Unipol polypropylene process reactor block material detection system and method

Abstract

The invention discloses a Unipol polypropylene process reactor block material detection system and method, and the system comprises a polypropylene block material and a reactor, and also comprises a sound wave detection module and a vibration detection module; the sound wave detection module comprises at least two ultrasonic detectors, and the ultrasonic detectors are axially distributed along the outer wall of the reactor and are used for collecting sound wave signals of material flowing in the reactor; the vibration detection module comprises at least two vibration sensors, and the vibration sensors are distributed in the circumferential direction of the outer wall of the reactor and used for monitoring the vibration frequency of the outer wall of the reactor. Real-time detection: through collaborative analysis of sound wave, vibration and temperature data, early warning can be triggered at the initial stage of block material formation, and the time is advanced by more than 30% compared with the prior art; accurate positioning: multi-sensor three-dimensional layout is combined with algorithm optimization, a block material area can be accurately positioned, and the false alarm rate is reduced; efficient cleaning is achieved, an early warning system is linked with the cleaning process, the reducing cleaning time is greatly shortened, and shutdown losses are reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of polypropylene production, and particularly relates to a block detection system and method for a Unipol polypropylene process reactor. Background Art

[0002] The Unipol polypropylene process is a fluidized bed process widely used in polypropylene production. Its reaction system mainly includes a reactor, a recycle gas compressor, and a recycle gas cooler. The recycle gas enters the reactor under the action of the compressor to drive the powder in the reactor to fluidize, so as to achieve a good fluidization state. In the propylene polymerization reaction, the heat generated by the exothermic reaction needs to be removed in time through the recycle gas cooler. However, when the heat removal is incomplete or the reaction is abnormal, polypropylene block materials are likely to be generated in the reactor, resulting in system fluctuations and even equipment blockages.

[0003] The prior art mainly deals with the block material problem in the following ways: Variable-diameter pipeline interception: When the block materials generated by the polymerization reaction are small, a variable-diameter structure is set on the pipeline of the reactor discharge system to intercept the block materials physically. However, this method needs to be cleaned frequently, with low efficiency and potential safety hazards; Fluidization density detection: The fluidization density is calculated based on the pressure difference, but it is easily interfered by parameters such as gas density and pressure. When the fluidization density fluctuates, the pressure fluctuates, and the gas density fluctuates, it is impossible to accurately judge the generation of block materials; Electrostatic detection: Block materials are detected through a single electrostatic probe, but the propylene raw material suppresses the electrostatic signal, and there is only one electrostatic probe in the reactor. Conventional reactors are large in size, usually with a diameter exceeding 5 meters and a height exceeding 20 meters, and the probe coverage is limited, resulting in significant detection lag.

[0004] The above methods have the following defects: Detection lag: The block materials cannot be discovered in time after they are formed, resulting in the expansion of abnormal reactions; Inefficient cleaning: The cleaning process of the variable-diameter structure is complex, and the shutdown time is long; High false alarm rate: The fluidization density and electrostatic detection are easily interfered by other parameters, making it difficult to accurately locate the problem.

[0005] Therefore, the present invention provides a block detection system and method for a Unipol polypropylene process reactor to solve the problems raised in the above background art. Summary of the Invention

[0006] Aiming at the problems raised in the above background art, the object of the present invention is to provide a block detection system and method for a Unipol polypropylene process reactor, which has the effects of low false alarm rate, timely detection, and efficient cleaning.

[0007] To achieve the above technical object, the technical solution adopted by the present invention is as follows:

[0008] A block detection system for a Unipol polypropylene process reactor includes polypropylene block materials and a reactor, and further includes an acoustic wave detection module and a vibration detection module;

[0009] The acoustic wave detection module includes at least two ultrasonic detectors axially distributed along the outer wall of the reactor for collecting acoustic wave signals of the material flow in the reactor; the vibration detection module includes at least two vibration sensors circumferentially distributed along the outer wall of the reactor for monitoring the vibration frequency of the outer wall of the reactor.

[0010] It is further defined that a temperature monitoring module is also included, and the temperature monitoring module is integrated with temperature sensors on the inner wall of the reactor for obtaining temperature data of different regions of the reactor in real time.

[0011] It is further defined that a data processing unit is also included. The data processing unit is respectively connected to the temperature monitoring module, the acoustic wave detection module and the vibration detection module. The data processing unit is used to receive acoustic wave, vibration and temperature signals, and analyze and judge the position and scale of the polypropylene bulk material generated through algorithms.

