CN-115879233-B - Data-driven pressure equipment facility dynamic risk and health evaluation method

CN115879233BCN 115879233 BCN115879233 BCN 115879233BCN-115879233-B

Abstract

The invention discloses a data-driven pressure equipment facility dynamic risk and health evaluation method, which belongs to the technical field of pressure equipment facility risk evaluation, establishes a data-driven petrochemical equipment facility real-time dynamic risk and health evaluation model, and calculates the current dynamic risk level and health level of the pressure equipment facility in real time, wherein the method comprises the steps of establishing a spheroidization mechanism k model, a graphitization mechanism k model, a high-temperature sulfur/naphthenic acid corrosion mechanism k model and an ammonium bisulfide corrosion mechanism k model, and dynamically correcting the failure possibility by introducing a failure possibility influence coefficient so as to obtain the dynamic risk level. According to the invention, dynamic risk level change is applied, particularly when the risk is changed from low-level risk to high-level risk, the system can automatically give out the influence factors with increased failure probability, so that operators are guided to reduce the running risk of the pressure equipment facility by optimizing the operation process parameters and the like, and the running safety and reliability of the equipment facility are ensured.

Inventors

XU SHUJIAN
QU DINGRONG
HAN LEI
LIU XIZE

Assignees

中国石油化工股份有限公司
中石化安全工程研究院有限公司

Dates

Publication Date: 20260508
Application Date: 20210927

Claims (4)

1. The data-driven pressure equipment facility dynamic risk and health evaluation method is characterized by comprising the following steps of: S1, acquiring failure sensitive characteristic parameter data of pressure equipment facilities in real time, wherein the failure sensitive characteristic parameter data comprise monitoring parameter data corresponding to a spheroidization mechanism, a graphitization mechanism, a high-temperature sulfur/naphthenic acid corrosion mechanism and an ammonium bisulfide corrosion mechanism; S2, calculating a real-time corrosion rate and a real-time service life based on the real-time operation failure sensitive characteristic parameter value and the design failure sensitive characteristic parameter value; S3, calculating a real-time dynamic failure possibility influence factor k, wherein the calculation formula of the real-time dynamic failure possibility influence factor k is as follows: (3) Wherein, the To design the possibility of failure of the petrochemical facility, Representing pressure equipment facility design parameters, i=1, 2., n; To the extent that petrochemical facilities under operating conditions may fail, Representing pressure equipment facility operating parameters, i=1, 2., n; s4, calculating real-time health degree based on the real-time dynamic failure possibility influence factor k; S5, outputting the current health grade of the pressure equipment facility in real time based on the health evaluation criterion; s6, calculating a dynamic failure probability grade based on a real-time dynamic failure probability influence factor k and a static RBI evaluation failure probability discriminant; S7, calculating and outputting a real-time dynamic risk level based on a dynamic RBI risk discrimination matrix constructed by the static RBI failure result level and the dynamic failure probability level; based on the graphitization mechanism, the high-temperature sulfur/naphthenic acid corrosion mechanism, the ammonium bisulfide corrosion mechanism and the monitoring parameter data corresponding to the spheroidization mechanism, the graphitization mechanism is respectively constructed Model, high temperature sulfur/naphthenic acid corrosion mechanism Model, ammonium bisulfide corrosion mechanism Model, spheroidization mechanism A model; the content of the graphitization mechanism k model is as follows: Service life of the product The calculation formula of (2) is as follows: (6) the calculation formula of the real-time dynamic failure possibility influence factor k corresponding to the graphitization mechanism is as follows: (7) Wherein, the The service life is prolonged, t is the working temperature under actual operation, and t 0 is the design temperature; the high temperature sulfur/naphthenic acid corrosion mechanism The contents of the model are: the failure sensitive characteristic parameters of high temperature sulfur/naphthenic acid corrosion are operation temperature, sulfur content of oil products, acid value and gas phase H 2 S content; the corrosion rate fitting formula is: (8) the calculation formula of the real-time dynamic failure possibility influence factor k corresponding to the high-temperature sulfur/naphthenic acid corrosion mechanism is as follows: (9) Wherein, the Is the corrosion rate, t is the working temperature under actual operation, and t 0 is the design temperature; The mechanism of corrosion of ammonium bisulfide The contents of the model are: The sensitive characteristic parameter of the ammonium bisulfide corrosion mechanism is cyanide concentration, the applicable material is carbon steel, the operating condition is that PH is more than 7, the operating temperature is (25-65) DEGC, and the NH 4 HS concentration is more than 2wt%; When the cyanide concentration is more than 20ppm, the corrosion rate model is: (10) the calculation formula of the real-time dynamic failure possibility influence factor k corresponding to the ammonium bisulfide corrosion mechanism is as follows: (11) Wherein, the In order to achieve a corrosion rate, For the cyanide concentration under the actual operating conditions, The cyanide concentration is designed under the condition; the mechanism of spheroidization The contents of the model are: The spheroidizing mechanism parameters are material carbon steel and low alloy steel, wherein the material carbon steel and low alloy steel comprise C-0.5Mo, 1Cr-0.5Mo, 1.25Cr-0.5Mo, 2.25Cr-1Mo and 9Cr-1Mo, and the operating conditions are that the operating temperature is 440-760 ℃; The relation expression of the operation life L of the pressure equipment facility and the temperature t is as follows: (12) the calculation formula of the real-time dynamic failure possibility influence factor k corresponding to the spheroidization mechanism is as follows: (13) Wherein, the Is the service life, t is the working temperature under actual operation, Is the design temperature.
2. The method for evaluating dynamic risk and health of a data-driven pressure equipment facility according to claim 1, wherein the calculation formula of health is: (4) Wherein, the Represents the magnitude of the technological parameters of the real-time dynamic monitoring process, Indicating the size of the likelihood of failure, Representing the real-time dynamic failure possibility influencing factors of the device.
3. The method for evaluating dynamic risk and health degree of a data-driven pressure equipment facility according to claim 2, wherein the health degree evaluation criterion adopts a fuzzy comprehensive membership method to perform statistical analysis and definition, and the health degree is divided into four health states of excellent, good, allowed and disallowed, and the intervals are respectively [1,0.75 ], [0.75,0.5 ], [0.5,0.25 ], [0.25, 0).
4. The method for evaluating the dynamic risk and the health degree of the data-driven pressure equipment facility according to claim 1, wherein the calculation formula of the real-time dynamic risk level is as follows: (5) Wherein, the For real-time dynamic risk of a pressure equipment facility, For the real-time dynamic failure probability influencing factors of the pressure equipment facilities, Is the potential for failure of the pressure equipment infrastructure under operating conditions, As a consequence of failure.

