CN105389648A - Distinguishing method for steady-state operating condition of atmospheric and vacuum distillation device - Google Patents

Distinguishing method for steady-state operating condition of atmospheric and vacuum distillation device Download PDF

Info

Publication number
CN105389648A
CN105389648A CN201510688319.2A CN201510688319A CN105389648A CN 105389648 A CN105389648 A CN 105389648A CN 201510688319 A CN201510688319 A CN 201510688319A CN 105389648 A CN105389648 A CN 105389648A
Authority
CN
China
Prior art keywords
atmospheric
vacuum distillation
data
distillation unit
window
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN201510688319.2A
Other languages
Chinese (zh)
Inventor
陈夕松
罗凡
张向荣
梅彬
费树岷
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
NANJING RICHISLAND INFORMATION ENGINEERING Co Ltd
Original Assignee
NANJING RICHISLAND INFORMATION ENGINEERING Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by NANJING RICHISLAND INFORMATION ENGINEERING Co Ltd filed Critical NANJING RICHISLAND INFORMATION ENGINEERING Co Ltd
Priority to CN201510688319.2A priority Critical patent/CN105389648A/en
Publication of CN105389648A publication Critical patent/CN105389648A/en
Pending legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/04—Manufacturing
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/30—Computing systems specially adapted for manufacturing

Landscapes

  • Business, Economics & Management (AREA)
  • Human Resources & Organizations (AREA)
  • Engineering & Computer Science (AREA)
  • Economics (AREA)
  • Strategic Management (AREA)
  • General Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • Theoretical Computer Science (AREA)
  • Educational Administration (AREA)
  • Marketing (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Development Economics (AREA)
  • Tourism & Hospitality (AREA)
  • Physics & Mathematics (AREA)
  • Operations Research (AREA)
  • Quality & Reliability (AREA)
  • Game Theory and Decision Science (AREA)
  • Manufacturing & Machinery (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Primary Health Care (AREA)
  • Vaporization, Distillation, Condensation, Sublimation, And Cold Traps (AREA)

Abstract

The invention discloses a distinguishing method for a steady-state operating condition of an atmospheric and vacuum distillation device. The distinguishing method is used for judging whether the atmospheric and vacuum distillation device is in a steady state through performing steady-state analysis on operating parameters of the atmospheric and vacuum distillation device. The criterion is a standard deviation between a monomial coefficient and a fitting offset of a data fitting equation in a current window, and the error distinguishing problem of the conventional statistical method because the measuring error cannot be effectively reduced and the measuring data cannot be effectively utilized is avoided. The distinguishing method can effectively achieve timely judgment of the steady-state operating condition after oil switching especially when the production adjustment occurs frequently and instantaneous fluctuation of the device is large due to processing crude oil switching, and lays a foundation for real-time optimization of the device.

