CN114782004A - Method for establishing state risk degree dynamic threshold of production system - Google Patents
Method for establishing state risk degree dynamic threshold of production system Download PDFInfo
- Publication number
- CN114782004A CN114782004A CN202210376750.3A CN202210376750A CN114782004A CN 114782004 A CN114782004 A CN 114782004A CN 202210376750 A CN202210376750 A CN 202210376750A CN 114782004 A CN114782004 A CN 114782004A
- Authority
- CN
- China
- Prior art keywords
- production system
- state
- time
- risk
- dynamic threshold
- 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
Links
- 238000004519 manufacturing process Methods 0.000 title claims abstract description 209
- 238000000034 method Methods 0.000 title claims abstract description 31
- 230000008859 change Effects 0.000 claims abstract description 77
- 230000004044 response Effects 0.000 claims abstract description 64
- 230000000694 effects Effects 0.000 claims abstract description 54
- 238000012545 processing Methods 0.000 claims abstract description 11
- 238000012544 monitoring process Methods 0.000 claims description 23
- 238000004364 calculation method Methods 0.000 claims description 16
- 230000008569 process Effects 0.000 claims description 8
- 238000013519 translation Methods 0.000 claims description 8
- 230000003111 delayed effect Effects 0.000 claims description 6
- BULVZWIRKLYCBC-UHFFFAOYSA-N phorate Chemical compound CCOP(=S)(OCC)SCSCC BULVZWIRKLYCBC-UHFFFAOYSA-N 0.000 claims description 6
- 238000006243 chemical reaction Methods 0.000 claims description 5
- 230000001105 regulatory effect Effects 0.000 claims description 5
- 238000009792 diffusion process Methods 0.000 claims description 4
- 230000007774 longterm Effects 0.000 claims description 3
- 238000010606 normalization Methods 0.000 claims description 3
- 230000009466 transformation Effects 0.000 claims description 3
- 230000002265 prevention Effects 0.000 abstract description 4
- VNWKTOKETHGBQD-UHFFFAOYSA-N methane Chemical compound C VNWKTOKETHGBQD-UHFFFAOYSA-N 0.000 description 28
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 230000002301 combined effect Effects 0.000 description 2
- 238000011156 evaluation Methods 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 2
- 231100000681 Certain safety factor Toxicity 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000002347 injection Methods 0.000 description 1
- 239000007924 injection Substances 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
Images
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
- G06Q10/10—Office automation; Time management
- G06Q10/103—Workflow collaboration or project management
-
- 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
-
- 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
- G06Q50/10—Services
- G06Q50/26—Government or public services
- G06Q50/265—Personal security, identity or safety
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- Entrepreneurship & Innovation (AREA)
- Economics (AREA)
- Educational Administration (AREA)
- Theoretical Computer Science (AREA)
- Marketing (AREA)
- Development Economics (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Computer Security & Cryptography (AREA)
- Data Mining & Analysis (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Game Theory and Decision Science (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention belongs to the field of production system dynamic risk early warning and safety prevention and control, and particularly relates to a method for establishing a state risk degree dynamic threshold of a production system. Comprising the following steps, S100: checking the arrangement structure of the production system, and judging the time domain response type of the production system change, wherein the time domain response type comprises a hysteresis response with a time delay effect, a viscous response with a space delay effect and a hysteresis + viscous combined response with a space-time delay effect; s200: calculating and determining a time lag parameter of the state change of the production system; s300: calculating a dynamic threshold value of the state of the production system according to the time lag parameter; s400: calculating the distance between the state dynamic threshold of the production system and the risk critical value of the state of the production system, and carrying out standardization processing on the distance; s500: and calculating a dynamic threshold value of the state risk degree of the production system according to the distance after the standardization processing.
Description
Technical Field
The invention belongs to the field of production system dynamic risk early warning and safety prevention and control, and particularly relates to a method for establishing a state risk degree dynamic threshold of a production system.
