Intelligent monitoring method for the operating status of the coiler side guide servo valve

Abstract

The present invention discloses an intelligent monitoring method for the operation status of a coiler side guide plate servo valve. The method collects position control signals of the coiler side guide plate servo valve from a coiler operation and maintenance platform, including a servo valve position given signal I REF and position feedback signal I FBK , and the coiler speed data V, the classification indicators are used to monitor the deterioration trend of the coiler side guide servo valve operating status, including the servo valve position feedback signal I FBK The alarm threshold, servo valve zero drift fault coefficient Z and servo valve spool jam fault coefficient C are used to predict the zero drift fault, spool jam fault and side guide position abnormal fault of the coiler side guide servo valve when the classification indicators are abnormal. The coiler side guide failure status is given in real time to guide the operation and equipment management personnel to take countermeasures to support the normal production of the coiler.

Description

Technical Field

[0001] The present invention relates to the field of detection and diagnosis technology, and in particular to an intelligent monitoring method for the operating status of a coiler side guide plate servo valve. Background Art

[0002] The coiler's side guides prevent the strip from straying, align the strip with the rolling line, and guide the strip into the downcoiler. During the strip rolling and coiling process, the coiler's side guides work together to smoothly guide the strip head, which has strayed from the center of the runout roller table, to the coiler's centerline for delivery. They continue to guide and center the strip throughout the coiling process, completing the entire strip coiling process.

[0003] At the same time, the side guides are the main control components for correcting the towering shape of the strip reel. If the side guides move too slowly, resulting in a long edge-finding time, a large tower can form at the head of the reel. This means that the head tower correction effect is poor and the tower shape is likely to exceed the standard. If the side guides move too quickly, they become unstable and form a large overshoot, causing the strip to coil into a tower-shaped coil. This not only affects the appearance quality of the steel coil, but also causes damage during lifting due to uneven cross-sections, and the numbering machine cannot print numbers. This has a negative impact on production and quality, especially when rolling thicker steel grades, where coil misalignment is more likely to occur. Therefore, monitoring the operating status of the coiler's side guides is very important.

[0004] The failure modes of the hydraulic control system of the coiler side guide plate are mainly manifested as servo valve zero drift, servo valve spool jamming and other faults. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide an intelligent monitoring method for the operating status of the coiler side guide servo valve. This method targets the main failure modes of the servo valve of the coiler side guide hydraulic control system, collects corresponding data from the coiler operation and maintenance platform, and uses classification indicators to realize intelligent monitoring of the coiler side guide operating status, real-time warning of the coiler side guide failure status, and guides the remote intelligent operation and maintenance of the coiler side guide.

[0006] To solve the above technical problems, the present invention provides an intelligent monitoring method for the operating status of a coiler side guide plate servo valve, comprising the following steps:

[0007] Step 1: Collect the position signal I of the coiler side guide servo valve REF , Position feedback signal I FBK and the coiler speed data V, and obtain the servo valve position feedback signal I within a period of time from the coiler operation and maintenance platform FBK Historical data is used to train alarm thresholds;

[0008] Step 2: Feedback signal I of servo valve position FBKThe historical data is calculated to obtain the maximum value I max , minimum value I min , mean value A and standard deviation σ;

[0009] Among them, A=[(I FBK (1)+I FBK (2)┈+I FBK (N)] / N (1)

[0010]

[0011] Step 3: Establish servo valve position feedback signal I FBK The alarm threshold is set, and the historical data of coiler speed V<150RPM are filtered out to obtain the data sequence I after data cleaning. FBK '(i)(i=1,2,……,N), calculate the maximum value I according to formula (1) and formula (2) max ', minimum value I min ', mean value A' and standard deviation σ';

[0012] Step 4: Establish servo valve position feedback signal I FBK The alarm thresholds H and L, where H is the upper limit of the normal range of the servo valve position, and L is the lower limit of the normal range of the servo valve position;

[0013] H=1.5×σ'+0.5×(Q3+1.5×W) (3)

[0014] L=1.5×σ'+0.5×(Q1-1.5×W) (4)

[0015] In the formula, Q3=I max '-0.25×(I max '-I min '), Q1=I min '+0.25×(I max '-I min '), W = Q3-Q1;

[0016] When the coiler servo valve position feedback signal I FBK >H or I FBK When <L, it is predicted that the position of the coiler side guide is abnormal;

[0017] Step 5: Establish the zero drift fault coefficient Z of the coiler side guide servo valve, and give the signal I according to the servo valve position. REF and position feedback signal I FBK , calculate the servo valve zero drift failure coefficient Z,

[0018] Z=|(I REF -I FBK )| / IREF ×100% (5)

[0019] Monitor the zero drift fault coefficient Z of the coiler side guide plate servo valve. When 5%≤Z≤15%, predict the zero drift fault of the coiler side guide plate servo valve.

