A rice crushing machine automatic control method and system

Abstract

The present invention relates to the field of automatic control technology, and in particular to an automatic control method and system for a rice crusher, comprising: obtaining a feature data sequence of the rice crusher at the current moment and at a plurality of previous consecutive moments, comparing the feature data at the current moment with the feature data in its corresponding feature data sequence, and calculating a floating value at the current moment; then, calculating a state parameter at the current moment based on the floating value; calculating an abnormal value of the rice crusher at the current moment based on the state parameter at the moment corresponding to the feature data at the current moment and the similarity between the feature data in the feature data sequence corresponding to the current moment, and then judging whether the device is in an abnormal working state, and automatically controlling the rice crusher to stop running in response to the abnormal value being greater than a set threshold. The present invention solves the problem of reduced rice quality due to increased equipment loss of the rice crusher.

Description

Technical Field

[0001] The present invention relates to the field of automatic control technology, and more specifically, to an automatic control method and system for a rice crushing machine. Background Art

[0002] With the rapid development of agricultural mechanization and automation technology, rice crushing equipment occupies an important position in the modern grain processing industry. As an indispensable equipment in the rice processing process, the performance and working status of the rice crusher are directly related to the quality of rice and processing efficiency. However, most of the existing rice crusher control methods rely on manual operation or are based on simple automation control technology, which fails to fully cope with complex and changeable working environments and production conditions. This limitation greatly affects the stability, efficiency and operational safety of the equipment.

[0003] More importantly, the existing automatic control system of rice crushers also has certain deficiencies in terms of safety. When the equipment is in an abnormal state, such as overheating, excessive vibration, or excessive inlet and outlet, the system fails to detect in time and take effective measures. In this case, the continued operation of the equipment may not only cause damage to the equipment itself, but also pose a potential safety threat to the operator. In addition, long-term abnormal operation will also affect the rice milling effect, resulting in a decrease in the yield of rice and damage to the economic interests of users. Therefore, the lack of perfect abnormality detection is a major defect of the existing technical solution.

[0004] The patent application document with application publication number CN113450498A discloses a rice milling control method, device and system for an intelligent rice milling vending machine. The patent application document includes: obtaining the first position information of the current location of the user terminal; sending the first position information to the server; taking the first position as the center and the preset distance as the radius, obtaining the second position information and service function information of the rice milling equipment within the radius; generating rice milling order information, and sending the rice milling order information to the server; wherein the server sends an instruction to control the rice milling equipment to perform rice milling operations according to the rice milling order information. However, although the above technical solution realizes the automatic control of the rice milling equipment, it does not fully consider the impact of the dynamic changes of the equipment environment and working status on the safety of the equipment. This neglect may cause safety hazards when the equipment is running in harsh or abnormal environments, thereby affecting the rice breaking effect, thereby leading to the problem of reduced rice breaking quality due to increased equipment loss. Summary of the invention

[0005] In order to solve the problem that the dynamic changes of equipment environment and working status on equipment safety are not fully considered in the above background technology, and the quality of broken rice is reduced due to increased equipment loss, the present invention provides solutions in the following aspects.

[0006] In a first aspect, the present invention provides an automatic control method for a rice crusher, comprising: obtaining a characteristic data sequence of the rice crusher at a current moment and a plurality of previous consecutive moments; calculating a floating value at a current moment, wherein the floating value is positively correlated with the characteristic data at the current moment and negatively correlated with the absolute value of the difference between the characteristic data at the current moment and the characteristic data in the corresponding characteristic data sequence; and calculating a state parameter at the current moment based on the floating value:

[0007] ;

[0008] In the formula, For the The state parameters at a moment, For the The moment corresponds to the first The floating value of each feature data at the corresponding moment, For the The floating value at the moment corresponding to the first feature data in the feature data sequence at the moment corresponding to the feature data, For the The maximum value of the floating values ​​of all the feature data at the corresponding moment in the feature data sequence corresponding to the moment; the abnormal value at the current moment is calculated, and the abnormal value is positively correlated with the state parameters of all the feature data at the corresponding moment in the feature data sequence corresponding to the current moment, and is negatively correlated with the similarity between the two feature data in the feature data sequence corresponding to the current moment; in response to the abnormal value being greater than the set threshold value, the rice crushing machine is automatically controlled to stop running.