Description

A kind of method of discrimination of atmospheric and vacuum distillation unit steady state condition
Technical field
The present invention relates to a kind of method of discrimination of atmospheric and vacuum distillation unit steady state condition, particularly relate to before atmospheric and vacuum distillation unit carries out real-time optimization, method atmospheric and vacuum distillation unit running status judged by operating parameter.
Background technology
Current petrochemical field generally adopts statistical method and means, as selected the statistics such as average, standard deviation, the coefficient of variation (comprising the extreme difference coefficient of variation, the standard deviation coefficient of variation), and the statistical technique such as histogram, control chart, steady-state analysis is carried out to production run.On the one hand, due to the limitation of sampling, sample information can not be the complete reaction of overall information, adopts the method for stationary window or segmentation statistics, easily causes erroneous judgement.On the other hand, in actual industrial is measured, various measuring error can be produced, parameter fitting is carried out iff the traditional order polynomial of employing, the information of some non-slope variation can be fitted to once in item, the data that cause misjudgment, in the illusion of change, affect stable state and differentiate.
The technology of the present invention, proposes a kind of fitting of a polynomial steady state detecting method for use based on moving window.The method adopts moving window to carry out fitting of a polynomial to the data in current window, and judge stable state and the unstable state of signal according to the size of the polynomial Monomial coefficient after matching, the length of filter window can be determined according to history steady state data self-adaptation.In the process of window sliding, measurement data can repeatedly be utilized, and improves the accuracy that stable state detects.The length of window can be determined according to history steady state data self-adaptation, and compare and rule of thumb determine the size of window, the former is less on the impact of stable state testing result.In addition, adopt quadratic polynomial to carry out matching, while ensureing fitting precision, the data misjudgment that a time fitting of a polynomial causes can be avoided again.
When carrying out stable state to atmospheric and vacuum distillation unit operating mode and judging, and if only if characterizes the processing duty parameter of atmospheric and vacuum distillation unit and is all in stable state, just thinks that atmospheric and vacuum distillation unit is in stable state, the follow-up real-time optimization that can carry out device in this section of time range.
Summary of the invention
The present invention proposes a kind of method of discrimination of atmospheric and vacuum distillation unit steady state condition, and by carrying out steady-state analysis to the operating parameter of atmospheric and vacuum distillation unit, whether comprehensive descision atmospheric and vacuum distillation unit is in stable state.
The stable state determination methods that the present invention proposes comprises the following steps:
1) select the processing duty parameter that can characterize atmospheric and vacuum distillation unit, read history steady state condition data, determine the length H of moving window;
2) with current time T afor benchmark, before history direction, push away 4h, determine the initial time T of data acquisition b: T b=T a-4h take certain hour as the time interval, gathers the processing duty parameter data that can characterize atmospheric and vacuum distillation unit in this section of time range, forms data segment respectively;
3) be that the moving window left end of H is fixed on the current reference position needing the data segment judged by length, to the data (each point (t in window in current window i, x i)) carry out fitting of a polynomial, judge whether the data in current window are in stable state according to stable state judgment rule:
If unstable state, then think current T bto T ain time range, device is in unstable state, terminates to judge;
If stable state, then go to step 4);
4) T is judged bto T awhether the supplemental characteristic in order to stable state judgement in the period is all detected:
If not yet all detected, then moving window to the right, has returned step 3), judge next time;
If all detected, then export initial time and the end time of steady section.
Preferably, step 1) in determine that the step of the length H of moving window is:
101) the length H=2 of initialization moving window, given threshold alpha ∈ (0,1);
102) the initial time T of history steady state condition data is determined 1, be that the moving window left end of H is fixed on T by length 1place, carries out fitting of a polynomial to the data in current window, the standard deviation δ of data in difference evaluator matching front window 1with the standard deviation δ of data in fitting of a polynomial rear hatch 2;
103) Normalized standard deviation δ is calculated h=δ 2/ δ 1, judge δ hwith the size of α:
If δ h≤ α, then go to step 4);
If δ h> α, then H=H+1 returns step 2);
104) current H is the length of required moving window.
α＝0.1。
Preferably, step 2) described in certain hour be 3min.
Preferably, step 3) judgement of middle stable state judgment rule foundation following formula:
|p 1|＜λ
Wherein p 1for step 3) coefficient of the polynomial expression that obtains of matching once item, λ=3 δ/H, δ are the standard deviation of deviation between data after image data and matching before matching, and H is the length of current window.
Preferably, step 3) in, for each point (t in window i, x i) equation that carries out fitting of a polynomial is:
x i = p 0 + p 1 t i + p 2 t i 2
Wherein, t ifor the moment point of data acquisition in current window, and there is t i=i (i=1,2 ..., H), x ifor at moment point t itime the data that collect, p 0, p 1, p 2be respectively the coefficient of polynomial expression zero degree item, once item, quadratic term.
Preferably, step 4) in, each distance h slided judges according to following formula:
