment index I (t)j) The calculation formula is as follows:
Figure FDA0002367715490000021
6) the comprehensive judgment index I (t)j) Exceeds a threshold value I0And the interval exceeds TpMarking the peak time as a suspected peak, and marking the time tqiWherein i ═ 1,2, …, Q; q is the number of suspected peaks identified, QiAnd marking the time sequence number corresponding to the moment for the ith suspected peak.
2. The method for automatically identifying the suspected peak of the ship tail gas telemetry data according to claim 1, wherein the data length N and the data length P corresponding to the time scale are both even.
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112763465A (en) * 2020-12-24 2021-05-07 交通运输部天津水运工程科学研究所 Anti-interference sniffing identification method for exceeding sulfur content of marine diesel oil

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CN205593933U (en) * 2015-12-31 2016-09-21 青岛市光电工程技术研究院 Boats and ships sulfur dioxide gaseous emission telemeasuring equipment during whole day
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CN106198428A (en) * 2016-08-04 2016-12-07 青岛市光电工程技术研究院 A kind of portable boats and ships throat discharge waste gas sulfur dioxide detector
CN107589100A (en) * 2017-09-08 2018-01-16 交通运输部天津水运工程科学研究所 A kind of bunker oil sulfur content sniff estimation algorithm

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Publication number Priority date Publication date Assignee Title
CN112763465A (en) * 2020-12-24 2021-05-07 交通运输部天津水运工程科学研究所 Anti-interference sniffing identification method for exceeding sulfur content of marine diesel oil

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