Control system for optimizing operation condition of refrigeration host

Abstract

The utility model discloses a control system for optimizing operation conditions of a refrigeration host. The control system comprises a controller, a data acquisition unit, a human-computer interface, an Internet of Things communication unit, a server and a client, the controller is directly connected with the data acquisition unit, the human-computer interface and the Internet of Things communication unit, the server is connected with the Internet of Things communication unit, and the client is connected with the server; the data acquisition unit comprises a plurality of acquisition modules, and the plurality of acquisition modules comprise an electrical parameter acquisition module, a refrigerant circulation loop parameter acquisition module, an evaporator loop parameter acquisition module, a condenser loop parameter acquisition module and a throttling device parameter acquisition module. The control system for optimizing the operation condition of the refrigeration host can assist debugging personnel to realize rapid debugging and maintenance of the refrigeration host, and meanwhile, the control system supports remote debugging, guidance and expert diagnosis service through the Internet of Things technology so as to achieve the optimal operation condition and effect.

Description

TECHNICAL FIELD

[0001] The utility model relates to refrigeration machine control system technical field especially relates to a control system of optimization refrigeration host computer operating condition. BACKGROUND

[0002] The efficient operation of the refrigeration host computer is realized, first, the refrigeration host computer is tested according to the national standard before leaving factory, and only after passing the test, it is allowed to leave factory. The refrigeration host computer needs to be maintained and optimized in the project site for a long time, to ensure that the refrigeration host computer is in the best performance state. In addition to relying on the skills of the debugging engineer, the more important thing is to have a simple and practical debugging tool or debugging control system, which has very important significance for ensuring the debugging effect. However, the current technical defects are that the above system for realizing the performance detection of the refrigeration host computer can only be detected manually, and the rapid and accurate system detection cannot be realized, so that the performance detection becomes a bottleneck process in the production process.

[0003] In view of the above-mentioned defects, the technical problem to be solved by those skilled in the art is to design a control system for optimizing the operating condition of the refrigeration host computer, which can be used for performance detection of the refrigeration host computer and debugging in the project site, and can improve the detection efficiency and accuracy. CONTENT OF THE UTILITY MODEL

[0004] In order to overcome the defects of the prior art, the utility model proposes a control system for automatically collecting and calculating the operating condition parameters of the refrigeration host computer, comparing with the data indicators of the built-in standard database, and giving the measures and methods for optimizing the operating condition of the refrigeration host computer. The control system solves the problems of low efficiency and poor precision of the debugging tool or method in the process of debugging, maintenance and energy-saving reconstruction of the refrigeration host computer.

[0005] The utility model solves the technical problems by adopting the following technical scheme:

[0006] A control system for optimizing the operating condition of the refrigeration host computer, comprising a controller, a data acquisition unit, a man-machine interface, an internet of things communication unit, a server and a client;

[0007] The controller is directly connected with the data acquisition unit, the man-machine interface and the internet of things communication unit, the server is connected with the internet of things communication unit, and the client is connected with the server;

[0008] The data acquisition unit comprises a plurality of acquisition modules, and the plurality of acquisition modules comprise an electric parameter acquisition module, a refrigerant circulation loop parameter acquisition module, an evaporator loop parameter acquisition module, a condenser loop parameter acquisition module and a throttling device parameter acquisition module.

[0009] The data acquisition unit is also connected with the refrigeration host.

[0010] The electric parameter acquisition module is connected with a power supply voltage collector, a running current collector, a running frequency collector, and a power factor collector.

[0011] The fluorine loop parameter acquisition module is connected with an exhaust pressure sensor, an exhaust temperature sensor, a suction pressure sensor, a suction temperature sensor, an evaporation temperature sensor, and a condensation temperature sensor.

[0012] The control system for optimizing the running condition of the refrigeration host includes the following steps when running:

[0013] ①. In the running state of the refrigeration host, the control device automatically collects the running parameters of the refrigeration host, including electric parameters: power Pe, voltage U, current I, frequency F, etc.; refrigerant circulation loop parameters: exhaust pressure p_mo, exhaust temperature t_mo, suction pressure p_mi, suction temperature t_mi, evaporation temperature te, condensation temperature tc, etc.; throttling device state v_ev; refrigerant medium temperature to, cooling medium temperature tq, etc.