[0012] It is further defined that the ultrasonic detector includes a first ultrasonic detector and a second ultrasonic detector. Both the first ultrasonic detector and the second ultrasonic detector are axially distributed along the outer wall of the reactor, and the first ultrasonic detector is arranged above the second ultrasonic detector.

[0013] It is further defined that the vibration detection module includes a first vibration sensor and a second vibration sensor. Both the first vibration sensor and the second vibration sensor are circumferentially distributed along the outer wall of the reactor, and the first vibration sensor is arranged above the second vibration sensor.

[0014] It is further defined that the installation distance between the first ultrasonic detector and the second ultrasonic detector is / ~ / of the height of the reactor. Such a structural design can cover the area with the largest fluctuation of the fluidization density of the reactor.

[0015] It is further defined that the installation positions of the first vibration sensor and the second vibration sensor are staggered with those of the first ultrasonic detector and the second ultrasonic detector. Such a structural design can facilitate the formation of a three-dimensional detection network.

[0016] A method for detecting polypropylene bulk material in a Unipol polypropylene process reactor includes the following steps:

[0017] Step 1: Collect acoustic wave signals of the material flow in the reactor through the acoustic wave detection module and analyze the acoustic wave spectrum characteristics.

[0018] Step 2: Obtain the vibration frequency of the outer wall of the reactor through the vibration detection module and judge whether the material flow is abnormal in combination with the acoustic wave signals.

[0019] Step 3: Synchronously obtain the data of the temperature monitoring module, and trigger a warning for bulk materials when the temperature locally rises abnormally;

[0020] Step 4: Based on the multi-source data fusion algorithm, determine the position and size of the bulk materials, and generate a cleaning instruction.

[0021] Further defined, the multi-source data fusion algorithm includes weighted analysis of acoustic signals and vibration signals and temporal matching of temperature trends.

[0022] Advantages of the present invention:

[0023] 1. Real-time detection: Through the collaborative analysis of acoustic, vibration and temperature data, a warning can be triggered at the initial stage of the formation of bulk materials, which is more than 30% earlier than the prior art;

[0024] 2. Precise positioning: The three-dimensional layout of multiple sensors combined with algorithm optimization can accurately locate the bulk material area with an error ≤ ±0.5 m, reducing the false alarm rate;

[0025] 3. Efficient cleaning: The warning system is linked with the cleaning process, greatly shortening the cleaning time for diameter change and reducing the downtime loss;

[0026] 4. Data traceability: Completely record the changes in process parameters before the generation of bulk materials, providing data support for subsequent process optimization. Description of the drawings

[0027] The present invention can be further illustrated by the non-limiting embodiments given in the drawings;

[0028] Figure 1 It is a schematic structural diagram of an embodiment of a bulk material detection system and method for a Unipol polypropylene process reactor of the present invention;

[0029] Figure 2 It is a schematic ultrasonic detection diagram of an embodiment of a bulk material detection system and method for a Unipol polypropylene process reactor of the present invention;

[0030] Figure 3 It is a schematic vibration detection diagram of an embodiment of a bulk material detection system and method for a Unipol polypropylene process reactor of the present invention.

[0031] Main component symbol descriptions are as follows: First ultrasonic detector 1, second ultrasonic detector 2, first vibration sensor 3, second vibration sensor 4, polypropylene bulk material 5, reactor 6, temperature sensor 7. Detailed implementation manners

[0032] In order to enable those skilled in the art to better understand the present invention, the technical solution of the present invention will be further described below in conjunction with the accompanying drawings and embodiments. The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0033] It should be noted that all directional indications (such as up, down, left, right, front, back...) in the embodiments of the present invention are only used to explain the relative position relationship and movement conditions between components in a specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0034] In addition, the descriptions involving "first", "second", etc. in the present invention are only for descriptive purposes, and cannot be understood as indicating or implying their relative importance or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one of such features. In addition, the technical solutions between various embodiments can be combined with each other, but it must be based on the ability of those of ordinary skill in the art to implement. When the combination of technical solutions results in contradictions or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the protection scope required by the present invention. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0035] As Figures 1 - 3 shown, a block material detection system for a Unipol polypropylene process reactor of the present invention includes polypropylene block material 5 and reactor 6, and further includes an acoustic wave detection module and a vibration detection module;

[0036] The acoustic wave detection module includes at least two ultrasonic detectors axially distributed along the outer wall of reactor 6 for collecting acoustic wave signals of the material flow in reactor 6; the vibration detection module includes at least two vibration sensors circumferentially distributed along the outer wall of reactor 6 for monitoring the vibration frequency of the outer wall of reactor 6.

