Intelligent monitoring system of vacuum decontamination equipment based on multi-data fusion

Abstract

The application discloses a vacuum decontamination equipment intelligent monitoring system based on multi-data fusion, which comprises a sensor installation module, a data acquisition module, a data analysis module, an intelligent control module and an intelligent monitoring module. The application belongs to the technical field of data processing and specifically relates to a vacuum decontamination equipment intelligent monitoring system based on multi-data fusion. The data analysis module is used for performing Kalman filter noise reduction on the collected data, and multi-parameter fusion is used for mining correlation trends. A three-level early warning mechanism is used to change the traditional post-fault processing into pre-warning and hierarchical intervention, so as to reduce the driving risk. The intelligent control module is used for performing three-level early warning judgment, an improved vacuum pump cooperative control algorithm is used for optimizing the start-stop logic of a plurality of pump groups, dynamic load distribution is performed, predictive start-stop is implemented in combination with demand fluctuation, the intelligent monitoring module is used for monitoring the real-time operation state of the system, and the decontamination unit hose recovery state monitoring function and the system low-power operation function are realized.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of data processing, and particularly relates to an intelligent monitoring system for vacuum sewage unloading equipment based on multi-data fusion. BACKGROUND

[0002] The intelligent monitoring system for vacuum sewage unloading equipment is a system that, taking multi-data fusion as the core, combining sensor perception, intelligent communication, data analysis and remote management and control technology, and monitoring the running state of railway vacuum sewage unloading equipment in real time, intelligently controlling and fault warning, aiming to comprehensively improve the fine management level of station and section equipment, and realizing the functions of intelligent control, remote intervention, energy saving and consumption reduction, safe communication and fault auxiliary processing of the vacuum sewage unloading system.

[0003] The traditional railway vacuum sewage unloading operation has the technical problems that the running data of the sewage unloading system is not collected and analyzed, potential faults cannot be identified through data trends, and only post-fault processing is available, resulting in resource waste and increased driving risk; the system does not have a logic of running on demand, needs to be turned on all the time, has high energy consumption, and has no unified monitoring system, relies on manual inspection, has no special technical monitoring of the hose recovery state, has the driving risk of driving with the hose, and cannot realize real-time perception and fine management and control of the equipment state. SUMMARY

[0004] In view of the above problems, in order to overcome the defects of the prior art, the intelligent monitoring system for vacuum sewage unloading equipment based on multi-data fusion provided by the application comprehensively collects the key running data of the sewage unloading unit and the vacuum unit through a data collection module, ensures real-time and accurate uploading of the data through multi-interface compatibility and safe transmission technology, performs Kalman filter noise reduction on the collected data through a data analysis module, mines the correlation trends through multi-parameter fusion, changes the traditional post-fault processing into pre-warning and graded intervention through a three-level early warning mechanism, and reduces the driving risk; in view of the technical problems that the system does not have a logic of running on demand, needs to be turned on all the time, has high energy consumption, has no unified monitoring system, relies on manual inspection, has no special technical monitoring of the hose recovery state, has the driving risk of driving with the hose, and cannot realize real-time perception and fine management and control of the equipment state, the intelligent control module is used to make a three-level early warning judgment, an improved vacuum pump cooperative control algorithm is used to optimize the start-stop logic of the multi-pump group, dynamically allocate the load, implement predictive start-stop in combination with demand fluctuation, link the soft start current and the load distribution coefficient to ensure state synchronization, and the intelligent monitoring module is used to monitor the real-time running state of the system, realize the hose recovery state monitoring function of the sewage unloading unit, and realize the low-power running function of the system.

[0005] The application provides a vacuum decontamination equipment intelligent monitoring system based on multi-data fusion, which comprises an installation sensor module, a data acquisition module, a data analysis module, an intelligent control module and an intelligent monitoring module.

[0006] The installation sensor module is specifically an installation sensor, which prepares for the data acquisition module.

[0007] The data acquisition module is specifically configured to collect sensor signals of the decontamination unit and the vacuum unit through a decontamination unit data acquisition submodule and a vacuum unit data acquisition submodule, and then transmit the vacuum decontamination data to the data analysis module through a decontamination unit data communication submodule.

