CN113477721B - Method for monitoring working states of steel coil trolley and walking beam - Google Patents
Method for monitoring working states of steel coil trolley and walking beam Download PDFInfo
- Publication number
- CN113477721B CN113477721B CN202110792797.3A CN202110792797A CN113477721B CN 113477721 B CN113477721 B CN 113477721B CN 202110792797 A CN202110792797 A CN 202110792797A CN 113477721 B CN113477721 B CN 113477721B
- Authority
- CN
- China
- Prior art keywords
- speed
- time
- walking beam
- signal
- steel coil
- 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.)
- Active
Links
Images
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B21—MECHANICAL METAL-WORKING WITHOUT ESSENTIALLY REMOVING MATERIAL; PUNCHING METAL
- B21B—ROLLING OF METAL
- B21B38/00—Methods or devices for measuring, detecting or monitoring specially adapted for metal-rolling mills, e.g. position detection, inspection of the product
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B21—MECHANICAL METAL-WORKING WITHOUT ESSENTIALLY REMOVING MATERIAL; PUNCHING METAL
- B21B—ROLLING OF METAL
- B21B39/00—Arrangements for moving, supporting, or positioning work, or controlling its movement, combined with or arranged in, or specially adapted for use in connection with, metal-rolling mills
- B21B39/02—Feeding or supporting work; Braking or tensioning arrangements, e.g. threading arrangements
Landscapes
- Engineering & Computer Science (AREA)
- Mechanical Engineering (AREA)
- Winding, Rewinding, Material Storage Devices (AREA)
Abstract
The invention discloses a method for monitoring the working state of a steel coil trolley and a walking beam, which comprises the steps of counting various historical running signals of the steel coil trolley and the walking beam, and calculating the running physical quantity of the steel coil trolley and the walking beam according to the running signals; calculating the mean value and standard deviation of each operation physical quantity, and determining the upper limit and the lower limit of an abnormal judgment threshold according to a 3 sigma principle; collecting various running signals of the steel coil trolley and the walking beam in real time, and calculating real-time running physical quantities of the steel coil trolley and the walking beam; judging whether the real-time operation physical quantity falls into a normal range, and if the continuous abnormal times exceed 2 times, causing leakage faults of the steel coil trolley and the walking beam; and if the connection reduction or increase times of the operation physical quantity exceed 2 times, judging the trend that the steel coil trolley and the walking beam have faults. The monitoring method can monitor the normal operation problems of the steel coil trolley and the walking beam in real time, and can perform early warning, maintenance and adjustment on the leakage problems in time, thereby avoiding accidents.
Description
Technical Field
The invention belongs to the technical field of cold rolling conveying, and relates to a method for monitoring the working states of a steel coil trolley and a walking beam.
Background
The cold rolling conveying equipment is generally applied to a cold rolling production line, is conveying equipment for conveying and conveying cold rolled steel coils, and the reliability of the working operation of the cold rolling conveying equipment is a basis for guaranteeing the continuous, stable and efficient work of the cold rolling production line. However, under the condition of normal operation, the equipment and instruments are in severe environments such as environmental interference, frame vibration interference, temperature environment influence, narrow working space and the like, and due to the factors, the working state of the cold rolling conveying equipment is difficult to directly observe, and sudden faults are easily caused. When a sudden failure occurs, if the equipment is not timely processed and maintained, serious product quality problems and potential safety hazards can be caused.
The conventional monitoring means is to combine the corresponding data information according to the common fault occurrence condition of the equipment and judge according to the experience of a master worker, and the method has more subjective factors and further reduces the relative accuracy, so that the method is difficult to adopt in large quantity. Therefore, a method is needed to monitor the monitoring data in real time, and realize trend prediction and fault early warning.
Disclosure of Invention
In order to solve the technical problems, the invention aims to provide a steel coil trolley and a stepping Liang Shishi monitoring method, which can monitor the normal running problems of the steel coil trolley and a stepping beam in real time, early warn the leakage problem in time, maintain and adjust the leakage problem and avoid accidents.
The invention provides a method for monitoring the working state of a steel coil trolley and a walking beam, which comprises the following steps:
step 1: counting various historical operating instruction signals of the steel coil trolley and the walking beam, and calculating the operating physical quantities of the steel coil trolley and the walking beam according to the corresponding operating instruction signals;
step 2: each kind of operation physical quantity is distributed in a positive-phase and negative-phase mode, the mean value and the standard deviation of each kind of operation physical quantity are respectively calculated, and the upper limit and the lower limit of the abnormal judgment threshold are determined according to the 3 sigma principle;
and step 3: collecting various operation instruction signals of the steel coil trolley and the walking beam in real time, and calculating real-time operation physical quantities of the steel coil trolley and the walking beam;
and 4, step 4: judging whether the real-time operation physical quantity falls into a normal range, namely between the upper limit and the lower limit of an abnormal judgment threshold, and if the continuous abnormal times exceed 2 times, causing leakage faults of the steel coil trolley and the walking beam;
and 5: and if the connection reduction or increase times of the operation physical quantity exceed 2 times, judging the trend that the steel coil trolley and the walking beam have faults.
