Meishan pig estrus monitoring method based on acoustic information
An acoustic and acoustic signal technology, applied in the field of estrus monitoring of Meishan pigs based on acoustic information, can solve weak problems, achieve the effects of reducing labor costs, improving the level of informatization, and improving monitoring efficiency
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Embodiment 1
[0038] A method for monitoring Meishan pig estrus based on acoustic information, said method comprising the following steps:
[0039] Step 1: Collect the sound signals produced by Meishan pigs when they are in estrus through the recording equipment placed in the pigsty, and at the same time collect the sound signals of sneezing, eating, screaming, humming and ear shaking of Meishan pigs and Landrace pigs in the pig farm environment ;
[0040] Step 2: The Wiener speech enhancement algorithm based on wavelet threshold multi-window spectrum preprocesses the pig sound signal collected in step 1, realizes denoising of the pig sound signal, and obtains the pig sound signal after denoising;
[0041] Step 3: Using the double-threshold endpoint detection method based on short-term energy to extract the effective signal from the denoised pig sound signal in step 2 to obtain an effective pig sound signal;
[0042] Step 4: Analyze the time-frequency characteristics of the effective pig s...
Embodiment 2
[0055] 1 Pig sound collection and preprocessing
[0056] 1.1 Pig sound collection
[0057] The sound collection of pigs was completed in the boutique pig breeding farm of Huazhong Agricultural University. The acquisition device is Meibo-M66 recording pen, the sampling frequency is 48kHz, the sampling accuracy is 16 bits, two-channel continuous acquisition, and the maximum working time is 24h. The pigs are distributed in three adjacent pens, with 5 Meishan pigs in the middle pen and 5 Landrace pigs in the other two pens. The experienced manager of the pig farm confirmed that there were only 3 Meishan pigs in estrus. The sound signal in the pig farm environment is complex and diverse, mixed with a variety of noises and the sounds of multiple pigs. The collected pig sounds were classified, marked and screened, and 500 Meishan pig estrous sound samples and 500 non-estrous sound samples were selected, among which the non-estrous sound samples included 100 sneezing samples, 110 e...
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