[0009] The above technical solution realizes dynamic monitoring and abnormality detection of the equipment operation status by calculating the floating value and state parameters at the current moment; at the same time, by calculating the relationship between the abnormal value and the state parameters and the similarity of the characteristic data, accurate fault warning and intelligent control are realized, thereby solving the problem of the deterioration of the broken rice quality due to the increased equipment wear of the rice breaking machine.

[0010] Furthermore, the floating value is:

[0011] ;

[0012] In the formula, For the The floating value at a moment, For the The characteristic data at each moment, For the The moment corresponds to the first feature data, For the Each moment corresponds to the number of feature data in the feature data sequence, and || is the absolute value.

[0013] The above technical solution defines the floating value as the difference between the average absolute difference of the current feature data and its corresponding feature data sequence, thereby enhancing the sensitivity to changes in the equipment's operating status. This precise floating value calculation method can more effectively capture the fluctuations in feature data, thereby providing a more reliable basis for anomaly detection. This dynamic evaluation mechanism enables the rice crusher to respond promptly to potential faults, optimizes the equipment's operating safety and stability, and thus improves overall production efficiency.

[0014] Furthermore, the characteristic data includes: temperature data, vibration data or material input and output data of the rice crushing machine.

[0015] Furthermore, the abnormal value is:

[0016] ;

[0017] In the formula, For the The outlier value at a moment, For the The state parameters at a moment, For the The sum of the variances of the state parameters of all feature data at the corresponding time in the feature data sequence corresponding to the time, For the The average value of the similarity between each pair of feature data in the feature data sequence corresponding to each moment.

[0018] The above technical solution improves the detection accuracy of equipment operation anomalies by defining the anomaly value as a combination of state parameters, state parameter variance and feature data similarity. The calculation method of the anomaly value effectively combines the change range of the current state and its similarity with other feature data, ensuring timely and accurate identification when potential faults occur. This mechanism not only improves the fault warning capability of the rice crusher, but also optimizes the efficiency of equipment maintenance and management, reduces the risk of downtime due to faults, and thus enhances the safety and stability of the overall production process.

[0019] Furthermore, the dynamic time warping algorithm is used to calculate the similarity between each pair of feature data.

[0020] The above technical solution significantly improves the accuracy and flexibility of feature data comparison. The dynamic time warping algorithm can effectively handle the deformation and time delay of different time series, so that even when the data collection frequency or time point is inconsistent, the similarity of feature data can still be accurately evaluated, providing a more reliable basis for anomaly detection, so that the rice crushing machine can more sensitively identify potential problems during operation.

[0021] Furthermore, it also includes: performing data denoising and data normalization processing on the feature data.

[0022] Furthermore, the temperature data of the rice crushing machine is collected by a temperature sensor, the vibration data of the rice crushing machine is collected by a vibration sensor, and the material input and output data of the rice crushing machine is collected by a photoelectric sensor.

[0023] Furthermore, the automatic control of the rice crushing machine to stop operation is specifically as follows:

[0024] In response to the abnormal value being greater than the set threshold, a stop command is sent to the control system of the rice crushing machine. After receiving the stop command, the control system gradually reduces the running speed of the rice crushing machine until it stops, and at the same time turns off the driving power supply and sends a fault alarm signal to remind the operator.

[0025] The above technical solution ensures the safe shutdown process of the equipment by sending a gradual stop command to the rice crusher control system when the abnormal value exceeds the set threshold. This measure not only effectively reduces the risk of equipment damage caused by sudden failures, but also promptly notifies the operator by issuing a fault alarm signal, thereby enhancing the controllability and safety of the equipment. In addition, the design of gradually reducing the operating speed helps to smoothly shut down the machine, avoiding the operational risks that may be caused by sudden shutdown, thereby improving the overall safety management level and production efficiency of the rice crusher.