In the method for monitoring the working state of the steel coil trolley and the walking beam, the operation instruction signal comprises the following steps: a high speed up signal, a low speed up signal, a high speed down signal, a low speed down signal, a height position signal, a forward signal, a backward signal, a horizontal position signal, a up limit signal, a up signal, a translation limit signal, and a translation signal.
In the method for monitoring the working state of the steel coil trolley and the walking beam, the running physical quantity comprises the following steps: the high-speed, the low-speed, the translational inclination rate and the running time of the walking beam of the steel coil trolley;
the high speed comprises a high speed ascending speed and a high speed descending speed which are equal; the low-speed comprises a low-speed ascending speed and a low-speed descending speed which are equal;
the running time of the walking beam comprises lifting time, descending time, translation time and retreating time, the lifting time is equal to the descending time, and the translation time is equal to the retreating time.
In the method for monitoring the working state of the steel coil trolley and the walking beam, the invention comprises the following steps:
(1) Calculating the high-speed ascending speed of the coil car according to the following formula:
wherein V is a high-speed rising speed, H1Is a high-speed rising end position, h1Is the high-speed rising starting point position, and T is the high-speed rising signal duration;
(2) Calculating the low-speed ascending speed of the coil car according to the following formula:
wherein v is a low rising speed, H2At the low-speed rising end position, h2Is the low-speed rising starting point position, and t is the duration of the low-speed rising signal;
(3) Calculating the translational tilt rate of the steel coil trolley according to the following formula:
wherein w is the translational tilt rate, H3Is the terminal height position, h3As a starting height position, L2For horizontal run end position, L1A horizontal running starting point position;
(4) The lift time of the walking beam is calculated according to the following formula:
T1＝T11-T12
wherein, T1Lifting time for beam-in, T11For rising limit signal trigger time, T12Triggering time for the rising signal;
(5) The translation time of the walking beam is calculated according to the following formula:
T2＝T21-T22
wherein, T2For translation time of feed beam, T21For translation limiting signal trigger time, T22The time is triggered for the translation signal.
In the method for monitoring the working state of the steel coil trolley and the walking beam, the upper limit and the lower limit of the abnormal judgment threshold are respectively as follows:
wherein Z isUpper part ofFor determining an upper threshold for an abnormality of the operating physical quantity Z, ZLower partThe lower limit of the threshold value is judged for the abnormality of the operating physical quantity Z,
σ is the standard deviation of the operating physical quantity Z as the mean value of the operating physical quantity Z.
In the method for monitoring the working state of the steel coil trolley and the walking beam, the PLC system is used for collecting the running signals and uploading the running signals to the upper computer to calculate the corresponding running physical quantity.
The monitoring method of the steel coil trolley and the stepping Liang Shishi firstly obtains related data signals of the steel coil trolley and the stepping beam; calculating the speed of the steel coil trolley and the walking beam and the required time according to a large amount of historical data, and determining the upper and lower limits of the data of the steel coil trolley and the walking beam; judging the new data, calculating the speed, the slope and the required time of the steel coil trolley and the walking beam, judging whether the steel coil trolley and the walking beam leak according to whether the numerical values are in the normal upper and lower limits, determining which part has hydraulic leakage, and facilitating maintenance and inspection; and judging the running trend of the steel coil trolley and the walking beam according to the historical speed and the required time, giving early warning to the state and maintaining in time.
Drawings
FIG. 1 is a flow chart of a method for monitoring the working condition of a coil car and a walking beam according to the present invention;
FIG. 2 is a logic diagram of the method of FIG. 1.
Detailed Description
The steel coil trolley is one of the main devices of the cold rolling process, and is mainly used for feeding a steel coil into an uncoiler for rolling and then unloading a finished steel coil from a winding drum. The steel coil trolley plays an important role in the cold rolling conveying system and is a guarantee for maintaining the normal operation of the whole cold rolling system. The total number of the steel coil trolleys in the whole unit is 4, and 2 steel coil trolleys are arranged at the inlet of the unit and mainly used for feeding steel coils to an uncoiler for uncoiling; and 2 outlets are provided, and the main function of the outlets is to unload the finished steel coil product from the coiling machine and transport the finished steel coil product to an outlet walking beam. The basic operation sequence and the hydraulic driving system of the steel coil trolley are approximately the same whether the steel coil trolley is an inlet steel coil trolley or an outlet steel coil trolley. The lifting and lowering actions of the coil car are driven by hydraulic pressure, and the translation and retraction actions are driven by a motor. The lifting hydraulic system of the steel coil trolley has a high-speed mode and a low-speed mode under the high-pressure mode and the low-pressure mode respectively.