Background
The risk threshold is an important parameter for carrying out dynamic risk evaluation and early warning on the production system, and when the risk evaluation result of the state of the production system is greater than the risk threshold, early warning is immediately carried out and safety regulation measures are implemented. Therefore, the research on the risk threshold of the production system state is developed, scientific and reasonable regulation and control time can be selected for production accident prevention and control, and the method has important significance for guaranteeing production safety.
The setting of the risk threshold in the current safety control research and application of the production system is mostly determined according to experience or experimental test results, and the production safety is guided to a certain extent. However, the setting of the current state risk threshold still has three disadvantages: firstly, a critical value of state risk degree or a product of the critical value and a certain safety factor (less than 1) is basically set as a threshold value of the risk degree, the setting mode ignores the influence of time or space delay time lag aftereffect on safety regulation, often leads to the selection delay of regulation and control time, and even if regulation and control measures are implemented, the risk degree still exceeds the critical value to cause the fault or production accident of a production system; secondly, the risk threshold is mostly set to be the same, however, different production system structures and different types of regulation and control activities have different time lag parameters such as time or space delay time and change rate, the same risk threshold is difficult to cope with different time lag parameter changes, and the problem of time lag aftereffect cannot be solved; thirdly, the risk degree threshold is often set to be a constant related to the distance only, however, the risk degree of the state is not only influenced by the single factor of the distance, but also limited by the change rate and the direction of the state, at different times, the distance between the state and the threshold is different, the regulation and control activities with different intensities are different, the change rates of the states are different, the risk degree threshold set to be the constant is 'invariable and variable', and the coupling influence of the parameters such as the distance, the change rate and the direction of different time states on the risk magnitude is difficult to reflect. Therefore, the existing state risk threshold setting method is difficult to meet the requirement of selecting reasonable regulation and control time, and needs to develop a risk dynamic threshold matched with the change parameters and the time-lag parameters of the state of the production system urgently, so that theoretical and technical support is provided for the dynamic risk early warning and safety prevention and control of the production system.
Disclosure of Invention
The invention provides a method for establishing a state risk degree dynamic threshold of a production system, which aims to solve the problems that the existing risk degree threshold cannot cope with the effect after time lag, the risk degree threshold calculation result is one-sided due to only using distance indexes, and the risk degree threshold set as a constant cannot reflect the influence of regulation and control activities at different moments and different intensities on the risk degree.
The invention adopts the following technical scheme: a method for creating a dynamic threshold of a risk level of a production system state includes the following steps, S100: checking the arrangement structure of the production system, and judging the time domain response type of the production system change, wherein the time domain response type comprises a hysteresis response with a time delay effect, a viscous response with a space delay effect and a hysteresis + viscous combined response with a space-time delay effect; s200: calculating and determining a time lag parameter of the state change of the production system; s300: calculating a dynamic threshold value of the state of the production system according to the time lag parameter; s400: calculating the distance between the state dynamic threshold of the production system and the risk critical value of the state of the production system, and carrying out standardization processing on the distance; s500: and calculating a dynamic threshold value of the state risk degree of the production system according to the distance after the standardization processing.
In the step S100, the process is performed,
s101: and calculating the distance between a station for regulating the production activity state in the production system and a station where the production system state monitoring sensor is located, wherein when the distance is more than 50m, the state change of the production system has a time delay effect, and the time domain response type of the state change of the production system is judged to be a delayed response.
S102: and analyzing the relation between the state change of the production system and the spatial structure of the production system, when the state change of the production system is influenced by the spatial effect of the production system and has a diffusion state, the state change of the production system has a spatial delay effect, and judging that the time domain response type of the state change of the production system is viscous response.
S103: and when the time domain response type of the state change of the production system has both hysteresis response and viscous response, judging that the time domain response type of the state change of the production system is hysteresis + viscous combined response.
In step S200, when the production system is a delayed response: the time lag parameters comprise lag time and a lag rate; when the production system is viscous response: the time lag parameters comprise viscosity increasing time and viscosity increasing speed; when the production system responds for the hysteresis and viscous combination: the time lag parameters include lag time, lag rate, sticky time, and sticky rate.