[0020] Step 6: Establish the coiler side guide plate servo valve core jamming fault coefficient C, and give the servo valve position signal I according to the servo valve position. REF and position feedback signal I FBK , calculate the servo valve core blocking failure coefficient C,

[0021] C=[|(I REF -I FBK )| / I REF -0.15]×100% (6)

[0022] Monitor the coiler side guide plate servo valve spool jam fault coefficient C. When C ≥ 0, predict the servo valve spool jam fault.

[0023] Furthermore, the coiler operation and maintenance platform is a coiler DCS system or a rolling line remote control system.

[0024] Since the intelligent monitoring method for the operation status of the coiler side guide plate servo valve of the present invention adopts the above technical solution, that is, the method collects the position control signal of the coiler side guide plate servo valve from the coiler operation and maintenance platform, including the servo valve position given signal I REF and position feedback signal I FBK , and the coiler speed data V, the classification indicators are used to monitor the deterioration trend of the coiler side guide servo valve operating status, including the servo valve position feedback signal I FBK The alarm threshold, servo valve zero drift fault coefficient Z and servo valve spool jam fault coefficient C are used to predict the zero drift fault, spool jam fault and side guide position abnormal fault of the coiler side guide servo valve when the classification indicators are abnormal. The coiler side guide failure status is given in real time to guide the operation and equipment management personnel to take countermeasures to support the normal production of the coiler. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments:

[0026] Figure 1 This is a flowchart of the intelligent monitoring method for the operating status of the coiler side guide plate servo valve of the present invention. DETAILED DESCRIPTION

[0027] Implementation example Figure 1 As shown, the method for intelligently monitoring the operating status of the coiler side guide plate servo valve of the present invention includes the following steps:

[0028] Step 1: Collect the position signal I of the coiler side guide servo valve REF , Position feedback signal I FBK and the coiler speed data V, and obtain the servo valve position feedback signal I within a period of time from the coiler operation and maintenance platform FBK Historical data is used to train alarm thresholds;

[0029] Step 2: Feedback signal I of servo valve position FBK The historical data is calculated to obtain the maximum value I max , minimum value I min , mean value A and standard deviation σ;

[0030] Among them, A=[(I FBK (1)+I FBK (2)┈+I FBK (N)] / N (1)

[0031]

[0032] Step 3: Establish servo valve position feedback signal I FBK The alarm threshold is set, and the historical data of coiler speed V<150RPM are filtered out to obtain the data sequence I after data cleaning. FBK '(i)(i=1,2,……,N), calculate the maximum value I according to formula (1) and formula (2) max ', minimum value I min ', mean value A' and standard deviation σ';

[0033] Step 4: Establish servo valve position feedback signal I FBK The alarm thresholds H and L, where H is the upper limit of the normal range of the servo valve position, and L is the lower limit of the normal range of the servo valve position;

[0034] H=1.5×σ'+0.5×(Q3+1.5×W) (3)

[0035] L=1.5×σ'+0.5×(Q1-1.5×W) (4)

[0036] In the formula, Q3=I max '-0.25×(I max '-I min '), Q1=I min '+0.25×(I max '-I min '), W = Q3-Q1;

[0037] When the coiler servo valve position feedback signal I FBK >H or I FBK When <L, it is predicted that the position of the coiler side guide is abnormal;

[0038] Step 5: Establish the zero drift fault coefficient Z of the coiler side guide servo valve, and give the signal I according to the servo valve position. REF and position feedback signal I FBK , calculate the servo valve zero drift failure coefficient Z,

[0039] Z=|(I REF -I FBK )| / I REF ×100% (5)

[0040] Monitor the zero drift fault coefficient Z of the coiler side guide plate servo valve. When 5%≤Z≤15%, predict the zero drift fault of the coiler side guide plate servo valve.