The outlet walking beam is another main device of the cold rolling process, and mainly bears the work of sending out the steel coils conveyed by the outlet steel coil trolley, and according to the process requirements of the production line, the walking Liang Bujin needs to run at a high speed and a high yield, and the working frequency is high, so the stability of the outlet walking beam is also important. The outlet walking beam has the main function that the steel coil conveyed by the steel coil trolley is conveyed to a bundling machine for bundling, at most 7 steel coils are borne, and the quantity of the steel coils borne by the current walking beam can be known through the space-occupying grating signals. The action time sequence of the walking beam sequentially comprises advancing, ascending, retreating and descending, the four actions are executed in a reciprocating mode, and limit switches are arranged at the corresponding stroke end positions.
In the lifting process of the coil car, if the hydraulic cylinder has a leakage problem, the lifting oil cylinder does not act or the lifting speed is obviously lower than the lifting speed in a normal state. In the descending process, if the hydraulic cylinder has a leakage problem, the lifting oil cylinder does not act or cannot descend to a specified height position for a long time. In the process of Liang Jusheng stepping, if the hydraulic cylinder leakage problem occurs, the lifting oil cylinder does not act or does not reach the lifting position for a long time, and the cost is far beyond the normal time to reach the position with a specific height. In the descending process, if the hydraulic cylinder leaks, the lifting oil cylinder slows down or cannot descend to a specified height position for a long time, and the cost is far beyond the normal time to reach the specific height position. In the translation process, the lifting oil cylinder needs to maintain pressure, if internal leakage occurs, the lifted height of the steel coil can be reduced, and the steel coil can be contacted with the ground in serious conditions to cause coil overturning.
The working state of the hydraulic equipment has various expressions, such as feeding amount, temperature, change of oil particles and the like. The hydraulic equipment can reflect the running condition of the equipment through the feed amount and the time signal, and is an ideal equipment state monitoring signal. The hydraulic problems frequently occurring in the hydraulic systems of the inlet steel coil trolley, the outlet steel coil trolley and the outlet walking beam are that hydraulic oil leaks, air pocket crawling and the like, and the hydraulic problems can be determined and analyzed according to operation instruction signals and corresponding real-time displacement in the operation process.
The data acquisition scheme of the monitoring method supports the use of data acquired at a sampling frequency of not less than 1s, and the data is analyzed and processed by acquiring an operation instruction signal. The number of the device data and the operation instruction signals which can be collected is 55. The collected running instruction signals of the cold rolling transportation equipment are signals of high-speed and low-speed rising, high-speed and low-speed falling, advancing, retreating and bearing of an inlet steel coil trolley and an outlet steel coil trolley, and signals of rising, falling, advancing, retreating, ascending limit, descending limit, advancing limit, retreating limit, bearing steel coil number and the like of an outlet walking beam.
As shown in fig. 1, the method for monitoring the working state of the steel coil trolley and the walking beam comprises the following steps:
step 1: counting various historical operating instruction signals of the steel coil trolley and the walking beam, and calculating the operating physical quantities of the steel coil trolley and the walking beam according to the corresponding operating instruction signals;
step 2: each kind of operation physical quantity is distributed in a positive-phase and negative-phase mode, the mean value and the standard deviation of each kind of operation physical quantity are respectively calculated, and the upper limit and the lower limit of the abnormal judgment threshold are determined according to the 3 sigma principle;
and step 3: collecting various operation instruction signals of the steel coil trolley and the walking beam in real time, and calculating real-time operation physical quantities of the steel coil trolley and the walking beam;
and 4, step 4: judging whether the real-time operation physical quantity falls into a normal range, namely between the upper limit and the lower limit of an abnormal judgment threshold, and if the continuous abnormal times exceed 2 times, causing leakage faults of the steel coil trolley and the walking beam;
and 5: and if the connection reduction or increase times of the operation physical quantity exceed 2 times, judging the trend that the steel coil trolley and the walking beam have faults.
During specific implementation, the hydraulic valve is blocked when the coil car ascends or descends, the lifting speed or the descending speed of the coil car is obviously reduced, the ascending and descending usually occur in pairs, the analysis principle is the same, the characteristic dimension reduction can be carried out on the coil car, the lifting state of the hydraulic cylinder is diagnosed by monitoring the ascending displacement, namely the speed, of the coil car in unit time, the ascending and descending process is divided into high speed and low speed, and the speed needs to be calculated separately and whether the judgment is normal or not is more accurate.