The specific calculation process is as follows;
s201: continuously recording the status value of the production system monitored by the sensor without changing the production activity
，i=0,1, 2, …, and when the monitored data satisfies equation (1), the time point is recorded as
；
S202: in thatt 0The control increment of the production activity state is given at any moment, and the state value of the production system monitored by the sensor is continuously recorded
，j=i, i+1, i+2, …, when the monitored data satisfies the formula (2), the time point is recorded ast j = t c ；
S203: continuously recording the state of the production system monitored by the sensor, and recording the time point when the monitoring data meets the formula (3)t j = t n+ Stopping monitoring and recording;
s204: using monitoring datat 0Andt c calculating lag time of production system state changeT c ；
Using monitoring datax(t 0) Andx(t c ) And lag timeT c Calculating a hysteresis rate for a change in a state of a production system
；
Using monitoring datat n+ Andt c calculating a stick time for a change in a state of a production systemT n+ ；
Using viscous rise timeT n+ And hysteresis rate
Calculating viscous rate of increase of change of state of production system
；
In step S300, dynamic state threshold
Dynamic threshold of state divided into production systems with hysteresis effect
State dynamic threshold of production system with viscous effect
And state dynamics threshold of production system with hysteresis + viscous combination effect
。
The specific calculation process of step S300 is:
s301: state dynamic threshold for production systems with hysteresis effects
The calculation formula of (c) is:
s302: dynamic threshold of state of production system with viscous effect
The calculation formula of (c) is:
s303: state dynamics threshold for production systems with hysteresis + stick combining effect
The calculation formula of (2) is as follows:
wherein,
in order to be a safety factor,
；ais a critical value of the risk of the production system state when the production system state reachesaWhen the system is in failure or accident.
A specific calculation method of the distance normalization processing in step S400 is,
s401: dynamic state threshold for production systems
Critical value of risk of the state of the production systemaIs a distance of
Statistical data obtained during long-term operation of the production systemhThe distance between the status of the production system in the group data and its threshold is
，h=0, 1, 2, …, rTo, for
Performing translation standard deviation transformation:
S402：
carrying out translation and range conversion;
order to
The distance between the dynamic threshold of the standardized production system state and the critical value of the risk is
，
。
In step S500, a dynamic threshold of risk for the status of the production system
Comprises the following steps:
in the formula,
is the real-time rate of change of the state of the production system;
the real-time change direction of the state of the production system.
Compared with the prior art, the invention has the following beneficial effects:
according to the structural arrangement of the production system and the change rule of the state of the production system after the regulation and control of the state of the production activity, the invention defines three different time domain response types of the state change of the production system and provides a judgment method of each response type.
The dynamic threshold of the state risk degree of the production system simultaneously considers the influence of hysteresis parameters such as the hysteresis time, the hysteresis rate, the viscous increasing time and the viscous increasing rate of the state change of the production system on the threshold setting after the implementation of the regulation and control measures, and can effectively solve the problem of the hysteresis of the regulation and control measures caused by the time lag after-effect due to the structure and the state characteristics of the production system;
according to the method, on the basis of considering the influence of the real-time distance between the state risk and the critical value thereof on the threshold setting, the real-time change rate and the real-time change direction of the state are increased as parameters for creating the risk threshold function, so that the problem that the risk threshold calculation result is one-sidedness due to the fact that only a single index is used is solved, the time-varying threshold can be changed along with the change of the regulation and control activities at different moments and different intensities, and the problem that the constant risk threshold cannot be changed in a 'ten-thousand' manner is solved.
The method organically couples state time-varying parameters such as real-time distance, real-time change rate, real-time direction and the like between the state dynamic threshold value which has influence on the degree of risk and the critical value thereof and state time-varying parameters such as lag time, lag rate, viscous increase time, viscous increase rate and the like, thereby establishing a dynamic threshold function of the state risk of the production system and laying a theoretical and technical foundation for scientifically and reasonably selecting the state regulation and control opportunity of the production system.