[0037] In the actual application of this embodiment, a temperature monitoring module is further included, and the temperature monitoring module is integrated with a temperature sensor on the inner wall of reactor 6 for obtaining temperature data of different regions of reactor 6 in real time.

[0038] In the practical application of this embodiment, it further includes a data processing unit, which is respectively connected to the temperature monitoring module, the acoustic wave detection module, and the vibration detection module. The data processing unit is used to receive acoustic wave, vibration, and temperature signals, and determine the position and scale of the polypropylene bulk material 5 through algorithm analysis and judgment.

[0039] In the practical application of this embodiment, the ultrasonic detector includes a first ultrasonic detector 1 and a second ultrasonic detector 2. The first ultrasonic detector 1 and the second ultrasonic detector 2 are both axially distributed along the outer wall of the reactor 6, and the first ultrasonic detector 1 is arranged above the second ultrasonic detector 2.

[0040] In the practical application of this embodiment, the vibration detection module includes a first vibration sensor 3 and a second vibration sensor 4. The first vibration sensor 3 and the second vibration sensor 4 are both circumferentially distributed along the outer wall of the reactor 6, and the first vibration sensor 3 is arranged above the second vibration sensor 4.

[0041] In the practical application of this embodiment, the installation distance between the first ultrasonic detector 1 and the second ultrasonic detector 2 is 1 / 5 to 1 / 3 of the height of the reactor 6. Such a structural design can cover the area with the largest fluctuation in the fluidization density of the reactor 6.

[0042] In the practical application of this embodiment, the installation positions of the first vibration sensor 3 and the second vibration sensor 4 are staggered with those of the first ultrasonic detector 1 and the second ultrasonic detector 2. Such a structural design can facilitate the formation of a three-dimensional detection network.

[0043] A method for detecting bulk materials in a Unipol polypropylene process reactor includes the following steps:

[0044] Step 1: Collect the acoustic wave signals of the material flow in the reactor 6 through the acoustic wave detection module, and analyze the acoustic wave spectrum characteristics.

[0045] Step 2: Obtain the vibration frequency of the outer wall of the reactor 6 through the vibration detection module, and combine the acoustic wave signals to judge whether the material flow is abnormal.

[0046] Step 3: Synchronously obtain the data of the temperature monitoring module, and trigger a bulk material warning when the temperature locally rises abnormally.

[0047] Step 4: Based on the multi-source data fusion algorithm, determine the position and size of the bulk materials, and generate a cleaning instruction.

[0048] In the practical application of this embodiment, the multi-source data fusion algorithm includes the weighted analysis of acoustic wave signals and vibration signals and the temporal matching of temperature trends.

[0049] Example 1:

[0050] Acoustic wave detector: The first ultrasonic detector 1 is installed at 1 / 4 of the height from the bottom of the reactor 6, and the second ultrasonic detector 2 is installed in the middle of the reactor 6. Specifically, the ultrasonic detector uses the SDT170 ultrasonic detector, which is suitable for ultrasonic detection in industrial environments, can effectively collect acoustic wave signals, and is suitable for monitoring the material flow in the polypropylene reactor.

[0051] Vibration sensor: The first vibration sensor 3 is located at the 90° position in the circumferential direction of the outer wall of the reactor 6, and the second vibration sensor 4 is located at the 270° position. Specifically, the vibration sensor uses the VibRunner vibration and noise test and analysis system, which can collect vibration response signals, and can collect up to 32 signals simultaneously, and is suitable for monitoring the vibration frequency of the outer wall of the polypropylene reactor.

[0052] Temperature sensor: Four thermocouples are arranged along the inner wall of the reactor 6 at an interval of 2m to cover the high-temperature risk area.

[0053] Detection process:

[0054] Acoustic wave signal acquisition: The first ultrasonic detector 1 and the second ultrasonic detector 2 scan at a frequency of 20 kHz to capture the acoustic wave characteristics of the material flow (as Figure 2 shown, the acoustic wave amplitude in the bulk material area is significantly reduced);

[0055] Vibration signal analysis: The detection frequency range of the first vibration sensor 3 and the second vibration sensor 4 is 10 - 1000 Hz, and a low-frequency peak appears in the vibration spectrum when the bulk material is formed (as Figure 3 shown);

[0056] Temperature trend matching: When the local temperature rises above the set threshold (the set threshold is 5℃ / min), a warning is triggered;

[0057] Data fusion and decision-making: The data processing unit synthesizes the acoustic wave attenuation rate, vibration frequency shift, and temperature gradient to determine the position of the bulk material (the area shown by the polypropylene bulk material 5), and automatically starts the cleaning program.

[0058] Specifically, the data processing unit in the first embodiment uses the AMD EPYC series processors. The AMD EPYC series is a server-level processor designed for data centers and high-performance computing, with a high number of cores and threads, and can efficiently process parallel computing tasks. Specifically, the EPYC 7742 is used, which has 64 physical cores and 128 threads, supports PCIe 4.0 and high-speed memory, and is suitable for large-scale data processing.

[0059] Embodiment 2:

[0060] Acoustic wave detector: The first ultrasonic detector 1 is installed at the 1 / 5 height of the bottom of the reactor 6, and the second ultrasonic detector 2 is installed at the 1 / 3 height of the reactor 6; specifically, the ultrasonic detector uses the SDT170 ultrasonic detector, which is suitable for ultrasonic detection in industrial environments, can effectively collect acoustic wave signals, and is suitable for monitoring the material flow in the polypropylene reactor.

[0061] Vibration sensor: The first vibration sensor 3 is located at the 180° circumferential position of the outer wall of the reaction 6, and the second vibration sensor 4 is located at the 270° position; specifically, the vibration sensor uses the VibRunner vibration noise test and analysis system, which can collect vibration response signals and can collect up to 32 signals simultaneously, and is suitable for monitoring the vibration frequency of the outer wall of the polypropylene reactor.

[0062] Temperature sensor: Six thermocouples are arranged along the inner wall of the reactor 6 at an interval of 1.5 m to cover the high-temperature risk area.

[0063] Detection process:

[0064] Acoustic wave signal acquisition: The first ultrasonic detector 1 and the second ultrasonic detector 2 scan at a frequency of 20 kHz to capture the acoustic wave characteristics of the material flow (as Figure 2 shown, the acoustic wave amplitude in the bulk material area is significantly reduced);

[0065] Vibration signal analysis: The detection frequency range of the first vibration sensor 3 and the second vibration sensor 4 is 10 - 1000 Hz, and a low-frequency peak appears in the vibration spectrum when the bulk material is formed (as Figure 3 shown);

[0066] Temperature trend matching: When the local temperature rises above the set threshold (the set threshold is 4 °C / min), a warning is triggered;

[0067] Data fusion and decision-making: The data processing unit comprehensively considers the acoustic wave attenuation rate, vibration frequency shift, and temperature gradient to determine the position of the bulk material (the area shown by the polypropylene bulk material 5), and automatically starts the cleaning program.

[0068] Specifically, the data processing unit in the second embodiment uses the AMD Ryzen Threadripper series processors. The AMD Ryzen Threadripper series is a desktop processor designed for high-performance computing and big data processing, with multi-core and multi-thread technologies. Specifically, the Threadripper 5950X is used, which has 16 cores and 32 threads, is suitable for complex computing tasks, and has a more obvious cost advantage for the device.

[0069] Example three:

[0070] Acoustic Wave Detector: The first ultrasonic detector 1 is installed at half of the height at the bottom of the reactor 6, and the second ultrasonic detector 2 is installed at the bottom of the reactor 6. Specifically, the ultrasonic detector uses the SDT170 ultrasonic detector, which is suitable for ultrasonic detection in industrial environments, can effectively collect acoustic wave signals, and is suitable for monitoring the material flow in the polypropylene reactor.

[0071] Vibration Sensor: The first vibration sensor 3 is located at the 90° position in the circumferential direction of the outer wall of the reactor 6, and the second vibration sensor 4 is located at the 270° position. Specifically, the vibration sensor uses the VibRunner vibration noise test and analysis system, which can collect vibration response signals and can collect up to 32 signals simultaneously, and is suitable for monitoring the vibration frequency of the outer wall of the polypropylene reactor.

[0072] Temperature Sensor: Eight thermocouples are arranged along the inner wall of the reactor 6 at an interval of 1 m to cover the high-temperature risk area.

[0073] Detection Process:

[0074] Acoustic Wave Signal Acquisition: The first ultrasonic detector 1 and the second ultrasonic detector 2 scan at a frequency of 20 kHz to capture the acoustic wave characteristics of the material flow (as Figure 2 shown, the acoustic wave amplitude in the bulk material area is significantly reduced);

[0075] Vibration Signal Analysis: The detection frequency range of the first vibration sensor 3 and the second vibration sensor 4 is 10 - 1000 Hz, and a low-frequency peak appears in the vibration spectrum when the bulk material is formed (as Figure 3 shown);

[0076] Temperature Trend Matching: When the local temperature rises above the set threshold (the set threshold is 5 °C / min), a warning is triggered;

[0077] Data Fusion and Decision: The data processing unit synthesizes the acoustic wave attenuation rate, vibration frequency shift, and temperature gradient to determine the position of the bulk material (the area shown by the polypropylene bulk material 5), and automatically starts the cleaning program.

[0078] Specifically, the data processing unit in Embodiment 3 uses an Intel Xeon series processor. The Intel Xeon series processor is a common choice for servers and workstations, has powerful multi-core processing capabilities and high reliability. Specifically, Xeon Platinum 9282 is used, which has 56 physical cores and 112 threads, and uses a 4D Mesh architecture, suitable for high-performance computing.

[0079] The above embodiments are only used to exemplarily illustrate the principles and effects of the present invention, rather than to limit the present invention. Any person familiar with this technology can modify or change the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or changes completed by those with ordinary knowledge in the technical field without departing from the spirit and technical ideas disclosed by the present invention should still be covered by the claims of the present invention.

Claims

1. A Unipol polypropylene process reactor block detection system, comprising a polypropylene block (5) and a reactor (6), characterized in that: It also includes a sound wave detection module and a vibration detection module; The sound wave detection module comprises at least two ultrasonic detectors, which are axially distributed along the outer wall of the reactor (6) and are used to collect sound wave signals of material flow in the reactor (6); the vibration detection module comprises at least two vibration sensors, which are circumferentially distributed along the outer wall of the reactor (6) and are used to monitor the vibration frequency of the outer wall of the reactor (6).

2. A Unipol polypropylene process reactor block detection system according to claim 1, characterized in that: It also comprises a temperature monitoring module, wherein the temperature monitoring module is integrated with a temperature sensor on the inner wall of the reactor (6) and is used to obtain temperature data of different areas of the reactor (6) in real time.

3. A Unipol polypropylene process reactor block detection system according to claim 1, characterized in that: It also includes a data processing unit, which is connected to the temperature monitoring module, the sound wave detection module and the vibration detection module respectively. The data processing unit is used to receive sound wave, vibration and temperature signals, and to determine the location and scale of the polypropylene block (5) through algorithm analysis.

4. A Unipol polypropylene process reactor block detection system according to claim 1, characterized in that: The ultrasonic detector comprises a first ultrasonic detector (1) and a second ultrasonic detector (2), wherein the first ultrasonic detector (1) and the second ultrasonic detector (2) are both distributed axially along the outer wall of the reactor (6), and the first ultrasonic detector (1) is arranged above the second ultrasonic detector (2).

5. A Unipol polypropylene process reactor block detection system according to claim 4, characterized in that: The vibration detection module comprises a first vibration sensor (3) and a second vibration sensor (4), wherein the first vibration sensor (3) and the second vibration sensor (4) are both distributed along the circumference of the outer wall of the reactor (6), and the first vibration sensor (3) is arranged above the second vibration sensor (4).

6. A Unipol polypropylene process reactor block detection system according to claim 4, characterized in that: The installation distance between the first ultrasonic detector (1) and the second ultrasonic detector (2) is 1 / 5 to 1 / 3 of the height of the reactor (6).

7. A Unipol polypropylene process reactor block detection system according to claim 5, characterized in that: The installation positions of the first vibration sensor (3) and the second vibration sensor (4) are staggered with the first ultrasonic detector (1) and the second ultrasonic detector (2).

8. A method for detecting bulk material of a Unipol polypropylene process reactor, characterized in that: The steps include: Step 1: Collect the acoustic wave signal of the material flow in the reactor (6) through the acoustic wave detection module and analyze the acoustic wave spectrum characteristics Step 2: obtaining the vibration frequency of the outer wall of the reactor (6) through the vibration detection module, and judging whether the material flow is abnormal in combination with the sound wave signal; Step 3: synchronously obtain the data of the temperature monitoring module, and trigger a block material warning when the temperature rises abnormally locally; Step 4: Based on the multi-source data fusion algorithm, determine the location and size of the block material and generate cleaning instructions.

9. A Unipol polypropylene process reactor block detection method according to claim 8, characterized in that: The multi-source data fusion algorithm includes weighted analysis of acoustic wave signals and vibration signals and time series matching of temperature trends.

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