Taking the ascending signal of the No. 1 inlet steel coil trolley as an example, when the No. 1 operation instruction signal of the hydraulic valve exists, the ascending signal is in a high-speed mode and represents that the steel coil trolley ascends at a high speed, the signal is defined as a high-speed ascending signal, the duration time of the signal is the high-speed ascending time, and the starting time point and the disappearance time point of the signal are the starting point and the end point of the high-speed ascending, so that the duration time of the high-speed ascending can be calculated. And reading the rising height values corresponding to the starting point time and the ending point time, and dividing the difference of the two heights by the duration time to obtain the high-speed rising speed. And when only the No. 2 instruction of the hydraulic valve exists, the low-speed mode is adopted, and the trolley is in a low-speed ascending state. The signal command is defined as a low-speed rising signal, the duration of the signal command is the low-speed rising time, the starting time point and the disappearance time point of the signal are the starting point and the ending point of the low-speed rising, and the duration of the low-speed rising can be calculated. And reading the rising height values corresponding to the starting point time and the ending point time, and dividing the difference of the two heights by the duration time to obtain the low-speed rising speed. In the steel coil trolley translation process, if the oil cylinder leakage occurs, the lifting height of the steel coil is inevitably reduced, the steel coil trolley is provided with the displacement sensor, the height data of the steel coil trolley can be acquired in real time, and therefore, whether the steel coil trolley is highly reduced or not in the translation process is monitored. During this time, the amount of change in the horizontal distance of advancement and the amount of change in height, on average, how many millimeters of decrease per meter was calculated.
Through the analysis, aiming at the state monitoring of the steel coil trolley, the operation instruction signals needing to be collected comprise: a high speed up signal, a low speed up signal, a high speed down signal, a low speed down signal, a height position signal, a forward signal, a backward signal, a horizontal position signal.
The working stroke of the walking beam comprises four parts of advancing, ascending, retreating and descending. Because the signals of each stage of the walking beam are digital quantity signals, the logic analysis is operated as follows: continuously outputting a high level in the backing process until the steel coil reaches a preset backing position, triggering a limit switch to stop backing, and continuously maintaining a high level signal with a backing limit signal after a backing signal is converted into a low level for a period of time to ensure that the walking beam can continuously stay at the last position; continuously outputting a high level in the rising process until the steel coil reaches a preset height, triggering a limit switch, and then converting a rising signal into a low level; continuously outputting high level in the translation motion process until reaching a specified forward position, starting a forward limit switch, and then converting a forward signal into a low level signal; during the descending action, the high level is continuously output until reaching the appointed lowest position to trigger the descending limit switch, then the forward signal is converted into a low level signal, and in order to keep the lowest position continuously, the descending limit high level signal is continuously output. Through analysis, the initial state is that the walking beam is at the last lowest position, so that a descending limit signal and a retreating limit signal are always in an excited state, then the forward signal is triggered, the walking beam moves forward to work, a forward limit switch is turned on after reaching a specified position, the forward process is finished, a rising instruction is turned on, the walking beam starts to rise slowly, when reaching a rising specified position, the rising limit switch is triggered to stop rising, then the retreating signal is turned on, the walking beam starts to retreat, after retreating to the specified position, the retreating limit signal starts, the retreating process is finished, then the descending signal is triggered, the walking beam descends to the specified position, the descending limit is triggered, and the walking beam and the retreating limit signal are triggered all the time to ensure that the trolley is always located at the specified initial position and is unchanged, and the whole walking beam movement process is formed. In the process, if the hydraulic cylinder leaks in a certain process, the time spent on the steel coil reaching the preset position is far longer than the time spent on the hydraulic cylinder in a normal state.
The operation instruction signal to be collected for the state monitoring of the outlet walking beam through the analysis comprises the following steps: a forward signal, a reverse signal, a horizontal position signal, a rise limit signal, a rise signal, a translation limit signal, and a translation signal.
And collecting the operation signals through a PLC system, transmitting the collected data to an upper computer, and calculating corresponding operation physical quantity through the upper computer. And transmitting the data through the TCP/IP and storing the data in a database. In the historical operation signal acquisition process, the calculated operation physical quantity is accurate to 2 bits behind the decimal point, and the upper limit and the lower limit of the abnormality judgment threshold are accurate to 3 bits behind the decimal point. The method is favorable for improving the precision of the data range.