Drawings
Fig. 1 is a flowchart of a method for creating a dynamic threshold of risk of a state of a production system according to an embodiment of the present invention.
Detailed Description
The invention is explained in further detail below with reference to the drawings of the specification so that the advantages and features of the invention may be more readily understood by those skilled in the art, and thus the scope of the invention is more clearly and clearly defined.
Referring to fig. 1, a method for creating a state risk dynamic threshold of a production system first determines a time domain response type of a state change of the production system according to an arrangement structure of the production system, and then calculates and determines lag time, a lag rate, a sticky time, a sticky rate and other lag parameters of the state change of the production system by monitoring and recording change data of the state of the production system after the state of production activity is changed. On the basis, a dynamic threshold of the production system state under the influence of the time lag effect and a distance between the dynamic threshold and the state danger critical value are calculated, the distance is subjected to standardization processing, and finally a risk degree dynamic threshold function of the production system state is created, wherein the risk degree dynamic threshold function is composed of a state regulation time lag parameter, a real-time distance between the state dynamic threshold and the critical value, a real-time change rate, a real-time direction and coupling relations among the parameters.
The specific process is as follows:
s100: checking the arrangement structure of the production system, judging the time domain response type of the production system change, wherein the response type can be judged by calculating the distance between a station for regulating the production activity state in the production system and a station where a production system state monitoring sensor is located and analyzing the relation between the production system state change and the production system space attribute. Wherein the time domain response types comprise a hysteresis response with a time delay effect, a viscous response with a space delay effect and a hysteresis + viscous combined response with a space-time delay effect.
In this embodiment, a specific determination method for the time domain response type of the state change of the production system includes:
calculating the distance between a station for regulating the production activity state in the production system and a station where a production system state monitoring sensor is located, wherein when the distance is greater than 50m, the state change of the production system has a time delay effect, and the time domain response type of the state change of the production system is judged to be a delayed response; for example, when the distance between the position of the drain water quantity regulating valve and the position of the flow meter is greater than 50m, then the water flow quantity state change has a time delay effect.
Analyzing the relation between the state change of the production system and the space structure of the production system, when the state change of the production system is influenced by the space effect of the production system and has a diffusion form, the state change of the production system has a space delay effect, and judging that the time domain response type of the state change of the production system is viscous response; for example, the concentration of methane is monitored in a space, and since methane belongs to a gas, the concentration of methane is a result of its diffusion in the space, and therefore, the change in the state of methane concentration has a spatially delayed effect.
And when the time domain response type of the state change of the production system has both hysteresis response and viscous response, judging that the time domain response type of the state change of the production system is hysteresis + viscous combined response. For example, a pipeline with the length larger than 50m is provided, a methane release switch is arranged at one end of the pipeline, methane injection flow regulation and control can be performed, a methane concentration sensor is arranged at the other end of the pipeline, methane concentration monitoring can be performed, the distance between a regulation input end and a concentration monitoring end is larger than 50m, the change of the methane concentration in the pipeline due to the distance effect has a time delay effect, meanwhile, methane is used as gas, the concentration of the methane is a result after the methane is diffused in the pipeline, and the change of the methane concentration state has a space delay effect, so that the change of the methane concentration in the pipeline system has delay response and viscous response.
S200: and calculating and determining a time lag parameter of the state change of the production system. The time lag parameters comprise the lag time and the lag rate of the lag response and the viscous increase time and the viscous increase rate of the viscous response, and the time data and the real-time state data required by calculating each time lag parameter can be obtained by monitoring and recording the change data of the state of the production system after the state of the production activity is changed.