[0026] In a second aspect, the present invention provides an automatic control system for a rice crushing machine, comprising a memory and a processor, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, any one of the above-mentioned automatic control methods for a rice crushing machine is implemented.

[0027] The beneficial effects of the present invention are:

[0028] The present invention significantly improves the safety and operating efficiency of the rice crusher by combining dynamic monitoring of feature data sequences, floating value calculation, abnormal value analysis and intelligent control mechanism. It can acquire and process feature data at multiple times in real time, accurately calculate the state parameters and abnormal values ​​of the equipment, and enhance the similarity comparison between feature data through dynamic time warping algorithm. This system not only realizes the rapid identification and early warning of faults, but also ensures the safety of operators and the stable operation of equipment through the gradual cessation of operation and fault alarm mechanism, thereby optimizing the automation control and management level of the rice crusher and reducing the risk of downtime and maintenance costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] By reading the following detailed description with reference to the accompanying drawings, the above and other objects, features and advantages of the exemplary embodiments of the present invention will become readily understood. In the accompanying drawings, several embodiments of the present invention are shown in an exemplary and non-limiting manner, and the same or corresponding reference numerals represent the same or corresponding parts, wherein:

[0030] Figure 1 is a flow chart schematically showing an automatic control method for a rice crushing machine according to an embodiment of the present invention;

[0031] Figure 2 The figure schematically shows a structural block diagram of an automatic control system for a rice crushing machine according to an embodiment of the present invention. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0033] The specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0034] An embodiment of an automatic control method for a rice crushing machine.

[0035] like Figure 1 As shown, a flow chart of an automatic control method for a rice crushing machine according to an embodiment of the present invention comprises the following steps:

[0036] S1: Obtain the characteristic data sequence of the rice crusher at the current moment and multiple consecutive moments before it.

[0037] In one embodiment, the characteristic data includes temperature data, vibration data or material inlet and outlet data of the rice crusher. The collection and processing of these data are intended to comprehensively monitor and evaluate the operating status of the equipment.

[0038] First, the temperature sensor is used to collect the temperature data of the rice crusher in real time. Temperature is an important indicator for evaluating the thermal status of the equipment. Too high a temperature may cause the equipment to overheat, affecting its performance and life. Therefore, continuous monitoring of temperature changes helps to detect potential problems in a timely manner and take corresponding cooling measures.

[0039] Secondly, vibration sensors are used to collect vibration data from the rice crusher. Vibration data is a key parameter for evaluating the operating stability of the equipment and identifying faults. By analyzing the vibration signal, it can be determined whether the equipment is in normal operation or whether there is a risk of failure such as wear and looseness. Therefore, monitoring vibration data can provide early warning and prevent unexpected downtime.

[0040] In addition, photoelectric sensors are used to monitor the inlet and outlet data of the rice crusher in real time to ensure that the material flow is normal. The inlet and outlet data not only reflects the production efficiency, but also helps optimize the material handling process and avoid production stagnation caused by material blockage or shortage.

[0041] In terms of data processing, the collected feature data is first denoised to reduce the impact of environmental interference and sensor errors on the data. Denoising can use filtering techniques, such as mean filtering or median filtering, to ensure the stability and reliability of the data. Secondly, data normalization is performed to convert feature data of different dimensions into a unified range. This process helps to eliminate dimensional differences between data, making subsequent analysis and comparison more intuitive and effective.

[0042] The feature data at the current moment and multiple consecutive moments therebetween constitute a set of feature data sequences.

[0043] Exemplarily, taking temperature data as an example, assuming that the temperature data of the rice crushing machine at time T5 and the temperature data T4, T3 and T2 at three times before time T5 are collected, the temperature data sequence {T2, T3, T4, T5} at time T5 can be obtained.

[0044] S2: Calculate the floating value at the current moment based on the comparison between the feature data at the current moment and the feature data in the corresponding feature data sequence.

[0045] In one embodiment, the floating values ​​are:

[0046] ;

[0047] In the formula, For the The floating value at a moment, For the The characteristic data at each moment, For the The moment corresponds to the first feature data, For the Each moment corresponds to the number of feature data in the feature data sequence, and || is the absolute value.