Through the collection analysis to coil of strip dolly and walking beam one month's operating data, to high-speed rising stage, low-speed rising stage, horizontal motion and each stage time analysis, obtain the operation physical quantity that coil of strip dolly needs monitoring and include: high speed, low speed, horizontal tilt rate and walking beam operation time of the steel coil trolley. The high-speed comprises a high-speed ascending speed and a high-speed descending speed which are equal to each other; the low speed includes a low speed rising speed and a low speed falling speed, which are equal to each other. The operation physical quantity needing to be monitored by the walking beam comprises lifting time, descending time, translation time and backspacing time, wherein the lifting time is equal to the descending time, and the translation time is equal to the backspacing time.
In specific implementation, the operation physical quantity to be monitored is calculated by the following formula:
(1) Calculating the high-speed ascending speed of the coil car according to the following formula:
wherein V is a high-speed rising speed, H1Is a high-speed rising end position, h1The high-speed rising start position, T is the high-speed rising signal duration. The high speed rise signal duration is the time of the high speed rise. And reading positions corresponding to the starting time point and the disappearance time point of the high-speed signal, namely a high-speed rising starting position and a high-speed rising end position, and dividing the height difference of the two positions by the high-speed rising time to obtain the high-speed rising speed.
(2) Calculating the low-speed ascending speed of the coil car according to the following formula:
wherein v is a low-speed rising speed,H2at the low-speed rising end position, h2The low-speed rising start position, and t is the duration of the low-speed rising signal. The duration of the slow-rise signal is the time of the slow rise. And reading positions corresponding to the starting time point and the disappearance time point of the low-speed signal, namely a low-speed rising starting position and a low-speed rising end position, and dividing the height difference of the two positions by the low-speed rising time to obtain the low-speed rising speed.
(3) Calculating the horizontal inclination rate of the steel coil trolley according to the following formula:
wherein w is the horizontal tilt rate, H3Is the terminal height position, h3As a starting height position, L2For horizontal run end position, L1A horizontal running starting point position;
only the condition that a steel coil is arranged on the trolley is analyzed, when a steel coil trolley advancing signal is sent out, the trolley advances, and the duration time indicates how long the trolley advances. In this time, the ratio of the amount of height change to the horizontal distance of advance is the horizontal tilt rate. Calculate how many millimeters of change in height per meter on average.
(4) The lift time of the walking beam is calculated according to the following formula:
T1＝T11-T12
wherein, T1Lifting time for beam-in, T11For rising limit signal trigger time, T12Triggering time for the rising signal;
(5) The translation time of the walking beam is calculated according to the following formula:
T2＝T21-T22
wherein, T2For translation time of feed beam, T21For translation limiting signal trigger time, T22The time is triggered for the translation signal.
In specific implementation, the invention adopts a statistical process control method to calculate the upper limit and the lower limit of the abnormal judgment threshold of the running physical quantity. The mean and standard deviation are the two most fundamental parameters in mathematical statistics. And judging whether problems occur or not by comparing the control limits, and timely adjusting. The upper and lower control limits are parameters calculated by statistical rules and system performance, and are different from parameters manually determined according to experience. When the work is in a stable state, the work quality index follows normal distribution, the average value of the normal distribution is set as mu, the standard deviation is set as sigma, mu +/-3 sigma is usually selected as the control limit of statistical analysis, and the reasonable probability in the range is considered to be 99.73% by the principle. Whether the production state is stable or not can be judged by observing the distribution state.
Therefore, the upper limit and the lower limit of the abnormality judgment threshold of the physical quantity in operation are respectively set as follows:
wherein Z isOn the upper partFor determining an upper threshold for an abnormality of the operating physical quantity Z, ZLower partThe lower limit of the threshold value is judged for the abnormality of the operating physical quantity Z,
σ is the standard deviation of the operating physical quantity Z as the mean value of the operating physical quantity Z. When in use
It is normal.
In specific implementation, because the statistical process control method algorithm conforms to the normal distribution principle, correct data are identified as abnormal data with a probability of 95% to 97%, and therefore errors are reported, and in combination with actual operation conditions, if hydraulic leakage faults occur in cold rolling conveying equipment, the measured data are continuously lower than a speed threshold value, so that in order to prevent error early warning, the operation physical quantity acquired and calculated once exceeds a normal range, the equipment is not diagnosed to be abnormal, an alarm is given, and the method may be caused by accidental factors such as data transmission errors. If the continuous abnormality exceeds M times, the leakage fault of the steel coil trolley and the walking beam is reflected, the fault early warning is carried out, and if the leakage fault occurs only once, the abnormality early warning is only carried out to serve as a reminding function, so that the accuracy of the fault early warning is improved.
The M value needs to be reasonably defined based on data according to different devices, and over-alarming and under-alarming are prevented. The concrete adjustment basis is as follows: according to historical data in a period of time under normal working conditions, the maximum value of the times of continuously exceeding the threshold range is M, and when the continuous abnormal times of the data are greater than M, equipment failure is prompted. In this example, M =2.