[0008] The data analysis module is specifically configured to store vacuum decontamination data, perform fault early warning analysis according to the data, perform single-parameter noise reduction and multi-parameter fusion, and perform three-level early warning judgment on abnormal parameters.

[0009] The intelligent control module is specifically configured to optimize the start-stop logic of multiple pump groups by using an improved vacuum pump cooperative control algorithm according to the three-level early warning judgment, dynamically allocate loads, implement predictive start-stop of the pump groups in combination with demand fluctuations, and combine the soft start current with the load distribution coefficient to ensure state synchronization.

[0010] The intelligent monitoring module is specifically configured to monitor the real-time running state of the system, realize the decontamination unit hose recovery state monitoring function and the system low-power running function.

[0011] Further, the installation sensor module specifically comprises an installation-in-place detection sensor, a vacuum sensor, a temperature sensor, a current sensor, a voltage sensor and a vibration sensor.

[0012] Further, the data acquisition module comprises a decontamination unit data acquisition submodule, a decontamination unit data communication submodule and a vacuum unit data acquisition submodule.

[0013] The decontamination unit data acquisition submodule is installed in the on-site decontamination unit electric control box, connected with the data output end of the installation-in-place detection sensor through a data transmission signal line, and connected with the signal input end of the decontamination unit data communication submodule through an RS485 industrial communication network.

[0014] The decontamination unit data communication submodule is installed at the end of each decontamination line, and its signal input end is connected with the decontamination unit data acquisition submodule, and its signal output end is connected with the input end of the data analysis module through an optical fiber industrial network; through data encryption technology, identity authentication technology, access control technology, secure communication protocol, data integrity check and other technologies, the safe communication of the vacuum decontamination key data is realized.

[0015] The vacuum unit data acquisition submodule is installed in a vacuum pump house vacuum unit electric control cabinet and is connected with a data analysis module input end through an industrial Ethernet.

[0016] The decontamination unit data acquisition submodule and the vacuum unit data acquisition submodule are designed with various data interfaces, including RS232, RS485, optical fiber, Ethernet, LORA and the like, for compatibility design of various interface devices.

[0017] Further, the data analysis module comprises a data storage analysis server, a switch and a firewall.

[0018] The data storage analysis server is installed in an information room and is used for storing all operation data collected by the system, including basic data and device operation data uploaded by a subserver, and providing background data analysis work for the system, wherein the background data analysis work mainly comprises fault early warning analysis and energy consumption analysis.

[0019] The fault early warning analysis is achieved by collecting system vacuum degree, vacuum tank liquid level, cam pump temperature and cam pump current in real time, processing and fusing various data by using Kalman filtering algorithm, and comparing multiple data to realize device abnormal state early warning, including the following contents.

[0020] Parameter acquisition, four types of core data, namely, system vacuum degree, vacuum tank liquid level, cam pump temperature and cam pump current, are collected in real time.

[0021] Single parameter Kalman filtering denoising, eliminating sensor noise and outputting purified parameters.

[0022] Multi-parameter fusion, parameter correlation is mined by extended Kalman filtering, fusion state vector is outputted, hidden correlation between parameters is captured, static value and dynamic change rate are combined, absolute state of the device is contained, change trend of the device is contained, limitation of single parameter is broken through, and data reliability is improved.

[0023] Three-level early warning judgment, when the deviation between the calculated parameter and the rated value exceeds 5%, level one early warning is triggered, which belongs to slight abnormality; when the actual associated parameter relationship is compared with the normal model, the deviation exceeds 10%, level two early warning is triggered, which belongs to associated abnormality; when the monitored parameter changes suddenly and exceeds the normal range, level three early warning is triggered, which belongs to emergency fault.

[0024] Level one early warning, the system records the abnormality and reminds the operation and maintenance personnel to perform inspection; level two early warning, the system automatically adjusts the load and triggers sound and light alarm; level three early warning, the power supply of part of the pump group is immediately cut off to prevent damage to the device, and an emergency fault signal is sent to the staff.

[0025] The switch is installed in an information room, is a network device for forwarding electrical signals, and provides exclusive electrical signal paths for any two network nodes connected to the switch.

