The invention discloses a water chilling unit testing platform. The water chilling unit testing platform comprises a frame body; a groove is formed in the middle of the upper end of the frame body; sliding grooves in the side walls of the groove are connected with sliding strips on the two sides of a testing plate table in a sliding mode; clamping mechanisms are arranged on the left side and the right side of the upper end of the testing plate table; and adjusting mechanisms are arranged on the front side and the rear side of the left end of the upper surface of the frame body. The water chilling unit testing platform is simple in structure and convenient to operate; pipelined stable conveying is realized; a water inlet and a water outlet of a water chiller can be connected in a proper position through the adjusting mechanisms; water pressures of the water inlet and the water outlet of the water chiller can be rapidly and accurately detected through a water pressure testing device; real-time measurement of noise and ambient temperature during operation of the water chiller is realized through a noise and temperature testing device; and various testing data is uniformly integrated and analyzed through a PLC and then is intuitively displayed on a display, so that the workload of workers is relieved, the production quality of the water chiller is ensured, and the use efficiency ofthe water chilling unit testing platform is improved.

Water chilling unit testing platform

The invention discloses a method and a system for correcting a central air conditioner simulation model. The method comprises the following steps: collecting input and output parameters in an air conditioner equipment simulation model during the operation of a central air conditioner, and forming air conditioner parameter big data; and inputting the air conditioning parameter big data into the airconditioning equipment simulation model, and correcting the air conditioning equipment simulation model. The central air conditioner simulation model can be corrected.

Method and system for correcting central air conditioner simulation model

The invention discloses an industrial circulating cooling water energy-saving system and method based on a central cooling system, and belongs to the technical field of energy management and energy conservation. The industrial circulating cooling water energy-saving system mainly solves the problems of high energy consumption and poor cooling effects of an existing machine room type cooling systemdue to the fact that the existing machine room type cooling system cannot be coupled and connected with an existing motor cooling system. The industrial circulating cooling water energy-saving systemis mainly characterized by comprising a machine room type cooling system, a motor type cooling system, a cold accumulator, a water storage tank, a cooling water tank, a refrigerating unit, a temperature adjusting water tank and a heater. According to the industrial circulating cooling water energy-saving system; and aiming at the phenomenon that the water temperature in the water storage tank andan outlet of the cooling water tank changes due to seasonal changes, five corresponding circulating cooling paths are arranged according to different water temperature ranges of the water storage tank and the outlet of the cooling water tank, so that the purposes of peak clipping and valley filling, environment cooling capacity and system waste heat utilization are achieved. The industrial circulating cooling water energy-saving system has the advantages of convenience in adjustment, stability in operation and remarkable electricity saving effects.

Industrial circulating cooling water energy-saving system and method based on central cooling system

The invention relates to the technical field of heat exchanger fault diagnosis, and discloses a heat exchanger early fault diagnosis method based on a BP neural network. The method comprises the stepsof: A) collecting key parameters of a heat exchanger in a normal working state; B) dividing the acquired key parameters into a training set, a verification set and a test set; C) constructing a BP neural network model; D) obtaining a mean value [mu] and a standard deviation [sigma] of a test output error; E) predicting the outlet data of the heat exchanger by using the trained BP neural network model to obtain predicted output of the outlet data of the heat exchanger; and F) performing fault diagnosis, and determining whether the predicted output error is continuously out of a normal error range within the error determination time length T. According to the method, the BP neural network model is established with no need for fault samples, the model can be established only by adopting thedata of the heat exchanger in the normal working state, then the fault of the heat exchanger is diagnosed through the determination standard, and the fault diagnosis accuracy is high.

Heat exchanger early fault diagnosis method based on BP neural network

The invention discloses a central air-conditioning system modeling and energy efficiency optimizing method and device. The central air-conditioning system modeling and energy efficiency optimizing method comprises the steps of selecting corresponding fitting models according to the type and amount of collected data, saving and preprocessing the collected data, carrying out model fitting on the preprocessed data and the fitting models, establishing a cold source system simulation platform to analyze the influencing factors of the operation efficiency of a central air-conditioning cold source system, and obtaining the running conditions of the central air-conditioning cold source system and the energy consumption conditions of a refrigeration water pump, a cooling water pump, a water chillerand a cooling tower based on the optimization control, wherein the influencing factors include the inlet and outlet water temperature, flow rate and inlet and outlet water pressure difference corresponding to the refrigeration water pump, the cooling water pump, the water chiller and the cooling tower, and the outdoor temperature and humidity. The energy-saving potential of the central air-conditioning system can be fully tapped, the overall operation efficiency of the central air-conditioning system is improved, and the operation energy consumption of the central air-conditioning system is reduced.

Central air-conditioning system modeling and energy efficiency optimizing method and device

The invention discloses a water chiller fault diagnosis method based on a hybrid neural network, and aims at the problem that the single BP neural network is difficult to perform accurate prediction of the water chiller and the BP neural network has its own disadvantages. According to the method, a hybrid neural network model RBF-BP based on wavelet transform is put forward to perform fault diagnosis of the water chiller through combination of the characteristic that RBF neural network can approximate any function. The RBF network and the BP network are connected in parallel as one neural network, which is called the RBF-BP implicit strata for short. The algorithm has the advantages of both the RBF network and the BP network. Its learning process converges quickly and avoids the problem that the training process is liable to fall into the local minimum value. The method can be effectively applied to fault diagnosis of the water chiller and improve the performance of fault diagnosis.

He Bin

Papers

Central air-conditioning system modeling and energy efficiency optimizing method and device

Water chiller fault diagnosis method based on hybrid neural network