And in specific implementation, judging the abnormal historical trend. And comparing the upper limit and the lower limit of the abnormal judgment threshold according to the calculated values of the rising speed and the horizontal inclination rate of the newly acquired steel coil trolley and the lifting and translation time of the walking beam. And if the corresponding operation physical quantity continuously increases or decreases for K times, judging the trend that the steel coil trolley and the walking beam have faults. In this example, K =2.
Example (b):
1. analyzing historical data, namely analyzing and acquiring the relation between the operation signal and the low-speed ascending speed, the high-speed ascending speed, the translational tilt rate, the stepping Liang Jusheng time, the time required for retreating and the like of the coil car, and analyzing and calculating each operation stage to obtain the high-speed ascending speed Z of the coil car1Low rising speed Z2Horizontal tilt rate Z3Step Liang Jusheng time Z4Translation time Z5. According to Z1、Z2、Z3、Z4、Z5The data are normally distributed and mean values are obtained respectively
And standard deviation σ1、σ2、σ3、σ4、σ5Identify Z1Below the upper limit
And is highAt the lower limit of
Normal value, Z is identified2Below the upper limit
And is higher than the lower bound
Normal value, Z is identified3Below the upper limit
And is higher than the lower bound
Normal value, Z is identified4Below the upper limit
And is higher than the lower bound
Normal value, Z is identified5Below the upper limit
And is higher than the lower bound
Is a normal value.
2. And a real-time data acquisition step, namely acquiring running signals of the working states of the steel coil trolley and the walking beam in real time, and acquiring corresponding signals every 1 second.
3. And a data judgment step, namely judging whether the data is normal or not between the upper limit and the lower limit in the step according to the operation physical quantity calculated according to the newly acquired operation signals of the steel coil trolley and the walking beam. And if the data for 2 times are abnormal continuously, reflecting that the steel coil trolley or the walking beam has hydraulic leakage.
4. And a trend judgment step, namely judging that the steel coil trolley or the walking beam has a hydraulic leakage trend if the corresponding data is continuously reduced for 2 times according to the newly acquired and calculated running physical quantity of the steel coil trolley and the walking beam.
The operation principle of the monitoring method of the present embodiment is shown in fig. 2 and described in detail as follows.
The speed, the gradient and the required time are calculated by monitoring the motion state signals of all parts of the steel coil trolley and the walking beam, and data are obtained every 1 second.
And accumulating historical data of the ascending speed, the horizontal inclination rate and the walking beam moving time in a normal working state for a period of time, and determining the upper and lower limits of the running physical quantity of each part of the steel coil trolley and the walking beam.
And then, judging the new operation physical quantity acquired and calculated in real time, calculating the operation physical quantity of the steel coil trolley and the walking beam at the corresponding stage, and judging whether the induction steel coil trolley and the walking beam have the leakage problem or not according to whether the numerical value of the operation physical quantity is within the upper limit and the lower limit of the abnormal judgment threshold value or not.
Meanwhile, according to the continuous trend of the physical quantity data of the steel coil trolley and each part of the walking beam, the operation trend of each part of the steel coil trolley and the walking beam is judged, the state is early warned in advance, and the state can be maintained in time.
Data acquisition and transmission are carried out through the PLC, and management and analysis are facilitated.
In some embodiments, M =2 may be caused to be in the data judging step.
And the M is set to be 2, so that the misjudgment of zinc leakage of the zinc pot due to accidental abnormal data can be effectively avoided.
K =2 may be caused in the trend judgment step. Selecting K =2 can well identify that the data has a descending trend according to the continuous descending times of the data.
The invention discloses a method for monitoring the working state of a steel coil trolley and a walking beam, which can monitor the state of cold rolling conveying equipment, master the working state of the cold rolling conveying equipment in real time, realize the aim that transparent production is pursued by steel plants, and carry out the work on key equipment by some advanced foreign units.
The data signals of the equipment are analyzed by collecting and extracting the signals of the monitoring equipment and combining the functional action, structural composition and working characteristics of the equipment, so that value mining and information extraction are carried out, and the work of state monitoring, abnormal early warning, fault diagnosis and the like of the equipment is further realized.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the scope of the present invention, which is defined by the appended claims.