[0026] The firewall is installed in an information room, and is used to protect computer systems and networks from external threats.

[0027] Further, the intelligent control module optimizes the start-stop logic of the multi-pump group according to the three-level early warning judgment, adopts an improved vacuum pump cooperative control algorithm, dynamically allocates the load, accurately matches the load of the running pump group with the actual demand, reduces the full-load operation in non-full-time periods, reduces invalid energy consumption, avoids single-pump overload, reduces equipment wear and tear and failure risks caused by long-term single-pump overload, prolongs the overall service life of the pump group, introduces a soft start strategy to avoid current shock problems, and includes the following contents:

[0028] Dynamic load allocation of the multi-pump group, based on real-time operation parameters of each vacuum pump, calculates the optimal load allocation coefficient of each pump to avoid single-pump overload;

[0029] Predictive start-stop of the pump group, dynamically adjusts the number of pneumatic pumps in combination with demand fluctuations to reduce frequent start-stop;

[0030] Calculate the soft start current, link the soft start current with the load allocation coefficient to ensure that the current and the load rise synchronously during the start process, and improve the safety of the start process.

[0031] Further, the intelligent monitoring module includes an information management computer, a video camera, and a video recorder;

[0032] The information management computer is installed in the control room monitoring room and connected to the data analysis module through an industrial Ethernet, the video camera is installed in the vacuum pump room and connected to the video recorder through an Ethernet;

[0033] The information management computer is used to display the real-time operation state of the intelligent monitoring system of the vacuum sewage unloading device, realizes remote monitoring of the unloading unit hose recovery state, and realizes low-power operation of the system.

[0034] The above scheme has the following beneficial effects:

[0035] (1) In view of the technical problems that there is no collection and analysis of the operation data of the unloading system, potential faults cannot be identified through data trends, and only post-fault processing can be performed, resulting in waste of resources and increase of driving risk, a data collection module is adopted to comprehensively collect key operation data of the unloading unit and the vacuum unit, real-time and accurate data uploading is ensured by means of multi-interface compatibility and safe transmission technology, the collected data is subjected to Kalman filter denoising through a data analysis module, multi-parameter fusion is used to mine correlation trends, and a three-level early warning mechanism is used to change the traditional post-fault processing into pre-warning and hierarchical intervention, thereby reducing driving risk;

[0036] (2) In view of the technical problems that the system does not have a logic for on-demand operation, needs to be turned on at all times, has high energy consumption, has no unified monitoring system, relies on manual inspection, has no special technical monitoring of the hose recovery state, has the risk of driving with the hose, and cannot realize real-time sensing and fine control of the equipment state, an intelligent control module is adopted to make a three-level early warning judgment, an improved vacuum pump cooperative control algorithm is used to optimize the start-stop logic of multiple pump groups, dynamically allocate the load, implement predictive start-stop in combination with demand fluctuations, and link the soft start current and the load distribution coefficient to ensure state synchronization, and a wisdom monitoring module is used to monitor the real-time operation state of the system, thereby realizing the hose recovery state monitoring function of the unloading unit and the low-power operation function of the system. BRIEF DESCRIPTION OF DRAWINGS

[0037] Figure 1 A schematic diagram of the intelligent monitoring system of the vacuum unloading equipment based on multi-data fusion provided by the present application is shown in the figure.

[0038] Figure 2 A schematic diagram of the intelligent control module is shown in the figure.

[0039] The accompanying drawings are used to provide a further understanding of the present application, and constitute a part of the specification, together with the embodiments of the present application, to explain the present application, and do not constitute a limitation of the present application. DETAILED DESCRIPTION

[0040] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0041] In the description of the present application, it should be understood that the terms "upper", "lower", "front", "back", "left", "right", "top", "bottom", "inner", "outer" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation on the present application.

[0042] Embodiment one, refer to Figure 1 The present application provides a vacuum sewage unloading equipment intelligent monitoring system based on multi-data fusion, comprising a sensor installation module, a data acquisition module, a data analysis module, an intelligent control module and a smart monitoring module.

[0043] The sensor installation module is specifically a sensor installation module, which prepares for the data acquisition module;

[0044] The data acquisition module is specifically a sewage unloading unit data acquisition submodule and a vacuum unit data acquisition submodule, which acquires sensor signals of the sewage unloading unit and the vacuum unit, and then transmits the vacuum sewage unloading data to the data analysis module through the sewage unloading unit data communication submodule;

[0045] The data analysis module is specifically for storing vacuum sewage unloading data, performing fault early warning analysis according to the data, performing single-parameter noise reduction and multi-parameter fusion, and performing three-level early warning judgment on abnormal parameters;

[0046] The intelligent control module is specifically for optimizing the start-stop logic of multiple pump groups, dynamically distributing the load, combining the demand fluctuation to implement predictive start-stop of the pump group, and combining the soft start current with the load distribution coefficient to ensure state synchronization according to the three-level early warning judgment and the improved vacuum pump cooperative control algorithm;

[0047] The smart monitoring module is specifically for monitoring the real-time running state of the system, realizing the hose recovery state monitoring function of the sewage unloading unit and the low-power running function of the system.

[0048] Embodiment two, refer to Figure 1 This embodiment is based on the above embodiment, and the sensor installation module is specifically a position detection sensor, a vacuum sensor, a temperature sensor, a current sensor, a voltage sensor and a vibration sensor;

[0049] The position detection sensor is installed at the hose recovery position of the sewage unloading unit, and is used to detect whether the sewage unloading hose of the sewage unloading unit is recovered in place after the sewage unloading operation is completed; the data output end of the position detection sensor is connected to the data input end of the sewage unloading unit data acquisition submodule in the data acquisition module through a data transmission signal line;

[0050] The vacuum sensor is installed on the vacuum unit pipeline, and is used for detecting the real-time vacuum pressure of the vacuum sewage discharge system. The signal output end is connected with the vacuum pressure detection port of the vacuum unit data acquisition submodule in the data acquisition module through the data transmission signal line.

[0051] The temperature sensor is installed on the shell of the cam pump, the vacuum pump and the unit motor, and is used for detecting the real-time running temperature of the vacuum sewage discharge equipment. The signal output end is connected with the temperature detection port of the vacuum unit data acquisition submodule through the data transmission signal line.

[0052] The current sensor is installed on the main cable in the vacuum unit electric control cabinet, and is used for detecting the real-time running current of the vacuum sewage discharge system. The signal output end is connected with the current detection port of the vacuum unit data acquisition submodule through the data transmission signal line.

[0053] The voltage sensor is installed on the main circuit breaker in the vacuum unit electric control cabinet, and is used for detecting the real-time power supply voltage of the vacuum sewage discharge system. The signal output end is connected with the voltage detection port of the vacuum unit data acquisition submodule through the data transmission signal line.

[0054] The vibration sensor is installed on the shell of the cam pump of the vacuum unit, and is used for detecting the real-time vibration condition of the cam pump of the vacuum unit. The signal output end is connected with the vibration detection port of the vacuum unit data acquisition submodule through the data transmission signal line.

[0055] Embodiment three, refer to Figure 1 The data acquisition module comprises a sewage discharge unit data acquisition submodule, a sewage discharge unit data communication submodule and a vacuum unit data acquisition submodule.

[0056] The sewage discharge unit data acquisition submodule is installed in the on-site sewage discharge unit electric control box, is connected with the data output end of the in-place detection sensor through the data transmission signal line, and is connected with the signal input end of the sewage discharge unit data communication submodule through the RS485 industrial communication network. The sewage discharge unit data acquisition submodule is used for acquiring signals such as the sewage discharge unit hose recovery state, the sewage discharge unit vacuum pressure and the manual confirmation button, and outputting the sewage discharge unit hose recovery state signal.

[0057] The data communication submodule of the unloading unit is installed at the end of each unloading line, the signal input end is connected with the data acquisition module of the unloading unit, and the signal output end is connected with the input end of the data analysis module through the optical fiber industrial network; the data communication submodule of the unloading unit is installed at the end of each unloading line, the signal input end is connected with the data acquisition module of the unloading unit, and the signal output end is connected with the input end of the data analysis module through the optical fiber industrial network; for real-time receiving of the unloading unit data acquisition submodule monitored unloading unit running state signal, and the collected signal is converted, and the data analysis module is communicated through the optical fiber, and the real-time monitoring of the safe running state of the unloading unit is realized; through data encryption technology, identity authentication technology, access control technology, secure communication protocol, data integrity check and other technologies, the safe communication of the key data of the vacuum unloading is realized;

[0058] The data acquisition submodule of the vacuum unit is installed in the electric control cabinet of the vacuum pump house, and is connected with the input end of the data analysis module through the industrial Ethernet; for real-time receiving of the vacuum sensor, temperature sensor, current sensor, voltage sensor and vibration sensor signals installed in the vacuum unit, and simultaneously connected with the control system PLC through the industrial Ethernet, the communication reading of the real-time running data of the vacuum unit is realized;

[0059] The data acquisition submodule of the unloading unit and the data acquisition submodule of the vacuum unit are designed with various data interfaces, including RS232, RS485, optical fiber, Ethernet, LORA and the like, for compatibility design of various interface devices.

[0060] Embodiment four, refer to Figure 1 The data analysis module includes a data storage analysis server, a switch and a firewall based on the above-mentioned embodiments;

[0061] The data storage analysis server is installed in the information room, used for storing all running data collected by the system, including basic data and device running data uploaded by the subserver, and providing background data analysis work for the system, the background data analysis work mainly includes fault early warning analysis and energy consumption analysis;

[0062] The fault early warning analysis is realized by real-time collection of the system vacuum degree, the vacuum tank liquid level, the cam pump temperature and the cam pump current, processing and fusion of each data by using Kalman filter algorithm, and comparison of multiple data, including the following contents:

[0063] Parameter acquisition, real-time acquisition of four kinds of core data, the core data is the system vacuum degree, the vacuum tank liquid level, the cam pump temperature and the cam pump current, the sampling frequency is set to 10 Hz, to ensure the capture of instantaneous abnormality;

[0064] Single parameter Kalman filter denoising, eliminating sensor noise, outputting purified parameters;

[0065] Multi-parameter fusion, parameter correlation is mined through extended Kalman filter, output fusion state vector, capture the hidden correlation between parameters, combine static value and dynamic change rate, both contain the current absolute state of the device, and contain the change trend of the device, break through the limitation of single parameter, improve the reliability of data, the formula is as follows:

[0066] ;

[0067] In the formula, indicates the fusion state vector at time t, indicates the purified system vacuum degree, indicates the purified vacuum tank liquid level, indicates the purified cam pump temperature, indicates the purified cam pump current, indicates the change rate of vacuum degree, indicates the change rate of current, and T indicates vector transpose symbol;

[0068] Three-level early warning judgment, when the deviation of the calculated parameter and the rated value exceeds 5%, trigger the first-level early warning, which belongs to slight abnormality; Compared with the actual correlation parameter relationship and the normal model, the deviation exceeds 10%, trigger the second-level early warning, which belongs to correlation abnormality; When the parameter changes suddenly, it exceeds the normal range and triggers the third-level early warning, which belongs to emergency failure;

[0069] The calculated parameter represents the actual value of the core operating parameter of the device obtained after data acquisition and Kalman filter denoising;

[0070] The correlation parameter relationship represents the actual cooperative relationship among multiple parameters;

[0071] The first-level early warning, the system records the abnormality and reminds the operation and maintenance personnel to inspect; The second-level early warning, the system automatically adjusts the load, and triggers the sound and light alarm; The third-level early warning, immediately cut off part of the pump group power supply to prevent damage to the device, and send an emergency failure signal to the staff;

[0072] The switch is installed in the information room, and is a network device for forwarding electrical signals, which provides exclusive electrical signal path for any two network nodes connected to the switch;

[0073] The firewall is installed in the information room, and is used for protecting the computer system and network from external threats.

[0074] By performing the above operation, the key operation data of the decontamination unit and the vacuum unit are comprehensively collected by using the data collection module, the data is ensured to be uploaded in real time and accurately by means of multi-interface compatibility and safe transmission technology, the collected data is subjected to Kalman filter denoising by the data analysis module, the correlation trend is mined by multi-parameter fusion, the traditional post-fault processing is changed into pre-warning and graded intervention by the three-level early warning mechanism, the driving risk is reduced, and the technical problems that the operation data of the decontamination system cannot be collected and analyzed, potential faults cannot be identified through data trend, and only post-fault processing can be performed, resulting in waste of resources and increase of driving risk are solved.

[0075] In the fifth embodiment, with reference to Figure 1 and Figure 2 , based on the above-mentioned embodiments, the intelligent control module optimizes the start-stop logic of the multi-pump group by using an improved vacuum pump cooperative control algorithm according to the three-level early warning judgment, dynamically allocates the load, makes the load of the running pump group accurately match the actual demand, runs in non-full-time period and full load, reduces invalid energy consumption, avoids single-pump overload, reduces equipment wear and tear and fault risk caused by long-term overload of single pump, prolongs the overall service life of the pump group, introduces a soft start strategy to avoid current impact problems, and includes the following contents:

[0076] Multi-pump group dynamic load allocation, based on real-time operation parameters of each vacuum pump, calculates the optimal load allocation coefficient of each pump to avoid single-pump overload, and the formula is as follows:

[0077] ;

[0078] In the formula, represents the optimal load allocation coefficient of the i-th pump at time t, represents the real-time load rate of the i-th pump at time t, represents the health state coefficient of the i-th pump at time t, represents the pump group set in the running state at time t, represents the soft start correction coefficient of the i-th pump, represents the rated load reference coefficient of the i-th pump at time t, and j is used to traverse all pumps in the running state at present;

[0079] Pump group predictive start-stop, dynamically adjusts the number of pneumatic pumps in combination with demand fluctuation to reduce frequent start-stop, and the formula is as follows:

[0080] ;

[0081] In the formula, represents the number of pumps to be started at time t, represents the upward rounding symbol to ensure that the load demand is met, Total load demand of the system at time t, k represents the demand change sensitivity coefficient, Rate of change of total load demand, Maximum load distribution coefficient in the running pump group at time t, Rated load capacity of a single pump, Redundancy coefficient;

[0082] The soft start current is calculated, and the soft start current is linked with the load distribution coefficient to ensure that the current and the load rise synchronously during the starting process, thereby improving the safety of the starting process, and the formula used is as follows:

[0083]

[0084] In the formula, Real-time current during the soft start process at time t, Rated current of the motor, and T1 represents the time constant of the soft start, Base no-load current of the pump.

[0085] Embodiment six, refer to Figure 1 This embodiment is based on the above-mentioned embodiments, and the intelligent monitoring module comprises an information management computer, a video camera, and a video recorder.

[0086] The information management computer is installed in the control room monitoring machine room and is connected with the data analysis module through an industrial Ethernet, the video camera is installed in the vacuum pump room and is connected with the video recorder through an Ethernet, and the information management computer comprises a system display computer, an operation table, a power supply, and the like.

[0087] The information management computer comprises a system display computer, an operation table, a power supply, and the like, and is used to display the real-time running state of the intelligent monitoring system of the vacuum sewage unloading equipment; and remote monitoring of the hose recycling state of the sewage unloading unit and low-power running of the system are realized.

[0088] The hose recycling state of the sewage unloading unit is remotely monitored, the information management computer is connected with the data analysis module through an Ethernet, the data analysis module receives the hose recycling state signal collected by the sewage unloading unit data collection submodule in the data collection module, the information management computer acquires the signal from the data analysis module, and the hose recycling state is displayed in real time through the system display interface, the hose recycling state comprises recycled, not recycled, and recycling, thereby realizing remote monitoring of the hose recycling state of the sewage unloading unit, effectively avoiding train driving accidents with the hose, and ensuring train operation and staff safety.

[0089] ​The low-power operation system, the information management computer as a monitoring terminal, automatically reduces the display screen brightness during the idle period of the system, enters the sleep mode, and only maintains the core data receiving function; at the same time, the video camera is remotely controlled by the information management computer to start and stop and adjust the shooting frame rate, and the frame rate is reduced during the unnecessary period, thereby reducing the energy consumption of video data transmission and processing, and indirectly supporting the low-power operation of the whole system.

[0090] By performing the above operation, the intelligent control module is used to make three-level early warning judgment, the improved vacuum pump cooperative control algorithm is used to optimize the start-stop logic of the multi-pump group, the load is dynamically allocated, the predictive start-stop is implemented combined with demand fluctuation, the soft start current and the load distribution coefficient are linked to ensure state synchronization, and the intelligent monitoring module is used to monitor the real-time operation state of the system, so that the sewage unloading unit hose recovery state monitoring function and the system low-power operation function are realized, the technical problems that the system does not run on demand, needs to be started all the time, has high energy consumption, and has no unified monitoring system, relies on manual inspection, has no special technical monitoring of the hose recovery state, has the risk of driving with the hose, and cannot realize real-time perception and fine control of the equipment state are solved.

[0091] It should be noted that, in this text, relational terms such as first and second and the like are used merely to distinguish one entity or action from another, without necessarily requiring or implying that there is any such actual relationship or order between such entities or actions. In addition, the terms "comprises", "comprising" or any other variant thereof are intended to cover non-exclusive inclusions, so that a process, method, article or apparatus including a series of elements includes not only those elements, but also other elements not explicitly listed or inherent to such a process, method, article or apparatus.

[0092] Although embodiments of the present application have been shown and described, it will be understood by those having ordinary skill in the art that various changes, modifications, alternatives, and variations can be made thereto without departing from the principles and spirit of the application.

[0093] The above describes the present application and its embodiments, which are not limited, and the drawings only show one of the embodiments of the present application, and the actual structure is not limited thereto. In general, if a person skilled in the art is inspired by it, without departing from the purpose of the present application, without creative design, similar structure and embodiments of the technical solution can be designed, which should belong to the protection scope of the present application.

Claims

1. A vacuum decontamination equipment intelligent monitoring system based on multi-data fusion, characterized in that: The system comprises a sensor installation module, a data acquisition module, a data analysis module, an intelligent control module and a smart monitoring module; The sensor installation module is specifically a sensor installation module, which prepares for the data acquisition module; The data acquisition module is specifically a data acquisition module that acquires sensor signals of the decontamination unit and the vacuum unit through a decontamination unit data acquisition submodule and a vacuum unit data acquisition submodule, and then transmits the vacuum decontamination data to the data analysis module through a decontamination unit data communication submodule; The data analysis module is specifically a data analysis module that stores vacuum decontamination data, performs fault early warning analysis according to the data, performs single-parameter noise reduction and multi-parameter fusion, and performs three-level early warning judgment on abnormal parameters; The intelligent control module is specifically an intelligent control module that optimizes the start-stop logic of multiple pump groups by using an improved vacuum pump cooperative control algorithm according to the three-level early warning judgment, dynamically allocates loads, implements predictive start-stop of pump groups in combination with demand fluctuations, and combines soft start current and load distribution coefficients to ensure state synchronization; The formula used for calculating the optimal load distribution coefficient of each vacuum pump based on real-time operating parameters of each vacuum pump is as follows: ； In the formula, represents the optimal load distribution coefficient of the i-th pump at time t, represents the real-time load rate of the i-th pump at time t, represents the health state coefficient of the i-th pump at time t, represents the set of pump groups in the running state at time t, represents the soft start correction coefficient of the i-th pump, represents the rated load reference coefficient of the i-th pump at time t, j is used to traverse all the pumps currently in the running state; The formula used for dynamically adjusting the number of air-driven pumps in combination with demand fluctuations is as follows: ； wherein, represents the number of pumps that should be started at time t, represents the upward rounding symbol, ensuring that the load demand is met, represents the total load demand of the system at time t, k represents the demand change sensitivity coefficient, represents the rate of change of the total load demand, represents the maximum load distribution coefficient in the pump group operating at time t, represents the rated load capacity of a single pump, represents the redundancy coefficient; The formula used for calculating soft start current and linking soft start current with load distribution coefficients to ensure that the current and the load rise synchronously during the start-up process is as follows: ； wherein represents the real-time current at time t during the soft start process, represents the rated current of the motor, and T1 represents the time constant of the soft start, represents the base no-load current of the pump; The smart monitoring module is specifically a smart monitoring module that monitors the real-time operating state of the entire system, realizes the function of monitoring the recovery state of the decontamination unit hose, and realizes the function of low-power operation of the system.

2. The multi-data fusion based intelligent monitoring system for vacuum decontamination equipment according to claim 1, characterized in that: The data analysis module comprises a data storage and analysis server, a switch and a firewall; The data storage and analysis server is installed in an information room and is used to store all operating data collected by the system, including basic data and device operating data uploaded by a subserver, and to provide background data analysis work for the system, wherein the background data analysis work mainly comprises fault early warning analysis; The fault early warning analysis is performed by real-time collection of vacuum degree, vacuum tank liquid level, cam pump temperature and cam pump current, processing and fusion of the data by using a Kalman filter algorithm, comparison of multiple data, realization of device abnormal state early warning, and the following contents: Parameter acquisition, real-time acquisition of four types of core data, wherein the core data are system vacuum degree, vacuum tank liquid level, cam pump temperature and cam pump current; Single-parameter Kalman filter noise reduction, output of purified parameters; Multi-parameter fusion, parameter correlation mining by using an extended Kalman filter, output of a fusion state vector, capture of hidden correlations between parameters, combination of static values and dynamic change rates; Three-level early warning judgment, triggering of a first-level early warning when the deviation of the calculated parameter from the rated value exceeds 5%, belonging to a slight abnormality; Comparison of actual correlation parameter relationship and a normal model, triggering of a second-level early warning when the deviation exceeds 10%, belonging to a correlation abnormality; Monitoring of sudden changes in parameters, triggering of a third-level early warning when the parameters exceed the normal range, belonging to an emergency fault; First-level early warning, system recording of abnormalities and reminding of maintenance personnel for inspection; Second-level early warning, automatic adjustment of loads by the system and triggering of audible and light alarms; Three-level early warning, immediately cut off part of the pump power, to prevent equipment damage, and send emergency fault signal to the staff; The switch is installed in the information room, is a network device for telecommunication signal forwarding, and provides exclusive telecommunication signal passage for any two network nodes connected to the switch. The firewall is installed in the information room, and is used for protecting the computer system and network from external threats.

3. The intelligent monitoring system for vacuum decontamination equipment based on multi-data fusion according to claim 1, characterized in that: The intelligent monitoring module comprises an information management computer, a video camera and a video recorder. The information management computer is installed in the control room and connected to the data analysis module through an industrial Ethernet, and the video camera is installed in the vacuum pump room and connected to the video recorder through an Ethernet. The information management computer is used for displaying the real-time running state of the intelligent monitoring system of the vacuum sewage unloading equipment, and realizes remote monitoring of the hose recovery state of the sewage unloading unit and low-power running of the system.

4. The intelligent monitoring system for vacuum sewerage equipment based on multi-data fusion according to claim 1, characterized in that: The data acquisition module comprises a sewage unloading unit data acquisition submodule, a sewage unloading unit data communication submodule and a vacuum unit data acquisition submodule. The sewage unloading unit data acquisition submodule is installed in the on-site sewage unloading unit electric control box, connected to the data output end of the in-place detection sensor through a data transmission signal line, and connected to the signal input end of the sewage unloading unit data communication submodule through an RS485 industrial communication network. The sewage unloading unit data communication submodule is installed at the end of each sewage unloading line, and the signal input end is connected to the sewage unloading unit data acquisition submodule, and the signal output end is connected to the input end of the data analysis module through an optical fiber industrial network. The vacuum unit data acquisition submodule is installed in the vacuum unit electric control cabinet of the vacuum pump room, and connected to the input end of the data analysis module through an industrial Ethernet. The sewage unloading unit data acquisition submodule and the vacuum unit data acquisition submodule are designed with various data interfaces for compatibility design of various interface devices.

5. The intelligent monitoring system for vacuum sewerage equipment based on multi-data fusion according to claim 1, characterized in that: The installation sensor module specifically comprises an in-place detection sensor, a vacuum sensor, a temperature sensor, a current sensor, a voltage sensor and a vibration sensor.

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