The specific calculation method of each time lag parameter in this embodiment is as follows:
continuously recording the state value of the production system monitored by the sensor under the condition of not changing the production activity state
，i=0,1, 2, …, when the monitored data satisfies formula (1), the time point of this is recorded as
；
In thatt 0The control increment of the production activity state is given at any moment, and the state value of the production system monitored by the sensor is continuously recordedx(t j )，j=i, i+1, i+2, …, when the monitored data satisfies equation (2), the time point is recorded ast j = t c ；
Continuously recording the state of the production system monitored by the sensor, and recording the time point when the monitoring data meets the formula (3)t j = t n+ Stopping monitoring and recording;
using monitoring datat 0Andt c calculating lag time of state change of production systemT c As shown in equation (4):
using monitoring datax(t 0) Andx(t c ) And lag timeT c Calculating a hysteresis rate for a change in a state of a production system
As shown in equation (5):
using monitoring datat n+ Andt c calculating a stick time for a change in a state of a production systemT n+ As shown in equation (6):
using viscous rise timeT n+ And hysteresis rate
Calculating viscous rate of increase of change of state of production system
As shown in equation (7):
s300: calculating a dynamic threshold value of the state of the production system according to the time-lag parameter; including a state dynamics threshold of the production system with hysteresis effects, a state dynamics threshold of the production system with viscous effects, and a state dynamics threshold of the production system with hysteresis + viscous combined effects. The state dynamic threshold with the hysteresis effect can be calculated by using the hysteresis time and the hysteresis rate, the state dynamic threshold with the viscosity effect can be calculated by using the viscosity increasing time and the viscosity increasing rate, and the state dynamic threshold with the hysteresis + viscosity combined effect can be calculated by using the hysteresis time, the hysteresis rate, the viscosity increasing time and the viscosity increasing rate.
Referring to fig. 1, a specific method for calculating the dynamic threshold of the various skew effect production system states in this embodiment is as follows:
when the time domain response type of the production system state change is a hysteresis response, the state dynamic threshold of the production system with hysteresis effect
The formula (8) is shown as follows:
wherein,
in order to ensure the safety factor,
；ais a critical value of the risk of the production system state when the production system state reachesaWhen the system is in failure or accident.
Establishing a state dynamic threshold of the production system with viscous effect when the time domain response type of the production system state change is viscous response
The formula (9) is shown as follows:
establishing a state dynamic threshold of the production system with hysteresis and viscous combination effect when the time domain response type of the state change of the production system is hysteresis and viscous combination response
Is represented by equation (10):
s400: and calculating the distance between the state dynamic threshold of the production system and the risk critical value of the state of the production system, and standardizing the distance. The distance standardization process includes translation, standard deviation conversion and translation and range conversion.
Referring to fig. 1, a specific calculation method of the distance normalization process in the present embodiment is as follows:
order to
Dynamic threshold for state of production system
Critical value of risk related to the state of the production systemaA distance between them, order
Is the first one obtained by statistics in the long-term operation of the production systemhThe distance between the status of the production system and its threshold in the team data,h=0, 1, 2, …, rto, for
The translation and standard deviation transformation is performed as shown in equations (11) and (12):
for is to
The translation and range conversion is performed as shown in formula (13):
order to
Normalizing the distance between the dynamic threshold of the status of the production system after processing and the critical value of the risk thereof
。
S500: and calculating a dynamic threshold value of the state risk degree of the production system according to the distance after the standardization processing.
Referring to FIG. 1, the present embodiment shows a dynamic threshold of risk for the status of the production system
As shown in equation (14).
In the formula,
is the real-time rate of change of the state of the production system;
the real-time change direction of the state of the production system.
The state risk dynamic threshold of the production system is composed of a state regulation time-lag parameter, a real-time distance between the state dynamic threshold and a critical value thereof, a real-time change rate, a real-time direction and a coupling relation among the parameters, and is a time-varying value related to the state regulation time-lag parameter and the state time-varying parameter, so that the problem of regulation measure hysteresis caused by time-lag after-effect caused by the structure and the state characteristics of the production system can be effectively solved, the problem that the constant risk threshold cannot be changed in a ten thousand way due to the change of regulation activities at different moments and different intensities is solved, and a theoretical and technical basis can be laid for scientifically and reasonably selecting the state regulation time of the production system.