Preferably, the described processing duty parameter that can characterize atmospheric and vacuum distillation unit is Chang Yizhong capacity of returns and normal two wires extracted amount.
Beneficial effect:
The present invention proposes a kind of atmospheric and vacuum distillation unit steady state condition method of discrimination, by carrying out steady-state analysis to the operating parameter of atmospheric and vacuum distillation unit, realize the accurate judgement to atmospheric and vacuum distillation unit operating condition state, especially switching at processing crude oil causes production adjustment comparatively frequent, when device momentary fluctuation is larger, effectively can realize the timely judgement of the steady state condition after cutting oil, for device real-time optimization lays the foundation.
Accompanying drawing explanation
Fig. 1 is real-time stable state decision flow chart.
Concrete case study on implementation
Elaborate to embodiments of the invention below, the present embodiment is implemented under premised on technical solution of the present invention, give detailed embodiment and concrete operating process, but protection scope of the present invention is not limited to following embodiment.
For certain enterprise's atmospheric and vacuum distillation unit, this enterprise's atmospheric and vacuum distillation unit has Petrochemical Enterprises typical process, comprises primary tower, atmospheric tower and vacuum distillation tower.Be limited to patent length, at this, Chang Yizhong capacity of returns, normal two wires these two operating parameters of extracted amount analyzed.
1) read history steady state condition data, determine the length H of moving window, in the present embodiment, realized by following 3 steps:
101) the length H=2 of initialization moving window, given threshold alpha ∈ (0,1), in the present embodiment, α=0.1.
102) the initial time T of history steady state condition data is determined 1(2015-05-0100:00) with end time T 2(2015-05-0104:00), the history steady state condition data of Chang Yizhong capacity of returns, normal two wires extracted amount are read, respectively as shown in table 1, table 2:
Table 1 Chang Yizhong capacity of returns history steady state condition data
Table 2 normal two wires extracted amount history steady state condition data
Be that the moving window left end of H=2 is fixed on T by length 1place, carries out fitting of a polynomial to the data in current window, the standard deviation δ of data in difference evaluator matching front window 1with the standard deviation δ of data in fitting of a polynomial rear hatch 2.
103) Normalized standard deviation δ is calculated h=δ 2/ δ 1if, δ h≤ α, then current H is the length of final moving window, otherwise H=H+1, continues to judge.The standard deviation that Chang Yizhong capacity of returns, normal two wires extracted amount obtain under different windows length is respectively as shown in table 3, table 4:
The standard deviation of table 3 Chang Yizhong capacity of returns under different windows length before and after data fitting
The normal standard deviation of two wires extracted amount under different windows length before and after data fitting of table 4
104) according to the Normalized standard deviation δ in table 3, table 4 h, need δ be met h≤ 0.1, then the length of window of Chang Yizhong capacity of returns is chosen to be H=25, and the length of window of normal two wires extracted amount is chosen to be H=37.
2) with current time T a(2015-05-2509:00) be benchmark, before history direction, push away 4h, determine the initial time T of data acquisition b(2015-05-2505:00), be originally be the time interval with 3min in embodiment, gather the supplemental characteristic of the Chang Yizhong capacity of returns of atmospheric and vacuum distillation unit in this section of time range, normal two wires extracted amount, respectively as shown in table 5, table 6:
Table 5 Chang Yizhong capacity of returns real time data
Table 6 normal two wires extracted amount real time data
3) be that the moving window left end of H is fixed on T by length bplace, carries out fitting of a polynomial to the data in current window, and calculates the standard deviation of deviation between measurement data and fitting data in current window.
4) if meet stable state judgment rule, and current T bto T asteady-state Parameters in period has not yet all detected, then the moving window that moves right continues to judge.The polynomial Monomial coefficient p that Chang Yizhong capacity of returns, normal two wires extracted amount matching in each window obtain 1, before matching after image data and matching between data the standard deviation δ of deviation respectively as shown in table 7, table 8:
The Monomial coefficient of table 7 Chang Yizhong capacity of returns polynomial fitting and measured deviation standard deviation
The Monomial coefficient of table 8 normal two wires extracted amount polynomial fitting and measured deviation standard deviation
According to table 7, exist after carrying out fitting of a polynomial at the 4th time | p 1|>=λ=3 δ/H, according to stable state Rule of judgment of the present invention, in this section of time range, this parameter of (2015-05-2505:00 to 2015-05-2509:00) Chang Yizhong capacity of returns is not in stable state.According to table 8, in each window, all have | p 1|≤λ=3 δ/H, according to stable state Rule of judgment of the present invention, in this section of time range, (2015-05-2505:00 to 2015-05-2509:00) normal two wires this parameter of extracted amount is in stable state.Because this parameter of Chang Yizhong capacity of returns is not in stable state, therefore in this section of time range, (2015-05-2505:00 to 2015-05-2509:00) atmospheric and vacuum distillation unit is not in stable state, follow-uply can not carry out real-time optimization, and this judges to terminate.
Although the present invention is illustrated with reference to accompanying drawing and preferred embodiment, for a person skilled in the art, the present invention can have various modifications and variations.Various change of the present invention, change, and equivalent has the content of appending claims to contain.
It is all same as the prior art that the present invention does not relate to technology, maybe can adopt existing techniques in realizing.