[0041] Step 6: Establish the coiler side guide plate servo valve core jamming fault coefficient C, and give the servo valve position signal I according to the servo valve position. REF and position feedback signal I FBK , calculate the servo valve core blocking failure coefficient C,

[0042] C=[|(I REF -I FBK )| / I REF -0.15]×100% (6)

[0043] Monitor the coiler side guide plate servo valve spool jam fault coefficient C. When C ≥ 0, predict the servo valve spool jam fault.

[0044] The 3σ rule, based on the normal distribution, assumes that the data follows a normal distribution, but actual data often does not strictly follow a normal distribution. Its criteria for determining outliers are based on the mean and standard deviation of the calculated data batch. However, the mean and standard deviation are extremely resistant, and outliers themselves can have a significant impact on them. Consequently, the number of outliers generated will not exceed 0.7% of the total.

[0045] Therefore, this method uses the historical data already available on the operation and maintenance platform, selects data from a certain time period as training samples, removes abnormal points through data preprocessing, uses the cleaned offline data to establish alarm thresholds for production process data, and deploys the thresholds on the operation and maintenance platform for real-time monitoring to realize the state abnormality judgment of the coiler side guide process data.

[0046] Preferably, the coiler operation and maintenance platform is a coiler DCS system or a rolling line remote control system.

[0047] This method makes up for the current deficiency that the operating status of the coiler side guide servo valve cannot be grasped in real time, solves the problem that the coiler side guide servo valve zero drift, servo valve jamming, and servo valve position abnormality cannot be monitored in real time, and provides an effective basis for grasping the operating status of the coiler side guide servo valve and intelligent operation and maintenance.

[0048] The application of this method can monitor the operating status of the coiler side guide in real time, promptly discover various defects of the coiler side guide servo valve, and ensure the normal operation of the equipment and the coiling quality of the strip.

Claims

1. An intelligent monitoring method for the operating status of a coiler side guide servo valve, characterized in that This method comprises the following steps: Step 1: Collect the position signal I of the coiler side guide servo valve REF , Position feedback signal I FBK and the coiler speed data V, and obtain the servo valve position feedback signal I within a period of time from the coiler operation and maintenance platform FBK Historical data is used to train alarm thresholds; Step 2: Feedback signal I of servo valve position FBK The historical data is calculated to obtain the maximum value I max , minimum value I min , mean value A and standard deviation σ; Wherein, A = [(I FBK (1)+I FBK (2)┈+I FBK (N)] / N (1) Step 3: Establish servo valve position feedback signal I FBK The alarm threshold is set, and the historical data of coiler speed V<150RPM are filtered out to obtain the data sequence I after data cleaning. FBK '(i)(i=1,2,……,N), calculate the maximum value I according to formula (1) and formula (2) max ', minimum value I min ', mean value A' and standard deviation σ'; Step 4: Establish servo valve position feedback signal I FBK The alarm thresholds H and L, where H is the upper limit of the normal range of the servo valve position, and L is the lower limit of the normal range of the servo valve position; H=1.5×σ'+0.5×(Q3+1.5×W) (3) L=1.5×σ'+0.5×(Q1-1.5×W) (4) Where Q3 = I max ’ - 0.25×(I max ’ - I min ’), Q1 = I min ’ + 0.25×(I max ’ - I min ’), W = Q3 - Q1; When the coiler servo valve position feedback signal I FBK >H or I FBK When <L, it is predicted that the position of the coiler side guide is abnormal; Step 5: Establish the zero drift fault coefficient Z of the coiler side guide servo valve, and give the signal I according to the servo valve position. REF and position feedback signal I FBK , calculate the servo valve zero drift failure coefficient Z, Z=|(I REF -I FBK )| / I REF ×100% (5) Monitor the zero drift fault coefficient Z of the coiler side guide plate servo valve. When 5%≤Z≤15%, predict the zero drift fault of the coiler side guide plate servo valve. Step 6: Establish the coiler side guide plate servo valve core jamming fault coefficient C, and give the servo valve position signal I according to the servo valve position. REF and position feedback signal I FBK , calculate the servo valve core blocking failure coefficient C, C=[|(I REF -I FBK )| / I REF -0.15]×100% (6) Monitor the coiler side guide plate servo valve spool jam fault coefficient C. When C ≥ 0, predict the servo valve spool jam fault.

2. The method for intelligently monitoring the operating status of the coiler side guide servo valve according to claim 1, characterized in that: The coiler operation and maintenance platform is a coiler DCS system or a rolling line remote control system.

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