Claims (8)
1. A method for creating a state risk degree dynamic threshold value of a production system is characterized by comprising the following steps: comprises the following steps of (a) carrying out,
s100: checking the arrangement structure of the production system, and judging the time domain response type of the production system change, wherein the time domain response type comprises a hysteresis response with a time delay effect, a viscous response with a space delay effect and a hysteresis + viscous combined response with a space-time delay effect;
s200: calculating and determining a time lag parameter of the state change of the production system;
s300: calculating a dynamic threshold value of the state of the production system according to the time lag parameter;
s400: calculating the distance between the state dynamic threshold of the production system and the risk critical value of the state of the production system, and carrying out standardization processing on the distance;
s500: and calculating a dynamic threshold value of the state risk degree of the production system according to the distance after the standardization processing.
2. The method for creating the dynamic threshold of the status and risk of the production system according to claim 1, wherein: in the above-mentioned step S100, the first step,
s101: calculating the distance between a station for regulating the production activity state in the production system and a station where a production system state monitoring sensor is located, wherein when the distance is greater than 50m, the state change of the production system has a time delay effect, and the time domain response type of the state change of the production system is judged to be a delayed response;
s102: analyzing the relation between the state change of the production system and the spatial structure of the production system, when the state change of the production system is influenced by the spatial effect of the production system and has a diffusion state, the state change of the production system has a spatial delay effect, and judging that the time domain response type of the state change of the production system is viscous response;
s103: and when the time domain response type of the state change of the production system has both hysteresis response and viscous response, judging that the time domain response type of the state change of the production system is hysteresis + viscous combined response.
3. The method for creating the dynamic threshold of the status and risk of the production system according to claim 1, wherein: in the above-mentioned step S200,
when the production system is a delayed response: the time lag parameters comprise lag time and a lag rate;
when the production system is viscous response: the time lag parameters comprise viscosity increasing time and viscosity increasing rate;
when the production system responds for the hysteresis and viscous combination: the lag parameters include lag time, lag rate, sticky rise time, and sticky rise rate.
4. The method for creating the dynamic threshold of the status and risk of the production system according to claim 3, wherein: the specific calculation process of the step S200 is as follows;
s201: continuous recording of sensor monitored production system status values without changing the status of production activities
，i=0,1, 2, …, and when the monitored data satisfies equation 1, the time point is recorded as
；
S202: in thatt 0The control increment of the production activity state is given at any moment, and the state value of the production system monitored by the sensor is continuously recorded
，j=i, i+1, i+2, …, when the monitored data satisfies equation 2, the time point is recorded ast j = t c ；
S203: continuously recording the state of the production system monitored by the sensor, and recording the time point when the monitoring data meet the formula 3t j = t n+ Stopping monitoring and recording;
s204: using monitoring datat 0Andt c calculating lag time of production system state changeT c ；
Using monitoring datax(t 0) Andx(t c ) And lag timeT c Calculating a hysteresis rate for a change in a state of a production system
；
Using monitoring datat n+ Andt c calculating a stick time for a change in a state of a production systemT n+ ；
Using viscous rise timeT n+ And hysteresis rate
Calculating viscous rate of increase of change of state of production system
；
5. The method for creating a dynamic threshold for status and risk of production system according to claim 1 or 4, wherein: in the step S300, the dynamic threshold value
Dynamic threshold of state divided into production systems with hysteresis effects
State dynamic threshold of production system with viscous effect
And state dynamics threshold of production system with hysteresis + viscous combination effect
。
6. The method for creating a dynamic threshold for status and risk of production system according to claim 5, wherein: the specific calculation process of step S300 is as follows:
s301: state dynamics threshold for production systems with hysteresis effects
The calculation formula of (c) is:
s302: state dynamics threshold for production systems with viscous effects
The calculation formula of (2) is as follows:
s303: state dynamics threshold for production systems with hysteresis + viscous combined effect
The calculation formula of (c) is:
wherein,
in order to be a safety factor,
；ais a critical value of the risk of the production system state when the production system state reachesaIn time, the system is in failure or accident.