Claims (8)

1. a method of discrimination for atmospheric and vacuum distillation unit steady state condition, is characterized in that judging that whether operating mode is the step of stable state and is:
1) select the processing duty parameter that can characterize atmospheric and vacuum distillation unit, read history steady state condition data, determine the length H of moving window;
2) with current time T afor benchmark, before history direction, push away 4h, determine the initial time T of data acquisition b: T b=T a-4h take certain hour as the time interval, gathers the processing duty parameter data that can characterize atmospheric and vacuum distillation unit in this section of time range, forms data segment respectively;
3) be that the moving window left end of H is fixed on the current reference position needing the data segment judged, to each point (t in current window by length i, x i) carry out fitting of a polynomial, judge whether the data in current window are in stable state according to stable state judgment rule: if unstable state, then think current T bto T ain time range, device is in unstable state, terminates to judge; If stable state, then go to step 4);
4) T is judged bto T awhether the supplemental characteristic in order to stable state judgement in the period is all detected:
If not yet all detected, then moving window to the right, has returned step 3), judge next time;
If all detected, then export initial time and the end time of steady section.
2. the method for discrimination of a kind of atmospheric and vacuum distillation unit steady state condition according to claim 1, is characterized in that step 1) in determine that the step of the length H of moving window is:
101) the length H=2 of initialization moving window, given threshold alpha ∈ (0,1);
102) the initial time T of history steady state condition data is determined 1, be that the moving window left end of H is fixed on T by length 1place, carries out fitting of a polynomial to the data in current window, the standard deviation δ of data in difference evaluator matching front window 1with the standard deviation δ of data in fitting of a polynomial rear hatch 2;
103) Normalized standard deviation δ is calculated h=δ 2/ δ 1, judge δ hwith the size of α:
If δ h≤ α, then go to step 4);
If δ h> α, then H=H+1 returns step 2);
104) current H is the length of required moving window.
3. the method for discrimination of a kind of atmospheric and vacuum distillation unit steady state condition according to claim 2, is characterized in that α=0.1.
4. the method for discrimination of a kind of atmospheric and vacuum distillation unit steady state condition according to claim 1, is characterized in that step 2) described in certain hour be 3min.
5. the method for discrimination of a kind of atmospheric and vacuum distillation unit steady state condition according to claim 1, is characterized in that step 3) judgement of middle stable state judgment rule foundation following formula:
|p 1|＜λ
Wherein p 1for step 3) coefficient of the polynomial expression that obtains of matching once item, λ=3 δ/H, δ are the standard deviation of deviation between data after image data and matching before matching, and H is the length of current window.
6. the method for discrimination of a kind of atmospheric and vacuum distillation unit steady state condition according to claim 1, is characterized in that step 3) in, for each point (t in window i, x i) equation that carries out fitting of a polynomial is:
x i = p 0 + p 1 t i + p 2 t i 2
Wherein, t ifor the moment point of data acquisition in current window, and there is t i=i (i=1,2 ..., H), x ifor at moment point t itime the data that collect, p 0, p 1, p 2be respectively the coefficient of polynomial expression zero degree item, once item, quadratic term.
7. the method for discrimination of a kind of atmospheric and vacuum distillation unit steady state condition according to claim 1, is characterized in that step 4) in, the distance h of moving window judges according to following formula to the right at every turn:
8. the method for discrimination of a kind of atmospheric and vacuum distillation unit steady state condition according to claim 1, the processing duty parameter that can characterize atmospheric and vacuum distillation unit described in it is characterized in that is Chang Yizhong capacity of returns and normal two wires extracted amount.
CN201510688319.2A 2015-10-21 2015-10-21 Distinguishing method for steady-state operating condition of atmospheric and vacuum distillation device Pending CN105389648A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201510688319.2A CN105389648A (en) 2015-10-21 2015-10-21 Distinguishing method for steady-state operating condition of atmospheric and vacuum distillation device