[0048] Exemplarily, taking temperature data as an example, assuming that the temperature data of the rice crushing machine at time T5 and the temperature data T4, T3 and T2 at three times before time T5 are collected, the above parameters are substituted into the calculation formula to obtain the floating value at time T5.

[0049] S3: Calculate the state parameter at the current moment based on the floating value, and calculate the abnormal value of the rice crushing machine at the current moment based on the similarity between the state parameter and the pairwise feature data in the feature data sequence.

[0050] In one embodiment, the state parameter is:

[0051] ;

[0052] In the formula, For the The state parameters at a moment, For the The moment corresponds to the first The floating value of each feature data at the corresponding moment, For the The floating value at the moment corresponding to the first feature data in the feature data sequence at the moment corresponding to the feature data, For the The maximum value of the floating value of all feature data at the corresponding moment in the feature data sequence at the corresponding moment;

[0053] The abnormal values ​​are:

[0054] ;

[0055] In the formula, For the The outlier value at a moment, For the The state parameters at a moment, For the The sum of the variances of the state parameters of all feature data at the corresponding time in the feature data sequence corresponding to the time, For the The average value of the similarity between each pair of feature data in the feature data sequence corresponding to each moment.

[0056] It should be noted that the dynamic time warping algorithm can be used to calculate the similarity between two feature data. Of course, the cosine similarity algorithm can also be used to obtain the similarity between two feature data, providing a more accurate and reliable basis for the status monitoring and anomaly detection of rice crushing machine equipment.

[0057] S4: In response to the abnormal value being greater than the set threshold, the rice crushing machine is automatically controlled to stop running.

[0058] In one embodiment, when the detected abnormal value exceeds a preset threshold, the system will automatically control the rice crusher to stop running to ensure the safety and stability of the device. Specifically, the set threshold can be set to 0.3. Of course, in actual applications, it can be adjusted and optimized according to the specific operating status and environmental conditions of the device to ensure the best response sensitivity. And the rice crusher is automatically controlled to stop running, specifically:

[0059] In response to an abnormal value greater than the set threshold, a stop command is immediately sent to the control system of the rice crusher. The control system will gradually reduce the operating speed of the rice crusher instead of stopping it immediately to reduce the impact on the equipment. This process ensures that the equipment gradually slows down within a safe range through fine adjustment, reducing the risk of failure. As the operating speed gradually decreases to zero, the control system will automatically cut off the driving power of the rice crusher to ensure that the equipment no longer consumes energy when it is stopped. At the same time, in order to remind the operator in time, the system will issue a fault alarm signal to ensure that the operator can quickly identify and deal with potential problems.

[0060] The solution of the present invention realizes intelligent monitoring and safety control of the rice crusher. By acquiring and analyzing the characteristic data sequence in real time, calculating the floating value and state parameters, the abnormal state of the equipment can be accurately identified, and the accuracy of the similarity evaluation of the characteristic data can be improved through the dynamic time warping algorithm. At the same time, when an abnormality is detected, the system can automatically issue a stop command and gradually slow down, reducing the operational risk and enhancing the safety and stability of the equipment. In addition, through data denoising and normalization processing, the data quality is improved, and the reliability of abnormality detection is further optimized, thereby improving the overall production efficiency and management level of the rice crusher.

[0061] An embodiment of an automatic control system for a rice crushing machine:

[0062] like Figure 2 As shown, a structural block diagram of an automatic control system for a rice crushing machine according to an embodiment of the present invention includes a processor and a memory.

[0063] The present invention also provides an automatic control system for a rice crusher. Figure 2 As shown, the system includes a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the above-mentioned method for automatically controlling a rice crushing machine according to the present invention is implemented.

[0064] The automatic control system for a rice crushing machine also includes other components well known to those skilled in the art, such as a communication interface, and the configuration and functions of the components are known in the art, so they will not be described in detail here.