Description

Data-driven pressure equipment facility dynamic risk and health evaluation method Technical Field The invention belongs to the technical field of pressure equipment facility risk evaluation, and particularly relates to a data-driven pressure equipment facility dynamic risk and health evaluation method. Background Currently, the integrity of a pressure equipment facility includes the integrity of management, the integrity of technology. Specifically, the RBI evaluation is carried out on the pressure equipment facilities, so that the checking strategy and the checking content of the pressure equipment facilities are optimized, the equipment operation risk is reduced, the equipment operation safety and reliability are improved, and the equipment risk assessment grade is mainly used for guiding the checking and maintenance of the pressure equipment facilities after the shutdown. However, for daily operation, maintenance and inspection of the pressure equipment facility, the static risk level is irrelevant to the current operating temperature, operating pressure, operating flow, medium composition change and other factors, and the static risk level of RBI evaluation is enhanced and perfected for guiding the daily pressure equipment facility. The risk dynamic calculation of the pressure equipment facilities is the basis for uninterrupted long-term development of risk-based testing (RBI) assessment. The risk of the in-service pressure equipment facility is affected by temperature, pressure, flow and working medium changes, and the risk has obvious dynamic properties, such as changes of processing raw materials, operating process temperature, operating process pressure, operating process medium components and corrosion and protection effects, which can cause the corrosion failure possibility of the pressure equipment facility to change. The prior RBI technology can give quantitative risk and inspection plan, lays the foundation for risk control and management, but parameters adopted by RBI computing equipment risk such as operating pressure, operating temperature, flow rate and medium composition, wall thickness and material of pressure-bearing equipment facilities, material composition and the like are all adopted design values in the evaluation process, so the computed risk is a static value. In the actual running of the equipment, the technical basic parameters related to RBI evaluation are dynamically changed, and if the running risk of the current equipment facility is represented by the RBI static risk, the running risk has a certain deviation from the predictive maintenance and the actual checking working requirements of the equipment facility, so that the daily running operation and maintenance of the pressure-bearing equipment facility are difficult to guide. Disclosure of Invention In order to solve the problems, the invention provides a data-driven pressure equipment facility dynamic risk and health evaluation method, and the equipment risk grade obtained by the evaluation method can be used for guiding daily pressure equipment facility process optimization operation. The technical scheme of the invention is as follows: a data-driven pressure equipment facility dynamic risk and health evaluation method comprises the following steps: S1, acquiring failure sensitive characteristic parameter data of pressure equipment facilities in real time, wherein the failure sensitive characteristic parameter data comprise monitoring parameter data corresponding to a spheroidization mechanism, a graphitization mechanism, a high-temperature sulfur/naphthenic acid corrosion mechanism and an ammonium bisulfide corrosion mechanism; S2, calculating a real-time corrosion rate and a real-time service life based on the real-time operation failure sensitive characteristic parameter value and the design failure sensitive characteristic parameter value; s3, calculating a real-time dynamic failure possibility influence factor k; s4, calculating real-time health degree based on the real-time dynamic failure possibility influence factor k; S5, outputting the current health grade of the pressure equipment facility in real time based on the health evaluation criterion; s6, calculating a dynamic failure probability grade based on a real-time dynamic failure probability influence factor k and a static RBI evaluation failure probability discriminant; s7, calculating and outputting a real-time dynamic risk level based on the dynamic RBI risk discrimination matrix constructed by the static RBI failure result level and the dynamic failure probability level. Preferably, the calculation formula of the real-time dynamic failure probability influencing factor k is as follows: where P f0＝f(α10,α20,α30,…,αn0) is the probability of failure of the petrochemical plant facility under design conditions, α i0 (i=1, 2..n.) represents the pressure equipment facility design parameters, and P f＝f(α1,α2,α3,…,αn) is the probability of failure of the petrochem