A pulse valve fault diagnosis method

Abstract

The application provides a pulse valve fault diagnosis method, which can realize real-time monitoring of the operation state of the pulse valve, greatly reduce the workload of fault identification, improve the work efficiency, and ensure the health of workers; the method comprises the following steps: S1, collecting pressure data of the pulse valve after being opened by a pulse valve monitoring device in real time, and fitting a pressure exponential function according to the pressure data; S2, performing first derivation on the pressure exponential function to obtain a first derivative; S3, selecting a set number of first derivatives of the pulse valve according to a time sequence to obtain an absolute maximum derivative value and an absolute average value corresponding to each pulse valve, then averaging the absolute maximum derivative value and the absolute average value of the pulse valve under the set number to obtain corresponding signal values, and then comparing the first derivative value of the pulse valve with the corresponding signal values to determine whether the pulse valve under the compressed air main branch exists a fault phenomenon.

Description

Technical Field

[0001] This invention relates to the field of pulse valve technology, specifically a method for diagnosing pulse valve faults. Background Technology

[0002] Particulate matter remains a major pollutant of concern to domestic environmental protection departments, and various regions have successively issued industrial air pollutant emission standards that have set the emission limit for particulate matter at 10 mg / m3. Industries such as power generation, industrial boilers, cement, waste incineration, ceramics, chemicals, steel, carbon black, coatings, tire manufacturing, food, and pharmaceuticals require multiple dust collectors in their processes. Currently, most dust collectors have been replaced by baghouse dust collectors. Baghouse dust collectors must be equipped with pulse valves for effective cleaning of the filter bags. Large baghouse dust collectors typically have hundreds of pulse valves, which effectively clean the filter bags, thereby reducing unit resistance and minimizing bag clogging. However, currently, the quality of pulse valves is entirely determined manually on-site by hearing, which is not only labor-intensive but also prone to errors. Furthermore, the noise level of pulse valves can exceed 100 decibels, and prolonged exposure to such an environment may cause permanent hearing loss, posing a significant challenge to the occupational health of employees. Summary of the Invention

[0003] To address the aforementioned problems, this invention provides a pulse valve fault diagnosis method, which enables real-time monitoring of the pulse valve's operating status, significantly reduces the workload of fault diagnosis, improves work efficiency, and ensures employee health.

[0004] This invention adopts the following technical solution: a pulse valve fault diagnosis method, characterized by comprising the following steps:

[0005] S1. Real-time pressure data after the pulse valve in the compressed air main pipe branch is opened is collected through the pulse valve monitoring device, and a pressure exponential function is fitted based on the pressure data.

[0006] S2. Take the first derivative of the pressure exponential function to obtain the first derivative;

[0007] S3. According to the time series, select the first derivative of a set number of pulse valves to obtain the maximum absolute derivative value and the average absolute value of each pulse valve. Then, average the maximum absolute derivative value and the average absolute value of the pulse valves under the set number to obtain the corresponding signal value. Then compare the first derivative value of the pulse valve with the corresponding signal value to determine whether there is a fault in the pulse valve under the compressed air main pipe branch.

[0008] Further, in step S1, the pulse valve monitoring device receives the DI timing signal for the pulse valve opening and, after a delay of 10ms to 50ms, performs real-time pressure data acquisition; then, after the DI timing signal for the pulse valve opening disappears and after a delay of 1.1 to 1.5 times the pulse valve blowing pulse width, it stops sampling pressure data.

[0009] Further, in step S1, after receiving the DI timing signal indicating that the pulse valve is opening, and after a delay of 10ms to 50ms, the pulse valve monitoring device collects pressure data pairs after the pulse valve opens in real time according to a set sampling frequency, denoted as [Y1, x1], [Y2, x2], [Y3, x3]...[Y...]. n x n ];

[0010] Where n is the data length, and n = 1.1 to 1.5 times the pulse valve opening time;

[0011] x n Y represents the time parameter after the pulse valve blows. n Indicates the pressure value;

[0012] Furthermore, the fitted pressure exponential function is: y = e ax+c +b, where a, b, and c are constants, and x is a time parameter;

[0013] Subsequently, the least squares method was used to establish...

[0014]

[0015] Then, according to the least squares method, solve the nonlinear equation:

[0016]

[0017]

[0018]

[0019] This allows us to obtain the values ​​of parameters a, b, and c;

[0020] Furthermore, in step S2, the pressure exponential function y = e ax+c Taking the derivative of +b once, we obtain the first derivative y′=ae. ax ;

[0021] Furthermore, step S3 also includes the following steps:

[0022] S3.1 According to the time series, select the first derivative of the pulse valves in the first 5% to 30% of the series to obtain the maximum absolute value of the derivative y′max for each pulse valve;

[0023] Based on the time series, the first derivatives of 60% to 90% of the continuous pulse valves in the series are selected to obtain the average absolute value y′avg for each pulse valve;

[0024] S3.2 Sort the y′max of all pulse valves under the pulse valve monitoring equipment in descending order, and take 60% to 90% of the number of pulse valves in each order as valid samples of operation, and then calculate the average of the valid samples of operation to obtain the result.

[0025] The y′avg values ​​of all pulse valves under the pulse valve monitoring device are sorted in descending order. 60%-90% of the pulse valves are then selected as valid closed samples, and the average of these valid closed samples is calculated to obtain the result.

[0026] S3.3, If the first derivative value of the pulse valve is less than Then it is determined that the pulse valve is abnormally open;

[0027] If the first derivative of the pulse valve is less than If this is the case, the pulse valve is determined to be abnormally closed.

[0028] The beneficial effects of this invention are that it measures the pressure data changes of the pulse valves in the compressed air main pipe branch in real time through the pulse valve monitoring equipment, and evaluates the performance of the pulse valves based on the first derivative of the pressure exponential function, so as to realize real-time monitoring of the pulse valve operation status. This can alert users to pulse valves that may be faulty, greatly reduce the workload of fault diagnosis, improve work efficiency, and enable timely fixed-point repair of faulty pulse valves, while ensuring the health of employees and having good economic value. Attached Figure Description

[0029] Figure 1 This is a schematic diagram of the structure of the present invention;

[0030] Figure 2 This is a pressure change curve after the pulse valve blows in this invention. Detailed Implementation

[0031] like Figure 1 , Figure 2 As shown, the present invention provides a pulse valve fault diagnosis method, comprising the following steps:

[0032] S1. For multiple pulse valves 2 under a compressed air main pipe branch 1, the pulse time of their opening is approximately the same, and they share a compressed air main pipe. The inlet pressure of all pulse valves 2 is approximately the same. Therefore, the pulse valves 2 under a compressed air main pipe branch 1 have the same working conditions.

[0033] Upon receiving the DI timing signal indicating the opening of pulse valve 2, pulse valve monitoring device 3, due to the delay between the pulse signal (or pulse width) of pulse valve 2 taking effect and the full opening of the pulse valve diaphragm, delays by 30ms. Then, pulse valve monitoring device 3 collects pressure data pairs after the pulse valve 2 opens in real time at a sampling frequency of 1000 Hz, denoted as [Y1, x1], [Y2, x2], [Y3, x3]...[Y...]. n x n Based on the obtained pressure data, the pressure exponential function is fitted as: y = e ax+c +b, where a, b, and c are constants, and x is a time parameter;

[0034] Subsequently, the least squares method was used to establish...

[0035]

[0036] Then, according to the least squares method, solve the nonlinear equation:

[0037]

[0038]

[0039]

[0040] This allows us to obtain the values ​​of parameters a, b, and c;

[0041] Where n is the data length, n = 1.2 times the pulse valve opening time, and the sampled data length is 180ms;

[0042] x n Y represents the time parameter after the pulse valve blows. n Indicates the pressure value;

[0043] Similarly, after the pulse signal of pulse valve 2 fails, there will be a delay in the closing of the pulse valve diaphragm. Therefore, after the DI timing signal for opening pulse valve 2 disappears and is delayed by 1.1 to 1.5 times the pulse width of the pulse valve, pressure data sampling is stopped; the pulse width of the pulse valve is 150ms.

[0044] The acquisition of the DI timing signal for the opening of the pulse valve is as follows: at the same time as the pulse valve 2 opens, an active or passive switching signal is output to the digital acquisition point of the pulse valve monitoring device 3, or the pulse valve monitoring device 3 acquires an active or passive switching signal output when the first pulse valve opens, and then obtains the opening time of other pulse valves according to a certain timing sequence.

[0045] S2, regarding the pressure exponential function y = e ax+c Taking the derivative of +b once, we obtain the first derivative y′=ae. ax ;

[0046] S3. According to the time series, select the first derivative of a set number of pulse valves to obtain the maximum absolute derivative value and the average absolute value of each pulse valve. Then, average the maximum absolute derivative value and the average absolute value of the pulse valves under the set number to obtain the corresponding signal value. Then compare the first derivative value of the pulse valve with the corresponding signal value to determine whether there is a fault in the pulse valve under the compressed air main pipe branch 1.

[0047] Step S3 specifically includes the following steps:

[0048] S3.1. Based on the time series, select the first derivative of pulse valve 2 within the first 5% to 30% of the sequence, that is, calculate x9 to x... 54 Find the first derivative and its maximum absolute value to obtain the maximum absolute derivative value y for each pulse valve. ′ max, which is the main characteristic for the opening of pulse valve 2;

[0049] Based on the time series, select the first derivative of pulse valve 2, which represents 60% to 90% of the continuous pulses in the series; that is, calculate x in the series. 108 ~x 162 By taking the first derivative and calculating the absolute average, we obtain the absolute average value y for each pulse valve. ′ avg, as the main characteristic of pulse valve 2 being closed;

[0050] S3.2, For all pulse valves 2 under pulse valve monitoring device 3, y ′ The pulse valves are sorted in descending order, and 80% of each pulse valve is taken as the valid open sample. The average of these valid open samples is then calculated to obtain the result. This serves as the normal operating signal for pulse valve 2;

[0051] For all pulse valves 2 under pulse valve monitoring device 3, y ′ The average value (avg) is sorted in descending order, and 82% of the pulse valve counts are taken as valid closed samples. The average of these valid closed samples is then calculated to obtain the result. This serves as the normal operating signal for pulse valve 2;

[0052] S3.3, If the first derivative value of the pulse valve is less than Then it is determined that the pulse valve is abnormally open;

[0053] If the first derivative of the pulse valve is less than If this is the case, the pulse valve is determined to be abnormally closed.

[0054] This invention involves installing a pulse valve monitoring device 3 on the air reservoir 4 or the compressed air main pipe branch 1 connected to the air reservoir 4. When the pulse valve 2 opens, airflow is directly injected into the bag filter chamber (not shown in the figure), causing a rapid change in pressure in the compressed air main pipe branch 1. As air is replenished in the compressed air main pipe branch 1, the pressure at the measuring point exhibits a non-linear change, and the pressure change on the branch is closer to y = e ax+c The +b function collects real-time pressure change data after the pulse valve opens, specifying [Y1, x1], [Y2, x2], [Y3, x3], ... Y n, x n Fit it to y = e ax+c For a function with +b, use the least squares method to find the constants a, b, and c, and then use the first derivative y′=ae ax The rate of change is evaluated to approximate the opening and closing capabilities of the pulse valve. This invention is applicable to industries such as power, industrial boilers, cement, waste incineration, ceramics, chemicals, steel, carbon black, coatings, tire manufacturing, food, and pharmaceuticals, where fixed beds, such as bag filters and ceramic tube dust collectors, are used to remove particulate matter, and pulse valves are used to clean these dust collectors. It is also applicable to applications where air cannons are used to loosen materials.

[0055] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

[0056] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A method for diagnosing pulse valve faults, characterized in that, Includes the following steps: S1. Real-time pressure data after the pulse valve in the compressed air main pipe branch is opened is collected through the pulse valve monitoring device, and the pressure data is fitted into a pressure exponential function. The fitted pressure exponential function is: Where a, b, and c are all constants. For time parameters; S2. Take the first derivative of the pressure exponential function to obtain the first derivative; S3. According to the time series, select the first derivative of a set number of pulse valves to obtain the maximum absolute derivative value and the average absolute value of each pulse valve. Then, average the maximum absolute derivative value and the average absolute value of the pulse valves under the set number to obtain the corresponding signal value. Then compare the first derivative value of the pulse valve with the corresponding signal value to determine whether there is a fault in the pulse valve under the compressed air main pipe branch. Step S3 further includes the following steps: S3.

1. Based on the time series, select the first derivative of the pulse valves in the first 5% to 30% of the series, and obtain the maximum absolute derivative value for each pulse valve. ; Based on the time series, the first derivatives of 60% to 90% of the consecutive pulse valves in the series are selected to obtain the average absolute value for each pulse valve. ; S3.2, For all pulse valves under the pulse valve monitoring equipment Sort the samples in descending order, and take 60% to 90% of the pulse valve counts as valid open samples. Then, average the valid open samples to obtain the result. ; For all pulse valves under the pulse valve monitoring equipment Sort the samples in descending order, and take 60%-90% of the pulse valve counts as valid closed samples. Then, average the valid closed samples to obtain the result. ; S3.3, If the first derivative value of the pulse valve is less than If so, the pulse valve is determined to be abnormally open; If the first derivative of the pulse valve is less than If so, the pulse valve is determined to be abnormally closed.

2. The pulse valve fault diagnosis method according to claim 1, characterized in that, In step S1, the pulse valve monitoring device receives the DI timing signal for the pulse valve to open and then delays for 10ms to 50ms before collecting pressure data in real time. Subsequently, after the DI timing signal for the pulse valve to open disappears and after a delay of 1.1 to 1.5 times the pulse width of the pulse valve, the pressure data sampling stops.

3. The pulse valve fault diagnosis method according to claim 2, characterized in that, In step S1, after receiving the DI timing signal indicating that the pulse valve is opening, and after a delay of 10ms to 50ms, the pulse valve monitoring device collects pressure data pairs after the pulse valve opens in real time according to a set sampling frequency, and records them as follows: ; in, For data length, =1.1~1.5 times the pulse valve opening time; This indicates the time parameter after the pulse valve blows. This indicates the pressure value.

4. The pulse valve fault diagnosis method according to claim 3, characterized in that, The fitted pressure exponential function is: Where a, b, and c are all constants. For time parameters; Subsequently, the least squares method was used to establish... ； Then, according to the least squares method, solve the nonlinear equation: ； ； ； This allows us to obtain the values ​​of parameters a, b, and c.

5. The pulse valve fault diagnosis method according to claim 4, characterized in that, In step S2, the pressure exponential function is... Taking the first derivative yields the first derivative. .

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