[0065] In the present invention, the aforementioned memory may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, apparatus or device. For example, a computer-readable storage medium may be any appropriate magnetic storage medium or magneto-optical storage medium, such as a resistive random access memory RRAM (Resistive Random Access Memory), a dynamic random access memory DRAM (Dynamic Random Access Memory), a static random access memory SRAM (Static Random-Access Memory), an enhanced dynamic random access memory EDRAM (Enhanced Dynamic Random Access Memory), a high-bandwidth memory HBM (High-Bandwidth Memory), a hybrid memory cube HMC (Hybrid Memory Cube), etc., or any other medium that can be used to store the required information and can be accessed by an application, a module, or both. Any such computer storage medium may be part of a device or accessible or connectable to a device. Any application or module described in the present invention may be implemented using computer-readable / executable instructions that may be stored or otherwise maintained by such a computer-readable medium.

[0066] In the description of this specification, "plurality" or "several" means at least two, such as two, three or more, etc., unless otherwise clearly and specifically defined.

[0067] Although this specification has shown and described a number of embodiments of the present invention, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Those skilled in the art will conceive of many modifications, changes and alternatives without departing from the ideas and spirit of the present invention. It should be understood that in the practice of the present invention, various alternatives to the embodiments of the present invention described herein may be employed.

Claims

1. A rice crushing machine automatic control method, characterized in that: include: Acquire a characteristic data sequence of the rice crushing machine at the current moment and at a plurality of previous consecutive moments, including: temperature data, vibration data or material inlet and outlet data of the rice crushing machine; Calculate the floating value at the current moment, ; In the formula, For the The floating value at a moment, For the The characteristic data at each moment, For the The jth feature data in the feature data sequence corresponds to each moment. For the Each moment corresponds to the number of feature data in the feature data sequence, and || is the absolute value; Calculate the current state parameter based on the floating value: ； In the formula, For the The state parameters at a moment, For the The floating value at the moment corresponding to the jth feature data in the feature data sequence at the moment corresponding to the jth feature data, For the The floating value at the moment corresponding to the first feature data in the feature data sequence at the moment corresponding to the feature data, For the The maximum value of the floating value of all feature data at the corresponding moment in the feature data sequence at the corresponding moment; Calculate the abnormal value at the current moment, the abnormal value is positively correlated with the state parameters of all feature data at the corresponding moment in the feature data sequence corresponding to the current moment, and is negatively correlated with the similarity between any two feature data in the feature data sequence corresponding to the current moment; In response to the abnormal value being greater than a set threshold, the rice crushing machine is automatically controlled to stop running.

2. The automatic control method of a rice crushing machine according to claim 1, characterized in that: The abnormal values ​​are: ； In the formula, For the The outlier value at a moment, For the The state parameters at a moment, For the The sum of the variances of the state parameters of all feature data at the corresponding time in the feature data sequence corresponding to the time, For the The average value of the similarity between each pair of feature data in the feature data sequence corresponding to each moment.

3. The automatic control method of a rice crushing machine according to claim 1, characterized in that: The dynamic time warping algorithm is used to calculate the similarity between two feature data.

4. The automatic control method of a rice crushing machine according to claim 1, characterized in that: Also includes: The feature data is subjected to data denoising and data normalization processing.

5. The automatic control method of a rice crushing machine according to claim 1, characterized in that: The temperature data of the rice crushing machine is collected by a temperature sensor, the vibration data of the rice crushing machine is collected by a vibration sensor, and the input and output data of the rice crushing machine is collected by a photoelectric sensor.

6. The automatic control method of a rice crushing machine according to claim 1, characterized in that: The automatic control of the rice crushing machine to stop operation is specifically as follows: In response to the abnormal value being greater than the set threshold, a stop command is sent to the control system of the rice crushing machine. After receiving the stop command, the control system gradually reduces the running speed of the rice crushing machine until it stops, and at the same time turns off the driving power supply and sends a fault alarm signal to remind the operator.

7. A rice crushing machine automatic control system, characterized in that: The invention comprises a memory and a processor, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the automatic control method of a rice crushing machine according to any one of claims 1 to 6 is implemented.

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