Claims (3)
1. A method for monitoring the working state of a steel coil trolley and a walking beam is characterized by comprising the following steps:
step 1: counting various historical operating instruction signals of the coil trolley and the walking beam, and calculating the operating physical quantities of the coil trolley and the walking beam according to the corresponding operating instruction signals;
step 2: each kind of operation physical quantity is distributed in a positive-phase and negative-phase mode, the mean value and the standard deviation of each kind of operation physical quantity are respectively calculated, and the upper limit and the lower limit of the abnormal judgment threshold are determined according to the 3 sigma principle;
and step 3: collecting various operation instruction signals of the steel coil trolley and the walking beam in real time, and calculating real-time operation physical quantities of the steel coil trolley and the walking beam;
and 4, step 4: judging whether the real-time operation physical quantity falls into a normal range, namely between the upper limit and the lower limit of an abnormal judgment threshold, and if the continuous abnormal times exceed 2 times, causing leakage faults of the steel coil trolley and the walking beam;
and 5: if the connection reduction or increase times of the running physical quantity exceed 2 times, judging the trend that the steel coil trolley and the walking beam have faults;
the operation instruction signal includes: a high speed up signal, a low speed up signal, a high speed down signal, a low speed down signal, a height position signal, a forward signal, a backward signal, a horizontal position signal, a up limit signal, a up signal, a translation limit signal, and a translation signal;
the operating physical quantities include: the high-speed, the low-speed, the translational inclination rate and the running time of the walking beam of the steel coil trolley;
the high speed comprises a high speed ascending speed and a high speed descending speed which are equal; the low-speed comprises a low-speed ascending speed and a low-speed descending speed which are equal;
the running time of the walking beam comprises lifting time, descending time, translation time and backspacing time, wherein the lifting time is equal to the descending time, and the translation time is equal to the backspacing time;
(1) Calculating the high-speed ascending speed of the coil car according to the following formula:
wherein V is a high-speed rising speed, H1For a high-speed rising end position, h1Is the high-speed rising starting point position, and T is the high-speed rising signal duration;
(2) Calculating the low-speed ascending speed of the coil car according to the following formula:
wherein v is a low-speed rising speed, H2At the low-speed rising end position, h2Is the low-speed rising starting point position, and t is the duration of the low-speed rising signal;
(3) Calculating the translational tilt rate of the steel coil trolley according to the following formula:
wherein w is the translational tilt rate, H3Is the terminal height position, h3As a starting height position, L2For horizontal run end position, L1A horizontal running starting point position;
(4) The lift time of the walking beam is calculated according to the following formula:
T1＝T11-T12
wherein, T1Lifting time for beam-in, T11For rising limit signal trigger time, T12Triggering time for the rising signal;
(5) The translation time of the walking beam is calculated according to the following formula:
T2＝T21-T22
wherein, T2For translation time of feed beam, T21For translation limiting signal trigger time, T22The time is triggered for the translation signal.
2. The method for monitoring the working state of the steel coil trolley and the walking beam as claimed in claim 1, wherein the upper limit and the lower limit of the abnormal judgment threshold are respectively as follows:
wherein Z isOn the upper partFor determining an upper threshold for an abnormality of the operating physical quantity Z, ZLower partThe lower limit of the threshold value is judged for the abnormality of the operating physical quantity Z,
σ is the standard deviation of the operating physical quantity Z as the mean value of the operating physical quantity Z.
3. The steel coil car and walking beam working condition monitoring method according to claim 1, wherein the collection of the operation instruction signal is performed by a PLC system and uploaded to an upper computer to calculate the corresponding operation physical quantity.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110792797.3A CN113477721B (en) | 2021-07-14 | 2021-07-14 | Method for monitoring working states of steel coil trolley and walking beam |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110792797.3A CN113477721B (en) | 2021-07-14 | 2021-07-14 | Method for monitoring working states of steel coil trolley and walking beam |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113477721A CN113477721A (en) | 2021-10-08 |
| CN113477721B true CN113477721B (en) | 2022-11-01 |
Family
ID=77939269
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110792797.3A Active CN113477721B (en) | 2021-07-14 | 2021-07-14 | Method for monitoring working states of steel coil trolley and walking beam |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113477721B (en) |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH06339725A (en) * | 1993-05-31 | 1994-12-13 | Nippon Steel Corp | Method for detecting trouble at the time of inserting band steel coil into mandrel or pulling out the same |