[0014] ②. Running condition calculation: the controller analyzes and calculates the key index values of the running condition of the refrigeration host according to the collected refrigeration host running parameter data within a specified period of time.

[0015] ③. Compare the key index values of the running condition calculated in step ② with the standard database index value data built-in, and give the measures and methods for optimizing the running condition of the refrigeration host.

[0016] Further, after step ③ is completed, the following steps are included:

[0017] ④. The controller has a built-in standard database, which covers the physical parameters of various refrigerants, the running performance parameters of compressors of different brands and specifications, the structure and parameters of evaporators and condensers, and the parameters of various forms of throttling devices. The database is combined with long-term laboratory test data.

[0018] ⑤. The man-machine interface has a man-machine information interaction window and parameter input and running condition display programs.

[0019] ⑥. The controller realizes communication connection with the control system, the compressor, the evaporator, the condenser, the throttling device, and other components of the refrigeration host through the data acquisition unit.

[0020] ⑦. The controller realizes wireless data connection with the cloud server through the Internet of Things communication unit, and further realizes remote debugging guidance and expert diagnosis services.

[0021] Through the above structure setting, compared with the prior art, the utility model has the advantages that

[0022] The utility model discloses a control system of optimization refrigeration host computer operating condition sets a system framework, under the refrigeration host computer operating state, and control device automatic acquisition refrigeration host computer operating parameter, and controller is in the specified period time, according to the refrigeration host computer operating parameter data of collection, analysis and calculation refrigeration host computer operating condition key index value. The utility model whole based on the physical property parameter of refrigerant, compressor operating performance parameter, evaporator performance parameter, evaporator performance parameter and throttling device state, obtains operating condition key index value through adopting the mode of timing calculation, compares with the standard database index value of built-in, gives the measure method of refrigeration host computer optimization operation. As an auxiliary debugging control system or tool, can assist the debugging personnel to realize the quick debugging and maintenance of refrigeration host computer, and the control system passes through internet of things technology, supports remote debugging, guidance and expert diagnosis service, to reach the best operating condition and effect. BRIEF DESCRIPTION OF DRAWINGS

[0023] Figure 1 It is system structure schematic diagram for the utility model;

[0024] Figure 2 It is electric parameter acquisition module connection structure schematic diagram;

[0025] Figure 3 It is fluorine loop parameter acquisition module connection structure schematic diagram;

[0026] In the drawings, 1. man-machine interface, 2, controller, 3, data acquisition unit, 4, internet of things communication unit, 5, electric parameter acquisition module, 6, fluorine loop parameter acquisition module, 7, evaporator loop parameter acquisition module, 8, condenser loop parameter acquisition module, 9, throttling device loop parameter acquisition module, 10, refrigeration host computer, 11, server, 12, remote client, 13, power voltage collector, 14, operating current collector, 15, operating frequency collector, 16, power factor collector, 17, exhaust pressure sensor, 18, exhaust temperature sensor, 19, suction pressure sensor, 20, suction temperature sensor, 21, evaporating temperature sensor, 22, condensing temperature sensor. DETAILED DESCRIPTION

[0027] The following specific embodiments are used to explain the utility model in detail, and the person skilled in the art can easily understand other advantages and effects of the utility model from the disclosed content of the specification. However, it should be noted that the following specific embodiments do not technically limit the technical solutions, and those skilled in the art can further extend the technology under the guidance of the following technical solutions. The protection scope of the patent application is subject to the claims.

[0028] Embodiment 1:

[0029] In this embodiment, a control system for optimizing the operating condition of a refrigeration host includes a controller 2, a data acquisition unit 3, a human-machine interface 1, an Internet of Things communication unit 4, a server 11, and a remote client 12.

[0030] The controller 2 is directly connected to the data acquisition unit 3, the human-machine interface 1, and the Internet of Things communication unit 4. The server 11 is connected to the Internet of Things communication unit 4, and the remote client 12 is connected to the server 11. The remote client 12 can use a remote mobile phone APP.

[0031] The data acquisition unit 3 includes a plurality of acquisition modules, including an electric parameter acquisition module 5, a refrigerant circulation loop parameter acquisition module, an evaporator loop parameter acquisition module 7, a condenser loop parameter acquisition module 8, and a throttling device parameter acquisition module 9. The refrigerant circulation loop parameter acquisition module uses a fluorine loop parameter acquisition module 6.

[0032] Further, the data acquisition unit 3 is also connected to the refrigeration host 10. The electric parameter acquisition module 5 is connected to a power supply voltage collector 13, a running current collector 14, a running frequency collector 15, and a power factor collector 16.

[0033] The fluorine loop parameter acquisition module 6 is connected to an exhaust gas pressure sensor 17, an exhaust gas temperature sensor 18, a suction gas pressure sensor 19, a suction gas temperature sensor 20, an evaporation temperature sensor 21, and a condensation temperature sensor 22.

[0034] After the above system structure is connected, the control system disclosed in the utility model performs 485 communication with the refrigeration host 10 through the data acquisition unit 3, and the communication protocol is Modbus_RTU.

[0035] The Internet of Things communication unit 4 is a data collector, uses a 4G / 5G network, establishes a wireless communication connection with the server 11 through an mqtt protocol, and the server uses a cloud server. The client (or APP) 12 uses a mobile phone or a desktop computer to log in to the server, and provides remote support services.

[0036] At time t1, the state parameters of the refrigeration host are to = 8.5℃, p_mi = 2.20bar, Fm = 38Hz, and v_ev = 0.60. The measures and methods are v_evb = v_evb + 0.03 and Fmb = Fmb + 2.

[0037] The refrigeration host at time t2, state parameters: te=7.1℃, p_mi=2.56bar, Fm=50Hz, v_ev=0.79; measures and methods: v_evb=v_evb, Fmb=Fmb

[0038] The refrigeration host at time t3, state parameters: Atsubo=13.1K, Atsubi=2.7K, Fm=50Hz, v_ev=0.63; measures and methods: v_evb=v_evb-0.04, Fmb=Fmb+3

[0039] The refrigeration host at time t4, state parameters: Atsubo=15.7K, Atsubi=4.9K, Fm=50Hz, v_ev=0.72; measures and methods: v_evb=v_evb-0.02, Fmb=Fmb

[0040] The refrigeration host at time t5, state parameters: to=6.5℃, p_mi=2.26bar, Fm=30Hz, v_ev=0.55; measures and methods: lo=lob+0.3, check water pump and other auxiliary equipment.

[0041] The refrigeration host at time t6, state parameters: to=6.8℃, p_mi=2.48bar, Fm=49Hz, v_ev=0.75; measures and methods: lo=lob+0.1, v_evb=v_evb-0.03, Fmb=Fmb.

[0042] The refrigeration host at time t7, state parameters: to=8.9℃, tq=34℃, t_mo=85℃, Fm=45Hz, v_ev=0.52; measures and methods: lq=lqb+0.23, v_evb=v_evb-0.026, Fmb=Fmb-3.

[0043] The refrigeration host at time t8, state parameters: to=7.9℃, p_mi=2.52bar, Fm=45Hz, v_ev=0.60; measures and methods: v_evb=v_evb+0.10, Fmb=Fmb ... ...

[0046] Wherein:

[0047] v_evb: throttle opening information;

[0048] Fmb: compressor operating base frequency;

[0049] Atsubo: compressor discharge superheat;

[0050] Atsubi: compressor suction superheat

[0051] lob: evaporator rated refrigerant flow rate

[0052] lqb: condenser rated cooling medium flow rate

Claims

1. A control system for optimizing operating conditions of a refrigeration host, characterized by: It includes a controller, a data acquisition unit, a man-machine interface, an Internet of Things communication unit, a server and a client; The controller is directly connected with the data acquisition unit, the man-machine interface and the Internet of Things communication unit, the server is connected with the Internet of Things communication unit, and the client is connected with the server; The data acquisition unit includes a plurality of acquisition modules, and the plurality of acquisition modules include an electric parameter acquisition module, a refrigerant circulation loop parameter acquisition module, an evaporator loop parameter acquisition module, a condenser loop parameter acquisition module and a throttling device parameter acquisition module.

2. The control system for optimizing the operating conditions of a refrigeration host machine according to claim 1, characterized in that: The data acquisition unit is also connected with a refrigeration host.

3. The control system for optimizing the operating conditions of a refrigeration host machine according to claim 1, characterized in that: The electric parameter acquisition module is connected with a power supply voltage collector, a running current collector, a running frequency collector and a power factor collector.

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