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201510688319.2A CN105389648A (en) 2015-10-21 2015-10-21 Distinguishing method for steady-state operating condition of atmospheric and vacuum distillation device

Publications (1)

Publication Number Publication Date
CN105389648A true CN105389648A (en) 2016-03-09

Family

ID=55421913

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201510688319.2A Pending CN105389648A (en) 2015-10-21 2015-10-21 Distinguishing method for steady-state operating condition of atmospheric and vacuum distillation device

Country Status (1)

Country Link
CN (1) CN105389648A (en)

Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106124448A (en) * 2016-06-12 2016-11-16 南京富岛信息工程有限公司 A kind of atmospheric and vacuum distillation unit feed properties Forecasting Methodology under crude oil switching state
CN106933211A (en) * 2017-04-18 2017-07-07 中南大学 It is a kind of to recognize the industrial process dynamically interval method and apparatus of adjustment
CN106997391A (en) * 2017-04-10 2017-08-01 华北电力大学（保定） A kind of method of steady state condition data in quick screening large scale process data
CN107390661A (en) * 2017-08-28 2017-11-24 南京富岛信息工程有限公司 A kind of method for early warning of process flow industry process abnormal state
CN110261693A (en) * 2019-04-16 2019-09-20 南京华盾电力信息安全测评有限公司 A kind of online thermal test method and system based on stable state sampling technique
CN111047732A (en) * 2019-12-16 2020-04-21 青岛海信网络科技股份有限公司 Equipment abnormity diagnosis method and device based on energy consumption model and data interaction
CN111503810A (en) * 2019-01-30 2020-08-07 青岛海信网络科技股份有限公司 Alarming method, device and terminal based on refrigerating unit performance alarming curved surface

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103838216A (en) * 2014-03-07 2014-06-04 华北电力大学（保定） Power station boiler combustion optimization method based on data driven case matching
CN104977847A (en) * 2015-07-01 2015-10-14 南京富岛信息工程有限公司 Stable-state condition discrimination method facing atmospheric and vacuum optimization

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103838216A (en) * 2014-03-07 2014-06-04 华北电力大学（保定） Power station boiler combustion optimization method based on data driven case matching
CN104977847A (en) * 2015-07-01 2015-10-14 南京富岛信息工程有限公司 Stable-state condition discrimination method facing atmospheric and vacuum optimization

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
余黎黎: "基于实时运行数据的稳态在线优化系统研究", 《中国优秀硕士学位论文全文数据库 信息科技辑》 *