| HU0001196D0 (en) * | 2000-03-21 | 2000-05-28 | Apparatus for rolling of workpieces, hostly foils | |
| CN101419460A (en) * | 2008-11-12 | 2009-04-29 | 山西太钢不锈钢股份有限公司 | The hot continuous rolling band steel coil unloading carriage fault extreme simulation control method |
| CN103398043A (en) * | 2013-07-31 | 2013-11-20 | 中联重科股份有限公司 | Method, equipment, system and engineering machinery used for detecting internal leakage of oil cylinder |
| CN107165875A (en) * | 2017-07-20 | 2017-09-15 | 马鞍山钢铁股份有限公司 | A kind of section steel cooling bed step rate translates hydraulic cylinder synchronization control method |
| CN109894475A (en) * | 2019-02-28 | 2019-06-18 | 北京首钢股份有限公司 | A kind of cold-rolling continuous annealing equipment degradation trend method for early warning and device |
| CN109909306A (en) * | 2019-03-11 | 2019-06-21 | 北京首钢自动化信息技术有限公司 | A kind of monitoring method of acid rolling plant on-line monitoring and degradation trend intelligent early-warning |
| CN110064659A (en) * | 2019-04-09 | 2019-07-30 | 鞍钢股份有限公司 | A kind of hot rolling coiler coil stripping car connects the control method of volume |
-
2021
- 2021-07-14 CN CN202110792797.3A patent/CN113477721B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH06339725A (en) * | 1993-05-31 | 1994-12-13 | Nippon Steel Corp | Method for detecting trouble at the time of inserting band steel coil into mandrel or pulling out the same |
| HU0001196D0 (en) * | 2000-03-21 | 2000-05-28 | Apparatus for rolling of workpieces, hostly foils | |
| CN101419460A (en) * | 2008-11-12 | 2009-04-29 | 山西太钢不锈钢股份有限公司 | The hot continuous rolling band steel coil unloading carriage fault extreme simulation control method |
| CN103398043A (en) * | 2013-07-31 | 2013-11-20 | 中联重科股份有限公司 | Method, equipment, system and engineering machinery used for detecting internal leakage of oil cylinder |
| CN107165875A (en) * | 2017-07-20 | 2017-09-15 | 马鞍山钢铁股份有限公司 | A kind of section steel cooling bed step rate translates hydraulic cylinder synchronization control method |
| CN109894475A (en) * | 2019-02-28 | 2019-06-18 | 北京首钢股份有限公司 | A kind of cold-rolling continuous annealing equipment degradation trend method for early warning and device |
| CN109909306A (en) * | 2019-03-11 | 2019-06-21 | 北京首钢自动化信息技术有限公司 | A kind of monitoring method of acid rolling plant on-line monitoring and degradation trend intelligent early-warning |
| CN110064659A (en) * | 2019-04-09 | 2019-07-30 | 鞍钢股份有限公司 | A kind of hot rolling coiler coil stripping car connects the control method of volume |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113477721A (en) | 2021-10-08 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN101799320B (en) | Fault prediction method and device thereof for rotation equipment | |
| CN110849404B (en) | Continuous discrimination method for sensor data abnormity | |
| CN102107224B (en) | Method for judging thickness abnormality of thickness tester and hot-rolled plate during hot rolling production | |
| EP2864847B1 (en) | Monitoring a first system of a technical plant for producing a product | |
| CN107490479B (en) | Method and device for predicting residual life of bearing | |
| CN108255131A (en) | The method in the service life of lathe, production management system and prediction and/or detection instrument | |
| CN110701137A (en) | Intelligent online detection and diagnosis device and method for hydraulic system of heading machine | |
| CN113477721B (en) | Method for monitoring working states of steel coil trolley and walking beam | |
| CN108006017A (en) | Hot continuous rolling skin pass mill group hydraulic station real-time level tracking and controlling method | |
| CN112633614A (en) | Real-time fault degree diagnosis system and method based on feature extraction | |
| CN109894480B (en) | Method, device and system for processing bar tail ruler on continuous rolling production line and medium | |
| CN113007040B (en) | Online monitoring and fault early warning system and method for main shaft assembly movement of wind turbine generator | |
| EP3951528B1 (en) | Abnormality detection apparatus, and abnormality detection method | |
| CN113155443A (en) | Lubricating oil state monitoring and fault diagnosis system and method for reducer of coal mining machine | |
| EP2793088A1 (en) | Method for monitoring at least one machine tool | |
| CN110826024A (en) | Sampling discrimination method for sensor data abnormity | |
| CN115640879A (en) | Cylinder failure prediction system, prediction method, prediction apparatus, and storage medium | |
| CN111285050B (en) | Length correction and automatic stop control method for long-distance belt | |
| CN111366358B (en) | Fault detection device and method for lifting screw | |
| DE102021209846A1 (en) | Monitoring procedure for a flying crank shears process for plate billets | |
| CN109590448B (en) | Casting die health prediction method based on online wheel hub weight detection | |
| CN115722540A (en) | Method for predicting hot-rolling direct-connection roller way fault based on motor current value | |
| CN105893741A (en) | Lead screw health guaranteeing method capable of realizing whole process real-time data statistics | |
| CN218657064U (en) | High-precision shearing control system for multi-length shearing of bar | |
| CN116572256B (en) | Industrial robot state monitoring and fault diagnosis method |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |