The invention relates to the technical field of
sewage pump control, in particular to a
sewage pump multi-parameter
intelligent control method based on a bidirectional LSTM neural network. According to the method, firstly, multiple types of sensors for flow,
impurity concentration and the like are installed in a
sewage conveying
system, and the operation parameter acquisition function of a
servo motor body is utilized to obtain
system operation data in real time, transmit the
system operation data to a
data processing unit for preprocessing, and arrange the data according to a
time sequence to form a sample set; and next, constructing an adaptive neural
network model, selecting a proper
network structure, determining the number of nodes in each layer, an
activation function, a
loss function and an optimization
algorithm, and performing training and performance evaluation on the model by using the divided
training set,
verification set and
test set, so that the model has good generalization ability. During actual operation of the sewage pump, data collected and preprocessed in real time are input into the trained neural
network model, the model outputs sewage pump control instructions such as rotating speed adjustment, start-stop control and fault early warning, a
motor controller is driven to regulate and control operation of the sewage pump according to the control instructions, and meanwhile a real-time monitoring and alarming mechanism is set. And the running state accords with prediction. Intelligent and precise control over the sewage pump is achieved, the operation efficiency can be effectively improved,
energy consumption is reduced, the service life of equipment is prolonged, the
system stability is enhanced, and the system can adapt to various complex working conditions.