Cited By (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106124448A (en) * 2016-06-12 2016-11-16 南京富岛信息工程有限公司 A kind of atmospheric and vacuum distillation unit feed properties Forecasting Methodology under crude oil switching state
CN106124448B (en) * 2016-06-12 2019-02-01 南京富岛信息工程有限公司 A kind of atmospheric and vacuum distillation unit feed properties prediction technique under crude oil switching state
CN106997391A (en) * 2017-04-10 2017-08-01 华北电力大学（保定） A kind of method of steady state condition data in quick screening large scale process data
CN106997391B (en) * 2017-04-10 2020-11-03 华北电力大学（保定） Method for rapidly screening steady-state working condition data in large-scale process data
CN106933211A (en) * 2017-04-18 2017-07-07 中南大学 It is a kind of to recognize the industrial process dynamically interval method and apparatus of adjustment
CN106933211B (en) * 2017-04-18 2019-04-09 中南大学 A kind of method and apparatus that identification industrial process dynamic adjusts section
CN107390661A (en) * 2017-08-28 2017-11-24 南京富岛信息工程有限公司 A kind of method for early warning of process flow industry process abnormal state
CN107390661B (en) * 2017-08-28 2019-05-24 南京富岛信息工程有限公司 A kind of method for early warning of process flow industry process abnormal state
CN111503810A (en) * 2019-01-30 2020-08-07 青岛海信网络科技股份有限公司 Alarming method, device and terminal based on refrigerating unit performance alarming curved surface
CN111503810B (en) * 2019-01-30 2021-07-30 青岛海信网络科技股份有限公司 Alarming method, device and terminal based on refrigerating unit performance alarming curved surface
CN110261693A (en) * 2019-04-16 2019-09-20 南京华盾电力信息安全测评有限公司 A kind of online thermal test method and system based on stable state sampling technique
CN111047732A (en) * 2019-12-16 2020-04-21 青岛海信网络科技股份有限公司 Equipment abnormity diagnosis method and device based on energy consumption model and data interaction

Similar Documents

Publication Publication Date Title
CN105389648A (en) Distinguishing method for steady-state operating condition of atmospheric and vacuum distillation device
CN109239360B (en) Reaction curve abnormity detection method and device
CN108038044B (en) Anomaly detection method for continuous monitored object
CN102944583B (en) Metal-oxide gas sensor array concentration detecting method based on drift compensation
CN109461095A (en) A kind of data processing method and equipment of the load event detection for the identification of non-intrusion type load
CN102789545B (en) Based on the Forecasting Methodology of the turbine engine residual life of degradation model coupling
CN109446189A (en) A kind of technological parameter outlier detection system and method
EP3301586A1 (en) Pre-processor and diagnosis device
CN110008565A (en) A kind of industrial process unusual service condition prediction technique based on operating parameter association analysis
CN104990893A (en) Gasoline octane number detecting method based on similar discriminance
CN103631681A (en) Method for online restoring abnormal data of wind power plant
CN114490156A (en) Time series data abnormity marking method
CN102090705A (en) Method for improving tobacco-drying process capability
CN109813269B (en) On-line calibration data sequence matching method for structure monitoring sensor
CN105334185A (en) Spectrum projection discrimination-based near infrared model maintenance method
CN113127305A (en) Abnormality detection method and apparatus
CN110175353A (en) Elevator operating index trend analysis
CN105375449A (en) Method and system for setting voltage change rate criterion of direct current line travelling wave protection
CN104713730B (en) Method for determining degeneration rate of aircraft engine according to vibration signal
CN117235462B (en) Intelligent fault prediction method for bag type packaging machine based on time sequence data analysis
CN110046651B (en) Pipeline state identification method based on monitoring data multi-attribute feature fusion
CN115186762A (en) Engine abnormity detection method and system based on DTW-KNN algorithm
CN101813494B (en) Method for eliminating interference of sensor and outside thereof
CN110410057B (en) Method and system for detecting polished rod suspension point dead point of pumping well
CN105571558A (en) Compressor blade spanwise waviness quantitative determination method

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
RJ01 Rejection of invention patent application after publication
RJ01 Rejection of invention patent application after publication

Application publication date: 20160309