7. The method for creating the dynamic threshold of the status and risk of the production system according to claim 1, wherein: the specific calculation method of the distance normalization processing in step S400 is,
s401: dynamic state threshold for production systems
Critical value of risk related to the state of the production systemaIs a distance of
Statistical data obtained during long-term operation of the production systemhThe distance between the status of the production system in the group data and its threshold is
，h=0, 1, 2, …, rTo, for
And (3) translation standard deviation transformation is carried out:
S402：
carrying out translation and range conversion;
order to
The distance between the dynamic threshold of the standardized production system state and the critical value of the risk is
，
。
8. The method for creating a dynamic threshold for status and risk of production system according to claim 7, wherein: in step S500, a dynamic threshold of the risk level of the production system status
Comprises the following steps:
in the formula,
the real-time rate of change of the state of the production system;
the real-time change direction of the state of the production system.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210376750.3A CN114782004A (en) | 2022-04-12 | 2022-04-12 | Method for establishing state risk degree dynamic threshold of production system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210376750.3A CN114782004A (en) | 2022-04-12 | 2022-04-12 | Method for establishing state risk degree dynamic threshold of production system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114782004A true CN114782004A (en) | 2022-07-22 |
Family
ID=82429712
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210376750.3A Pending CN114782004A (en) | 2022-04-12 | 2022-04-12 | Method for establishing state risk degree dynamic threshold of production system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114782004A (en) |
-
2022
- 2022-04-12 CN CN202210376750.3A patent/CN114782004A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10353407B2 (en) | Demand management system for fluid networks | |
| US20080003095A1 (en) | Systems and Methods for Detecting Undesirable Operation of a Turbine | |
| US20180141534A1 (en) | Device and Method for Forecasting Wear in Brake Linings | |
| CN103971171A (en) | State evaluation method for power transmission equipment | |
| CN101140294A (en) | A method to evaluate a performance of a control valve and a system thereof | |
| CN103942735A (en) | Method for evaluating relay protection states | |
| CN107301570A (en) | Traffic prediction method, abnormal traffic quantity measuring method, device and electronic equipment | |
| CN105612289A (en) | Method of demand management and control of fluid pipe networks | |
| JPH04116419A (en) | Apparatus and method for measuring flow rate using fuzzy inference | |
| CN104318479A (en) | Method for determining critical state and safety allowance during operation of crude oil pipeline | |
| EP4016219A1 (en) | Method for rapid transitioning of polyolefin processes from one product to another | |
| CN114782004A (en) | Method for establishing state risk degree dynamic threshold of production system | |
| CN109193670A (en) | A kind of protective device and method of self-powered circuit | |
| Embiruçu et al. | Continuous soluble ziegler‐natta ethylene polymerizations in reactor trains, 2–estimation of kinetic parameters from industrial data | |
| Godoy et al. | Multivariate statistical monitoring of an industrial SBR process. Soft-sensor for production and rubber quality | |
| KR100486473B1 (en) | Method for managing gas supply system according the travel-rate of regulator | |
| US20170219412A1 (en) | Method and a system for metering flow through a fluid conduit | |
| Zhang et al. | An integrated FDD approach for an intensified HEX/Reactor | |
| Pylvänäinen et al. | Vibration‐based monitoring of gas‐stirring intensity in vacuum tank degassing | |
| CN105973629B (en) | Self-diagnosis method, system and device for uneven water distribution of multi-module unit | |
| CN113063097A (en) | Intelligent control method and device for sensitivity of automatic ball valve induction system | |
| US10578023B2 (en) | Controlling a water bath heater for fuel gas | |
| Minari et al. | Industrial SBR process: Computer simulation study for online estimation of steady‐state variables using neural networks | |
| Shayakhmetova et al. | Mathematical analysis of trend indicators of internet security resources cyber-diagrams dynamics in the Republic of Kazakhstan | |
| JPH03220498A (en) | Surveillance device for plant equipment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |