Equipment state monitoring system based on metal powder production

Abstract

The invention relates to the technical field of equipment state monitoring, and discloses a metal powder production-based equipment state monitoring system, which comprises a sensor module, a correction unit, a monitoring analysis unit and an early warning display unit, according to the invention, equipment vibration, temperature and environment dust concentration data are comprehensively collected, and dual monitoring of equipment and environment is realized; by accurately calculating an abnormal degree index and setting multi-level early warning, the abnormal condition of equipment operation can be reflected timely and accurately, and maintenance in advance is facilitated; the correction unit ensures that key data is accurate and reliable through the steps of determining a reference value, calculating a change rate, correcting data and the like aiming at powder adhesion interference; environment early warning adopts dual judgment standards of concentration threshold and change rate, early warning can be given out as long as any one trigger condition is needed, and the dust explosion risk is effectively prevented; the equipment stability and environment safety of metal powder production are guaranteed in an all-around mode.

Description

Technical Field

[0001] This invention relates to the field of equipment status monitoring technology, and more specifically to a status monitoring system for equipment used in metal powder production. Background Technology

[0002] In the metal powder production industry, stable equipment operation and a safe production environment are of paramount importance; however, many problems currently exist.

[0003] In terms of equipment condition monitoring, existing methods for monitoring vibration and temperature in metal powder production equipment are not precise or comprehensive enough. Traditional methods struggle to obtain key data on equipment operation in real time and accurately, failing to detect potential equipment failures in a timely manner. This leads to a high probability of sudden equipment failures, affecting production continuity and product quality, and increasing enterprise maintenance costs and the risk of production delays.

[0004] In terms of production environment monitoring, the production of metal powder generates a large amount of dust, and excessively high concentrations can easily lead to safety accidents such as explosions. However, traditional dust concentration monitoring methods have limitations, such as unreasonable distribution of monitoring points, low monitoring frequency, inability to reflect dynamic changes in dust concentration in the environment in a timely manner, and inability to effectively prevent dust explosion accidents, posing a serious threat to the safety of personnel and equipment.

[0005] Furthermore, metal powder easily adheres to the sensor surface, interfering with the acquisition of critical data and causing deviations in the monitoring data. Current technologies lack effective correction mechanisms, making it difficult to make reliable judgments about equipment status and environmental safety based on inaccurate data.

[0006] Therefore, developing a system that can comprehensively and accurately monitor the status of metal powder production equipment and environmental conditions, and can also correct the data, is of great significance for ensuring the efficiency and safety of metal powder production. Summary of the Invention

[0007] The purpose of this invention is to provide a status monitoring system for equipment used in metal powder production, which solves the technical problems mentioned in the background art.

[0008] The objective of this invention can be achieved through the following technical solutions:

[0009] A status monitoring system for equipment used in metal powder production includes:

[0010] The sensor module is used to collect key data from the metal powder production equipment. The sensor module includes vibration sensors and temperature sensors, with the key data referring to vibration data and temperature data. The sensor module also includes a dust concentration sensor, which is used to collect dust concentration data of the environment in which the metal powder production equipment is located.

[0011] The calibration unit is used to calibrate key data obtained from the sensor module.

[0012] The monitoring and analysis unit is used to monitor and analyze the corrected key data.

[0013] The early warning display unit is used to broadcast different levels of early warnings for the metal powder production equipment based on the abnormality indicators corresponding to the current vibration and temperature data of the metal powder production equipment; it is also used to provide environmental early warnings based on the dust concentration data of the environment in which the metal powder production equipment is located.

[0014] As a further aspect of the present invention, the monitoring and analysis method is as follows:

[0015] During normal operation of the metal powder production equipment, multiple sets of vibration and temperature data were acquired and labeled as Z. j and W j j = 1, 2, ..., m, where m represents the number of vibration and temperature data obtained under normal operating conditions of the metal powder production equipment;

[0016] Subsequently, multiple sets of vibration data Z were calculated. j and temperature data W j The corresponding mean and standard deviation are respectively labeled as ZP, ZB, WP and WB;

[0017] Where ZP is Z j The average value, ZB is Z j The standard deviation of WP is Z. j The average value of WB is Z. j Standard deviation;

[0018] Acquire the current vibration and temperature data of the metal powder production equipment and label them as Z0 and W0;

[0019] Then through: and

[0020] The abnormality indices QZ and QW corresponding to the current vibration and temperature data of the metal powder production equipment were calculated.

[0021] As a further aspect of the present invention: the different levels of early warning broadcasting methods are as follows:

[0022] Extract the pre-defined anomaly threshold sets [QZa, QZb] and [QWa, QWb], and compare the anomaly indices QZ and QW with the anomaly threshold sets [QZa, QZb] and [QWa, QWb] respectively:

[0023] If QZ < QZa, a Level 1 vibration warning will be issued; if QW < QWa, a Level 1 temperature warning will be issued.

[0024] If QZa≤QZ<QZb, a level two vibration warning will be issued; if QWa≤QW<QWb, a level two temperature warning will be issued.

[0025] If QZ≥QZb, a Level 3 vibration warning will be issued; if QW≥QWb, a Level 3 temperature warning will be issued.

[0026] As a further aspect of the present invention, the correction process is as follows:

[0027] Step K1.1, Determining the baseline value:

[0028] When the metal powder production equipment is running and in a state without powder adhesion, record the key data of the sensor module within a specified time period T0.

[0029] The average value of all key data within the specified time period T0 is then calculated, and this average value is used as the baseline value of the key data.

[0030] Step K1.2, Calculation of real-time rate of change:

[0031] During the normal production and operation of the metal powder production equipment, key data collected by the sensor module are recorded in real time at fixed time intervals t1.

[0032] Subsequently passed:

[0033] Calculate the rate of change (GBi) of key data corresponding to the normal production operation of the metal powder production equipment in each time interval;

[0034] In the formula, Gi represents the key data collected by the sensor module during the normal production operation of the metal powder production equipment, i = 1, 2, ..., n, where n represents the number of key data records, i represents the sequence number of the key data, and G0 is the baseline value of the key data.

[0035] Step K1.3, Judgment and Correction:

[0036] Extract the pre-set key data change rate threshold GBy, and then compare the corresponding key data change rate GBi during the normal production operation of the metal powder production equipment in each time interval with the key data change rate threshold:

[0037] When GBi > GBy, it is determined that the sensor may have powder adhering to it.

[0038] Extract a database that was previously established in a laboratory simulation, in which the database records the relationship between different powder adhesion thicknesses and the corresponding key data variation coefficients;

[0039] The powder adhesion thickness of the current sensor module is measured by a non-contact optical measurement method, and then the variation coefficient corresponding to the powder adhesion thickness is found in the database.

[0040] Then, according to the formula: GJi=GBi / h, the i-th key data is corrected to obtain the corrected i-th key data GJi;

[0041] In the formula, h is the variation coefficient retrieved from the database.

[0042] As a further aspect of the present invention, the environmental early warning method is as follows:

[0043] Obtain the pre-set dust concentration safety threshold based on the critical concentration for dust explosion and the safety standards of the production environment, and compare it with the current dust concentration data of the environment where the metal powder production equipment is located:

[0044] If the current dust concentration data is greater than or equal to the dust concentration safety threshold, it indicates that there is a potential risk of dust explosion in the environment where the metal powder production equipment is located, and an environmental warning signal is generated.

[0045] If the current dust concentration data is less than the dust concentration safety threshold, it indicates that there is no potential risk of dust explosion in the environment where the metal powder production equipment is located, and no environmental warning signal is generated.

[0046] As a further aspect of the present invention, the environmental early warning method is as follows:

[0047] The system acquires the dust concentration data of the environment where the metal powder production equipment is located at the current time point and the dust concentration data of the previous time point; where the time interval between the current time point and the previous time point is Tr, and Tr is a preset value; then, the dust concentration data of the previous time point is subtracted from the dust concentration data of the current time point, and the result is divided by the time interval Tr to obtain the rate of change of the dust concentration at the current time point. Then, the rate of change of the dust concentration is compared with a preset rate of change threshold.

[0048] If the rate of change of dust concentration is greater than or equal to the rate of change threshold, it indicates that there is a potential risk of dust explosion in the environment where the metal powder production equipment is located, and an environmental warning signal is generated.

[0049] If the rate of change of dust concentration is less than the rate of change threshold, it indicates that there is no potential risk of dust explosion in the environment where the metal powder production equipment is located, and no environmental warning signal is generated.

[0050] As a further aspect of the present invention: if either the rate of change of dust concentration data is greater than or equal to the rate of change threshold or the current dust concentration data is greater than or equal to the dust concentration safety threshold, it indicates that there is a potential risk of dust explosion in the environment where the metal powder production equipment is located, and an environmental warning signal is generated.

[0051] As a further aspect of the present invention: the dust concentration sensor adopts the principle of light scattering. Its working process is as follows: when light shines on dust particles, scattering occurs. The intensity of the scattered light is related to the dust concentration. Under certain conditions, the intensity of the scattered light and the dust concentration approximately satisfy a linear relationship F = γ × F + β, where γ and β are coefficients determined through calibration. Subsequently, the dust concentration value can be obtained by measuring the intensity of the scattered light.

[0052] The beneficial effects of this invention are:

[0053] Comprehensive data acquisition and monitoring: Through vibration sensors, temperature sensors, and dust concentration sensors in the sensor module, it is possible to comprehensively collect vibration data, temperature data, and dust concentration data of the metal powder production equipment and the environment in which the equipment is located; it can not only monitor the operating status of the equipment itself, but also monitor the production environment in real time, providing multi-dimensional data support for the stable operation of the equipment and production safety.

[0054] Precise anomaly analysis: In the monitoring and analysis unit, by calculating the average value and standard deviation of multiple sets of vibration and temperature data under normal operating conditions of the metal powder production equipment and comparing them with the current data, the anomaly index corresponding to the current vibration and temperature data can be accurately calculated. This precise analysis method helps to promptly identify potential problems in equipment operation, take measures in advance for maintenance and adjustment, and reduce the probability of equipment failure.

[0055] Multi-level early warning mechanism: The early warning display unit broadcasts different levels of early warnings based on the abnormality indicators corresponding to the current vibration and temperature data of the metal powder production equipment. This multi-level early warning mechanism can promptly and accurately convey the equipment's operating status information to the operators according to the different degrees of abnormality, enabling the operators to take corresponding measures according to the warning level and avoid production accidents and economic losses caused by equipment failure or abnormal operation.

[0056] Effective calibration processing: The calibration unit can effectively solve the impact of powder adhesion on sensor data by calibrating the key data obtained from the sensor module. Through steps such as determining the reference value, calculating the real-time change rate, and judgment and calibration, it can promptly detect possible powder adhesion on the sensor and perform calibration based on the simulated database and the measured powder adhesion thickness, ensuring the accuracy and reliability of key data and improving the precision and stability of the monitoring system.

[0057] Dual Environmental Early Warning System: The environmental early warning system employs two strategies. First, it compares the current dust concentration data with a pre-set safe dust concentration threshold. Second, it calculates the rate of change of dust concentration at the current time point and compares it with a pre-set rate of change threshold. When either scenario is true, it indicates a potential risk of dust explosion in the environment where the metal powder production equipment is located, generating an environmental early warning signal. This dual early warning mechanism can more comprehensively and promptly identify potential hazards in the production environment, providing a more reliable guarantee for production safety.

[0058] Reliable dust concentration measurement: The dust concentration sensor adopts the principle of light scattering. Under certain conditions, the intensity of scattered light and the dust concentration approximately satisfy a linear relationship. The dust concentration value can be obtained by measuring the intensity of scattered light. This measurement method has high accuracy and reliability, and can monitor the dust concentration in the production environment in real time and accurately, providing a reliable data source for environmental early warning. Attached Figure Description

[0059] The invention will now be further described with reference to the accompanying drawings.

[0060] Figure 1 This is a system block diagram of the equipment status monitoring system for metal powder production based on the present invention.

[0061] Figure 2 This is a flowchart illustrating the correction unit in the equipment status monitoring system for metal powder production according to the present invention. Detailed Implementation

[0062] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0063] Example 1

[0064] Please see Figure 1 and Figure 2As shown, the present invention is a status monitoring system for equipment used in metal powder production, comprising:

[0065] The sensor module is used to collect key data from metal powder production equipment. The sensor module includes vibration sensors and temperature sensors. The key data refers to vibration data and temperature data.

[0066] The monitoring and analysis unit is used to monitor and analyze key data obtained by the sensor module.

[0067] The monitoring and analysis methods are as follows:

[0068] During normal operation of the metal powder production equipment, multiple sets of vibration and temperature data were acquired and labeled as Z. j and W j j = 1, 2, ..., m, where m represents the number of vibration and temperature data obtained under normal operating conditions of the metal powder production equipment;

[0069] Subsequently, multiple sets of vibration data Z were calculated. j and temperature data W j The corresponding mean and standard deviation are respectively labeled as ZP, ZB, WP and WB;

[0070] Where ZP is Z j The average value, ZB is Z j The standard deviation of WP is Z. j The average value of WB is Z. j Standard deviation;

[0071] Acquire the current vibration and temperature data of the metal powder production equipment and label them as Z0 and W0;

[0072] Then through: and

[0073] Calculate the abnormality indices QZ and QW corresponding to the current vibration and temperature data of the metal powder production equipment, respectively;

[0074] The early warning display unit is used to broadcast early warnings of different levels based on the abnormality indicators corresponding to the current vibration and temperature data of the metal powder production equipment.

[0075] Specifically:

[0076] Extract the pre-defined anomaly threshold sets [QZa, QZb] and [QWa, QWb], and compare the anomaly indices QZ and QW with the anomaly threshold sets [QZa, QZb] and [QWa, QWb] respectively:

[0077] If QZ < QZa, a Level 1 vibration warning will be issued; if QW < QWa, a Level 1 temperature warning will be issued.

[0078] When a Level 1 vibration warning or a Level 1 temperature warning is issued, the system interface will flash a notification while simultaneously issuing an audible alarm to remind operators that the equipment has a moderate abnormality and should be inspected as soon as possible.

[0079] If QZa≤QZ<QZb, a level two vibration warning will be issued; if QWa≤QW<QWb, a level two temperature warning will be issued.

[0080] When a Level 2 vibration warning or a Level 2 temperature warning is issued, the system interface will flash to alert the operator that the equipment may have a minor abnormality and requires close attention.

[0081] If QZ≥QZb, a Level 3 vibration warning will be issued; if QW≥QWb, a Level 3 temperature warning will be issued.

[0082] When a Level 3 vibration warning or a Level 3 temperature warning is issued, the equipment should be stopped immediately, and relevant management personnel should be notified via SMS and email that the equipment has a serious abnormality and requires emergency handling.

[0083] In this embodiment, sensor modules collect key vibration and temperature data of metal powder production equipment. The monitoring and analysis unit uses the average value, standard deviation, and a specific formula to calculate the degree of abnormality index. The early warning display unit compares the degree of abnormality index with the threshold to broadcast early warnings of different levels. This allows operators to be promptly informed of abnormal equipment conditions so that appropriate measures can be taken to ensure stable equipment operation and reduce production interruptions and losses caused by equipment failures.

[0084] Example 2

[0085] Please see Figure 1 and Figure 2 As shown, as a second embodiment of the present invention, in specific implementation, compared with the first embodiment, the technical solution of this embodiment differs from that of the first embodiment only in that this embodiment further includes:

[0086] The calibration unit is used to calibrate key data obtained from the sensor module.

[0087] The correction process is as follows:

[0088] Step K1.1, Determining the baseline value:

[0089] When the metal powder production equipment is running and in a state without powder adhesion, record the key data of the sensor module within a specified time period T0.

[0090] The average value of all key data within the specified time period T0 is then calculated, and this average value is used as the baseline value of the key data.

[0091] In this embodiment, the status of the metal powder production equipment refers to the initial start-up or after thorough cleaning; T0 is 10 minutes; the reference value represents the normal output status of the sensor module when there is no powder adhering to it.

[0092] Step K1.2, Calculation of real-time rate of change:

[0093] During the normal production and operation of the metal powder production equipment, key data collected by the sensor module are recorded in real time at fixed time intervals t1.

[0094] Subsequently passed:

[0095] Calculate the rate of change (GBi) of key data corresponding to the normal production operation of the metal powder production equipment in each time interval;

[0096] In the formula, Gi represents the key data collected by the sensor module during the normal production operation of the metal powder production equipment, i = 1, 2, ..., n, where n represents the number of key data records, i represents the sequence number of the key data, and G0 is the baseline value of the key data.

[0097] In this embodiment, the rate of change reflects the degree of change of the current key data relative to the baseline value;

[0098] Step K1.3, Judgment and Correction:

[0099] Extract the pre-set key data change rate threshold GBy, and then compare the corresponding key data change rate GBi during the normal production operation of the metal powder production equipment in each time interval with the key data change rate threshold:

[0100] When GBi > GBy, it is determined that the sensor may have powder adhering to it.

[0101] Extract a database that was previously established in a laboratory simulation, in which the database records the relationship between different powder adhesion thicknesses and the corresponding key data variation coefficients;

[0102] The powder adhesion thickness of the current sensor module is measured by a non-contact optical measurement method, and then the variation coefficient corresponding to the powder adhesion thickness is found in the database.

[0103] Then, according to the formula: GJi=GBi / h, the i-th key data is corrected to obtain the corrected i-th key data GJi;

[0104] In the formula, h is the coefficient of change retrieved from the database;

[0105] This embodiment adds a calibration unit to perform calibration processing on key data obtained from the sensor module. By determining the baseline value under powder-free conditions, the rate of change of key data is calculated in real time and compared with a preset threshold to determine whether there is powder adhesion to the sensor. If so, the key data is calibrated using a simulated database and non-contact optical measurement methods, which improves the accuracy of the data, thereby enhancing the reliability of equipment status monitoring and reducing monitoring errors caused by powder adhesion.

[0106] Example 3

[0107] Please see Figure 1 and Figure 2 As shown, as a third embodiment of the present invention, in specific implementation, compared with embodiments one and two, the technical solution of this embodiment is to combine the solutions of embodiments one and two. The only difference between the technical solution of this embodiment and embodiments one and two is that: in this embodiment, the key data change coefficient includes the vibration data change coefficient and the temperature data change coefficient. Taking the vibration data change coefficient as an example, the database simulation establishment method is as follows:

[0108] Experimental preparation:

[0109] Prepare a simulated vibration device with similar vibration characteristics to that in metal powder production equipment. This device should be able to generate stable vibrations with adjustable frequency and amplitude.

[0110] Select the same type of vibration probe as used in actual production;

[0111] Prepare metal powder samples of different particle sizes and types;

[0112] And a non-contact optical thickness gauge for measuring powder adhesion thickness;

[0113] Experimental environment setup:

[0114] The simulated vibration device was placed in a closed experimental chamber to simulate a high-temperature, high-dust production environment.

[0115] The test chamber is equipped with a temperature and humidity control system that can be adjusted to parameters similar to the actual production environment.

[0116] At the same time, a ventilation and dust recovery device is installed to control the dust concentration in the experimental chamber and recover the powder generated during the experiment;

[0117] Baseline value acquisition:

[0118] Without any powder adhering to the vibration probe, the simulated vibration device is started, a fixed vibration frequency and amplitude are set, it is run for a certain period of time, and the output vibration amplitude data of the vibration probe at this time is collected. Then, its average value is calculated as the reference value and marked as Ga0.

[0119] Initial powder adhesion data acquisition:

[0120] First, a layer of metal powder is evenly attached to the vibration probe by spraying or dusting.

[0121] The thickness of the powder adhesion at this point is accurately measured using measuring tools and marked as d1;

[0122] Then, keeping the vibration frequency and amplitude of the simulated vibration device consistent with the initial state, run it again for a certain period of time, collect the output vibration amplitude data of the vibration probe, calculate its average value, and label it as Ga1.

[0123] Then, according to the formula h1=Ga1 / Ga0, the vibration amplitude variation coefficient h1 corresponding to the powder adhesion thickness d1 is calculated;

[0124] Multilayer powder adhesion data acquisition:

[0125] Continue adding powder adhesion in the same way, and measure the new powder adhesion thickness d2, d3, ... for each added layer;

[0126] Repeat the above steps of collecting vibration amplitude data and calculating the variation coefficient to obtain the average values ​​Ga2, Ga3, ... of the corresponding vibration amplitude data;

[0127] Then, using h2 = Ga2 / Ga0, h3 = Ga3 / Ga0, ..., the vibration amplitude variation coefficients h2, h3, ... corresponding to the powder adhesion thicknesses d2, d3, ... are calculated.

[0128] Experiments with different types and particle sizes of powders:

[0129] By changing to different types and particle sizes of metal powder, repeat the above powder adhesion and data acquisition steps to obtain the corresponding data of powder adhesion thickness and vibration amplitude variation coefficient under different powder conditions.

[0130] Finally, all the information obtained from the experiments, including powder adhesion thickness, corresponding vibration amplitude variation coefficient, and information on powder type and particle size, were compiled into a database.

[0131] Example 3 details the method of establishing the database through simulation. Taking the vibration data change coefficient as an example, by preparing experimental work such as preparing similar simulated vibration devices, a simulated production environment is built, and baseline values, initial and multi-layer powder adhesion data are collected. Experiments are conducted on powders of different types and particle sizes, and the experimental data are organized into a database. This provides reliable data support for the calibration unit to calibrate key data in Example 2, making the calibration process more scientific and accurate.

[0132] Example 4

[0133] Please see Figure 1 and Figure 2 As shown, as Embodiment 4 of the present invention, in specific implementation, compared with Embodiments 1, 2, and 3, the difference between this embodiment and Embodiments 1, 2, and 3 lies only in this embodiment:

[0134] The sensor module also includes a dust concentration sensor, which is used to collect dust concentration data of the environment in which the metal powder production equipment is located;

[0135] In this embodiment, the dust concentration sensor adopts the principle of light scattering. Its working process is as follows: when light shines on dust particles, scattering occurs. The intensity of the scattered light is related to the dust concentration. Under certain conditions, the intensity of the scattered light and the dust concentration approximately satisfy a linear relationship F = γ × F + β, where γ and β are coefficients determined through calibration. Subsequently, the dust concentration value can be obtained by measuring the intensity of the scattered light.

[0136] The early warning display unit is also used to issue environmental early warnings based on dust concentration data of the environment where the metal powder production equipment is located; the method is as follows:

[0137] Obtain the pre-set dust concentration safety threshold based on the critical concentration for dust explosion and the safety standards of the production environment, and compare it with the current dust concentration data of the environment where the metal powder production equipment is located:

[0138] If the current dust concentration data is greater than or equal to the dust concentration safety threshold, it indicates that there is a potential risk of dust explosion in the environment where the metal powder production equipment is located, and an environmental warning signal is generated.

[0139] If the current dust concentration data is less than the dust concentration safety threshold, it indicates that there is no potential risk of dust explosion in the environment where the metal powder production equipment is located, and no environmental warning signal is generated.

[0140] Simultaneously, it acquires the dust concentration data of the environment where the metal powder production equipment is located at the current time point and the dust concentration data of the previous time point; where the time interval between the current time point and the previous time point is Tr, and Tr is a preset value; then, it subtracts the dust concentration data of the previous time point from the dust concentration data of the current time point, divides the result by the time interval Tr, and obtains the change rate of the dust concentration corresponding to the current time point. Then, it compares the change rate of the dust concentration with a preset change rate threshold.

[0141] If the rate of change of dust concentration is greater than or equal to the rate of change threshold, it indicates that there is a potential risk of dust explosion in the environment where the metal powder production equipment is located, and an environmental warning signal is generated.

[0142] If the rate of change of dust concentration is less than the rate of change threshold, it indicates that there is no potential risk of dust explosion in the environment where the metal powder production equipment is located, and no environmental warning signal is generated.

[0143] In this embodiment, a dust concentration sensor is added to the sensor module to collect dust concentration data of the environment in which the equipment is located. The early warning display unit compares the dust concentration data with safety thresholds and the concentration change rate with the change rate threshold to determine whether there is a potential risk of dust explosion in the environment and generates an early warning signal. This helps to prevent dust explosion accidents in advance, ensures the safety of the production environment, and provides strong support for safe production.

[0144] Example 5

[0145] Please see Figure 1 and Figure 2 As shown, as a fifth embodiment of the present invention, in specific implementation, compared with embodiments one, two, three and four, the technical solution of this embodiment is to combine the solutions of embodiments one, two, three and four.

[0146] Example 5 integrates the technical solutions of Examples 1, 2, 3, and 4, combining the advantages of each example. It can monitor the equipment status through vibration and temperature data, correct key data, improve the accuracy of correction by using a scientifically established database, and monitor the concentration of ambient dust to prevent explosion risks. It comprehensively improves the functionality and reliability of the equipment status monitoring system based on metal powder production, ensuring the efficient and safe operation of the production process.

[0147] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters and thresholds in the formulas are set by those skilled in the art according to the actual situation.

[0148] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A status monitoring system for equipment used in metal powder production, characterized in that, include: Sensor modules are used to collect key data from metal powder production equipment; The calibration unit is used to perform calibration processing on the key data obtained by the sensor module, and obtain the calibrated key data based on the calibration processing results; The monitoring and analysis unit is used to monitor and analyze the corrected key data and obtain an indicator of the degree of abnormality of the metal powder production equipment. The early warning display unit is used to broadcast early warnings of different levels based on the abnormality indicators of the metal powder production equipment.

2. The equipment status monitoring system for metal powder production according to claim 1, characterized in that, The correction process is as follows: When the metal powder production equipment is running and there is no powder adhering, the key data of the sensor module are recorded within a specified time period; then the average value of all key data within the specified time period is calculated, and this average value is used as the benchmark value of the key data. During the normal operation of the metal powder production equipment, key data collected by the sensor module is recorded in real time at fixed time intervals t1; subsequently, through: Calculate the rate of change of key data corresponding to the normal production operation of the metal powder production equipment in each time interval, GBi; where Gi is the key data collected by the sensor module in real time during the normal production operation of the metal powder production equipment, i = 1, 2, ... n, n represents the number of key data records, i represents the sequence number of key data, and G0 is the baseline value of key data. Extract the pre-set key data change rate threshold GBy, and then compare the change rate GBi of the corresponding key data during the normal production operation of the metal powder production equipment in each time interval with the key data change rate threshold: when GBi>GBy, it is determined that there is powder adhesion on the sensor. Extract a pre-established database, which records the relationship between different powder adhesion thicknesses and the corresponding key data variation coefficients; Obtain the powder adhesion thickness of the current sensor module, then find the variation coefficient corresponding to the powder adhesion thickness from the database; then, according to the formula: GJi=GBi / h, correct the i-th key data to obtain the corrected i-th key data GJi; where h is the variation coefficient found from the database.

3. The equipment status monitoring system for metal powder production according to claim 1, characterized in that, The sensor module includes a vibration sensor and a temperature sensor, with key data referring to vibration data and temperature data.

4. The equipment status monitoring system for metal powder production according to claim 3, characterized in that, The monitoring and analysis methods are as follows: During normal operation of the metal powder production equipment, multiple sets of vibration and temperature data were acquired and labeled as Z. j and W j j = 1, 2, ..., m, where m represents the number of vibration and temperature data obtained under normal operating conditions of the metal powder production equipment; Subsequently, multiple sets of vibration data Z were calculated. j and temperature data W j The corresponding mean and standard deviation are respectively labeled as ZP, ZB, WP and WB; Where ZP is Z j The average value, ZB is Z j The standard deviation of WP is Z. j The average value of WB is Z. j Standard deviation; Acquire the current vibration and temperature data of the metal powder production equipment and label them as Z0 and W0; Then through: and The abnormality indices QZ and QW corresponding to the current vibration and temperature data of the metal powder production equipment were calculated.

5. The equipment status monitoring system for metal powder production according to claim 4, characterized in that, The warning broadcast method is as follows: Extract the pre-defined anomaly threshold sets [QZa, QZb] and [QWa, QWb], and compare the anomaly indices QZ and QW with the anomaly threshold sets [QZa, QZb] and [QWa, QWb] respectively: If QZ < QZa, a Level 1 vibration warning will be issued; if QW < QWa, a Level 1 temperature warning will be issued. If QZa≤QZ<QZb, a level two vibration warning will be issued; if QWa≤QW<QWb, a level two temperature warning will be issued. If QZ≥QZb, a Level 3 vibration warning will be issued; if QW≥QWb, a Level 3 temperature warning will be issued.

6. The equipment status monitoring system for metal powder production according to claim 2, characterized in that, in, The powder adhesion thickness was measured using a non-contact optical measurement method.

7. The equipment status monitoring system for metal powder production according to claim 1, characterized in that, The sensor module also includes a dust concentration sensor, which is used to collect dust concentration data of the environment in which the metal powder production equipment is located. The early warning display unit is also used to generate environmental early warning signals based on the dust concentration data of the environment in which the metal powder production equipment is located.

8. The equipment status monitoring system for metal powder production according to claim 7, characterized in that, The environmental early warning methods are as follows: Obtain the pre-set dust concentration safety threshold based on the critical concentration for dust explosion and the safety standards of the production environment, and compare it with the current dust concentration data of the environment where the metal powder production equipment is located: If the current dust concentration data is greater than or equal to the dust concentration safety threshold, it indicates that there is a potential risk of dust explosion in the environment where the metal powder production equipment is located, and an environmental warning signal is generated; otherwise, no environmental warning signal is generated.

9. The equipment status monitoring system for metal powder production according to claim 8, characterized in that, Environmental early warning methods also include the following: Acquire the dust concentration data of the environment where the metal powder production equipment is located at the current time point and the dust concentration data at the previous time point; where the time interval between the current time point and the previous time point is Tr, and Tr is a preset value; The dust concentration data at the current time point is then subtracted from the dust concentration data at the previous time point, and the result is divided by the time interval Tr to obtain the rate of change of the dust concentration at the current time point. This rate of change is then compared with a pre-set threshold. If the rate of change of dust concentration is greater than or equal to the rate of change threshold, it indicates that there is a potential risk of dust explosion in the environment where the metal powder production equipment is located, and an environmental warning signal is generated; otherwise, no environmental warning signal is generated.

10. The equipment status monitoring system for metal powder production according to claim 9, characterized in that, If either the rate of change of dust concentration data is greater than or equal to the rate of change threshold or the current dust concentration data is greater than or equal to the dust concentration safety threshold, it indicates that there is a potential risk of dust explosion in the environment where the metal powder production equipment is located, and an environmental warning signal is generated.

Images